diff --git a/.github/workflows/nbval.yaml b/.github/workflows/nbval.yaml index 10a6c5deb..2f0c9768e 100644 --- a/.github/workflows/nbval.yaml +++ b/.github/workflows/nbval.yaml @@ -19,23 +19,16 @@ jobs: steps: - uses: actions/checkout@v4 - - name: Set up Python - uses: actions/setup-python@v5 + - uses: prefix-dev/setup-pixi@v0.8.3 with: - python-version: "3.12" - - name: Install notebook environment + environments: dev + - name: Validate notebook output run: | - python -m pip install --upgrade pip wheel - pip install --timeout=300 -r requirements.txt -r docs/notebook_requirements.txt .[test] - - name: Run notebook and check output + pixi run -e dev pytest --nbval --nbval-sanitize-with docs/nbval_sanitization_rules.cfg docs/${{ matrix.notebook-file }} + - name: Convert notebook to HTML run: | - # --nbval-sanitize-with: pre-process text to remove irrelevant differences (e.g. warning filepaths) - pytest --nbval --nbval-sanitize-with docs/nbval_sanitization_rules.cfg docs/${{ matrix.notebook-file }} - - name: Run notebooks again, save files - run: | - pip install nbconvert[webpdf] mkdir docs/artifacts - jupyter nbconvert --to html --execute --ExecutePreprocessor.timeout=600 --allow-errors --output artifacts/${{ matrix.notebook-file }}.html docs/${{ matrix.notebook-file }} + pixi run -e dev jupyter nbconvert --to html --output artifacts/${{ matrix.notebook-file }}.html docs/${{ matrix.notebook-file }} - name: Upload artifacts uses: actions/upload-artifact@v4 with: diff --git a/.github/workflows/pytest.yaml b/.github/workflows/pytest.yaml index 2b117ff16..4d94630dd 100644 --- a/.github/workflows/pytest.yaml +++ b/.github/workflows/pytest.yaml @@ -9,24 +9,60 @@ on: jobs: - build: + validate-envs: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + - uses: prefix-dev/setup-pixi@v0.8.3 + with: + environments: core default dev + frozen: true + - name: Validate core environment + run: pixi run -e core python -c "import rdtools; print(rdtools.__version__)" + - name: Validate default environment + run: pixi run python -c "import rdtools; import jupyter; print('default OK')" + - name: Validate dev environment + run: pixi run -e dev python -c "import rdtools; import pytest; import jupyter; print('dev OK')" + + test: + runs-on: ubuntu-latest + strategy: + matrix: + environment: [dev-py310, dev-py311, dev-py312, dev-py313, dev-py314] + fail-fast: false + + steps: + - uses: actions/checkout@v4 + - uses: prefix-dev/setup-pixi@v0.8.3 + with: + environments: ${{ matrix.environment }} + - name: Test with pytest (${{ matrix.environment }}) + run: pixi run -e ${{ matrix.environment }} test + - name: Upload coverage reports to Codecov + uses: codecov/codecov-action@v4 + env: + CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }} + + test-min: + runs-on: ubuntu-latest + + steps: + - uses: actions/checkout@v4 + - uses: prefix-dev/setup-pixi@v0.8.3 + with: + environments: dev-min + - name: Test with pytest (minimum versions) + run: pixi run -e dev-min test + - name: Upload coverage reports to Codecov + uses: codecov/codecov-action@v4 + env: + CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }} + test-latest: runs-on: ubuntu-latest strategy: matrix: - python-version: ["3.10", "3.11", "3.12", "3.13"] - env: [ - '-r requirements.txt .[test]', - '-r requirements-min.txt .[test]', - '--upgrade --upgrade-strategy=eager .[test]' - ] - exclude: - - python-version: "3.11" - env: '-r requirements-min.txt .[test]' - - python-version: "3.12" - env: '-r requirements-min.txt .[test]' - - python-version: "3.13" - env: '-r requirements-min.txt .[test]' + python-version: ["3.10", "3.11", "3.12", "3.13", "3.14"] fail-fast: false steps: @@ -35,13 +71,12 @@ jobs: uses: actions/setup-python@v5 with: python-version: ${{ matrix.python-version }} - - name: Install ${{ matrix.env }} + - name: Install latest versions run: | python -m pip install --upgrade pip wheel - pip install --timeout=300 ${{ matrix.env }} - - name: Test with pytest ${{ matrix.env }} - run: | - python -m pytest --cov=./ --cov-report=xml + pip install --timeout=300 --upgrade --upgrade-strategy=eager .[test] + - name: Test with pytest (latest) + run: python -m pytest --cov=rdtools --cov-report=xml - name: Upload coverage reports to Codecov uses: codecov/codecov-action@v4 env: diff --git a/.github/workflows/requirements.yaml b/.github/workflows/requirements.yaml deleted file mode 100644 index cb1d8b00a..000000000 --- a/.github/workflows/requirements.yaml +++ /dev/null @@ -1,29 +0,0 @@ -name: requirements - -on: - push: - branches: - - master - - development - pull_request: - - -jobs: - requirements: - - strategy: - matrix: - os: [ubuntu-latest, macos-latest, windows-latest] - - runs-on: ${{ matrix.os }} - - steps: - - uses: actions/checkout@v4 - - name: Set up Python - uses: actions/setup-python@v5 - with: - python-version: "3.12" - - name: Install notebook environment - run: | - python -m pip install --upgrade pip wheel - pip install --timeout=300 -r requirements.txt -r docs/notebook_requirements.txt diff --git a/.gitignore b/.gitignore index 72111dd48..6ab4ff4e7 100644 --- a/.gitignore +++ b/.gitignore @@ -11,6 +11,7 @@ .coveralls.yml .coverage .coverage.* +coverage.xml htmlcov/ # ignore test cache @@ -38,5 +39,9 @@ rdtools.egg-info* *.pickle +# pixi environments (local, not committed) +.pixi/* +!.pixi/config.toml + # ignore vscode settings .vscode/ diff --git a/.pixi.lnk b/.pixi.lnk new file mode 100644 index 000000000..4852630c6 Binary files /dev/null and b/.pixi.lnk differ diff --git a/CITATION.cff b/CITATION.cff index 2c050d4b1..299bd5994 100644 --- a/CITATION.cff +++ b/CITATION.cff @@ -43,4 +43,4 @@ authors: orcid: "https://orcid.org/0000-0002-9867-8930" title: "RdTools" doi: 10.5281/zenodo.1210316 -url: "https://github.com/NREL/rdtools" \ No newline at end of file +url: "https://github.com/NatLabRockies/rdtools" \ No newline at end of file diff --git a/CODE_OF_CONDUCT.md b/CODE_OF_CONDUCT.md index c18f3d799..e7799a422 100644 --- a/CODE_OF_CONDUCT.md +++ b/CODE_OF_CONDUCT.md @@ -55,7 +55,7 @@ further defined and clarified by project maintainers. ## Enforcement Instances of abusive, harassing, or otherwise unacceptable behavior may be -reported by contacting the project team at RdTools@nrel.gov. All +reported by contacting the project team at RdTools@nlr.gov. All complaints will be reviewed and investigated and will result in a response that is deemed necessary and appropriate to the circumstances. The project team is obligated to maintain confidentiality with regard to the reporter of an incident. diff --git a/MANIFEST.in b/MANIFEST.in deleted file mode 100644 index 4232463ea..000000000 --- a/MANIFEST.in +++ /dev/null @@ -1,5 +0,0 @@ -include versioneer.py -include rdtools/_version.py -include rdtools/data/* -include rdtools/models/* -include LICENSE \ No newline at end of file diff --git a/README.md b/README.md index 189a4f610..84b6b5398 100644 --- a/README.md +++ b/README.md @@ -1,13 +1,13 @@ RdTools logo Master branch: -[![Build Status](https://github.com/NREL/rdtools/workflows/pytest/badge.svg?branch=master)](https://github.com/NREL/rdtools/actions?query=branch%3Amaster) +[![Build Status](https://github.com/NatLabRockies/rdtools/actions/workflows/pytest.yaml/badge.svg?branch=master)](https://github.com/NatLabRockies/rdtools/actions/workflows/pytest.yaml?query=branch%3Amaster) Development branch: -[![Build Status](https://github.com/NREL/rdtools/workflows/pytest/badge.svg?branch=development)](https://github.com/NREL/rdtools/actions?query=branch%3Adevelopment) +[![Build Status](https://github.com/NatLabRockies/rdtools/actions/workflows/pytest.yaml/badge.svg?branch=development)](https://github.com/NatLabRockies/rdtools/actions/workflows/pytest.yaml?query=branch%3Adevelopment) Code coverage: -[![codecov](https://codecov.io/gh/NREL/rdtools/graph/badge.svg?token=K2HDjFkBws)](https://codecov.io/gh/NREL/rdtools) +[![codecov](https://codecov.io/gh/NatLabRockies/rdtools/graph/badge.svg?token=K2HDjFkBws)](https://codecov.io/gh/NatLabRockies/rdtools) RdTools is an open-source library to support reproducible technical analysis of time series data from photovoltaic energy systems. The library aims to provide @@ -25,20 +25,46 @@ command line: pip install rdtools ``` +Optional extras are available: + +``` +pip install rdtools[notebooks] # Jupyter and notebook dependencies +pip install rdtools[test] # pytest, coverage, flake8 +pip install rdtools[dev] # notebooks + test combined +``` + +Alternatively, RdTools uses [pixi](https://pixi.sh) for reproducible +environment management. To get started with pixi: + +``` +pixi install # default environment (core + notebooks) +pixi run lab # launch Jupyter Lab +``` + +For development, use the `dev` environment which includes both notebook +and test dependencies: + +``` +pixi shell -e dev # activate the dev environment +pixi run -e dev test # run pytest with coverage +pixi run -e dev nbval # validate notebooks +pixi run -e dev lab # launch Jupyter Lab +``` + For API documentation and full examples, please see the [documentation](https://rdtools.readthedocs.io). -RdTools currently is tested on Python 3.9+. +RdTools currently is tested on Python 3.10+. ## Citing RdTools To cite RdTools, please use the following along with the version number and the specific DOI coresponding to that version from [Zenodo](https://doi.org/10.5281/zenodo.1210316): -- Michael G. Deceglie, Kevin Anderson, Adam Shinn, Ambarish Nag, Mark Mikofski, - Martin Springer, Jiyang Yan, Kirsten Perry, Sandra Villamar, Will Vining, +- Michael G. Deceglie, Martin Springer, Kevin Anderson, Adam Shinn, Kirsten Perry, Ambarish Nag, + Mark Mikofski, Jiyang Yan, Sandra Villamar, Will Vining, Gregory Kimball, Daniel Ruth, Noah Moyer, Quyen Nguyen, Dirk Jordan, Matthew Muller, and Chris Deline, RdTools, version {insert version}, Computer Software, - https://github.com/NREL/rdtools. DOI:{insert DOI} + https://github.com/NatLabRockies/rdtools. DOI:{insert DOI} The underlying workflow of RdTools has been published in several places. If you use RdTools in a published work, you may also wish to cite the following as @@ -76,5 +102,5 @@ Other useful references which may also be consulted for degradation rate methodo ## Further Instructions and Updates -Check out the [wiki](https://github.com/NREL/rdtools/wiki) for additional usage documentation, and for information on development goals and framework. +Check out the [wiki](https://github.com/NatLabRockies/rdtools/wiki) for additional usage documentation, and for information on development goals and framework. diff --git a/docs/Multi-year_on_year_example.ipynb b/docs/Multi-year_on_year_example.ipynb index afb662d54..0b1b06b1f 100644 --- a/docs/Multi-year_on_year_example.ipynb +++ b/docs/Multi-year_on_year_example.ipynb @@ -15,9 +15,11 @@ "1. Import and preliminary calculations: In this step data is imported and augmented to enable analysis with RdTools. **No RdTools functions are used in this step. It will vary depending on the particulars of your dataset.** \n", "2. Analysis with RdTools: This notebook illustrates the use of the TrendAnalysis API with the new feature: `multi_yoy=True`. Because we are implementing this with the `rdtools.TrendAnalysis` object-oriented API, it requires passing kwargs to `degradation_year_on_year` as a dictionary in the `TrendAnalysis.sensor_analysis(yoy_kwargs={})` input.\n", "\n", - "For a consistent experience, we recommend installing the packages and versions documented in `docs/notebook_requirements.txt`. This can be achieved in your environment by running `pip install -r docs/notebook_requirements.txt` from the base directory. (RdTools must also be separately installed.) This notebook was tested in python 3.12.\n", + "For a consistent experience, we recommend using [pixi](https://pixi.sh) to set up the notebook environment. From the base directory, run `pixi run -e notebooks lab` to launch JupyterLab with all required packages. Alternatively, install manually with `pip install rdtools[notebooks]`. This notebook was tested in python 3.13.\n", "\n", - "This notebook works with data from the NREL PVDAQ `[4] NREL x-Si #1` system. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n" + "This notebook works with data from system 4 of the PVDAQ dataset [1]. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n", + "\n", + "[1] Deline, C., Perry, K., Deceglie, M., Muller, M., Sekulic, W., and Jordan, D. \"Photovoltaic Data Acquisition (PVDAQ) Public Datasets,\" Open Energy Data Initiative (OEDI), NREL, 2021. DOI: [10.25984/1846021](https://doi.org/10.25984/1846021)" ] }, { diff --git a/docs/TrendAnalysis_example.ipynb b/docs/TrendAnalysis_example.ipynb index 53655879b..73437b649 100644 --- a/docs/TrendAnalysis_example.ipynb +++ b/docs/TrendAnalysis_example.ipynb @@ -7,16 +7,18 @@ "# TrendAnalysis object-oriented example\n", "\n", "\n", - "This juypter notebook is intended to demonstrate the RdTools analysis workflow as implemented with the `rdtools.TrendAnalysis` object-oriented API. For a consistent experience, we recommend installing the packages and versions documented in `docs/notebook_requirements.txt`. This can be achieved in your environment by running `pip install -r docs/notebook_requirements.txt` from the base directory. (RdTools must also be separately installed.) This notebook was tested in python 3.12.\n", + "This juypter notebook is intended to demonstrate the RdTools analysis workflow as implemented with the `rdtools.TrendAnalysis` object-oriented API. For a consistent experience, we recommend using [pixi](https://pixi.sh) to set up the notebook environment. From the base directory, run `pixi run -e notebooks lab` to launch JupyterLab with all required packages. Alternatively, install manually with `pip install rdtools[notebooks]`. This notebook was tested in python 3.13.\n", "\n", "The calculations consist of two phases:\n", "\n", "1. Import and preliminary calculations: In this step data is important and augmented to enable analysis with RdTools. **No RdTools functions are used in this step. It will vary depending on the particulars of your dataset. Be sure to understand the inputs RdTools requires and make appropriate adjustments.** \n", "2. Analysis with RdTools: This notebook illustrates the use of the TrendAnalysis API to year on year (YOY) degradation and recovery (SRR) soiling calculations.\n", "\n", - "This notebook works with data from the NREL PVDAQ `[4] NREL x-Si #1` system. Note that because this system does not experience significant soiling, the dataset contains a synthesized soiling signal for use in the soiling section of the example. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n", + "This notebook works with data from system 4 of the PVDAQ dataset [1]. Note that because this system does not experience significant soiling, the dataset contains a synthesized soiling signal for use in the soiling section of the example. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n", "\n", - "An older version of this notebook (RdTools<3) included emphasis on the clear sky workflow which uses clear sky modeled irradiance rather than measured (sensor) irradiance for analysis. The clear sky analysis served to double check the sensor based result for things like sensor drift, but there was high uncertainty with this approach because aerosal optical depth (AOD), an input to the clear sky irradiance model, can change from year to year. Therefore we have de-emphasized the clear sky workflow in this version of the notebook. We also include a new notebook that illustrates the use of satellite irradiance data, which can serve as a check on the sensor-based analysis." + "An older version of this notebook (RdTools<3) included emphasis on the clear sky workflow which uses clear sky modeled irradiance rather than measured (sensor) irradiance for analysis. The clear sky analysis served to double check the sensor based result for things like sensor drift, but there was high uncertainty with this approach because aerosal optical depth (AOD), an input to the clear sky irradiance model, can change from year to year. Therefore we have de-emphasized the clear sky workflow in this version of the notebook. We also include a new notebook that illustrates the use of satellite irradiance data, which can serve as a check on the sensor-based analysis.\n", + "\n", + "[1] Deline, C., Perry, K., Deceglie, M., Muller, M., Sekulic, W., and Jordan, D. \"Photovoltaic Data Acquisition (PVDAQ) Public Datasets,\" Open Energy Data Initiative (OEDI), NREL, 2021. DOI: [10.25984/1846021](https://doi.org/10.25984/1846021)" ] }, { diff --git a/docs/TrendAnalysis_example_NSRDB.ipynb b/docs/TrendAnalysis_example_NSRDB.ipynb index 4b36060c6..1dd19eff3 100644 --- a/docs/TrendAnalysis_example_NSRDB.ipynb +++ b/docs/TrendAnalysis_example_NSRDB.ipynb @@ -7,16 +7,18 @@ "# TrendAnalysis with satellite data\n", "\n", "\n", - "This juypter notebook is intended to demonstrate how to use the RdTools analysis workflow as implemented with the `rdtools.TrendAnalysis` object-oriented API with satellite weather/irradiance data, such as NSRDB, instead of ground-based sensor data. For a consistent experience, we recommend installing the packages and versions documented in `docs/notebook_requirements.txt`. This can be achieved in your environment by running `pip install -r docs/notebook_requirements.txt` from the base directory. (RdTools must also be separately installed.) This notebook was tested in python 3.12.\n", + "This juypter notebook is intended to demonstrate how to use the RdTools analysis workflow as implemented with the `rdtools.TrendAnalysis` object-oriented API with satellite weather/irradiance data, such as NSRDB, instead of ground-based sensor data. For a consistent experience, we recommend using [pixi](https://pixi.sh) to set up the notebook environment. From the base directory, run `pixi run -e notebooks lab` to launch JupyterLab with all required packages. Alternatively, install manually with `pip install rdtools[notebooks]`. This notebook was tested in python 3.13.\n", "\n", "The calculations consist of two phases:\n", "\n", "1. Import and preliminary calculations: In this step data is important and augmented to enable analysis with RdTools. **No RdTools functions are used in this step. It will vary depending on the particulars of your dataset. Be sure to understand the inputs RdTools requires and make appropriate adjustments.** \n", "2. Analysis with RdTools: This notebook illustrates the use of the TrendAnalysis API for year on year (YOY) degradation calculations.\n", "\n", - "This notebook works with data from the NREL PVDAQ `[4] NREL x-Si #1` system. Note that because this system does not experience significant soiling, the dataset contains a synthesized soiling signal for use in the soiling section of the example. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n", + "This notebook works with data from system 4 of the PVDAQ dataset [1]. Note that because this system does not experience significant soiling, the dataset contains a synthesized soiling signal for use in the soiling section of the example. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n", "\n", - "In prior versions of RdTools (RdTools<3) we emphasized a clear sky workflow which uses clear sky modeled irradiance rather than measured (sensor) irradiance for analysis. The clear sky analysis served to double check the sensor based result for things like sensor drift, but there was high uncertainty with this approach because aerosal optical depth (AOD), an input to the clear sky irradiance model, can change from year to year. Therefore we now recommend using satellite irradiance data to check that the results with ground measured irradiance are sensible. This can help catch problems with sensor drift." + "In prior versions of RdTools (RdTools<3) we emphasized a clear sky workflow which uses clear sky modeled irradiance rather than measured (sensor) irradiance for analysis. The clear sky analysis served to double check the sensor based result for things like sensor drift, but there was high uncertainty with this approach because aerosal optical depth (AOD), an input to the clear sky irradiance model, can change from year to year. Therefore we now recommend using satellite irradiance data to check that the results with ground measured irradiance are sensible. This can help catch problems with sensor drift.\n", + "\n", + "[1] Deline, C., Perry, K., Deceglie, M., Muller, M., Sekulic, W., and Jordan, D. \"Photovoltaic Data Acquisition (PVDAQ) Public Datasets,\" Open Energy Data Initiative (OEDI), NREL, 2021. DOI: [10.25984/1846021](https://doi.org/10.25984/1846021)" ] }, { diff --git a/docs/degradation_and_soiling_example.ipynb b/docs/degradation_and_soiling_example.ipynb index 390e4a03f..6afc6e07c 100644 --- a/docs/degradation_and_soiling_example.ipynb +++ b/docs/degradation_and_soiling_example.ipynb @@ -7,7 +7,7 @@ "# Degradation and soiling example\n", "\n", "\n", - "This jupyter notebook is intended to the RdTools trend analysis workflow using the functional API. In addition, the notebook demonstrates the effects of changes in the workflow. For a consistent experience, we recommend installing the specific versions of packages used to develop this notebook. This can be achieved in your environment by running `pip install -r requirements.txt` followed by `pip install -r docs/notebook_requirements.txt` from the base directory. (RdTools must also be separately installed.) These environments and examples are tested with Python 3.12.\n", + "This jupyter notebook is intended to the RdTools trend analysis workflow using the functional API. In addition, the notebook demonstrates the effects of changes in the workflow. For a consistent experience, we recommend using [pixi](https://pixi.sh) to set up the notebook environment. From the base directory, run `pixi run -e notebooks lab` to launch JupyterLab with all required packages. Alternatively, install manually with `pip install rdtools[notebooks]`. These environments and examples are tested with Python 3.13.\n", "\n", "The calculations consist of several steps illustrated here:\n", "
    \n", @@ -22,7 +22,9 @@ "\n", "Earlier versions of this notebook (RdTools<3.0) included a clear sky workflow in order to check the results for bias from sensor drift. With the wide availability of satellite data, we now recommend repeating the analysis with satellite data to double check the sensor-based result. This is illustrated using the object-oriented API in `TrendAnalysis_example_NSRDB.ipynb`\n", "\n", - "This notebook works with data from the NREL PVDAQ `[4] NREL x-Si #1` system. Note that because this system does not experience significant soiling, the dataset contains a synthesized soiling signal for use in the soiling section of the example. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal)." + "This notebook works with data from system 4 of the PVDAQ dataset [1]. Note that because this system does not experience significant soiling, the dataset contains a synthesized soiling signal for use in the soiling section of the example. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n", + "\n", + "[1] Deline, C., Perry, K., Deceglie, M., Muller, M., Sekulic, W., and Jordan, D. \"Photovoltaic Data Acquisition (PVDAQ) Public Datasets,\" Open Energy Data Initiative (OEDI), NREL, 2021. DOI: [10.25984/1846021](https://doi.org/10.25984/1846021)" ] }, { @@ -30,10 +32,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:26:13.141622Z", - "iopub.status.busy": "2026-02-04T19:26:13.140622Z", - "iopub.status.idle": "2026-02-04T19:26:17.065980Z", - "shell.execute_reply": "2026-02-04T19:26:17.065980Z" + "iopub.execute_input": "2026-03-20T15:40:03.434045Z", + "iopub.status.busy": "2026-03-20T15:40:03.433440Z", + "iopub.status.idle": "2026-03-20T15:40:06.636469Z", + "shell.execute_reply": "2026-03-20T15:40:06.635075Z" } }, "outputs": [], @@ -51,10 +53,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:26:17.068991Z", - "iopub.status.busy": "2026-02-04T19:26:17.068991Z", - "iopub.status.idle": "2026-02-04T19:26:17.080496Z", - "shell.execute_reply": "2026-02-04T19:26:17.079990Z" + "iopub.execute_input": "2026-03-20T15:40:06.638962Z", + "iopub.status.busy": "2026-03-20T15:40:06.638591Z", + "iopub.status.idle": "2026-03-20T15:40:06.649321Z", + "shell.execute_reply": "2026-03-20T15:40:06.648220Z" } }, "outputs": [], @@ -76,10 +78,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:26:17.083512Z", - "iopub.status.busy": "2026-02-04T19:26:17.083512Z", - "iopub.status.idle": "2026-02-04T19:26:17.085952Z", - "shell.execute_reply": "2026-02-04T19:26:17.085952Z" + "iopub.execute_input": "2026-03-20T15:40:06.652063Z", + "iopub.status.busy": "2026-03-20T15:40:06.651704Z", + "iopub.status.idle": "2026-03-20T15:40:06.655295Z", + "shell.execute_reply": "2026-03-20T15:40:06.654606Z" } }, "outputs": [], @@ -109,16 +111,16 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:26:17.087964Z", - "iopub.status.busy": "2026-02-04T19:26:17.087964Z", - "iopub.status.idle": "2026-02-04T19:27:47.520756Z", - "shell.execute_reply": "2026-02-04T19:27:47.520756Z" + "iopub.execute_input": "2026-03-20T15:40:06.657430Z", + "iopub.status.busy": "2026-03-20T15:40:06.657147Z", + "iopub.status.idle": "2026-03-20T15:41:50.529683Z", + "shell.execute_reply": "2026-03-20T15:41:50.528520Z" } }, "outputs": [ { "data": { - "image/png": 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", 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", 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    " ] @@ -193,16 +195,16 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:27:47.574769Z", - "iopub.status.busy": "2026-02-04T19:27:47.573846Z", - "iopub.status.idle": "2026-02-04T19:28:55.133218Z", - "shell.execute_reply": "2026-02-04T19:28:55.132714Z" + "iopub.execute_input": "2026-03-20T15:41:50.576933Z", + "iopub.status.busy": "2026-03-20T15:41:50.576427Z", + "iopub.status.idle": "2026-03-20T15:43:03.651629Z", + "shell.execute_reply": "2026-03-20T15:43:03.650121Z" } }, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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v3LjRsz0pChQooBag9ygeeeSRJI+D2QtA2diJ+fMXS/Pm1rysfEncUT5WyjmneU758qhIo8BtP0O/Az0+t/ViXatAVqxYkSA8NhTC3R+0aNFC3nzzTRk/frxnHAhMWlOmTFEj0vVeAnoZly5dkuLFiwc9H0xO169fl+eff96zDk51XyWBcNnRo0crX0rFihXFTvTcINK8uTgOvOiRfMEjff5ocO3aNY+PzkoiWZbVqlWTauJ+mvRZLF84/HmMmAKBSSgaQEm0bNlSVfzHjx+XIkWKKMc4ru/dm8HgwtWrV4umaZ51SEOC8SA4R+rUqVWE1ddffy1DhgyRypUre/YbO3as2gbfCHoqMI9NnjxZKSWMRoc/hBBvKvdZ7AluMJNL10SyWqA/nNBrchq7JDaxlQ8ETJ8+XQYOHKgqc4Teli1bVr744gvlFA8GHOaff/65LFy4UG7cuKGO++STT5RC8uaee+5RI9onTpwop06dUmNBMM4ESqRevXpiB5xiGvHlXhH5xoXlciJC5y332teW9aJ2v1JPSgxaIbGC03urdsVWUVh6yC5SmaBngOgrpDdp2LBhgn1WrVqVoPcBGjdurHwl8J9cvHhRjVz3VR56Diz0THB+pECBklq6dKltlIcVmFUpT4rySxpJZRKpCseqiqySz/dgEY0kNOKplIwrkCVLlqjKOGfOnMpkhMF4vgshxB7MZWVH7KJA5s2bp/JM/fHHH/Loo4+qkDpkwsX/aNnAfPTyyy+bLy0xjZlNg4c1E/fh1jE4biTOISZsQwoEI7LhN0COqUGDBnlCfWfOnKkc2TAPFSpUyGxZY5ZIPEzwBTkRVn5Ep5vNKtk4m8ljWwXy008/qd4GzFQwX+khiSAuLk66du0qI0aMMFdSYjlz5tjvBYE/i8QmX4i7iHdgz9CQAsmYMaMn3BUjvDE6Wx8tDm677TbZv3+/eVISW9DHfzJkS+my4u+GC4k9mlgtgCQOTog1DCmQu+66S/VCdDBCHGG3GLSHyCmkRtdHgxNntEYi0f2OxS59uLCMwn8vMLq9fZWc0q55TrGauQ7sNViuQB566CGVd0pPfNi/f38VWoveCEZ5IxNunz59zJaVWIAdu9V2lAmMHk2FGQ2QGsX7kzhMgSDNCEZu64kFEZEFBYJ5yJ966in55ptv1NzmhMQSo3+3WoLYoJx2SuKPnFKfdiMuxnrdpg0k/M9//iNvv/22ymVVt25ds05LIvhgRqIlb0XvwMqX1sjvtWMPykkV34ubRb498vcnsRbbjUQnxI788MMP4jZutVoAEpsKBGlEMIETxoIgg62/Ueh6eC8hkSBflIu16cyD4jY22bAn5ETiY7gcDdXyvXr1krfeektFX7Vr106yZ89uvmTEsUkVo8Ealg0hzlQgSLGOSZqQ7Za4ByfPsREJ2anA7Y8dn9k4G8pkKxPW5cuX5b777jNfGkIIIQonWB8MKZB7771XNm9mCEQs4oSH2mn4Tk1AgvNGBZaQoxXI+++/Lxs2bJDXX39dTcpEooNTQnmdPmdHNPisVR7P/4X6fmmpLE6jVSv73fd4k55Fpz3ThlOZ7Nu3T80ceOutt6pZ/bJkyZJgyZo1q/nSEuKS3lGFCmxGkxh1osOBniJFCvOlIbYkXGfy8PL2TLxI3IPTWupuxZACmTp1qvmSENdEAj36aGPpsz06MjuxfIg72fVqQyn96tKYisTiSHRCiIKKOHmkj8Gx04Z+8vTp04Nuh3krffr0ki9fPmXr1ZMuEvvj9JaT1fJbfX1iHaljMPuGoV+MTLu6D8Q3BNF7Pf6HQ71v375q9Doh5F829KwoP/0uUvJ260qFJkASdRPW9u3bpWzZsirr7rx582THjh1qmTt3rtSpU0elOFm7dq3ahh4IFMi4ceOSJShxbiiv28veaPndfvvt0nHOVqk2eivNRyR2FAjStmPa2uXLl6vJpcqUKaOWhx9+WK3DpFKTJk2S5s2by7Jly6RatWpq7AghkYAKkNiRuBgI7jCkQObPny/NmjXzuw1mqwcffFA+++yzvy+QMqUK+/3tt9+SJykhFnAnS50QcxXIzZs3Zc+ePQG3//zzz2ofHTjR4VQPBUyT27t3b8mbN69kyJBBqlatqnoxoTBnzhxlMsO10Avq1KmTnDx50u++6CGVKFFC7Vu0aFF57733xM4tbO/FaS0rJ7fEVtigvIlziDf5eelg83fHkAJBDwMmqTFjxsiVK1c86/E/KuIPPvhAmjZt6lm/fv16KVKkSMgOeqSKb9u2rbzzzjtqbpFGjRrJmjVrgh4HH0ubNm0kR44c6nhMrwuFgrxd3jICzGXSuXNnKVWqlJK3evXq8txzz8mIESPCLgtiD+ykYAkxi1XiwigsVOx79+5VlS7mR8+T5++8PseOHZO//vpLTTSFfQAqb/QkXnjhhSTPu2nTJlXpjxw5Up0XtG/fXkqXLq2iuNatW+f3OFyzX79+UqtWLdVb0SPBatSooRTZhAkTpHv37p5Mwv3795fGjRsrpz+AskGPafDgwdKlS5eYn9/EXyjq6mdKS+1xu0J+RsqJyI6Q9yaE+KOOiPt6IGjlI8oKFfDjjz+ucmNhwf9Yh4oe+wCYiFCBo3eQFDgWPQ5U4jo4HqYo9GIOHTrk97hdu3bJ2bNnpXXr1glSrDRp0kQyZ86slJLOypUrVQLIrl27JjjHs88+KxcvXpTFi+3dZbSKggULhrX/AvYEQuIOn0/iLuIMmKC8e9NTbf4eGR75gooaUVdYzGLbtm1SrFgxNXbEG/Ro9PDh/Pnz+/WbAPR0fME6nBc9DDj08T+oVKlSgv0qVqzo2Y5ZFv2B6+jXAufPnxe3UF9EQvM0ETNZa/MKghDHpDKBCUw3h3mjrzt69Kjf4+AEh0JDr8gbOPpPnDihzFZnzpzxXAO9HGQR9iZt2rSSM2fOgNcAw4YNU1mG9cWfMnMqE1iREZgdd9DwSEzugRQqVEi1zhFdlSZNGvU9qWy82A4/STigoveX9kSP4MJ2f+TKlUtatWqlptpFZBXGphw5ckT5PSDvtWvXPMfiE8rCH7hOoGsADIj09uWgB+ImJUJIs9mHJb4cPFjEKPExlOAzJAVSu3ZtpRCgRLy/mw3MTd4mIh09isqfico7sgqVP5zvugMepqjChQurMSnwhejngNPdH7rDPxBQbszrRQghYSgQ3/TtkUrnDlMVeg6+wOwEMDYkEDApLViwQA4ePCjx8fHK6YsFkVgYE5ItWzbPNW7cuCHHjx9PYMaCUoFzPdg1CAmFTz9dLC1bOse3EUstZivo2WexjHapidhWPhDk0Prll18SOac3btzo2Z4UBQoUUOG8UB6IzNq6davcd999Ca4BtmzZkuA4fIejPZRrxAJJVShfffVVWOcbMMAdFVS/fkn/jv9tjYooxCHMF/diOJni7NmzE6xbunSpqrgxclwfAxIuLVq0UL2D8ePHe9bBpDVlyhR1Xt3fgF4G/DFJAZ/F9evX5fnnn/esq1evngox9k3uiO8ZM2ZU40NI0jy96kZYxfTRdXeU6qx/EywkYFTlaEtCiEPDeDGoD5WtPrZj//79ynGNKCaYgOBohi/BezxHKEBJtGzZUlX8MDFh9Doc4zBJIfWIDgYXrl69OkEq+eHDh6vxIDgH8vIjX9fXX38tQ4YMkcqV/327IRcGDGLcB67VsGFD+e677+Sjjz6SoUOHesavEBIOjzzSWF7c7I5eFkk+8TFiFkxtNNTvf//7X4IJphAaizEUiIjCgD6kMwlXgejnGjhwoMyYMUOF3iJt/BdffKF6N8FANuDPP/9cFi5cqHoxOO6TTz5RSsIXDCJEdNaoUaPU/ujZIMNwjx49wpbXTSSVBiTcl8ItL5FbfgchtlAg586dU70NnS+//FLq16+vlAfA/0uWLDEkEEJpkcoESyBWrUqcIQamp3DMT0hfgoUQQiJNnEtnqjTkA0Ek0+7duz0RUnBUN2jQwLP9zz//9IT8EkIIcSeGeiCYCwRZbDFuAhFSGBsBH4i3ievOOzmTAiGEuBlD3QQ4ppEDC34KOLsxLgQzFAKE4CIponePhBDiHOjvMYd4F5qsTOmBYFT3zJkzA247fPiwitIihBDiXgxn4w0EfB8YFU4IIcTd0NNNoobbTSPvVBepV/DvT6cRC+YWq4lz4fNveg+ExA5Tpy6WDh1Y8eg0a9ZYmll6RwiJLuyBEMO8mnQ2GUJimvribqhASFjcE2Z5udE04kZTBIkME1z4/HtDBULCYqbLXwhCSIR9IN9++23Q7ZhsCilJ8uXL53eKWkIIiUXiXJbSxJACqVOnTsgzEmK+8kGDBqkEiyQ2ccMLw4SKhJikQDCZUO/evdVcHUhIiLTr4Ndff5WJEyeqlOkDBgyQAwcOqKlmH3vsMZWtF/N9EEIIiXEFAhMV8mClTZs2Uap09FA2bNggI0aMkKeffloqVaqk/qcCIYTEGvEung7AkBMdaUzQq/BVHgCKpW3btmoiKP17u3bt5Keffkq+tISQqODWCo/YQIFcvHhR/vjjj4DbkeIdKd11smXLpkxYhBAS63R3kXI2pEAwr/jo0aPVTIG+LFq0SM2Jjn2851CPi4tLnqSEkIjihmAHJ7BIYtwHMmbMGKlbt66aF+SOO+6QwoULq/V79+6VI0eOSMGCBdV8IQBzhhw8eFA6d+5sruTEFtTvs1iWseIhJCYxpEAKFCggP/zwg5r3fOnSpSraCpQoUUJ69uwpTz31lGTKlMnjA8GUt8Sd/Gq1AIQ4gHiXOtINJ1PEfB8vvPCCWkhs8XpZkX47rZaCEGI1TGVCwuaxx2grJyRcvmhXUHrVK6g+JdZ7IDBdTZo0Sfbt2ydnzpwRTdMSbMdIdfhECHEjbktJQSJP6dKlpXRpd5W0IQUycuRI6dOnj5oHvUqVKlKmTBnzJSOEEOI+BaKH6cI5niZNGvOlIoQQ4k4fCExWSEsSCeWB/FrIs5U3b16VU6tq1aqybNmykI5dvny5Ci/OlSuXGryI3tGMGTMS7Qfzmr9l+PDhpv8e4h5osiLEhB4IKuY9e/ZIJOjQoYPMnTtXhQMjk+/UqVOlUaNGsnLlSqlZs2bA4xYuXCjNmzeX6tWry6uvvqoUwieffCLt27eXkydPyvPPP59g//r166tt3tx9990R+U2EOBH6eUhEFMj7778vDzzwgEqSiJxYZrFp0yaZM2eO8rG89NJLah0qeTifevXqJevWrQs6uBFzj6xYsULSpUun1mE8SvHixZUS8lUgxYoVUzm6CCGERNGEhbk9rl+/Lv/9738la9asUqpUKSlbtmyCpVy5cmGfFz0P5Mzq0qWLZx0GInbq1EnWr18vhw4dCnjs+fPnJXv27B7lAVKnTq3MWTCF+ePy5ctqpDxJHm4cIBWr0ExHIq5AcuTIocxLtWrVkgoVKsitt94qOXPmTLBgn3DZtm2b6hlkyZIlkclMz6kVCKSQ//HHH2XgwIHy22+/qRDiwYMHy5YtW1TvxRf0SjBaHsqlZMmSMmvWrJD8M1BU3gshhMQqhkxYq1atMl+Sf7L4+psCV1939OjRgMdCcezfv1+GDh0qQ4YM8YyWnzdvnsrZ5U2NGjWkVatWUqhQIXXOsWPHqhT0586dk2eeeSbgNYYNG6ZmVySEEGKzkegwKXmboLzNWPr2QOA49F4QHTZ79mz56KOPlI8Gfg5MbuXN2rVrpUePHvLggw+qCa+2bt2q/Cz9+vULeo2+ffsqJaMvwUxqboemDkJISD2Qb7/9Vn3CZOX9PSn0/UMF5iSYiXzR/RSBfBmgW7duSlF8//33kjLl33oRvQz4Z6AsMHtiIDAxFo7XlUmgaC8oKX8KjhBCYpGQFAj8CwiLRescla3+PRBIa4LtN27cCEsYmKqQDt6faQtgbIg//vrrL5VWBb4OXXkAjFNBtBgitLCPvxkUdfLnz68+T58+HZbMhBASq4SkQDAGA+gVsP7dbMqXL6/ODee0tyNd7z1guz9OnTqlosL8Kaxr167JzZs3k1RmyOkFcufOncxfQQghsUEKzTcLooVAUVSrVi3BOBCYtOCfQGSX7svABFWXLl1SYzwAlAPCdRENhnlKdEWHaXUxR0nmzJll9+7dat2JEycSKYkLFy6oQYTwa6AHFKyn4g0UHcKYcZxv5Fishe/SJ+IeeF9jm/Nh1GuGs/FGAqQtadmypXJWHz9+XIoUKSLTpk2T+Ph4ZaLSweDC1atXezIAY+wIFM6AAQOUAsJ2KBUcc/jwYeVQ10HE1fz586Vp06ZqYiyYxyZPnqyUEtKehKo8CCEk1glJgXTs2DHsE8MH4l3ph8r06dNVSC4qc+TcwqBEzL2elEO+f//+KiwXiR4RaoueC47F4MRHHnnEs98999yjRrRPnDhRmb4wFgTjTKBEvOdxJ0nDXgchsU1IJqy4uLigTnO/J06RwuNXcCuxbsIisZFZgA2F2OK82SYsmJAIIYQQ2w4kJIRYD3scJFSoQAghhBgiJBMWBudhQegsopTwf1I+EWzH2AxCCCExrEBefvllpRCQHt37OyGEkNglJAWCGf6CfSeEEBJ70AdCCCEkugoEscIYsIdBeLfddpta8P9rr73GiZYIISQGMKRAMAkTckdBgSDfFEZ3Y7l48aIyb2GWQj2DLiGEEHdiKBdW79695ffff1cpRho1apRg25IlS1Q+qz59+qg8VoQQQtyJoR7IV199JT179kykPADm33juuefkyy+/NEM+QojFbN++3WoRiJsUCExV8HkE4vbbb1f7EEKcT/M5iSd5I8SwAilZsqSadxyz/PmbwAnbsA8hxJl8UCeV1SIQN/tAWrduraKuunbtKsWKFVPr9+zZIx988IHs3LlTPv74Y7NlJYREifvvv19kVcKsvISYokDgJIeJCo7yp59+2jMqHZnhMSsg5tZo0aKFkVMTQghxCIZnJOzQoYO0a9dOtmzZIgcOHFDrChYsKJUqVfKkPCGEEOJeklXTQ1FgClkshBBCYouURsP64Cj3ZunSpWraWcxrjmllCSGEuBtDCqRXr14JnOT79++Xhx56SH2CF154QcaPH2+elIQQQtyhQHbs2CE1a9b0fJ8+fbqkSpVKtm3bJhs3blQOdERjEUIIcS+GFAgmW8+ZM6fnO0ad169fX3LlyqW+4//ffvvNPCkJIYS4Q4HkyZNHdu/erf5H0sStW7dKgwYNPNuRYBGzFhJC3MGJEyesFoG4JQqrWbNm8t5778mVK1eUySpdunTKB+Jt4rrzzjvNlJMQYiGVR22S+OGNeQ9I8hXIkCFDVItkxowZki1bNpk6daonNxbmCZk7d648++yzRk5NCCHEIRiyM2XOnFlmzpwpZ86cUZFXGJnuve3w4cMyePBgQwJdvXpVpUrJmzevZMiQQYUFL1u2LKRjly9fLnXr1lW+GCg2pFqBkvPHpEmTpESJEpI+fXopWrSo6lERQv6FPQ6SFKY7KuD7yJo1q6RJk8bwCPe33npL2rZtq8aTILoLaePXrFkT9LiFCxcqPwwSPGJSq6FDhyoF1L59e3n77bcT7Pvhhx9K586dpVSpUkpxVK9eXaWgHzFihCGZCSEkFkmhIYGVTdi0aZPqcYwcOVJeeukltQ5+ltKlS6scW+vWrQt4LJTHjz/+KPv27VM+GXD9+nUpXry4ZMqUSfllwOXLlyV//vxq9DwmxNJBWpb58+fLoUOHJHv27CHJC3MdlCWi0rJkyZLMX0+I/Yjr829CRfZIYoPzYdRrtgqVgu8EPY4uXbp41sHE1KlTJ1m/fr2q3IP9aFT8uvLQU63AnIWeiM7KlSvl1KlTKouwN/DZIEHk4sXMQEoIIaFgKwWCgYhIDe+r9eDLSGpmtDp16qgeyMCBA9UYlL179yo/DJI9YuS89zUAkj56U7FiRWV+07cH8s9AUXkvhBASq9gqbS7GlGCMiS/6uqNHjwY8FooDDn34PhAlBjJmzCjz5s1TYcfe10AvByYxb9KmTasGRwa7xrBhw2TQoEGGfhshhLgNW/VA4J/wNkF5m7H07YHAcei9II0KEj1+9NFHqpcB38aGDRsSXAPKwh+4TrBr9O3bV9kF9SWYSY0QQtyOrXog8FXATOQLHOn69kB069ZNKYrvv//eMwq+VatWKtKqR48easCjfg5/U/Hq1wl2DSgpfwqOEEJiEVv1QGCqgonJF30dxob4AwoB4zoaN26cIIUKQokfeOAB5QfRlQaucePGDTl+/Hiic8C5HugahMQ6o0YxwITYWIGUL19efvnll0TOab33gO3+QMWPkF0oBl+uXbsmN2/e9GzTzwGl4g2+Y79A1yAk1nmP6bCInRUI/Beo6L3nEoFJa8qUKWp8CMZvgIMHD8rPP//s2QcOcYw8//zzzxOYp5DUcdGiRWosiG6aqlevnuTIkUPGjRuX4Nr4Dqc7ejGEkL95gR1y4hQfCJQE0qLAWQ0TU5EiRWTatGkSHx+vTFQ6GF2+evVq0cdAIqoKAw8HDBigBghiOxQRjkFaFTjUdaBIEN6LcR+4VsOGDeW7775T+yCCC8qFEPI3zz3XWN7yGkxIiG0ViD45FUJykcMKubbKli2rRoxjutxg9O/fXwoVKqTSnyDUFj0XHIvBiY888kiCfTGIEP6RUaNGqRQo6Nkg3Qmc7YQQQhyYysRpMJUJiQWYziS2OO/UVCaEEEKcAxUIIYQQQ1CBEEIIMQQVCCGEEENQgRBCCDEEFQghhBBDUIEQQgyF9BJCBUIIIcQQVCCEkKDMaZ6TJUT8QgVCCAkK8ssR4g8qEEIIIYagAiGEEGIIKhBCCCGGoAIhhBBiCCoQQgghhqACIYQQYggqEEIIIYagAiGEEGIIKhBCSFgwHxbRoQIhhBBiCCoQQkiSxA9vzFIiiaACIYQQYggqEEIIIYagAiGEEOIOBXL16lXp3bu35M2bVzJkyCBVq1aVZcuWJXlcXFycpEiRwu9StGjRBPsG2m/48OER/GWEEOIuUovN6NChg8ydO1d69uypKv6pU6dKo0aNZOXKlVKzZs2Ax40ePVr+/PPPBOsOHDggAwYMkAYNGiTav379+tK+ffsE6+6++24Tfwkh7mLaA5llwVGRZnmtloTYBs1GbNy4UYNII0eO9Ky7fPmyVrhwYa169ephn2/w4MHqfGvXrk2wHuueffbZZMt77tw5dS58EkKIGwinXrOVCQs9j1SpUkmXLl0869KnTy+dOnWS9evXy6FDh8I636xZs6RQoUJSo0YNv9svX74sV65cSbbchBASi9hKgWzbtk2KFSsmWbJkSbC+SpUq6nP79u1hnWv37t3y2GOP+d0O01imTJmUn6VkyZJK2RBCCHGoD+TYsWOSJ0+eROv1dUePHg35XDNnzlSfbdu2TbQNPZJWrVqp3gnOOXbsWLXfuXPn5Jlnngnq4Meic/78+ZDlIYQQt2ErBQKTUrp06RKthxlL3x4KN2/elDlz5iineIkSJRJtX7t2bYLvHTt2lIoVK0q/fv2UEx+9En8MGzZMBg0aFOKvIYQQd2MrExYqbu8Wvo7upwhUsfuyevVqOXLkiN/ehz/Spk0r3bp1k7Nnz8rWrVsD7te3b1/VS9GXcH0yhBDiJmzVA4GpChW/P9MWwNiQUM1XKVOmlDZt2oR87fz586vP06dPB9wHvSN/PSRCCIlFbKVAypcvr8Z7wLfg7UjfuHGjZ3tSoAczb948qVOnTsgKB+zbt0995s6dO+Rj/o4Ipi+EEOIedN+uXr8FRbMRGzZsSDQO5MqVK1qRIkW0qlWretYdOHBA2717t99zfPbZZ+ockyZN8rv9+PHjidadP39ejTXJlSuXdvXq1ZDlPXTokLoWF5YBnwE+A+KyMkD9lhS26oEgbUnLli2Vr+H48eNSpEgRmTZtmsTHx8ukSZM8+2EEOfwc/jQkzFcwMz3yyCN+r4GIq/nz50vTpk2lQIECyjw2efJkOXjwoMyYMUP5Q0IFPRz4QW655RaVCsWfJodpDPv4hibbBSfI6BQ5nSCjU+R0goxOkTNcGVGvXrhwISQLjq0UCJg+fboMHDhQVeZnzpyRsmXLyhdffCG1atUKqaAWL14sjRs3lqxZs/rd55577pF169bJxIkT5dSpU2osCMaZQInUq1cvLFnhZ8mXL1+S++Gm2fXhcpKMTpHTCTI6RU4nyOgUOcORMVD96UsKdEOSKRcJotBwIxCxZdeHywkyOkVOJ8joFDmdIKNT5IykjLYK4yWEEOIcqEAiCHwxr7zyiq1Df50go1PkdIKMTpHTCTI6Rc5IykgTFiGEEEOwB0IIIcQQVCCEEEIMQQVCCCHEEFQghBBCDEEFQgghDkazcCgfFQixDI5hJXYEA+6cwMcff6w+/aVRihZUIGGAaXKRM8v7AbNbJXjp0iWxO8h8DDntPh/9jh075Ndff5XDhw/b9n4vWLBAunbt6skmjcnU7Mjs2bNVzjjfydzsxGeffSYNGjSQt99+W+Xfsytz5syRwoULq+kq1qxZY6ksVCAhgLnVa9asKffee6+UK1dO5c5Cyvjr168r7W+HSmXPnj1qVsXOnTuLXdm5c6fKU4ZElphOGCn3UaHYofx85axfv740adJElSnu+bvvvuu533Zh2bJl8tBDD6m8ccgXp+dns1ujC0lSMesn7r0d031gWmvIhiStSKaaMWNGtdiNbf+U5eOPP66UMWZq9TcBX1QJOXd5jPLHH39od999t1ajRg1t8uTJaqlWrZqWLVs27ZVXXlH73Lx50zL5cO25c+dqxYoV01KkSKGWVatWaXbi+vXr2rvvvqvlzp1bq127tvbyyy9rXbt21fLnz68VL17cNvL+9ddf2tChQ9W9hZzvvfeeNnv2bK1OnTpalixZ1FQBdkB/3rZu3arlzJlTy5Ahg5ruYPv27Wr9jRs3LJZQ0y5duqQ98cQT6nlEWS5YsEC9S3YE73GJEiW0mTNnagcPHtTsxrlz57T27durssSziLJcvHixlj59eu3NN9/0vGNWQAWSBHPmzNFSp06tKmmdw4cPa61bt1Y3dPny5ZqV7N27VytdurSqSIYMGaKVLFlSKbhr165pduGrr77S7rzzTq1jx47azz//7Fm/du1aVYa9e/e2hbx4KStUqKD17NlT++WXXzwv5a+//qrkfOONNyxtLPiCZ7JBgwbaBx98oOTr16+fR2Yr5YQMUMSQ6cknn9ROnDgR8P5aXZ5QGLfddpv23HPPJVpvBzkvXryoFS1aVL0/48aNU3MhgX379mnZs2fXHn74YUsbDFQgSTBixAgta9asnpuEVqre+qtSpYqqvK1sWeGBQsWhtz7Hjh2rXtyJEydqduGtt95SLTzvybz0ibug7OrXr2+LymTNmjXaqFGjEk069vnnn2u33nqr9vHHH9tCTv36GzduVM8muO+++7Q8efJoy5Yts4WMW7Zs0e655x7Vw9RBy/nxxx/XevXqpXry4UzeFim+/fZbLWPGjKrBAKZPn64aYViaN2+uzZo1yzLZbvxT56xbt07btWuXp+7RqVy5suqRYNI9q+43FYjPzfK9EW+//bZ2yy23aCtXrlTfvVt4qFDSpUunvf76636PjZaMeIB09uzZo1ql+fLl006ePBlReZKS0VtOyOW9XS9LvAA1a9bULl++bJmcwfjuu+9UIwEmrFdffVX74YcftDNnziQ4h1UyogeC2TrBtm3bVMMBFfTp06eDHhctOfWe0YsvvqieSfwPefE+4X+0nlExep8j2jJC0cHCgEYClFrKlCm1Fi1aqHJEowFyTpkyJaKyhftcYhv2e/bZZ1UDQn8erVAiMa9AdLu3b4tdvxlo0UFJoPLQ1+k3+ffff9datWqlbPuRbE0FkjEQUGywi6OlFy3ClVFXMPAvwRyor7ODnPr9hWkNFUjdunVVhdKpUyflH3n00UctlVEvp02bNqnK+OjRo+o75MOzqreaYf6wQk5dPvSOURmjDOvVq6dMmVh35MgRbfDgwaqybtmypSUyeisQTGXdrl07rVy5ctrAgQO1CxcuqG07d+7UGjZsqMzDgabQtur9AZAVZbtw4ULNKmJagaD7WqpUKXUT0EL66aef/FZksIujokPr03c7HG9owcA+6e/YaMnovQ4mGPgb4GTTW3iRrJzDkdEbzLmcKVMmbdiwYVFxBIYqp/4drVIoY/Tk9HV9+/ZVFd/IkSMj0nIOpyw/+eQTFTyhm1DPnz+vzDFQeHBg//e///UoF7MJVU68Hx06dFD+Lt9tbdu2VS1ovQK06t2BqQ33FIoE5iJvvv76ay1Hjhxajx49ItZT+jbM90eXAb1jHIPnINj+kSRmFcj69euVfTYuLk61gnAj4O/wdvbpFRpst9gOJ7VuatG3wTQDc1GXLl1Mf7hCkTEQ33zzjXbHHXdoDz30kKkymSkjXhzsv3Tp0ojKGK6cwV5EONRhhkFr1dt0GE0ZdflQgUBhQBHrtGnTRkuVKpWWJk0aFV30559/mipjqHLqMiKCyNenpO+3YcMGdax37z6aMurvMHpGegSj3tPQLQqQ/f7771cRg2bf7+S+P2gcwpHevXt39Z0KJIpAy6O7/+mnn6rv//nPf1S0A1pK/mjUqJGWN29ebdGiRYlay2g9IMzO7JsYroze10fFoXdxoUzA6tWrlTI0U04jMuq8//77qvemmwxQpogqg1nBTBmTKyfwbhxUr15dOf/NrlB8ZaxVq1ZQGREheNddd2lnz55VPjr4kqA84K+BkoOCiUTFYrQsfU3AiM6CSTASptZwZURvCO/KU089pb57V+Aww8GpDmVotZzeQLkVLFhQu/fee1Xv0wpisgeiV/7eLSO9NYxwPv1B8a40YLvNnDmzqji+//57z3q0ovDCDho0yBIZ/VUOutwImYX5rUyZMko+tKJgzzUraiw5MoKmTZuq8TUAreiPPvpImQoh86lTp0yRMbly+vYq0VtC6x6hvmYSjoy6nGgYpE2bVmvSpIlSHDDF4BiYNPTK0GzfnJlliQYEjpswYYIlMnrLg+cP77Fvj/jHH3/UChcurHwkZivi6yaUJQIR0IBFg5E9kAiAVhpepOHDh6ubo+Nd2PrNgKMULaL58+f7vdFTp07VChQooBUqVEgNjIPDC5UgKmY43KyU0R9QerA/693zZs2aJTB3WCUjjkGvA2GncEhjLM2DDz6oZIS5AONs7FaW8CWg94lBcWiN6v4wK2VEK7Vs2bIqRHrMmDHq3urPKpQJxmAkR4FEqiwRfAL/EmRHeSYnWtDM9xvnwjMJnwfKDtGVDzzwgDITJdfMOicCZYljYVbHe6NHOUZbibi2B4KHFBEUcNKiRYuHAF1F2IX1sDffQVeouNDLgFbXK1rcVO+bglHTeDnh/ENrHi8Bxg9YLaMvMF+gMoZzEK36UE010ZLxt99+U/Z7nBP7whSjm9rsJCfuNyoTmDEQ8QTfx+bNmy2VUTevIHIHlRGUma4o9OOSExYdybJ8+umnlZ8G++Lc+vglu7zfeE9wXlTgCOPFu+Nd4Vsppz8wzAAKxHugczRxrQKZNm2aakkgCgStR5hE0BpHJYA0Gr7oNw+hdKh0x48fn+DB8v4fLyfMQEYrkkjJ6A1a9TBvoGVqRxlXrFihHny8pMmVMZJyotcBfwLGq2CcgN1kjESLM1JliUoOFSPSriTXbBXJ9xvKGJX7jh07kiVjJMtSVyjHjh1TlhGrcK0CQdcY/gpvEBeP7iEqLqSt8KfZ0aqDzRMPuT46FY5dbzulWdFWkZTRrLBYs2X09r98+OGHiUbX2lFOfDfjnpspI3pwvvfbLCJZlqiU7fhcRuL9jrScVmcbcKUCwY1AdAy6jTA16ejdfqQgqVixosot43sDfMN2MZAMo1DR9YRTy6yBWbEuo5kRI5GU06wQ2EjKiKSFZhHrZWnmwMsbDpEzphUIYrYxwAdx0P379/doaoA8NrCr685Obw2PbiFuDOyHwLdFhJuMPDOIbMF+cKwhVpwyWleOvN8sSzu+306phyKFIxUIbJQvvfSSStdRqVIlFTeNAoY21+OpYW/FOtit9Zum36D4+HgVO41oKl/nI0J08RDAVgs75ejRoymjheXI+82ytOP77ZTnMtI4ToEg/BPZZ3GTMGIT4Wu4MXAaY6AfBuKgW4+bhIgZDMbCjfIFo18RaaHbIPWb161bN09SOn2AG2W0phx5v1mWdny/nfJcRgPHKZD9+/crjY2YaozA9QbrkNhQH8k8Y8YMdROQTly3G+qaHtlLEeWAeHRv2yQS1Om5aCijteXI+82ytOP77ZTnMho4ToFAO8N26I0eyYMRuEiNoeezwY1FLPXtt9+eaFAObhBuKsLsKKM9y5H3m2XJ59LeOE6BeGtpX6cTMqTC4eQ96x0G4mDGMQz31x1QSCeNLiLyyGCgD2W0bznyfrMs+VzaF0cqEF905xQiIdBK1lvSuoJBGgKEwKGlXL58eZUMD/mMkB8K+0Qjnpoysizt9kzyuYy9sjSbFPgjLqFSpUoSFxcnc+fOlRs3bkiqVKk8206ePCmTJk2SvXv3yvnz56VHjx5SvXp1yujQcnSKnE6Q0SlyOkFGJ8lpCppLwAhNhNPpE/3oLQJ9ek87QBlZlnZ7JgGfy9gqSzNJKS5h165dcuXKFalcubL6/vvvv8usWbOkYcOGcuLECbEDlJFlabdnEvC5jK2yNBPHKxDdArd582bJmjWr5M2bV1atWiVdu3aVjh07qu0pU6b07EcZnVuOTpHTCTI6RU4nyOgkOU1HcwkIM0XyMaTexshNjArFfMZ2gjKyLO32TAI+l7FVlmbiCgWC9OqIakB0A2YV03PL2AnKyLK0I3wuY6sszcY1UVi9e/eWFClSyKBBgyRdunRiRygjy9KO8LmMrbI0E9cokJs3byobo52hjCxLO8LnMrbK0kxco0AIIYREl9hRlYQQQkyFCoQQQoghqEAIIYQYggqEEEKIIahACCGEGIIKhBBCiCGoQAghhFCBEEIIiR7sgRBCCDEEFQghhBBDUIEQQgg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    " ] @@ -236,16 +238,16 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:28:55.141223Z", - "iopub.status.busy": "2026-02-04T19:28:55.141223Z", - "iopub.status.idle": "2026-02-04T19:30:37.831763Z", - "shell.execute_reply": "2026-02-04T19:30:37.830763Z" + "iopub.execute_input": "2026-03-20T15:43:03.655034Z", + "iopub.status.busy": "2026-03-20T15:43:03.654640Z", + "iopub.status.idle": "2026-03-20T15:44:52.903880Z", + "shell.execute_reply": "2026-03-20T15:44:52.902048Z" } }, "outputs": [ { "data": { - "image/png": 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", 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", 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    " ] @@ -293,16 +295,16 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:30:37.835763Z", - "iopub.status.busy": "2026-02-04T19:30:37.835763Z", - "iopub.status.idle": "2026-02-04T19:31:13.058697Z", - "shell.execute_reply": "2026-02-04T19:31:13.058188Z" + "iopub.execute_input": "2026-03-20T15:44:52.909279Z", + "iopub.status.busy": "2026-03-20T15:44:52.908586Z", + "iopub.status.idle": "2026-03-20T15:45:28.982781Z", + "shell.execute_reply": "2026-03-20T15:45:28.981346Z" } }, "outputs": [ { "data": { - "image/png": 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", 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xg0A1XrpJDCp/QCPb+X5qsIFADi2yne8LgEC+nxov3WR4QC/dJAaBaXlAbxKDwMrcgkDD9Shcj/h9QJMYBFYOl3lA1XjpJjGEeUBaZDvfT61+QLgehetR7n5A2/l+arwugkBYObTIdvuBQEJg5dAiMXlAdZMYBFbYdEBt5/up8bhyQOxRuB6FK3hAv58aL90FgED0/dR46VyBQDMzMzMzPYFAAyuHFtm2eUDdJAaBlfF6QIcW2c737YBAI9v5fmq/gEB9PzVeujl7QOXQItv5vHtAokW28/3WeUCiRbbz/QRtQMl2vp8a+XxAcT0K16MsdUCJFtnO9xV/QMl2vp8a3XRA9P3UeOlOeUD91HjpJhF1QPT91HjpJHRAnu+nxksvcEC8dJMYBGJ9QO58PzVedHxAEoPAyqHdeEBOYhBYOTByQHsUrkfhNHtA0SLb+X4wdkDufD81XrrZP7gehetRXHhAZDvfT42rdkC8dJMYBP5pQI2XbhKDbnZACKwcWmS3aEBGtvP91Nh2QPCnxks3yXdAL90kBoGzdUDXo3A9Cl9SQA4tsp3va2pAqMZLN4lxcEDdJAaBlbNNQKrx0k1isFZAjZduEoNcb0DufD81XtpwQOf7qfHS8WtALIcW2c5ja0Cq8dJNYhhsQI/C9Shco25A9P3UeOlOaUCDwMqhRVZOQA4tsp3vH25AWDm0yHYqZ0BmZmZmZlZKQJzEILByqGdATmIQWDnkXUBQjZduEqtWQLByaJHtbF5A1HjpJjEYVkDufD81XgJdQEW28/3UMFZAeekmMQicWUBmZmZmZvZaQDeJQWDlcFhAsHJoke38WUDVeOkmMRBXQLTIdr6fMlRAKVyPwvW4TkAlBoGVQxtGQNv5fmq8dNs/K4cW2c73Q0D91HjpJpFJQFpkO99PLUtAGARWDi0KUEAnMQisHDo6QHE9CtejcNU/iBbZzveTRUBkO99PjYdEQCcxCKwcekRAGy/dJAYRSECBlUOLbJdCQHNoke18vzlAK4cW2c6nQUANAiuHFtk8QGQ730+NVzRAF9nO91PDOED2KFyPwvU9QKjGSzeJgTxAKVyPwvWIN0CJQWDl0GI/QKJFtvP9tDVAJzEIrBzaNkBI4XoUric3QJHtfD81njdAyXa+nxoPM0AQWDm0yBY3QCUGgZVDyy1ArBxaZDvfDkDwp8ZLNwkoQC2yne+nBi5ASOF6FK4HK0D6fmq8dBMXQJzEILBy6BpAGQRWDi2yB0Dn+6nx0k0kQArXo3A9SilAg8DKoUU2IkB3vp8aL93cPyGwcmiR7Q9AI9v5fmo8FECq8dJNYhAWQEw3iUFg5eA/XI/C9SjcGEAMAiuHFtniP6jGSzeJQQ5A5/up8dJN8L9gukkMAiu3PzMzMzMzM/M/Vg4tsp3v5z8pXI/C9SgDwBBYObTIdvy/NV66SQwC0z/8qfHSTWLwvwIrhxbZzvM/tvP91HjpB0CkcD0K16P+P5HtfD81XhRAH4XrUbieGEB3vp8aL10SQMl2vp8a7yBAexSuR+H6HECe76fGS3coQH9qvHSTGCtAj8L1KFyPM0A5tMh2vn8+QIGVQ4tsx0VArkfhehQuREASg8DKoaU4QF+6SQwCqz1A5/up8dJ9R0ANAiuHFtlFQBxaZDvfT+U/RIts5/up5T/Jdr6fGg8wQDeJQWDlcD9AtMh2vp86T0AIrBxaZFtRQMdLN4lB8ElA8KfGSzdZSkB56SYxCHxXQOxRuB6Fe09AmpmZmZlZU0BGtvP91OhSQFg5tMh2HlhAVOOlm8TYU0CTGARWDu1EQIlBYOXQAldAyqFFtvPVVUDy0k1iELhPQIGVQ4tsB1VAGARWDi0qVEAfhetRuH5dQHNoke18d15ADAIrhxYlY0AnMQisHGJgQPLSTWIQGEhAZDvfT41PbEDP91PjpVdkQHnpJjEIfEVA16NwPQpvXkA5tMh2vjdcQNNNYhBYQV9AUrgehespYECyne+nxksmQKabxCCwOl1AkxgEVg5tYEB7FK5H4fpXQNv5fmq8BFhAkxgEVg5FYECq8dJNYtBhQIPAyqFFnlNAwcqhRbYTWUD+1HjpJqFqQEa28/3UEGxAw/UoXI9yXEAGgZVDi3xgQEw3iUFgXWBA46WbxCBQaUDNzMzMzORqQEFg5dAis2FAmpmZmZmRZEDNzMzMzBxdQGmR7Xw//WRASOF6FK4XZEB9PzVeugVjQOOlm8Qg8CJA8KfGSzcBX0AdWmQ73+duQJzEILByfGxANV66SQweZEDo+6nx0k1hQLKd76fGT2FASOF6FK53QkBWDi2ynedaQPLSTWIQEF1AxSCwcmg5V0CsHFpkOx8nQL+fGi/dJBdAdZMYBFa2X0A1XrpJDMpgQFK4HoXr2WBA7FG4HoULXUCTGARWDn1hQLgehetRkF1A0SLb+X5q5D+yne+nxstRQPCnxks3uV1AhetRuB4lYkDZzvdT4yUkQBSuR+F6NE5AjGzn+6mFYkCDwMqhRa5dQEoMAiuHomNAz/dT46WnY0AAAAAAAOBUQOj7qfHSbWVAJQaBlUMTZUBkO99PjXtlQLKd76fGu1dAIbByaJE1Z0DhehSuR0FcQIXrUbgeZVBA+n5qvHTnYkDNzMzMzExZQK5H4XoUxlVA9ihcj8KBZEDfT42XbjxwQNejcD0KLXNA6SYxCKz8PUAshxbZzrcoQPT91HjpAmNA2/l+aryUVUCPwvUoXOdyQHNoke18q3FAjZduEoMgMUBmZmZmZk5wQEjhehSut3NAYhBYObSIOUCYbhKDwIpjQKRwPQrXC25A16NwPQp7ZUBGtvP91KxnQKJFtvP9uGhACKwcWmR7ZUCNl24Sg0xlQIGVQ4tsD2RAYxBYObSIcECDwMqhRXZlQClcj8L1lnFA6iYxCKyKc0DkpZvEIDx2QDvfT42XTntAsHJoke3ic0BmZmZmZsBzQJMYBFYOj3BAfT81XrrVbkBPYhBYOeheQOXQItv5fuI/001iEFi3ckB1kxgEVqp1QOF6FK5HY3RAMzMzMzNzWUCYbhKDwGJwQCcxCKwc7nNATDeJQWBVU0BqvHSTGDxvQClcj8L12FJAyXa+nxrfVUAIrBxaZDdkQA4tsp3vCXVAuB6F61H8bkDRItv5fu5qQDvfT42Xtm1Ay6FFtvPpYEAUrkfhevp2QB+F61G4cntADAIrhxaJc0Aj2/l+agZ5QMl2vp8ahXhAj8L1KFx3fECycmiR7Vh+QCUGgZVD7XZAsp3vp8ajd0B56SYxCCR8QN0kBoGVg3lAi2zn+6kPeUAshxbZzpV1QGQ730+NU3ZAtMh2vp/se0B56SYxCCxgQIcW2c73A0NACtejcD1CeEAfhetRuE+AQKrx0k1iXGVA3SQGgZUJg0CF61G4Hn6DQJzEILByUINAvp8aL92UfEDD9Shcj5JJQG3n+6nxAHVAGy/dJAahZ0Cd76fGSw9hQOxRuB6Fo25A8tJNYhAjgkAdWmQ73wF7QI2XbhKDcINA2c73U+MfgkDsUbgehbOCQMUgsHJoiXBAOrTIdr5UgEDtfD81XjmDQHe+nxovNXVACtejcD1CdEB3vp8aL81aQIlBYOXQc4NAJQaBlUMneUDpJjEIrNhpQN0kBoGV33tA+n5qvHQXc0AzMzMzMxt1QBFYObTIDnVAkxgEVg45eUBg5dAi2ylrQBsv3SQGmWNA+FPjpZvsdEB46SYxCCh2QEa28/3U6HdAGQRWDi1MeUCPwvUoXFN7QHsUrkfh5HtAfT81Xrr5fEB/arx0k2BeQDVeukkMeH1ANV66SQw6fECBlUOLbJV7QCcxCKwc+ltAgZVDi2zvZ0DufD81Xph9QL+fGi/dZEFAI9v5fmpIb0CsHFpkOxl2QPYoXI/CnXxAaJHtfD/NcECJQWDl0PB5QJ7vp8ZLoXhAbxKDwMqVdkBqvHSTGIQ+QLByaJHtBGBAjZduEoNgQkAMAiuHFnFQQKwcWmQ7IXdAvHSTGASWeEB7FK5H4WJ6QFyPwvUoBGtAmG4Sg8CIfkBKDAIrh450QIlBYOXQ1IBArBxaZDvkgEBcj8L1KDWAQAaBlUOLrnpAFtnO91M/ZEArhxbZzv9QQLx0kxgEnmlAv8qhRbbz3T+TGARWDqFmQN0kBoGVE0ZAnu+nxktlcEAGgZVDi+58QC/dJAaBPXdAqMZLN4mDgUA3iUFg5ZuBQLpJDAIrq3dAj8L1KFyLhECNl24Sg1WFQEw3iUFgmoBATmIQWDnZhkDKoUW281+HQI/C9ShcsodA5/up8dIbfUAGgZVDiwaDQAAAAAAAQoNA4XoUrkf8gEDdJAaBlVyCQB+F61G4V4dAke18PzVWbUCDwMqhRf2HQHSTGARWB4VA16NwPQqpeECF61G4HiGAQNv5fmq8cn5AHVpkO985gkDJdr6fGhl0QCUGgZVDlYBAuB6F61GPgkBSuB6F66KCQH9qvHSTq4FAtMh2vp+DgUAX2c73U717QN9PjZdurIRAMzMzMzP3f0CXbhKDwGeHQDeJQWDlj4JATmIQWDlVhEBoke18P+eBQKRwPQrXG4BASOF6FK6uhkBfukkMAtaEQLTIdr6fQntAXI/C9SiqfUDRItv5fvGEQP7UeOkmgW9A0SLb+X6RgUBt5/up8Sp2QKjGSzeJoXVADQIrhxaYhECcxCCwcjh1QBFYObTIioBAwcqhRbZtfkAv3SQGgdd+QDvfT42Xsn5Ac2iR7Xy3hEC8dJMYBF6DQM/3U+OlzXpAYxBYObQPgUBfukkMAqiHQKRwPQrXUYZA/Knx0k3VhED+1HjpJot9QG8Sg8DKL4BAYOXQIttTcEApXI/C9UOAQDMzMzMzPYVAL90kBoGpgUBMN4lBYCKDQM3MzMzMLIhAWDm0yHaaakB9PzVeupqCQE5iEFg5t4RAE4PAyqHmgUC8dJMYBDZ3QMl2vp8aK4dALbKd76dKhEDFILByaE2HQOxRuB6Fg4hA4XoUrkfih0Cq8dJNYsyFQPhT46WbyYVAeOkmMQhEhUBs5/upccOCQGDl0CLbQoBAqvHSTWK+h0Do+6nx0seCQLJyaJHtCnxAEoPAyqHThkAcWmQ734OGQHSTGARW2YNAZDvfT42EhUCLbOf7qTN6QNv5fmq87IBAnMQgsHJIekC6SQwCK6N7QIXrUbgeAX1AmpmZmZlXckDpJjEIrBxqQFTjpZvEaoRAzczMzMy5g0BxPQrXo5h1QCUGgZVDZXZAsp3vp8a7dUCmm8QgsAyCQDeJQWDlgnBAK4cW2c5bg0D4U+OlmwJ2QPyp8dJNnYFAOrTIdr4qgUCsHFpkO3lzQArXo3A9I4BAAAAAAAADgEDdJAaBla1+QKabxCCw1HJAfT81Xro5d0DByqFFtsttQKRwPQrXo9g/Gy/dJAbZV0AxCKwcWkRgQFYOLbKde3dAg8DKoUXIdkDXo3A9Cq1yQNv5fmq8JGNArBxaZDtvZECsHFpkOwd0QFpkO99PY3JAf2q8dJNwVkDl0CLb+axxQA4tsp3vhXZAKVyPwvV2dkBSuB6F6yt2QDEIrBxaIGtA7FG4HoVHcEA/NV66SdRoQG3n+6nxpnNAmG4Sg8ACc0B7FK5H4TZkQFK4HoXrSWtAPQrXo3Dbc0Dz/dR46S5mQKJFtvP9enNAGy/dJAb5a0DNzMzMzFxyQHnpJjEISnJA8tJNYhBUZ0CgGi/dJDpoQLTIdr6fgltAj8L1KFy/V0Atsp3vp3hxQDEIrBxauGxA76fGSzdxY0AhsHJokX1yQKwcWmQ7/3JAL90kBoEpc0DjpZvEINJyQO+nxks3KWBAlkOLbOcPZkCgGi/dJMZyQLByaJHt7nJAi2zn+6mdaUCuR+F6FEJvQCuHFtnOv3JAtvP91Hj5aEDy0k1iEKBsQJzEILByQGlACtejcD0SbEC8dJMYBHZoQPLSTWIQkGJAppvEILBaakA5tMh2vs9uQFYOLbKdn2hAxSCwcmjxbkDufD81XgBzQFYOLbKdp2xAwcqhRbbbX0DXo3A9CgdgQKabxCCw0kxANl66SQw+ZkBeukkMAqdgQMHKoUW2E3FALIcW2c6TaEAxCKwcWsRkQAaBlUOLdGtA76fGSzfhZUAX2c73U9NrQBKDwMqhsWZAexSuR+GaZkA2XrpJDFpmQF66SQwCE2lApHA9CtcjSUDLoUW28wFnQLKd76fGX2tAokW28/1UZEA3iUFg5cRiQOOlm8Qg5GhA8KfGSzepWkAhsHJokW1oQGMQWDm0PGNA16NwPQqDaUBeukkMAqtTQDMzMzMz42NA76fGSzelYUAxCKwcWrBnQPT91Hjp+mZAarx0kxhkZkCq8dJNYgxmQFpkO99PEWZAVg4tsp3PPUA9CtejcKlhQPyp8dJNomVA/Knx0k2iZUCkcD0K15dgQNEi2/l+rmRAMQisHFpsWEDl0CLb+X5aQEa28/3U8GBAPQrXo3CdYkAAAAAAAOBJQKrx0k1iUFxAL90kBoENYkDdJAaBlQNeQLbz/dR4eUBACtejcD2iYECmm8QgsGJXQKAaL90kdlNAoBov3SQGX0BeukkMAjtgQN9PjZduomBA+n5qvHTDQEAbL90kBklcQAAAAAAAmFpAxSCwcmiR3T8lBoGVQ4vgP57vp8ZL91tAvp8aL93EW0C28/3UeBlMQCUGgZVDY1tAhxbZzvfzWEA9CtejcJ1ZQBKDwMqhhVpANV66SQwqU0AnMQisHAJXQFyPwvUoPFRARIts5/sJU0AAAAAAAOBUQOf7qfHSTUtAUrgeheuRVUDy0k1iEChUQI/C9Shcj1BALbKd76dmU0Cd76fGS7dTQArXo3A9WkxAnMQgsHI4U0DP91PjpUtUQHWTGARWjklA001iEFipVEC7SQwCK/9VQCPb+X5qRFVAYOXQItv53j8lBoGVQ4vgP1TjpZvEsEZA8tJNYhCYVkDwp8ZLN/FWQA4tsp3vP1FA3SQGgZWjQUCS7Xw/NQZWQEoMAiuHjlhAI9v5fmo8WEDdJAaBlZtWQI2XbhKDACJA8tJNYhBoU0Bcj8L1KOxBQAisHFpkq0FAhetRuB7tV0C0yHa+nzpPQHsUrkfhYl1A+FPjpZv0VUAtsp3vp/5UQKRwPQrXC11AqMZLN4nNY0AUrkfhelQ8QLgehetRqGRAMQisHFqkO0Bcj8L1KFzfP6wcWmQ7A2VAAAAAAACwZ0AW2c73U/dhQCcxCKwcRmhARrbz/dSsZ0D8qfHSTX5oQJZDi2znq2pAAAAAAABAQkD8qfHSTSJGQMl2vp8aD3JAK4cW2c6zc0ADK4cW2RpsQIlBYOXQhnJAqMZLN4mdbkCJQWDl0GJRQIXrUbgeBTBATDeJQWBdaECoxks3iQFRQG8Sg8DKXW1ASgwCK4fWakCamZmZme90QNv5fmq8mHRACKwcWmTpckCxcmiR7Tw6QKAaL90kKnJAke18PzW+YkAfhetRuDptQEw3iUFgBXBAhetRuB5FXECq8dJNYnBoQE5iEFg5DGVARrbz/dRIZECPwvUoXG88QB+F61G4tl9AeekmMQgYZECe76fGS09eQPhT46WbnGBAKVyPwvVgXEAj2/l+anRaQGiR7Xw/zVhAokW28/2UIED2KFyPwkVJQL6fGi/dZExABFYOLbJ9S0CPwvUoXO9DQEoMAiuHVkZAVOOlm8TQREANAiuHFplEQC/dJAaBBUJAAiuHFtleQ0CNl24Sg2AyQD0K16Nw7UJA/tR46SYRP0CamZmZmbk+QHe+nxov3TlAtvP91Hi5QUC8dJMYBLY0QB+F61G4HixACtejcD1KPkBKDAIrhxbhPwIrhxbZzjNA0SLb+X4qNEDLoUW28/00QIcW2c730y1AqvHSTWJQNEDwp8ZLNwk1QARWDi2ynSxAmG4Sg8CKLUApXI/C9WgiQLbz/dR4aSlABFYOLbKdCECDwMqhRTYZQFpkO99PzSZAx0s3iUGgJkB9PzVeuskUQFyPwvUoXBBAXI/C9SjcIkDdJAaBlcMeQE5iEFg5tBZA5/up8dJNwj956SYxCKwMQOj7qfHSTeI/ZDvfT42XFMD8qfHSTWKQP0Jg5dAiWyLAf2q8dJMYBUA730+Nl27aP8qhRbbz/QhA16NwPQpXF0A9CtejcD0GQOxRuB6FaxhAg8DKoUV2IUCJQWDl0CIYQArXo3A9iidAiUFg5dBiIUAdWmQ7308uQAAAAAAAIDBAbxKDwMpBMEDD9Shcj8IsQPhT46Wb5DRAEFg5tMgWN0Cq8dJNYnA+QEa28/3UOD1Aw/UoXI/iQEB3vp8aL71AQAAAAAAAoDhAarx0kxiEMEB1kxgEVs4tQDvfT42XLjRAXI/C9SgcRUAzMzMzMzM9QB+F61G4ni5ARIts5/uJRkADK4cW2a5FQEw3iUFgRUdAiUFg5dBCPUD8qfHSTQJIQFTjpZvEwENA1XjpJjFoQkBKDAIrhwZLQMuhRbbzjUdAwcqhRbaTSkAlBoGVQ4vgP1g5tMh2bk1AqvHSTWJwTkAIrBxaZMtDQL+fGi/dJOI/xSCwcmgxRUAtsp3vp3ZAQMHKoUW2Q0FAQmDl0CIbQ0AshxbZzndMQKrx0k1iwEVArkfhehSeS0Cyne+nxjtJQLpJDAIrR0lArBxaZDu/MEDazvdT4+U0QPp+arx0g05ATmIQWDlUR0CgGi/dJJZMQF66SQwCS1BASgwCK4fuUEDufD81XlpPQG3n+6nx2lFA4XoUrkfxVECcxCCwcsg6QF+6SQwCu0RAiUFg5dCCU0AOLbKd74dSQP3UeOkm0U1AjZduEoPgXEBEi2zn+4ldQEjhehSu71pA6Pup8dLlU0DTTWIQWJFfQEa28/3UqF5AwcqhRbaXZ0DazvdT48FkQPp+arx0Q2FA7FG4HoWzX0ApXI/C9ZheQO58PzVewl1AqvHSTWKMYUA3iUFg5RBZQN9PjZduDmFASOF6FK7TY0DjpZvEIFheQKAaL90kVl9AMQisHFr8ZED+1HjpJmFkQPYoXI/CkWVA5dAi2/kmXUCNl24Sg/BdQL+fGi/drFRALbKd76fGY0BqvHSTGHRfQEw3iUFgNV9A6Pup8dKFY0D4U+Olm2RWQLTIdr6fmmJA9ihcj8JVYkCF61G4HnVaQHWTGARW5l1AWDm0yHaOQUAZBFYOLZpWQPYoXI/CTV1Asp3vp8a7QECsHFpkO+9QQLTIdr6fUlhAsp3vp8YzV0BzaJHtfC9bQBSuR+F6zFpAdZMYBFa2WEAhsHJokeVYQCUGgZVDc1xAmG4Sg8BaXUDP91PjpcNcQLByaJHtrFtAhetRuB51SEBYObTIdjZWQBkEVg4tilxAsHJoke3sYUA1XrpJDPZjQD0K16NwrVpAyXa+nxobYUD4U+Olm1RVQO+nxks3MWVACKwcWmQTXkBcj8L1KGxHQBsv3SQG2WBAoBov3STGWkDy0k1iEChkQC2yne+nfmhA/Knx0k3OZ0D6fmq8dNNlQOXQItv5fuI/Rrbz/dRkcUBU46WbxGJ3QOF6FK5Hf3RA8tJNYhCueEBYObTIdi5+QPYoXI/CI3xACKwcWmSVdED2KFyPwrNxQM/3U+Oli09Aarx0kxjkckCPwvUoXPdnQD0K16NwA3BAO99PjZdmXkBOYhBYOU5wQKAaL90kAm9AGQRWDi1ubUAZBFYOLaJsQAMrhxbZ8mRAYxBYObT8ZEBt5/up8S5sQBFYObTIAmJAkxgEVg6lX0Db+X5qvHBpQD0K16Nw43BAjZduEoPucUACK4cW2dxzQJZDi2znn2tAWDm0yHYYcUCgGi/dJB5zQNnO91Pj2WJA0SLb+X5EdkCBlUOLbFF/QBbZzvdT4YBAxCCwcmixgkCe76fGS9N9QG3n+6nx2oJAVg4tsp0ndUAX2c73UyM/QEoMAiuH2nlAYOXQIttdfkDJdr6fGktmQOxRuB6Fh3pAtvP91HhthUBEi2zn+1mGQESLbOf7/4ZAZmZmZmbSgEA730+Nl0CFQARWDi2yj4VAjGzn+6mSgkBg5dAi20yEQKjGSzeJWoNAJzEIrByrgkCWQ4ts5wCDQAaBlUOLsHNASgwCK4eifEC28/3UeDl6QDeJQWDlPIFAaJHtfD/jcUA730+Nl5J3QPCnxks3UXRAeekmMQjEckBjEFg5tGJyQIts5/upvWtA9ihcj8JVYUAzMzMzM7tRQMHKoUW2NXFArBxaZDthcUAv3SQGge1vQPhT46WbUGtAAAAAAADQUUAQWDm0yIppQAwCK4cWhWxA30+Nl27YfEBEi2zn+2V9QO58PzVeDnhATmIQWDm8dUCIFtnO9111QKAaL90kmHtAqvHSTWJXgECJFtnO97F/QM/3U+Ol60RAJzEIrBzge0AfhetRuM5kQGq8dJMYXIJAeekmMQhegkDXo3A9Ci2BQPT91HjpnnhA8tJNYhASgkBkO99PjaSCQAAAAAAASFpALIcW2c5BhkB7FK5H4Xh/QLgehetRXn1A46WbxCBzgEDhehSuR4WAQJ3vp8ZLoIdAQWDl0CKhh0Dvp8ZLNwllQGq8dJMYl4NAuB6F61FtgkC7SQwCKxyHQHSTGARWnoRANV66SQwzgEAZBFYOLcZ5QIcW2c73v4NA9ihcj8LMgkAGgZVDiyiFQBsv3SQGJ3BA0SLb+X5tiEAhsHJokS1qQClcj8L14oZAF9nO91O1hEAOLbKd7997QJzEILByBYdASOF6FK5WhkBQjZduEv18QCcxCKwcsHdAWDm0yHbvhEA3iUFg5Y5/QFyPwvUoqIJAhetRuB5hZkCd76fGS6ODQFpkO99Pc4hA3SQGgZVoh0BI4XoUrkCBQFyPwvUopoNAQmDl0CLDf0CMbOf7qaaIQM/3U+Ol84ZAcT0K16OQWEBSuB6F64CIQFK4HoXrh3RAWDm0yHZwfUBANV66SYwWQGiR7Xw/HYBAE4PAyqFvc0Db+X5qvARGQFyPwvUopFJA5dAi2/mePkC8dJMYBHR8QNV46SYxCHhAAyuHFtmQf0C28/3UeGiGQAMrhxbZmHdAw/UoXI+UgkBkO99PjWeEQJqZmZmZaXlAiRbZzvcLfUAlBoGVQ82FQLTIdr6fGHZAWDm0yHaqc0A730+Nlw+GQBsv3SQGtYRANV66SQzUe0CBlUOLbDF8QIxs5/up14VA/tR46SaJeECPwvUoXIGGQGIQWDm0IHtAz/dT46VyiEA/NV66SRBkQLgehetRXG9A+n5qvHRIiEBxPQrXo4mGQCuHFtnOLYBAYxBYObQjh0DTTWIQWKqFQIts5/upcWdAoBov3STQeEChRbbz/caGQIlBYOXQXYRABFYOLbKFh0CNl24Sg/hTQGiR7Xw/i4NAhetRuB4mhUCmm8QgsESHQFpkO99PEXZAFK5H4XpFg0Ce76fGS9t+QKAaL90kpYdA7nw/NV7Kf0DLoUW285mBQI2XbhKDhnRAEFg5tMgweUB3vp8aLz+BQMuhRbbzO3pAZDvfT40HcUDhehSuR1t7QK5H4XoU/nJAzczMzMyod0A1XrpJDMx2QBFYObTIQ4BAvp8aL93ufUCoxks3icF8QDeJQWDlJnpAaJHtfD/Td0Av3SQGgY1yQA4tsp3vH3JAZDvfT40ncEARWDm0yOJyQE+Nl24SQ3ZAppvEILDKY0D0/dR46Tx2QEw3iUFg5dA/WDm0yHYadkCNl24Sg05zQJqZmZmZMWNALbKd76d2a0BGtvP91Dx2QPyp8dJNYuA/cT0K16MUY0CcxCCwcgxzQDvfT42XyHdAw/UoXI/8d0BCYOXQIiNbQPLSTWIQFIFAf2q8dJMUhEASg8DKoVl2QMP1KFyPnoBAPzVeukkCeEBvEoPAytl+QEjhehSuZYNA7FG4HoXRekCgGi/dJL5mQDeJQWDlHIBAokW28/0Ue0Coxks3iXFFQOxRuB6FooJAAiuHFtkEgEC28/3UeOkwQD81XrpJendAMzMzMzO3aUARWDm0yHhzQGZmZmZmxnNAiUFg5dDSa0AbL90kBtlpQLKd76fGT3FATmIQWDnYcUDByqFFtpl4QG8Sg8DK8VxA3SQGgZXDSkBzaJHtfD/dP3E9CtejwFJATmIQWDm8bEDl0CLb+fJvQBKDwMqhRd4/wcqhRbZjXkDGSzeJQQxjQNV46SYxeFxATDeJQWANYEB9PzVeuilYQF66SQwCk1xARIts5/uJVEDHSzeJQZhcQC/dJAaBhVJAzczMzMwYYUBYObTIdopgQJMYBFYO1V1AdZMYBFZmWEA3iUFg5WBOQIcW2c73C2BAjGzn+6ntYEAK16NwPZZhQLx0kxgEGmJAsHJoke1MYkC8dJMYBO5fQNEi2/l+umNAZDvfT40vWUBt5/up8TJdQKJFtvP9dEVA46WbxCCQQ0C6SQwCK+dXQNV46SYxKDVAPzVeukkMUkCF61G4HmVAQJ7vp8ZLl1pAvHSTGAQGVUD+1HjpJsFBQI/C9Shcz1hA001iEFg5UkBEi2zn+/FUQEjhehSud1RAc2iR7XxPRkCJQWDl0ApUQGQ730+NlytArkfhehR+SUDNzMzMzDRSQNEi2/l+6jJAO99PjZdu2j8lBoGVQ7tGQFYOLbKdr0FAqvHSTWIgRUAv3SQGgc1TQHNoke1851BA3SQGgZXDNkA3iUFg5bA1QMUgsHJowUBACtejcD3qQECmm8QgsCJBQKJFtvP9lEBAEoPAyqFlNED6fmq8dHM8QKrx0k1iQEBAnMQgsHIoM0A/NV66Scw8QMUgsHJokRRAukkMAitHNUDJdr6fGk83QFTjpZvEwCxALbKd76fGFUDD9Shcj4IoQJzEILBy6B9AAAAAAACAHkDNzMzMzEwiQKjGSzeJwRBAGy/dJAaBFkCgGi/dJMYoQDMzMzMzMyhA1HjpJjGIKEBt5/up8VIZQN0kBoGVAyhAQmDl0CJbLkCWQ4ts5/seQBKDwMqhxSdAnMQgsHIoI0A9CtejcP0mQDMzMzMzMx1AQmDl0CKbJ0Ce76fGSzcLQLByaJHtfBNAZDvfT40XGECDwMqhRbYVQBKDwMqhRRVAoUW28/3UFEAK16NwPQoEQKabxCCw8hhAHVpkO99PCECxcmiR7Xz1P6rx0k1iEAZAz/dT46Wb5D/8qfHSTWL+PzvfT42Xbtq/3SQGgZVDAUD4U+Olm0QdwH0/NV66yRRAjZduEoNAB0CDwMqhRbbjP3E9Ctej8BlAK4cW2c738T9pke18PzUXQDMzMzMz8yNA0SLb+X7qIkCJQWDl0GIhQKjGSzeJQR5Ac2iR7Xw/FUD0/dR46aYTQHSTGARWDhJACtejcD0K9T8AAAAAAAAAAN0kBoGVQwhARrbz/dT4E0CBlUOLbOcKQD0K16NwPRnAaJHtfD+1C8BYObTIdr7jvx+F61G4Hvs/001iEFg5+L+6SQwCK4e2v94kBoGVQ9e/ppvEILBy5L+d76fGS7ccwLgehetRuAXAwcqhRbbz/b9U46WbxCD3v+f7qfHSTfC/iUFg5dAi+7+oxks3iUHAv1yPwvUoXAjALbKd76fG/b/dJAaBlUP3v166SQwCK+8/okW28/3U8L9mZmZmZmbqP4ts5/up8cI/uB6F61G4BkDLoUW28/0NQHnpJjEIrBJA1XjpJjEIEECYbhKDwMoLQJZDi2zn+wzAMQisHFrkEkAshxbZzncfQMdLN4lBYApA2s73U+OlHEAGgZVDi+wmQDZeukkMgh1AmG4Sg8BKJEASg8DKocUYQOkmMQisnBtA001iEFg5H0DJdr6fGi8MQN0kBoGVgypA8/3UeOkmFkBoke18PzX+Py/dJAaBFSpAdZMYBFYOLUCgGi/dJAYdQIGVQ4ts5yJAd76fGi+dK0Cyne+nxoskQMuhRbbz3TJAEFg5tMg2KUCPwvUoXM8vQBsv3SQGQS1AeekmMQjsIEAnMQisHNowQPp+arx0szJA1XjpJjEoNUAGgZVDiywmQMP1KFyPQipABoGVQ4ssOEDb+X5qvJQ4QGQ730+Nt0BAPN9PjZcuMUA1XrpJDMIgQKrx0k1iQEBA1XjpJjHIP0AEVg4tsg1AQA4tsp3vx01AzczMzMwMQUCIFtnO93M6QKwcWmQ7b0JAppvEILBy9j/jpZvEILA5QLx0kxgEVjxAzczMzMzsMUDn+6nx0q1GQKabxCCwclZAPzVeukmUW0DfT42XbmpXQH0/NV66CV1ARIts5/s5XUC4HoXrUbBaQJHtfD81/lFAf2q8dJMwYkB0kxgEVkJjQN0kBoGVi2VAv58aL91MZkDP91PjpeNnQKrx0k1iFGpAYhBYObSYakAzMzMzM9tmQLTIdr6f/mZAGQRWDi3+ckAtsp3vpwpsQOXQItv5snVAzczMzMySdkApXI/C9dhwQC2yne+nLlpAtMh2vp/wdUB56SYxCJhwQPyp8dJNuoBAppvEILDZgUC0yHa+nyZuQPLSTWIQWARAsp3vp8bUhEDXo3A9CtWAQM3MzMzMdHxAIbByaJHLhEAxCKwcWqRoQDm0yHa+6X5AqMZLN4k4g0CgGi/dJOR4QA4tsp3va39A1HjpJjHrhEC28/3UeCmFQGZmZmZmWntAUI2XbhLlckAOLbKd7yt5QGZmZmZmXHBAarx0kxh3hkDKoUW282SGQBKDwMqhJXtAwcqhRbbzfUCR7Xw/NXKEQKFFtvP9DYdA5dAi2/mMdkDdJAaBlRlyQIlBYOXQXYZA30+Nl24XhEDHSzeJQTp/QKJFtvP99INAVg4tsp3ShkAAAAAAAOaGQE5iEFg5Wn9Af2q8dJPkZEBKDAIrh3+HQN0kBoGVtIZAj8L1KFzigUAv3SQGgV16QPLSTWIQFIdAke18PzUQhEAUrkfhegaGQGq8dJMYPYhAmpmZmZmaiEBU46WbxC+DQF+6SQwCAoVAexSuR+Egf0CycmiR7Rh4QFCNl24ScoJArBxaZDtqgECDwMqhRUSCQBKDwMqh1XdAIbByaJFxg0A/NV66SXiAQG8Sg8DKkWtAf2q8dJOEcEDP91PjpSlxQGC6SQwC6X9AeekmMQhygkAYBFYOLWmAQClcj8L1YHlA16NwPQpjf0CcxCCwcpCHQH9qvHST3n1AeOkmMQgJhkDLoUW288qCQIgW2c73W4hAsp3vp8ach0Bg5dAi2z90QNejcD0KKIJAdZMYBFZuTkBKDAIrhwiFQLgehetRxYRAJzEIrBzegkBEi2zn+098QDMzMzMzw4BAqMZLN4mRc0BvEoPAyvlhQMqhRbbzqIZAoBov3SQkf0CTGARWDsFhQGiR7Xw/G3NAK4cW2c6/gEAIrBxaZP93QPp+arx0535AQWDl0CITgUBSuB6F6w10QIGVQ4tsv2xA46WbxCAehEBqvHSTGIiGQCUGgZVDuoBAEVg5tMjihEBMN4lBYA+GQHWTGARWInFAAAAAAADQh0CTGARWDriCQE+Nl24SmohAi2zn+6mNf0DazvdT44uIQO18PzVeXmJA2/l+arzxgUDEILByaDKDQGmR7Xw/VYdA9ihcj8KIhkCcxCCwchGCQN9PjZduxIJAuB6F61HYYUAj2/l+ak5zQFpkO99PzUBASgwCK4fmZEApXI/C9fBhQArXo3A9Cn9ACKwcWmRHekBPjZduEjiGQIGVQ4tsM3FAke18PzVLgUDFILByaGGHQMUgsHJo9YRA6iYxCKy2gUBEi2zn+3lcQIxs5/upjXNA16NwPQoZh0BWDi2ynXF1QCYxCKwcO4ZAH4XrUbjkhkAlBoGVQ0WFQDVeukkMcHRAoUW28/3GdEARWDm0yPYbQM/3U+OlOzJAnu+nxkvPc0A6tMh2vkOAQNnO91PjvXFAhxbZzvdRckBqvHSTGIQzQGZmZmZmgYBAdJMYBFYWiEBvEoPAyiFCQAMrhxbZnntARIts5/sEhkBfukkMAg6GQJduEoPAJYhACKwcWmQDVECF61G4HuKCQNv5fmq8DHZAuB6F61HkgEAUrkfheluCQFyPwvUo4HFASgwCK4cSb0BkO99PjQ15QArXo3A9xIdAnMQgsHLYf0C7SQwCKzeFQOxRuB6FV35ASOF6FK6MhkCBlUOLbE18QH0/NV6643dAqvHSTWIhgEBuEoPAysSGQFg5tMh2GnJAjGzn+6nBVEBSuB6F68l3QPCnxks3b35AqvHSTWKUbkB56SYxCIqCQOOlm8QgMF9Ay6FFtvMTekAOLbKd722IQJHtfD81lIBAbef7qfGaZEAUrkfhevBwQNV46SYxqFFAaJHtfD8kgEA/NV66SbRdQLbz/dR4MWpABoGVQ4uPhEBYObTIdj2FQA4tsp3vN4ZAg8DKoUXea0CBlUOLbIdRQDeJQWDlJn5AYLpJDAJJeUCHFtnO96NiQI2XbhKDBHtA5/up8dJNwj/ByqFFtudmQIXrUbge1oFAu0kMAitUiEDwp8ZLN117QHWTGARW6ndAL90kBoFFa0AzMzMzM46HQM/3U+OlmXNAg8DKoUVwdkAIrBxaZCFwQBODwMqhi3NANV66SQywfkBt5/up8dIXQPp+arx0Q4NA4XoUrkfQgkDwp8ZLNzFdQHsUrkfhxnlAObTIdr5leECF61G4Hn1yQClcj8L1yGpA0SLb+X4GYUB/arx0k+hvQGDl0CLbhWpA+n5qvHRLZkCJFtnO91F6QKabxCCwmYNADAIrhxZ7f0C8dJMYBLWAQM/3U+Ol32xAzczMzMwsM0Av3SQGgXVoQCUGgZVDy2JAyXa+nxo3akDD9Shcj2ZmQGIQWDm0YGlA2/l+arykX0AbL90kBt1jQN0kBoGVP2BA5dAi2/ladUBkO99PjbN/QHnpJjEIa4RA+FPjpZv1h0CMbOf7qbSAQFg5tMh2G4FADQIrhxZnhUDD9Shcj7GBQHsUrkfht4RANV66SQxud0DFILByaA6IQKabxCCwhohAGy/dJAafg0BkO99PjVGDQAAAAAAA8odALIcW2c4hfUA9CtejcBuAQD0K16NwqYhA6iYxCKyggkDl0CLb+eCCQB+F61G4YIJAFK5H4Xr8gUAdWmQ730F5QNEi2/l+E4dAUrgehesXgEDl0CLb+aWBQBODwMqhAYBA2/l+arx6e0Dn+6nx0m9+QN0kBoGVu4JAVOOlm8TUdkApXI/C9R+FQCPb+X5q0nlA5dAi2/medUCwcmiR7XRqQNejcD0Kt19ACtejcD1aZkARWDm0yI5wQIlBYOXQgmtAy6FFtvNNU0DByqFFtrtsQCGwcmiRmWpAGy/dJAbhVkD4U+Olm36BQHsUrkfhYHFA46WbxCCMbUCuR+F6FJiAQGMQWDm0NIFAjGzn+6nVYUAX2c73UwtVQLJyaJHtnHpADAIrhxYNgkBWDi2ynSWCQDZeukkMyHRAyXa+nxo+gkDGSzeJQdOBQJZDi2znA4FAoBov3ST/gEDhehSuRw2BQHWTGARWtmhAy6FFtvPlekApXI/C9WB1QD0K16Nwe39Au0kMAiv9dEDpJjEIrMR1QPYoXI/CjXNAPQrXo3C5c0CMbOf7qcVgQC/dJAaBrWlAjZduEoOcfUDy0k1iEPp9QLx0kxgEljJAZmZmZmZeYUC4HoXrUQhGQPCnxks34XFArBxaZDs3cEBxPQrXo/x4QNNNYhBYp3VAz/dT46Xrd0D2KFyPwt1iQC2yne+nvl5A30+Nl248dEB7FK5H4VpCQOf7qfHSp3tAN4lBYOUOfEBt5/up8XBzQGDl0CLbZXtAw/UoXI8Ae0ArhxbZzu9yQMUgsHJoCW1APN9PjZcScEB7FK5H4Zh6QIXrUbgeTXpA/Knx0k1YekDn+6nx0gl6QDMzMzMzAXpAH4XrUbgaa0Cyne+nxuVyQOj7qfHS83RA1XjpJjFoeUARWDm0yDRzQJMYBFYOMW1AZmZmZmZecUBmZmZmZkRyQLKd76fGG1lAcT0K16OwWkDy0k1iEDxgQKabxCCwrmtALIcW2c43aUDNzMzMzBxSQHWTGARWXltAqvHSTWL4YECMbOf7qeVjQLgehetRnG5AHFpkO9+vZUDjpZvEIARtQEw3iUFgf3BALbKd76cickC6SQwCK79nQNv5fmq85FNACKwcWmSrYUDazvdT42U6QC2yne+n+mlAjGzn+6nxMkCmm8QgsApjQPT91Hjp+mZAc2iR7Xy3Y0CXbhKDwH5kQBgEVg4tvmRAYOXQItuhWkB/arx0k+BiQHsUrkfh+mhAzczMzMxsVEAUrkfhelRkQG3n+6nxwkNAIbByaJFFX0B9PzVeuhFiQPLSTWIQWFlAexSuR+EqVEBt5/up8SpSQJZDi2znW1JAsHJoke08UECiRbbz/TRPQNv5fmq8dENALbKd76c2Q0AbL90kBtFDQIlBYOXQIkRAnu+nxksHRECuR+F6FB5DQG8Sg8DKITxARrbz/dQYQUB9PzVeusk0QOxRuB6FqytAqMZLN4lhOkAXBFYOLbIeQBsv3SQGQSdA30+Nl25SIkDTTWIQWNk0QIgW2c730xlAJQaBlUOL3D/dJAaBlUMWQGiR7Xw/9SxAxSCwcmjRI0AOLbKd7+cuQARWDi2yHSRAv58aL92kFUCoxks3iUHYPzZeukkMAhZAAAAAAABAJUDFILByaBEdQB+F61G4nhhA9ihcj8J1IEBaZDvfT40dQOj7qfHSTRRA5dAi2/l+F0ADK4cW2c4GQJ3vp8ZLN/s/CtejcD0K+z9QjZduEoMHQNNNYhBYOQhAtMh2vp8a6z8MAiuHFtniP8UgsHJokfO/nMQgsHJo7T+amZmZmZkDwA4tsp3vp94/IbByaJHtD0Bcj8L1KFwMQKabxCCw8hhACtejcD0KG0D8qfHSTSIiQFpkO99PDSVAGQRWDi0yK0BEi2zn+wkxQH0/NV66aTFAmpmZmZmZL0Atsp3vp0Y3QM/3U+OlGzBA7FG4HoWrM0A/NV66Saw6QP3UeOkmMSlAJQaBlUMrQEB1kxgEVs5CQGQ730+NtzdAX7pJDAKLOEBQjZduEmNDQBfZzvdTs0BAiUFg5dByQkCWQ4ts53tJQHnpJjEIJFNAGy/dJAaRVkAEVg4tskVZQLpJDAIrL1BA9P3UeOm2TkCoxks3iVFYQOOlm8QgoF9ASOF6FK5XWUD+1HjpJnVgQLpJDAIrn1tAWDm0yHa2W0CBlUOLbCdhQCuHFtnOT2BA30+Nl246Y0CWQ4ts54tVQD0K16NwDV5A8tJNYhAEZ0AxCKwcWpRXQHNoke18n2VAZmZmZmamXEDGSzeJQfRkQDEIrBxaxDpAGy/dJAZFakD0/dR46Y5mQFyPwvUoqGtAwcqhRbY/Y0Coxks3iVVjQFYOLbKdO21ADi2yne8TZ0BjEFg5tHRkQAisHFpk62dAmG4Sg8BGa0BxPQrXo7BjQOf7qfHSBWdAyXa+nxpRcUB7FK5H4WJdQGQ730+NxXFAnMQgsHI4ZUAbL90kBrluQAAAAAAARGhAexSuR+Euc0BU46WbxDRwQPhT46WbSGdAYOXQItvNcEC6SQwCK9NiQPT91HjpWm9AoUW28/1OdUCHFtnO9+tbQB1aZDvfJ21AsXJoke2SdED4U+Olm7RWQLKd76fG8XFAJQaBlUP7bkBWDi2ynYdyQO58PzVelHdAkxgEVg6bd0C+nxov3Tx4QAwCK4cWu3BAjZduEoOGdECBlUOLbDNxQPLSTWIQHnNA/tR46SYBdEBqvHSTGLJ1QO58PzVeenNASOF6FK7Zc0CDwMqhReR6QH9qvHSTcHRA30+Nl26IdUC6SQwCKz94QIGVQ4ts6XRAFK5H4XosdECDwMqhRb5oQPp+arx0DXFAMQisHFpkd0DUeOkmMch1QPyp8dJNmHhAF9nO91NrdkDazvdT46N2QPhT46WbpHFAUrgehes9bEDFILByaNl8QNV46SYxuHhAUrgehev1dUAdWmQ73213QPLSTWIQhnxAiUFg5dACcEDsUbgehSiAQIlBYOXQJ4BAoBov3SRGVUCoxks3iZF7QJzEILByrYBAH4XrUbh+ckDl0CLb+eCAQI2XbhKD3oBAXrpJDAIMgUB1kxgEVuB5QGiR7Xw/9UVAKVyPwvUoPEBt5/up8VIzQIGVQ4tsVX1APQrXo3C8gUC0yHa+n0aBQOXQItv5MHhAkxgEVg55f0DsUbgehTyCQIlBYOXQU4JAv58aL92GgkBmZmZmZqaCQG8Sg8DKXXFAfT81XroFgkDP91PjpfF7QJ7vp8ZLt2xAbxKDwMpRgkAnMQisHGKDQARWDi2yjINAN4lBYOVIWUDpJjEIrFx8QJHtfD81nH9ADAIrhxZ1e0CJFtnO9/t2QCUGgZVD+YNAvHSTGAQjhEDtfD81XiOEQHNoke18aYRAUrgeheuYhEAX2c73U5qEQKwcWmQ7kYNAI9v5fmq84D9KDAIrhw5sQAwCK4cWVXxAke18PzUhgkACK4cW2eeCQEoMAiuHxHxAqMZLN4lhe0DByqFFtuNjQHNoke18oYVAObTIdr6xfUB7FK5H4euFQCyHFtnOBIZAAAAAAADEfEBxPQrXo3DhPyPb+X5qIGBATDeJQWB3f0BxPQrXo5B0QA4tsp3vC2pA3SQGgZXWgEDkpZvEICiGQAwCK4cW3oFAbef7qfFoe0BkO99PjS+HQCYxCKwcLIdAZDvfT41Hh0DTTWIQWEGHQK5H4XoUSH9AQDVeukkKdUCyne+nxj13QARWDi2ylodAJjEIrByfh0Boke18P11tQO58PzVefoZAJzEIrByockB9PzVeuhaIQArXo3A9k4BAsp3vp8Y/iECNl24Sg8iDQHE9Ctej0IRARIts5/segUAMAiuHFgV9QBgEVg4tG4JAlkOLbOcDh0B3vp8aL+lzQAIrhxbZWYRAXrpJDAKxgEAX2c73U/d9QKAaL90kRntA+FPjpZtDhEB7FK5H4f6GQDEIrBxawYRAQDVeukk4hkBmZmZmZs+GQOXQItv5xn1ATDeJQWAJdkBvEoPAyiWEQNv5fmq8j4NAEVg5tMgGZEDLoUW28+F8QFYOLbKdv39Asp3vp8YxeEBmZmZmZoZpQDm0yHa+tXdA001iEFjdhUCDwMqhRSKGQOF6FK5Hq35AxSCwcmg/dUDTTWIQWE2AQIXrUbgeJ3hADQIrhxaJhUBg5dAi2yWFQD0K16NwBWFAE4PAyqHdcECF61G4HtaFQDeJQWDlVnZAne+nxktBhUDhehSuR/CBQNejcD0KD11A16NwPQpPe0DGSzeJQf+DQOkmMQis6GpAy6FFtvMNX0Cyne+nxkdsQCUGgZVD5XVApHA9Ctf7fECmm8QgsKZmQMHKoUW2+3JAZDvfT42TbECmm8QgsP57QKrx0k1izINATmIQWDmmfECiRbbz/Zp+QO18PzVerINAjGzn+6l3dkCDwMqhReCCQAisHFpk/4dA/Knx0k0ZgUDD9Shcj9SGQL6fGi/dBDVAsnJoke2wfkC6SQwCKy9qQARWDi2yQX1AmpmZmZkTfkAOLbKd72OAQHE9CtejoEVAqvHSTWJEc0BU46WbxGKDQKwcWmQ7bYZAd76fGi8neUC4HoXrUWqEQG8Sg8DKHoBAWDm0yHYPhkAtsp3vp6B5QH9qvHSTa4NAmpmZmZkZS0DHSzeJQcxxQKjGSzeJoWBAVOOlm8Rsh0AK16NwPRx6QDeJQWDl9YJALIcW2c5tekCBlUOLbFN4QCuHFtnOd1dACKwcWmRxf0CNl24Sg8AIQHNoke184X1A2/l+arwoZkAEVg4tspGIQBKDwMqh6YVA6SYxCKxmhkCNl24Sg42CQBxaZDvf34RAZDvfT43th0Dl0CLb+fGEQDq0yHa+fYBAnMQgsHI/hUB9PzVeuuOHQNv5fmq8E4ZArkfhehTuh0CwcmiR7faDQFpkO99PWoNAvHSTGASAgUCsHFpkO9aGQD0K16NwFIBAE4PAyqErg0AdWmQ735F0QAisHFpkY25ArBxaZDt7gkBcj8L1KMx1QKabxCCwEm9AX7pJDAJfhkBaZDvfT/SGQDZeukkMz4ZAQDVeukmyiEC28/3UeNFnQPp+arx0fohAVOOlm8QMeEDRItv5fs5vQEoMAiuHkINAAAAAAADhhUAzMzMzM6uCQG3n+6nx8INATmIQWDm5gUAGgZVDi85xQIgW2c73doZAaJHtfD89a0AdWmQ73xCEQGQ730+NcIFAnMQgsHLqgkAzMzMzM0mCQHsUrkfhi4BAy6FFtvOBgUDP91PjpQeFQMUgsHJoBX9A30+Nl25mfUAj2/l+aupzQEJg5dAi83tA4XoUrkcPekDjpZvEIKxvQOF6FK5HCWtA3SQGgZWeg0Dn+6nx0l99QARWDi2yGX1Az/dT46Wtf0DfT42XbrJRQMdLN4lBRnZADi2yne+lh0DfT42XbiGEQHWTGARWHldAN4lBYOWAWUAAAAAAAIx/QDeJQWDluGNA3SQGgZXdhkA2XrpJDLCIQFyPwvUoAohAlkOLbOcJdkCF61G4HsVgQCYxCKwcNIhAH4XrUbhjiEDJdr6fGs6BQFTjpZvELYhAaZHtfD8RhUDZzvdT4w1xQBxaZDvfYYhA0SLb+X66d0CcxCCwcl+IQE5iEFg5R4hAYxBYObRAiEBEi2zn++d+QAisHFpkO9c/1XjpJjHwW0AbL90kBuqHQO18PzVetYBA6iYxCKyAgUDy0k1iEFR/QJhuEoPAbntAjGzn+6nHcUC7SQwCK0uHQIGVQ4tsCodA+n5qvHRDfUBU46WbxHiGQHE9CtejQn5ARrbz/dR2gEC0yHa+n5yGQAaBlUOLaoZACKwcWmRUhkC4HoXrUXx/QJLtfD81DIZADi2yne/6g0BiEFg5tJxsQNv5fmq8VYVA8/3UeOnzhEBKDAIrh9R5QCUGgZVDI4VAPQrXo3D+hED8qfHSTeaEQClcj8L1rIRAtvP91Hg1ZEAMAiuHFjF7QKAaL90kYHpAIbByaJFng0DTTWIQWM6CQJZDi2znoYJAoBov3ST1gkCgGi/dJOx1QKrx0k1iZoNA2/l+arw8akD8qfHSTYKDQB+F61G41HBA4XoUrkeTfEA830+Nl52AQFYOLbKdUXpAukkMAit9fEB1kxgEVuJ+QFg5tMh2lYFA/tR46SYbd0Ce76fGS8N8QIPAyqFFthVACKwcWmSbR0BBYOXQIlqBQE5iEFg5Nn5Ad76fGi/tZUAzMzMzM4l2QN9PjZdu5nBA5dAi2/nSeEBzaJHtfB2BQAaBlUOLuoFAc2iR7XzNgUBQjZduElyBQDzfT42XjIBAwcqhRba5e0DVeOkmMQuAQMHKoUW2aXxAPzVeuknXgEAhsHJoke14QH9qvHSTIHVAlkOLbOe8gEAtsp3vpyqBQCGwcmiR5oBA9P3UeOk2W0ASg8DKoZFrQL+fGi/dr4BArBxaZDtDa0Cq8dJNYpSAQDVeukkMgn9ADAIrhxZ/fUAIrBxaZDtzQARWDi2yOXBAxSCwcmi7ekC6SQwCK6FxQJZDi2znQ31AsnJoke1CfUCPwvUoXKdwQBKDwMqhx3tAukkMAisZeUDo+6nx0ud1QKabxCCwrmxAPzVeukm8YUB1kxgEViZzQLx0kxgEVHFAjZduEoN4b0AGgZVDi0hqQKAaL90kBtk/f2q8dJM8dUDsUbgehcF0QPT91HjpznBA2/l+ary4c0Dy0k1iEPJwQG8Sg8DKNXFAkxgEVg6Ba0AEVg4tsqVjQBfZzvdT02tAAyuHFtmGbUBg5dAi23FeQD81XrpJaGhAj8L1KFybYUAW2c73U3tgQI/C9ShcQ21AGQRWDi0qbUCPwvUoXM9oQMl2vp8ab1pAtvP91HidYUAIrBxaZDvXP7x0kxgERltA5/up8dK1b0ChRbbz/VRVQNv5fmq8lG5ADQIrhxZFZkB1kxgEVkJsQKrx0k1i4GpAukkMAisfWEBt5/up8Q5hQPP91HjpZmZACtejcD12ZkAIrBxaZHtlQLByaJHtPGFArkfhehSKYkDl0CLb+Z5OQKwcWmQ7B2BAoBov3SSGZEB9PzVeumVkQKAaL90kjlhARIts5/vJXEAdWmQ7329GQMl2vp8a719AvHSTGASOXkBt5/up8TJWQC/dJAaBBVZArBxaZDvPRUD+1HjpJlFRQC/dJAaB9URAokW28/2ERkCq8dJNYvBMQF+6SQwCG0tAlkOLbOcbSkAOLbKd7xdJQCGwcmiRnUNA1HjpJjGISEDjpZvEIDBEQGiR7Xw/tR9AVOOlm8QgOkCgGi/dJIZAQN4kBoGVU0FAGy/dJAYhQkCamZmZmZkvQOf7qfHSTTpAGQRWDi3SN0DVeOkmMUhAQLgehetReD1AUrgehevROUAfhetRuB4+QIPAyqFFdjxARIts5/spLECDwMqhRbY6QHsUrkfhejRAsXJoke0cOEDsUbgehesqQJZDi2znmzBAeekmMQhsLkCBlUOLbOcKQLByaJHtfCNAL90kBoHVJUDb+X5qvLQiQGQ730+NFx9AJQaBlUOL4D+TGARWDq0jQCGwcmiR7R9AsXJoke18CEADK4cW2U4WQLTIdr6fGus/eekmMQisEkCBlUOLbOfvv9v5fmq8dOs/mpmZmZmZ7T+gGi/dJAYRwPYoXI/C9eQ/F9nO91Pj1b8/NV66SQzaPzVeukkMAu+/vHSTGARWA8DByqFFtvMDQBKDwMqhRSVArkfhehRuNEB9PzVeuqk1QGiR7Xw/dTpAj8L1KFwPOUBGtvP91Jg1QJHtfD81bkBA3SQGgZVTQ0CJQWDl0CJAQMUgsHJokURAjGzn+6mRSkDfT42XbkJIQJ7vp8ZL50hA/Knx0k0CT0Coxks3iaFBQARWDi2y7U9AuB6F61EAUkBBYOXQIlNQQMUgsHJoMTRAsp3vp8arVkB3vp8aL5VYQBBYObTIxkVAbef7qfHiRUCR7Xw/NY5dQHE9CtejSF5A3SQGgZX7V0BEi2zn+wFUQG3n+6nxomFACtejcD1uYkBKDAIrh8pjQCyHFtnOE2VAUI2XbhKzXEBoke18P51cQA0CK4cWDWZAlkOLbOe7U0C28/3UeBlaQG3n+6nxemlAN4lBYOVQQkCiRbbz/QxqQHNoke18Z11AnMQgsHL8aECmm8QgsB5mQA4tsp3v52tAN4lBYOXQakDb+X5qvFRoQESLbOf73WhAfT81XrrhVkAUrkfhetRHQCUGgZVD+1xAf2q8dJPISkBvEoPAyuNwQBSuR+F68G9A46WbxCAEZEBoke18Py1aQCyHFtnOU2pAMQisHFrMcECR7Xw/NWZuQLpJDAIrBXFA+n5qvHRRcUAfhetRuGBwQIxs5/upzXFA/tR46SZhcEAEVg4tsvl1QIXrUbgeP3ZAFK5H4Xo0aUAlBoGVQx13QPYoXI/CUW9AiUFg5dCqd0Atsp3vpx5wQARWDi2yk3FA2/l+arxyckDHSzeJQaJwQKAaL90k0HBAukkMAitHdEDb+X5qvE51QBkEVg4tbnVANl66SQwudUB3vp8aL3d0QGQ730+NJ3BAmG4Sg8DcdEAfhetRuI5zQEoMAiuHwHVAoBov3SQYfEBmZmZmZlx8QPhT46WbYnJAexSuR+EGeEBKDAIrhwBwQIGVQ4tsxXNAnu+nxku9fEBeukkMAuduQKabxCCwNnlAjZduEoMgdEAdWmQ732drQN0kBoGVr39ArBxaZDsTb0AfhetRuKR8QDEIrBxaEH5AaJHtfD/ZZkAbL90kBjFyQKAaL90kunNADAIrhxZlekC28/3UeF99QK5H4XoU2n1Ake18PzXUeEAX2c73U3l/QBSuR+F69H5A2s73U+NjeEArhxbZzn9wQDEIrBxafHFA9ihcj8IpaEBkO99PjeVwQF66SQwCN25AQmDl0CLXc0DP91PjpYdgQP7UeOkmAXxAI9v5fmoGeUCxcmiR7fwWQJqZmZmZmeE/MQisHFosckBvEoPAytV0QHsUrkfhfYBAjZduEoOQRUC/nxov3STiP8uhRbbz13ZALbKd76cmXUBfukkMAmtlQMuhRbbz5WZAGy/dJAb9fkDD9Shcj1B+QPYoXI/CkYFAZmZmZmYEeECJFtnO9w93QEa28/3U1n1AaJHtfD/HcEBcj8L1KNZ/QKAaL90klnpAiRbZzvdnf0DByqFFtleBQDEIrBxaCoBAexSuR+EqhUDfT42XbmqFQL6fGi/dRn5AObTIdr6raUCmm8QgsH57QBkEVg4tfHlArkfhehR+Y0AAAAAAAIxqQNEi2/l+mnBALbKd76dbhkD2KFyPwlKGQAaBlUOL84VArkfhehRvhkBPjZduEqGGQEw3iUFgvIZA+n5qvHQShkBBYOXQItmAQH9qvHSTeGxAc2iR7XxPb0BmZmZmZniHQAAAAAAA6HlAbef7qfHIf0BKDAIrhyWIQEoMAiuHmodACKwcWmRxh0CDwMqhRUJuQLTIdr6f4IZAbef7qfHVg0B56SYxCDCDQG8Sg8DKL4JAIbByaJH8h0D4U+Olmyh0QH0/NV66uWZAnMQgsHKid0Bg5dAi23uCQDq0yHa+7YBAnu+nxktvdkDNzMzMzMhiQKjGSzeJr4dABFYOLbKnhUCTGARWDiVxQHNoke18P90/w/UoXI+GaUDvp8ZLNxKDQLKd76fGD3xA001iEFgfg0DLoUW28yyBQHe+nxovBIBAarx0kxh0eEB7FK5H4dx6QHsUrkfhXnxA1XjpJjEQWUBSuB6F6+14QFYOLbKd02dAv8qhRbbz3T8EVg4tsm1aQClcj8L11ntAEoPAyqFF3j9g5dAi29eCQHE9CtejHn1AXI/C9SgChkA/NV66SUyEQDvfT42X/ntAnMQgsHJOgkDl0CLb+TCEQCUGgZVDPYJAAAAAAABzhEDb+X5qvMeAQD81XrpJFoRAVOOlm8TQhkCuR+F6FP+FQJZDi2znu0pAgZVDi2xjbUC8dJMYBJiDQMl2vp8anYhAoBov3SSggEC4HoXrUe5+QOXQItv5gYBA/dR46SYtiEDfT42XbmqDQP7UeOkmYoNAiUFg5dDXhkBpke18P5yHQMuhRbbzFoJAz/dT46W5fkCamZmZmT2HQDEIrBxafHVAQDVeuklkhkAQWDm0yKR9QGMQWDm044JAu0kMAitohkCYbhKDwPZ3QEw3iUFg+31A0SLb+X4Jg0BMN4lBYLqFQAAAAAAARYNA16NwPQq9gkAhsHJokbqAQC2yne+nlodAxSCwcmi2hUATg8DKofeDQLKd76fGrYNATDeJQWD7g0AzMzMzM1OCQGiR7Xw/WoBASOF6FK4HUkBSuB6F686EQKwcWmQ7xYZAMzMzMzM0iEBvEoPAyst6QLgehetR3YJAku18PzXqh0B7FK5H4SWEQKRwPQrXsoVADi2yne+vg0CJQWDl0GI3QKrx0k1i5GVAwcqhRbbZfkDFILByaJ18QJzEILBy2FFAbef7qfF7hEAzMzMzM5WBQI2XbhKD4HlAjGzn+6k7h0DGSzeJQdaHQEoMAiuHF4hANl66SQzSVUDD9Shcj8KDQNnO91PjmYBAzczMzMw4h0Dl0CLb+ZR/QFK4HoXrY39Ad76fGi9rg0CTGARWDv1cQBgEVg4txoFAGy/dJAb7g0BKDAIrh65iQE+Nl24SOoVAVOOlm8RniEAxCKwcWtyGQPp+arx0AYZA001iEFgBd0DfT42XbhLnP7bz/dR4Y4NADi2yne+nBECq8dJNYpuEQCUGgZVD43xAc2iR7Xyyh0CIFtnO92yIQN9PjZdu/HlAEoPAyqGgiEA/NV66SUR3QD81XrpJ+HlAdJMYBFYYgUBt5/up8Rx6QI/C9Shc24NAf2q8dJMgg0B9PzVeugF+QFCNl24Sl4JAvHSTGAQBgECR7Xw/NVJ3QEjhehSuy4VAppvEILDeeEDkpZvEIMmFQBODwMqhZYNA46WbxCAygkCgGi/dJIOFQLTIdr6fRoFA1XjpJjEygUAGgZVDi9B+QArXo3A9KmJA76fGSzeng0C4HoXrUXeIQNNNYhBYY4NAd76fGi8kgUB0kxgEVtSEQCPb+X5qW4VAukkMAivHQ0BxPQrXo554QO+nxks3KIJAWDm0yHY6YUDfT42Xbpp3QKRwPQrXf4NAppvEILA9gUCgGi/dJNuFQFTjpZvEaFpAsHJoke23gkDRItv5fn6AQFK4HoXryYVAdJMYBFbqg0B7FK5H4feCQNrO91Pj1oZAEoPAyqENW0Atsp3vpzeFQN0kBoGVS4JAdZMYBFY+R0DNzMzMzNaCQPhT46WbxHhA8tJNYhD8hkB7FK5H4UJbQAisHFpk6X5AObTIdr4hfEBGtvP91DR9QG3n+6nxmINAnMQgsHLPhkCIFtnO9zM2QOSlm8Qg2odAMQisHFpIf0Av3SQGgfeDQDZeukkMt4hAw/UoXI8Af0Dy0k1iEJ+FQHE9CtejaYNA1HjpJjGxiECsHFpkO/VwQI2XbhKDLGJAHFpkO9+IhUCTGARWDvOBQFpkO99PX4hAVg4tsp35eUC+nxov3STWP2Q730+N83BAaJHtfD9fgUBt5/up8dqGQKabxCCwHYBAO99PjZcjiEBxPQrXow+IQBxaZDvf3YdAsXJoke3chECsHFpkO9l8QIgW2c73rodAqvHSTWJth0BOYhBYOX+HQFCNl24SyINAHVpkO9+1eUBcj8L1KBuHQN0kBoGV/4JAYOXQIttKhUAUrkfher2GQMP1KFyPSl9A1XjpJjE0fkBFtvP91EWFQCcxCKwcoYJAl24Sg8CthkBkO99PjblyQNNNYhBYjWVAoUW28/1WhkDpJjEIrFCFQNejcD0KJ3tA+FPjpZubgECoxks3iUHYP+58PzVe5mtAQDVeuknthUCTGARWDql7QMHKoUW2/3hASOF6FK7QgECiRbbz/XCBQCPb+X5qfYVArkfhehQBhUAtsp3vp0J5QNR46SYxMoVAz/dT46UVhUBpke18PwqFQHSTGARWU4RAz/dT46XKhECoxks3iaqEQG3n+6nxzmtAuB6F61HOc0C/nxov3ZWDQIts5/upuXlAYxBYObREcED+1HjpJqd6QCuHFtnOAYRAlkOLbOfXgkDtfD81XpGDQC/dJAaBooNAnMQgsHKeg0CiRbbz/XODQCUGgZVDgoNAnu+nxkspfUBoke18P/2AQGZmZmZmYmRA6SYxCKxkXUCd76fGS4dgQMuhRbbzhV5AFtnO91OkgkB3vp8aL+N4QNEi2/l+bHlAPQrXo3B9OUDP91PjpSF4QOj7qfHSFYFAxks3iUFegEAOLbKd7y1+QCUGgZVDSXFA/Knx0k0idkDb+X5qvDJwQE5iEFg5oHRAqMZLN4nbc0AQWDm0yDpqQI2XbhKDwNo/pHA9Ctej2D/fT42XbphyQESLbOf7f3BAF9nO91PvdEBYObTIdn5OQMHKoUW2P2tAsp3vp8Y7ZUCkcD0K1/N3QHnpJjEIUHJArkfhehRSYEARWDm0yI5wQKjGSzeJtWxAg8DKoUUWZUB56SYxCPZwQG3n+6nxkm9ACtejcD1iWUCmm8QgsKZvQLpJDAIrA3BASgwCK4cIcUDkpZvEICBVQC2yne+n6HNAi2zn+6kRbkBQjZduElNJQKAaL90kBtk/ukkMAiuH1j+yne+nxmNTQI2XbhKDPHRAvp8aL93UdkAOLbKd70VwQARWDi2yLXVABoGVQ4vQakC+nxov3cBqQJLtfD81gHZAKVyPwvUkakCF61G4Ht1vQFpkO99PgXhALbKd76dmYkAUrkfheoZxQDzfT42X9nJAy6FFtvPtakDP91PjpbtzQKabxCCwqnVAUrgehet1dUD2KFyPwtlvQBxaZDvfk2VA7nw/NV7SVUCF61G4HoluQMP1KFyP7mdAlkOLbOeLR0DVeOkmMYhfQIPAyqFFGHZARrbz/dSsb0DsUbgehfd0QBkEVg4tlmxAvHSTGATyckDD9Shcj0puQOOlm8QgJGdAgZVDi2x/VEDJdr6fGsN0QOxRuB6Fr25A3SQGgZVZdEBkO99PjQtrQNNNYhBYCUhAH4XrUbjWaUDdJAaBlQ1zQMuhRbbzCWxAPN9PjZdmcUCgGi/dJGJnQDzfT42XKnJA9ihcj8JFcEA1XrpJDH5wQOXQItv5/m5A5/up8dK5akCR7Xw/NWZXQDMzMzMzc0dAukkMAiufUkDD9Shcj/pVQLbz/dR4eURAYOXQIttpUUDy0k1iENhKQKjGSzeJUUZAGy/dJAaZU0CJQWDl0KIbQBgEVg4tMlFA001iEFjZNEDo+6nx0o0wQB+F61G4vkNA4XoUrkeBR0DHSzeJQcA1QI2XbhKDwNo/MQisHFp0SEA6tMh2vn9IQHWTGARWPkdAGy/dJAbRQ0BGtvP91ChCQMHKoUW200BA7Xw/NV4aMEDTTWIQWPkpQH0/NV66yT9AUI2XbhJjPUAlBoGVQ4szQOOlm8QgMDRAnMQgsHLoJEDD9Shcj+IwQLTIdr6f2jFAEFg5tMj2KkA5tMh2vh8oQGIQWDm0SCVA001iEFh5LEDRItv5fionQOOlm8QgcCtACtejcD2KMUD6fmq8dNMnQAMrhxbZzh5A2s73U+MlGUDhehSuR+EIQIPAyqFFthpAuB6F61G4GUAj2/l+arwQQDeJQWDl0Pa/fT81XrpJE0D6fmq8dJMTQJ7vp8ZLNwfAoBov3SSGFMAshxbZzvfnvy/dJAaBlQXANV66SQwC7z/jpZvEILD6P+F6FK5H4cq/PQrXo3C9EkD6fmq8dJMPQGq8dJMYBAZAzczMzMzMGkD8qfHSTWIcQM/3U+Ol2yFAAyuHFtmOKkDLoUW2870uQDeJQWDl0B1AZmZmZmYmKkCgGi/dJCYxQIcW2c73kzFA+FPjpZtkMkAK16NwPYo8QA4tsp3vBztAeekmMQjsK0CTGARWDi3mP/yp8dJNYj5A3SQGgZUjQEDNzMzMzNxEQLTIdr6f6kJARIts5/spSkCMbOf7qbFMQClcj8L1OE1A46WbxCCwUEB/arx0k4hNQKRwPQrX40tAd76fGi9tUEDRItv5fhpVQOOlm8QgsEJA001iEFgZPEARWDm0yM5SQNNNYhBYeSxArkfhehT+Q0CwcmiR7TxQQKrx0k1iAFVAsp3vp8a7TkACK4cW2V5DQN0kBoGVk0tA7FG4HoWLTECPwvUoXG9MQJhuEoPAOlJAPzVeukl8QEAbL90kBgFQQCGwcmiRLVFAKVyPwvU4QkC/nxov3STiP8HKoUW28+E/AAAAAADgSUC0yHa+n/pDQC2yne+njlJAiBbZzvezO0C4HoXrUTgsQHe+nxovxVRAhetRuB5FTEC0yHa+nzpPQFg5tMh2tlBAbef7qfECUUAX2c73U1tVQDeJQWDlYFBAFtnO91N7UEAbL90kBrFYQDMzMzMzW1lA8tJNYhDAV0C+nxov3QRZQOOlm8QgpGJA30+Nl27iVkBcj8L1KPhjQJzEILByGFhA001iEFjRXEA/NV66SURjQIlBYOXQmmJAsHJoke38IEC8dJMYBDZaQIlBYOXQgmRAJQaBlUNvY0Bg5dAi20VjQL+fGi/dFGRALbKd76fWZEAbL90kBl1gQD0K16NwcWlApHA9CtcPaEB1kxgEVm5tQEJg5dAi22lABFYOLbLdZEC0yHa+nyJjQLKd76fGA2RAzczMzMwoY0C/nxov3RRlQMl2vp8aT2BAObTIdr5fbEAK16NwPUJgQLKd76fGT2FAtvP91HipaEBmZmZmZt5lQB1aZDvfX0xAv58aL93QY0DD9Shcj8I0QOSlm8QgmGRAd76fGi8dR0BI4XoUrj9dQOOlm8QgYGJAL90kBoFNWUDRItv5fuZlQOXQItv5ZlxAj8L1KFwfXkCIFtnO93NVQGZmZmZmZi5A16NwPQpnYUD91HjpJpllQEjhehSu421A5dAi2/kibEDFILByaPdxQOXQItv5GHJA/Knx0k36YUDn+6nx0q1qQL+fGi/dHHFAUrgehes3cUAK16NwPS5wQG3n+6nxPnJAPN9PjZe+cUAOLbKd78FxQGDl0CLbOTxAtvP91Hi9cEBCYOXQIvNvQPyp8dJNKm9Aj8L1KFx/WEA/NV66SZxNQOj7qfHSTeI/cT0K16PoXED0/dR46fZ0QHNoke1843ZAjZduEoNQVkCxcmiR7exIQPT91HjpnnRAyXa+nxpZdkDTTWIQWFldQKrx0k1ifHBABFYOLbK9akApXI/C9UBqQGq8dJMYXGpAd76fGi+tTUAfhetRuBx0QPYoXI/ChXJAz/dT46XbYkApXI/C9TRzQD0K16NwwWdACKwcWmS1c0B/arx0k0ZzQEJg5dAis2pAwcqhRbbz4T8/NV66SRRdQKFFtvP9NHZAHVpkO9+fbEA3iUFg5XhmQIGVQ4ts83ZAaJHtfD9NeEDP91PjpU16QKRwPQrXxXhApHA9Ctc/bUDfT42Xbg5oQPyp8dJNDHFAnu+nxkvTfUA6tMh2vhV1QHjpJjEISHVANV66SQxsekAMAiuHFuF7QBSuR+F6NnZAsHJoke0ucUBqvHSTGOeAQMUgsHJovX9AtvP91HgygEBt5/up8QB5QG8Sg8DK4WpAEFg5tMjiekCmm8QgsHp5QNV46SYxwnpALIcW2c4re0CF61G4HmV4QPYoXI/CpXVACKwcWmRRgkBGtvP91CB5QO18PzVeXoFACKwcWmQ0gUAj2/l+akB/QLbz/dR4coJA2/l+aryyeEBQjZduEmSAQJHtfD819H9A/Knx0k2RhEAIrBxaZCd7QJMYBFYO2IFAN4lBYOXsf0AlBoGVQyd9QM/3U+Olm2xAeOkmMQhBhUBANV66SWKFQEA1XrpJzYRAN4lBYOVEb0CR7Xw/NQZ6QKJFtvP9ynZAwMqhRba0hEDb+X5qvHR3QESLbOf7T4JAsp3vp8Zfc0DVeOkmMayBQAIrhxbZMIBAKVyPwvWsakCDwMqhRT+BQN0kBoGVLYBA8KfGSzdRdEA3iUFg5QRyQDMzMzMzXYJAPQrXo3AqgUCTGARWDgt+QN9PjZdu+nxAWDm0yHb2fEC8dJMYBKJ7QDeJQWDlnn1AqvHSTWJCfkBjEFg5tCWAQH9qvHSTKYBAexSuR+FaQkDZzvdT46UzQPp+arx0/3hAbxKDwMoBf0CNl24Sg4p+QCUGgZVDjoBA7nw/NV5MeEAAAAAAAFuCQDzfT42XvmFACtejcD1/gEADK4cW2e6EQBxaZDvf84RAf2q8dJNahUBcj8L1KBhnQFYOLbKdqXpACKwcWmR7g0D6fmq8dLODQDzfT42XGYRAhetRuB74g0Av3SQGgT90QAAAAAAAbGdAPzVeukmsOkBkO99PjZ+BQJHtfD81UmNA2s73U+PFdkDP91PjpXKEQDeJQWDlY4ZAL90kBoGphUDpJjEIrI2FQBBYObTIAnpARIts5/tTdkBvEoPAyod6QDMzMzMzh2xA3SQGgZXugkDTTWIQWKWAQAaBlUOLOnpAAyuHFtnkeEDFILByaE1xQEJg5dAiP21A46WbxCDUc0A9CtejcLFuQCcxCKwcxnxAw/UoXI/6ZkB/arx0k/BrQOf7qfHSgX1AVg4tsp0df0ApXI/C9eB5QKabxCCwwIBAnMQgsHJrg0BMN4lBYGF+QDzfT42XR4FADAIrhxZvfEC8dJMYBDR6QIPAyqFFPHdAPzVeukkscUDfT42XbguDQE5iEFg5uYNArkfhehQ3g0CcxCCwcgmBQCyHFtnO12hAdZMYBFYwcUBg5dAi20N/QLbz/dR4woFA16NwPQolgkC28/3UePV1QAisHFpkmoFAg8DKoUWGb0CgGi/dJEGAQEoMAiuHsHRAgZVDi2zHNUCe76fGS8N4QNEi2/l+p4BA7Xw/NV6TgEC8dJMYBK5yQDeJQWDlBnNArBxaZDvDf0CBlUOLbKF+QLKd76fGC1FArBxaZDubf0D+1HjpJg1zQNejcD0KT4FAGy/dJAb9ZkBt5/up8W52QH0/NV66sIFAJQaBlUMngUAZBFYOLUpoQB+F61G4loBAxks3iUFIgUDNzMzMzP2BQKrx0k1iOnVAu0kMAiv/ZUAOLbKd78V4QA4tsp3v/YFA0SLb+X7dgED8qfHSTTJsQCuHFtnOdoFA2c73U+O+gkCBlUOLbBt7QCPb+X5qTEtAL90kBoG6g0CNl24SgwKAQPT91HjpJHxApHA9CtcZe0Dl0CLb+YZ7QDVeukkMVYJAWmQ730/+hEDfT42XbmiAQIgW2c73uoZAYxBYObSEhkCDwMqhRTWBQEoMAiuHKmxA9ihcj8JQg0BGtvP91GWAQKRwPQrX3IZAnMQgsHJufUBvEoPAygN4QEFg5dAiA4hA6SYxCKy4fkDfT42XblmFQFK4HoXr0IFAAyuHFtmehUD8qfHSTWyAQIXrUbge4INAO99PjZdYdUAj2/l+alxIQK5H4XoUQ4RAXI/C9SgihUBjEFg5tApyQFK4HoXrgoNAWDm0yHZiYEBqvHSTGDx/QE+Nl24Sa3ZACtejcD0IhkBxPQrXoxmCQGmR7Xw/NodAl24Sg8BYhkAhsHJokZaFQFyPwvUoZodA+n5qvHRZgkDGSzeJQVKBQKabxCCwz4dAL90kBoFFiEAlBoGVQwV1QKRwPQrXvoBAYhBYObSGf0Av3SQGgeaHQL+fGi/dOIhAne+nxktmg0BI4XoUrquAQMZLN4lBYINAYLpJDAKle0AIrBxaZOt7QBgEVg4tk4NA7nw/NV7ThkCYbhKDwJCDQJqZmZmZGINAN4lBYOWWfECPwvUoXGN8QOF6FK5H34NAMQisHFrodUAzMzMzM3NAQGiR7Xw/BX5AXrpJDALnckBBYOXQIhGEQGDl0CLbh4NAQDVeukkqhkBt5/up8b2FQESLbOf7DohAMQisHFquf0A/NV66ScxzQClcj8L1XH9A2s73U+N3hkC8dJMYBPqFQMDKoUW2i4ZAcT0K16NMhkC8dJMYBGWFQDMzMzMzr3hAGQRWDi2Gd0AGgZVDi52CQNv5fmq85nJA30+Nl24KX0CS7Xw/NRiFQE5iEFg5tnVADAIrhxYteUAfhetRuDCGQGq8dJMYaYhAyqFFtvPIh0ArhxbZznFwQARWDi2yXTVAWmQ730+5dUCLbOf7qdF7QNejcD0KF3pAGQRWDi1udUD4U+Olm+R7QI/C9ShcfoRAj8L1KFwvMEB7FK5H4YhwQJ7vp8ZLN31ATmIQWDlyfUCHFtnO9zaCQFTjpZvEI4JAd76fGi+jekAOLbKd74ODQNEi2/l+vmZA+n5qvHQJd0Bcj8L1KBGDQPyp8dJNroNAUrgeheuzgkA1XrpJDCp7QArXo3A9NoFARrbz/dSYgkCgGi/dJMWEQD0K16NwaXRAnMQgsHKLiEAhsHJokd17QEw3iUFgbohARIts5/tZgkD8qfHSTcKFQHSTGARW54FAc2iR7XxvWEDjpZvEIOSBQOF6FK5HD35AOrTIdr5Ph0DNzMzMzCh3QBSuR+F6yHRAiUFg5dA9h0A9CtejcPmBQPLSTWIQunNAOrTIdr4+h0CMbOf7qTuHQEoMAiuHCIdAku18PzXnhUCF61G4HtFgQLTIdr6fVHlABoGVQ4tngEAIrBxaZH2GQFg5tMh2tH1AVOOlm8SOfUBEi2zn+yOGQLKd76fGpXhAaJHtfD+mg0D+1HjpJs95QLTIdr6fxYRAtMh2vp9BgkBaZDvfTxF6QKjGSzeJZIVA+n5qvHTffUCkcD0K10eCQGZmZmZm9IJAoUW28/26hUCiRbbz/aiAQHE9CtejTIJAL90kBoFshUAUrkfhevx/QKrx0k1itoJAfT81XroDgUAMAiuHFpV+QCUGgZVD131A30+Nl24adEBgukkMAvt+QNNNYhBYioRAUrgeheu7f0BEi2zn+1mEQCuHFtnOJoRA0SLb+X7+c0C0yHa+n2R7QFK4HoXrBoRAi2zn+6nFeEBCYOXQIgV7QIgW2c73yXVAv58aL920g0AEVg4tsleAQFpkO99Pjdc/UI2XbhJDUUAnMQisHMGBQPT91Hjp1HxAmpmZmZn9gkBOYhBYOYxoQGDl0CLb0V9AoBov3SR7gkCwcmiR7a2CQI2XbhKDNnlArBxaZDtjgkC/nxov3T+CQAIrhxbZMIJAjGzn+6lxS0B/arx0k358QPLSTWIQKHlAAAAAAACrgUAlBoGVQw97QMP1KFyPkoFArkfhehR+gUApXI/C9axhQC2yne+ndmtAf2q8dJMCe0CWQ4ts54NyQOXQItv58YBArkfhehTOgEAAAAAAAL54QJhuEoPApHdAYOXQIttugEAUrkfhemJ4QG8Sg8DKQIBARIts5/v1bkDsUbgehUN2QKabxCCwnnpAxSCwcmhZdEDTTWIQWGV+QIgW2c73B3ZAMQisHFpKdEAOLbKd7y1+QBkEVg4trndAnMQgsHLobUBaZDvfT7F4QDq0yHa+/3NAnMQgsHI8e0BfukkMAq91QEjhehSuZ3xAnu+nxkvXZ0A9CtejcAVpQJMYBFYOtXJAppvEILBYeUDD9Shcj/5oQKAaL90kEHtAMQisHFrkb0BWDi2ynUlxQCGwcmiRhXdA46WbxCAKcEDFILByaDE/QB+F61G4FnBA8tJNYhDUdkDdJAaBlS12QPYoXI/CC3ZAgZVDi2zDckDsUbgehTNTQI/C9ShcyXRA30+Nl25abUDpJjEIrDx1QLtJDAIrY3VA+FPjpZsCdkAj2/l+avRlQDq0yHa+T2JAVg4tsp3v1z9U46WbxJhvQK5H4XoUfnNA3SQGgZV5c0CBlUOLbP9ZQC2yne+nim9Aw/UoXI+UckAnMQisHFByQNEi2/l+DnJAMQisHFqCcUDRItv5fihxQG8Sg8DKbW9AnMQgsHJkb0CiRbbz/bJwQL6fGi/dJG5AsXJoke08TkB/arx0k6RuQC2yne+nknBAx0s3iUEWcUAGgZVDi+BsQGQ730+NV3BALbKd76eKb0A3iUFg5exrQNEi2/l+El9Af2q8dJPsYUBYObTIdj5sQHWTGARWJmtAmG4Sg8AOYkADK4cW2T5PQFTjpZvEmF1A001iEFjJUUCamZmZmX1oQPLSTWIQNGRA76fGSzfBYkDvp8ZLN+lhQJMYBFYOLWFAvHSTGAQaY0Cmm8QgsIpUQA4tsp3vJz1AQmDl0CJ7OkAzMzMzMxM4QKAaL90k5j1A/tR46SYRN0ANAiuHFlk6QKabxCCwEjdAsXJoke1cOUDfT42XbpI2QEoMAiuH1jdAfT81XrppMUCamZmZmZkDQNnO91PjBTRA9ihcj8JVM0D6fmq8dBMzQIGVQ4tsRzBA0SLb+X5qK0CamZmZmRktQFg5tMh2/i5A5dAi2/l+IUBkO99PjdcvQKRwPQrXoxhAUrgehevRL0D6fmq8dNMhQCyHFtnONyZAz/dT46WbHkB7FK5H4TogQArXo3A9iiFArBxaZDvfHkDb+X5qvHQGQJhuEoPAiiJA5KWbxCCwFUC4HoXrUbgeQDEIrBxaZAFAVg4tsp3vDkA9CtejcD0WQCyHFtnO9whAfT81XrpJDUDKoUW28/3oPzMzMzMzMwpAFK5H4XoUEkCcxCCwcugTwM/3U+OlmxzADi2yne+n3j+jcD0K16MRwAwCK4cWmSLAYOXQItv5D8CWQ4ts5/sFwHWTGARWDvG/g8DKoUW24z+4HoXrUbjmP/T91HjpJv0/cT0K16NwvT8Tg8DKocUTQAIrhxbZDiNAVOOlm8QgBEC4HoXrUbgeQO58PzVe+iZAT42XbhLDKEAhsHJoka0kQHe+nxovXSdA1HjpJjGIKECTGARWDu0nQJqZmZmZGTdAZDvfT41HQ0B3vp8aL01OQAaBlUOLXERAL90kBoGVT0BaZDvfT81EQNnO91PjBUBACKwcWmTbMEDRItv5fmolQDEIrBxapC5AUrgehevRL0D2KFyPwrUxQB+F61G4vjJANl66SQyiOUDwp8ZLNyk3QFTjpZvEoDxAdZMYBFaOOUCamZmZmbk7QD0K16NwXTpAv58aL93EMED4U+Olm0REQHe+nxovTUdA9ihcj8LdUUArhxbZzjdRQAAAAAAA0EhAjZduEoNoVkCkcD0K17NaQLByaJHt1GJAGy/dJAapXUDRItv5ftZrQDvfT42XFmZAhxbZzvdbaEARWDm0yCBzQHNoke18U2hA6Pup8dKHcECYbhKDwC5xQESLbOf79WZAjGzn+6mBYEArhxbZzm9RQGMQWDm0UHNAz/dT46UzZkArhxbZzsthQGiR7Xw/83JAZDvfT43XW0CDwMqhRSh3QKAaL90krHdAvp8aL93Id0BANV66Sdx1QBODwMqh1UFA2/l+arwQaEAMAiuHFiluQMl2vp8aW29AWDm0yHaOc0CR7Xw/NdZxQGQ730+NM3NATmIQWDlac0AxCKwcWg50QFYOLbKdyXVAu0kMAitjdUB56SYxCHxvQFpkO99PaWpAXI/C9Shie0B3vp8aLx1qQFpkO99PS3BAYOXQItuLeUBoke18P9FyQC/dJAaBb3VAJQaBlUOdd0Atsp3vpwB2QJ7vp8ZL53FAuB6F61Eke0C0yHa+n15vQFpkO99PjeM/L90kBoFFQ0DazvdT4/ltQOF6FK5HTXNA001iEFgpf0A/NV66SQ5zQGiR7Xw/HYBAxSCwcmg1Z0AAAAAAACB7QARWDi2y3XlAc2iR7Xxdd0BmZmZmZoSAQP7UeOkmIWdA5dAi2/n+fkC/nxov3ZyBQJ7vp8ZLAXlAjGzn+6k2gkDqJjEIrH6CQArXo3A9k4JAJQaBlUNffkCwcmiR7eRwQOj7qfHSNVRAuB6F61FoXkAK16NwPYZwQOf7qfHSYW5AUI2XbhJDYkC6SQwCK69eQJhuEoPAyuE/ZmZmZmbqbEBKDAIrh5Z9QGQ730+NDXlA9ihcj8KhZkAMAiuHFgF7QBSuR+F6VIJAWmQ730+tQkDByqFFtl9lQEoMAiuHcHpAmG4Sg8DK4T8CK4cW2ZRxQAisHFpk63NAnMQgsHIHgEBQjZduEpVzQFg5tMh2/nFAarx0kxi0dkCJQWDl0LpxQKwcWmQ73yJAHVpkO98He0CiRbbz/dR8QJZDi2zn7X1Ad76fGi8FeUDRItv5ftpVQMUgsHJoz3pAmpmZmZlOh0AfhetRuD5XQHWTGARWjn1AppvEILC0hUADK4cW2WGHQB+F61G4SIZA7nw/NV5Ye0DsUbgeheeHQB1aZDvfx3RA16NwPQpZcUDP91PjpZd+QMUgsHJo9YRAc2iR7Xw/4T9oke18P0aAQGZmZmZm44JA7FG4HoW5fECDwMqhRU5uQL+fGi/dbnJAYhBYObSuf0DfT42XbvqGQKAaL90kP4dAFK5H4Xr3hkC6SQwCK9F6QG3n+6nxdoVAlkOLbOcTfECLbOf7qQV/QBFYObTIbYdAtMh2vp98dUBxPQrXo+qDQHjpJjEIsYVAQmDl0CLVfkBU46WbxPKAQAisHFpkZYRAXI/C9SiQckDkpZvEIFuIQN0kBoGVUoBAMzMzMzNMiECgGi/dJDeGQPP91Hjp7oVAO99PjZediEDFILByaCaIQCcxCKwcLmpAGy/dJAaZe0BvEoPAypWAQFK4HoXrfYZASOF6FK5giEAv3SQGgeV2QF+6SQwCr2VAg8DKoUV2XUBYObTIdoJ4QBfZzvdTh25ARrbz/dR4YUAMAiuHFu1yQHWTGARW9HFAHVpkO99PcUDazvdT43N+QPCnxks3nXVAz/dT46W7Z0D2KFyPwnVlQFTjpZvE6GZADQIrhxbthEBg5dAi2xl+QBFYObTIKHRAtMh2vp96dECS7Xw/NWp1QAAAAAAAxodA16NwPQq9hkCR7Xw/NQR9QGmR7Xw/Y3VAiUFg5dBUfUD+1HjpJqluQKFFtvP9HnVAF9nO91ORh0AIrBxaZC2BQG3n+6nx5HxAyXa+nxqHfUDjpZvEINJ2QLpJDAIrl29AI9v5fmoobEDdJAaBlSVxQPp+arx022pAj8L1KFzja0Cmm8QgsBpsQJzEILBy1GlArkfhehTWbkBmZmZmZv5vQBSuR+F6xnNAukkMAis/a0Atsp3vp3ZwQOF6FK5HCWNABFYOLbL9b0CF61G4HuluQC2yne+namRAc2iR7XxnXUAdWmQ737diQDVeukkMwltAyXa+nxpDaUBCYOXQIr9oQHsUrkfhGmNA8tJNYhBIZ0BI4XoUrvdoQMl2vp8a12BArkfhehRSaEADK4cW2bZoQHE9CtejhGlA8KfGSzd5aEB/arx0k+hnQOF6FK5H+WhAL90kBoGFaUAtsp3vp/5bQH9qvHSThGNAMQisHFroaUBCYOXQIhteQCuHFtnO719A7FG4HoWnaUDByqFFtsNhQBODwMqh/WNAHFpkO99PZUCBlUOLbCdiQDm0yHa+U21AI9v5fmqgY0ARWDm0yP5VQC2yne+nLmlAc2iR7XyfbkDo+6nx0jVwQESLbOf7U3JAbef7qfFeaEBaZDvfT71zQK5H4XoUWHRAN4lBYOUAc0BSuB6F611nQHNoke18M3ZA5dAi2/kmXUCiRbbz/Vp0QAMrhxbZcHhA/Knx0k1qdUApXI/C9VJ1QKJFtvP94HdAtMh2vp++eEC6SQwCK4VxQPyp8dJNyHhA16NwPQqnbkAQWDm0yCh4QOj7qfHSvXRALbKd76fEckBoke18P81wQE+Nl24SH2VAoUW28/2QdEAYBFYOLaZlQCYxCKwctHVAH4XrUbj8cEDy0k1iENB0QLKd76fGj29AsHJoke2yc0DJdr6fGmNwQCcxCKwcCmRAWDm0yHZWckA9CtejcKlpQMUgsHJoZ3RAw/UoXI9OaEAj2/l+anRaQPyp8dJNEllAXI/C9ShMXkAdWmQ73+dvQNNNYhBY6XRAvp8aL92sbkASg8DKoWFnQFpkO99PqWdAtvP91HilbkDRItv5fkh0QO58PzVe6HRAtMh2vp8WdUDHSzeJQVJ1QLFyaJHtcnVAwcqhRbbvYkASg8DKoTFqQEw3iUFgZ3ZAbef7qfFMdkD6fmq8dAF2QJZDi2znD3ZAtvP91HixdUASg8DKob11QDVeukkM1HdARIts5/uzd0DLoUW286F2QHWTGARWvnVAke18PzXKdkBxPQrXoxhXQDvfT42XQHdABoGVQ4vyckCJQWDl0LplQHNoke18q2RArBxaZDsZdkBBYOXQIidmQGiR7Xw/7VNAy6FFtvMpd0CiRbbz/Vh3QGiR7Xw/kWxA5/up8dJleEC4HoXrUWxpQKwcWmQ7221Asp3vp8ZHdUBMN4lBYNd8QP7UeOkmMeA/iUFg5dB+cUBGtvP91Ip8QB+F61G4xnBAXI/C9Sj0eUBoke18PxOAQA4tsp3vf29AQWDl0CIng0BeukkMAkGEQLgehetRwINARIts5/uzd0Bcj8L1KDRQQJ7vp8ZLd0RAoBov3SQ1g0B1kxgEVuR3QMl2vp8aLwVAMQisHFoUUkBWDi2ynbWFQN0kBoGVr4VAyXa+nxqza0BQjZduEuqDQI2XbhKDvIRA5KWbxCANhkBYObTIdlOAQGQ730+NFoZAwcqhRbZhg0DsUbgehZaHQO18PzVeI4JAxks3iUH6hkD0/dR46d2BQOSlm8Qg+FVADAIrhxa1eUAlBoGVQ5+EQL6fGi/dBHdAVg4tsp11d0BMN4lBYDuEQJzEILByCYVAH4XrUbiYg0BMN4lBYImEQIts5/upPXxAVg4tsp3JeUD6fmq8dPWGQMQgsHJotoNAI9v5fmoKe0CYbhKDwI2BQOj7qfHSAoBAwMqhRbaBhEB0kxgEVnCHQD0K16NwSX1A/Knx0k1efkCMbOf7qQKBQDMzMzMzM39ADAIrhxYsgEBaZDvfT/11QBSuR+F6vYZAiUFg5dAlh0CNl24Sg+CBQJzEILByfIFALbKd76eEfED4U+Olm66BQArXo3A9joFANV66SQxue0AUrkfheo6AQC2yne+njoRAnMQgsHKtgkApXI/C9VmDQDzfT42XTIJAv58aL90Rg0CJQWDl0A+GQEw3iUFgpoNAjGzn+6kKgEAGgZVDizyDQP3UeOkmxoZAnMQgsHIpiEDpJjEIrCGFQO58PzVeWYZAEoPAyqGlf0DfT42Xbk2GQFyPwvUo/YJA9ihcj8KTekDByqFFtjqCQGDl0CLbI4RADi2yne8fiEDLoUW288V/QD0K16NwaXxAarx0kxgrg0CgGi/dJAB+QJzEILByzIJAAiuHFtkOXkB7FK5H4ZpGQMl2vp8aY4JAiUFg5dC3gUAAAAAAAD55QMl2vp8aj4hACtejcD1FiEBBYOXQIhGIQOXQItv5/YdAiBbZzvfyh0BuEoPAyteHQEW28/3U5IdAne+nxkvFh0A2XrpJDJeHQM/3U+Olj4dAu0kMAitth0BSuB6F6xKHQG4Sg8DKGYdANl66SQxCh0DqJjEIrPOBQAisHFpkq31Ad76fGi8zdEBaZDvfT7V/QEJg5dAipXlAYOXQItuEgUDTTWIQWL9/QKjGSzeJDoZAQWDl0CJChUArhxbZzpaAQBsv3SQG+3lAexSuR+FOgEA3iUFg5VSBQG3n+6nxCIJAEFg5tMisekCamZmZmWF4QEw3iUFgz3tAlkOLbOcBfkAtsp3vp9CBQHSTGARWyoJAl24Sg8BMhUA2XrpJDEKFQF+6SQwC4oVAg8DKoUWGhUC28/3UeG2FQH0/NV66i4VAJjEIrBzIhUAv3SQGgTaFQNv5fmq8noRA2s73U+PWhECgGi/dJHKDQAaBlUOL5HZA7Xw/NV7pgUA3iUFg5QiCQOOlm8Qgc4JAOrTIdr4ygkBt5/up8XOBQA4tsp3veYFAPzVeukmgcUCgGi/dJEZeQOXQItv5BltAexSuR+FKWECyne+nxuNYQL6fGi/d3FlAoBov3SROW0CPwvUoXK9dQIcW2c73q15A2c73U+NdYECiRbbz/TRhQHE9CtejDGJA+n5qvHQTZEAGgZVDiyhnQBfZzvdTh2ZAqvHSTWJQZUCWQ4ts5zNjQClcj8L1XGJArkfhehTOYkBGtvP91ARkQFg5tMh2qmNAX7pJDAJ7ZkCNl24Sg7xoQPhT46WbwGZAL90kBoG1ZUBaZDvfT6VlQLgehetR4GVACtejcD3+Z0CuR+F6FC5sQIcW2c73Y21A9ihcj8LdakBYObTIdm5oQIXrUbgeL3BA46WbxCDYakDy0k1iEGxtQPyp8dJNFmtACtejcD1kcEBjEFg5tEpwQJhuEoPAWnNACKwcWmS9cEBEi2zn+6FsQNNNYhBYvWJAfT81XrpdYEDy0k1iEDBaQGQ730+Nf1dAWDm0yHYOVUBvEoPAyuFSQNnO91PjzVFAexSuR+GCUUBt5/up8YpTQArXo3A9ellAvHSTGASmXEAv3SQGgQFjQPyp8dJNcHRAhetRuB5fdUBYObTIdqZ1QE5iEFg52HVA2/l+aryYdECcxCCwcnZ1QOomMQisXHRArBxaZDs1c0CxcmiR7ep0QMuhRbbzuXRAd76fGi9xdECDwMqhRfpzQNv5fmq8uHNAH4XrUbgAc0D+1HjpJhtzQBsv3SQG4XJAyXa+nxrNckBGtvP91GxyQClcj8L1MnJAPN9PjZf0cUC6SQwCK8lxQMuhRbbzp3FAJzEIrBxwcUCPwvUoXGVxQNV46SYxHnFAppvEILB6bEAxCKwcWoBkQBkEVg4tcldArBxaZDs3VEBGtvP91MBTQBsv3SQGgVNAWDm0yHZ2U0Cmm8QgsPJSQH9qvHSTkFFAJQaBlUPjUEDwp8ZLN9lPQESLbOf7OU9A2/l+arzkTkBSuB6F6ylQQJMYBFYOLVBA7FG4HoVzUEBcj8L1KKRQQNEi2/l+SlFA/Knx0k1yUUBjEFg5tGBRQH9qvHSTmFBAE4PAyqGNUECq8dJNYnBQQPp+arx0U1BAbxKDwMrBUEBg5dAi2+FQQKJFtvP9JFBANl66SQyCTkC+nxov3URNQDq0yHa+L01AO99PjZf+S0CiRbbz/fRKQC2yne+ndktA/dR46SaBS0CuR+F6FJ5LQFg5tMh2rkpAWDm0yHaOSEAEVg4tsm1GQPyp8dJNokRA9ihcj8IlQ0BxPQrXo2BBQDMzMzMzcz5AObTIdr5/O0BSuB6F65E4QLKd76fGizdAtMh2vp/aNECWQ4ts5/szQCUGgZVDazFAZDvfT40XLkCYbhKDwAorQE5iEFg5dChA0SLb+X6qJEBfukkMAiseQNv5fmq89BdAy6FFtvP9DUDn+6nx0k3uP4lBYOXQIuu/L90kBoGV+79YObTIdr7zv5qZmZmZmam/MzMzMzMz8z/6fmq8dJMIQE5iEFg5tA9AWmQ7308NFUCxcmiR7XwYQD0K16NwvR5AmpmZmZnZIkCoxks3iYEmQDMzMzMz8yhARrbz/dQ4LUATg8DKoQUxQCuHFtnOtzJAukkMAitHNUBt5/up8TI3QHWTGARWjjlAL90kBoH1OkDpJjEIrBw9QIlBYOXQAj9AWmQ730/NQEB0kxgEVu5BQEoMAiuH9kJA001iEFg5REBqvHSTGGRFQNNNYhBYyUZA3SQGgZWTS0Bg5dAi22lRQJ3vp8ZLV1RArkfhehTGVUBfukkMAhtLQAIrhxbZ3lhAUI2XbhIbWUCPwvUoXM9YQAwCK4cW4VlAj8L1KFyvW0BxPQrXo9BcQBkEVg4tml1Asp3vp8ZLXkCLbOf7qeFfQKwcWmQ7q2BAuB6F61FEYUAK16NwPdphQDq0yHa+W2JAK4cW2c7nYkAEVg4tsqVjQFYOLbKdb2RAYOXQIts5ZUCF61G4HqVlQHnpJjEIlGZAbxKDwMphZ0BSuB6F6yloQNejcD0KI2hAtvP91Hj5aEBMN4lBYM1pQIcW2c73Q2pAQmDl0CL3akC6SQwCKyNrQM/3U+OlL2xAz/dT46WbbEAIrBxaZG9tQDeJQWDlGG5Ax0s3iUHAbkAUrkfheuxuQGq8dJMYxG9AexSuR+EwcECWQ4ts52twQJqZmZmZzXBAw/UoXI8mcUCYbhKDwGRxQIPAyqFF1HFArBxaZDv9cUA9CtejcHNyQARWDi2yvXJAOrTIdr7jckCDwMqhRV5zQA4tsp3vqXNA16NwPQrXc0D8qfHSTUB0QIPAyqFFqnRAAAAAAAC+dEAEVg4tsjt1QHjpJjEIanVABFYOLbKndUAdWmQ73+t1QI2XbhKDTHZAtvP91HjHdkBKDAIrhxJ3QIXrUbgeM3dApHA9CteTd0BQjZduErF3QDvfT42XDHhA9P3UeOloeED8qfHSTaZ4QNNNYhBY93hANV66SQz+eEAtsp3vp6B5QNNNYhBY8XlAWDm0yHYSekC8dJMYBFx6QAaBlUOLrnpA8KfGSzcFe0Dwp8ZLN0F7QNejcD0Kf3tATDeJQWDje0CiRbbz/T58QI2XbhKDhnxA9ihcj8LZfEBiEFg5tPp8QG8Sg8DKSX1Anu+nxkt7fUDb+X5qvOR9QEw3iUFgAX5AkxgEVg4ffkDfT42Xbop+QESLbOf7035A16NwPQo7f0AfhetRuI5/QKwcWmQ75X9AK4cW2c4BgEA6tMh2vjKAQFK4HoXrOYBAmpmZmZk/gEBxPQrXo2SAQOF6FK5He4BAqvHSTWKbgEBeukkMAs+AQKabxCCw74BAYOXQItv5gEBMN4lBYCyBQESLbOf7TYFAVOOlm8RlgUAtsp3vp3uBQAisHFpkjIFAgZVDi2ytgUCgGi/dJNiBQKwcWmQ7+oFATDeJQWAZgkCTGARWDkiCQM3MzMzMZoJAFtnO91OCgkAdWmQ734OCQM3MzMzMu4JAWDm0yHbXgkAW2c73U/yCQPhT46WbHINALbKd76c+g0CgGi/dJDWDQOOlm8Qge4NACKwcWmSFg0A6tMh2vq6DQNnO91PjuYNAzczMzMzvg0D2KFyPwgSEQKwcWmQ7FYRAmG4Sg8AlhEAGgZVDizeEQCcxCKwcVoRApHA9CtdphECamZmZmY2EQJzEILByo4RAPQrXo3DBhEBYObTIduiEQLbz/dR424RAIbByaJHmhEB46SYxCBiFQLx0kxgEMoVAQWDl0CJJhUCDwMqhRWSFQAisHFpkhYVAw/UoXI/FhUBzaJHtfM2FQH0/NV666oVALbKd76f1hUDFILByaAuGQNNNYhBYGoZAarx0kxgihkBI4XoUrlmGQBgEVg4tdoZACKwcWmR2hkA2XrpJDJWGQJLtfD81r4ZAF9nO91OahkA2XrpJDMiGQFYOLbKd8IZAuB6F61H4hkDGSzeJQQSHQAaBlUOLSodAxSCwcmgrh0CsHFpkOxCHQAisHFpknYdA9ihcj8KKh0ARWDm0yJaHQIlBYOXQn4dAyXa+nxrEh0D8qfHSTb+HQL+fGi/dwYdAxSCwcmjih0A2XrpJDOWHQEw3iUFgIIhAkxgEVg4wiEDsUbgehTyIQCyHFtnOPohAH4XrUbhciEANAiuHFmyIQHe+nxovgYhAgZVDi2yhiEBYObTIdryIQNv5fmq8l4hAyqFFtvN1iECxcmiR7eqGQBsv3SQGsohACtejcD17iEDazvdT4yyIQEW28/3ULYdADQIrhxbVhkANAiuHFkKHQHNoke18+4ZA/Knx0k2shkCBlUOLbFOGQCPb+X5qEoZA+FPjpZt+hUBFtvP91PqEQAIrhxbZSIRAdJMYBFajg0AnMQisHLCDQHnpJjEIsYNABoGVQ4sGg0BOYhBYOfGCQM3MzMzMJ4NAmG4Sg8BJg0AbL90kBkCDQOOlm8QgZ4NALbKd76dgg0BBYOXQIj+DQPLSTWIQRYJAN4lBYOVSgkA6tMh2vuSBQEjhehSuWIFAc2iR7XwMgUDZzvdT41CBQBFYObTI7oFAnMQgsHKSgkDRItv5fqeCQDEIrBxaqYJA9P3UeOmKgkDqJjEIrCuDQNv5fmq8BINAbef7qfHXgkDhehSuRzmDQIcW2c730oJAYOXQIttdgkAOLbKd7zCCQG3n+6nxk4JAcT0K16Msg0A1XrpJDIaDQPT91HjpDIRAVg4tsp02hEDfT42Xbu6DQN9PjZdusYNAqMZLN4mDg0D0/dR46bmCQIlBYOXQZ4JAz/dT46UugkAlBoGVQwCCQJqZmZmZ8YFAYxBYObQvgEAbL90kBjN/QM3MzMzMtn9A001iEFhDfkAxCKwcWpB9QOF6FK5Hr31AMQisHFrqfkCWQ4ts5xF/QGiR7Xw/E4BAexSuR+Egf0AQWDm0yCJ9QIkW2c73nXtAObTIdr4Le0CJQWDl0KZ5QBSuR+F6mnlA9P3UeOlweUCNl24Sg5x5QDvfT42XBnlACKwcWmRbekBI4XoUriN8QCyHFtnOp3xAkxgEVg5FfEB9PzVeund7QLJyaJHt4ntAWmQ730+Ne0DpJjEIrDp8QCPb+X5qDHxAi2zn+6mBfEDhehSuRxN9QM3MzMzMwH1A/Knx0k3QfUB7FK5H4aR9QFTjpZvE0HxAF9nO91OrfEDl0CLb+VJ8QNv5fmq8LH1A/tR46SZZfED+1HjpJvt7QFTjpZvEsHlAoBov3SSgeEAOLbKd75d5QEw3iUFgl3pAZmZmZmaCe0AnMQisHI57QD81XrpJWnxAnMQgsHIae0AMAiuHFrd6QAAAAAAAznpAEoPAyqFRfUCWQ4ts58V9QEJg5dAiPXxAKVyPwvWad0AfhetRuJB0QEJg5dAiu3JAwcqhRbajckB3vp8aLx90QLByaJHtCnRA5dAi2/ladUB9PzVeugN3QLKd76fGzXRAHVpkO98Pc0Coxks3idlyQN0kBoGVIXNADAIrhxaTcUCamZmZmXVsQFCNl24Se2tAmpmZmZlNbEB3vp8aL7VsQIts5/upAWxA5dAi2/maakCNl24Sg2xoQPT91Hjp0mZAxSCwcmiFZkBWDi2ynd9mQKRwPQrXr2dARrbz/dTwZ0AX2c73U5doQFYOLbKd72dA5/up8dL5Z0AK16NwPYZoQMuhRbbzfWlAGy/dJAbJaEC+nxov3VBoQK5H4XoUNmhAokW28/38aEA730+Nl25qQEw3iUFg6WpAI9v5fmoYa0Ce76fGS3NsQCGwcmiR/W1AO99PjZc+bkA/NV66SUhtQOOlm8Qg4G5AIbByaJGdbUAEVg4tstFtQNv5fmq8bG5AlkOLbOcDbkAj2/l+avxqQLgehetRDGlAnMQgsHK0ZkDb+X5qvBhlQGq8dJMYHGRAYOXQIttRY0CNl24Sg1RiQFTjpZvEdGFASgwCK4eqYEAhsHJokeVfQDvfT42Xjl1AAAAAAADgW0Boke18P61bQMP1KFyPKltA46WbxCBQWkB1kxgEVo5ZQPT91HjpRlpAexSuR+FqWkBGtvP91OhZQAaBlUOLZFpATmIQWDn8WUC+nxov3WxZQFyPwvUoBFtAAAAAAABoXEBqvHSTGARdQJzEILBy0F1AHVpkO9+fXUD4U+Olm8xdQLgehetRGF5AUI2XbhLrXkDZzvdT4+1eQEw3iUFgNV9AQmDl0CJbXUBKDAIrh85eQCUGgZVD/2BAAAAAAAA8Y0DTTWIQWBlhQI/C9ShcS2FAg8DKoUUOYEBxPQrXowhfQHE9CtejSF5AvHSTGAQWX0CMbOf7qeFgQIGVQ4tsa2JAVg4tsp0rY0BEi2zn+yFhQGMQWDm0ZGNAeOkmMQg0ZUDEILByaM1gQDeJQWDl4FpAuB6F61HYV0DufD81XqpWQPYoXI/C/VVAYxBYObSQVEA830+Nl85TQG3n+6nxslJAiUFg5dASUUBCYOXQIitPQP3UeOkmIUxANl66SQxySUCuR+F6FP5HQHsUrkfhCkdAc2iR7XwfRkDufD81XgpGQM3MzMzMfEVAuB6F61FoRUCq8dJNYiBFQKRwPQrXQ0RAqMZLN4nBQ0DjpZvEIJBDQM/3U+Olm0JA+n5qvHTTQUCsHFpkO+9AQIPAyqFF9j5AH4XrUbh+PECamZmZmZk5QG8Sg8DKATdAWmQ730/NM0Cmm8QgsJIxQP7UeOkmsTBAHVpkO9/PK0Aj2/l+ajwpQAMrhxbZDihA2s73U+OlJkDb+X5qvDQlQN0kBoGVwyNAF9nO91NjIkC+nxov3SQiQBfZzvdT4xpA7nw/NV46FUDP91PjpZsSQGIQWDm0yA5AAyuHFtnOBkAhsHJoke0FQMUgsHJokQFAjZduEoPA6j/pJjEIrBzKv05iEFg5tPS//Knx0k1iAMC+nxov3ST4v3E9CtejcO2/OrTIdr6f6r9OYhBYObTIv3sUrkfheug/Gy/dJAaBBkC+nxov3SQMQGZmZmZm5hFAuB6F61E4FkDl0CLb+X4XQOXQItv5fhxA1XjpJjGII0Bg5dAi27kmQLbz/dR4qS1ACtejcD1qMkDhehSuR8E0QLgehetR2DVArBxaZDtfOEA730+Nl+46QGQ730+NFz5ASgwCK4d2QUBQjZduEmNDQLTIdr6f2kRAyXa+nxr/RUD8qfHSTfJGQCPb+X5qLExAppvEILAiUUB9PzVeuqlUQBFYObTI7lRAyXa+nxo/TkDJdr6fGl9ZQBKDwMqhdVlAzczMzMxcWkBt5/up8TpaQAisHFpkS1lAI9v5fmqMWEA5tMh2vudbQOF6FK5HsV5AvHSTGAQyYEDByqFFtqdgQFYOLbKdM2BA+n5qvHQbYUCF61G4HkFjQKwcWmQ7o2RAwcqhRbbXZUB3vp8aL01nQMP1KFyPZmdAbxKDwMqlZ0C6SQwCK5dnQLTIdr6fDmhACtejcD2uZ0Coxks3if1mQGZmZmZmgmZACKwcWmRjZkDXo3A9CjdlQLx0kxgEimVADQIrhxZRZkDfT42XbsZlQEFg5dAiV2NA30+Nl24+ZUA730+Nl15oQF66SQwCd2xAi2zn+6mNb0B9PzVeuoFtQCUGgZVDb2xAMQisHFp4b0AbL90kBiFsQJZDi2znl2ZAnu+nxku7ZkA730+Nl55uQCcxCKwc8m5A7nw/NV62b0A/NV66SVxxQEa28/3UCnBA4XoUrkc1bEBkO99PjVNuQIts5/upIW9A7nw/NV5Kb0Dwp8ZLN7ltQOxRuB6FM2xAXrpJDAKtcEBU46WbxEBzQLbz/dR4NXBASgwCK4cYckCamZmZmcVzQAIrhxbZJnBAokW28/0gbkBoke18PxtzQMP1KFyPaHRAVOOlm8R6dUBKDAIrh25xQClcj8L1onBAhxbZzvfHb0CPwvUoXNVzQLByaJHtWHJAPN9PjZccckBiEFg5tNRtQH9qvHSTiHJAbef7qfHQdEBt5/up8WxxQJ7vp8ZLB21AYOXQIturcECyne+nxntzQKJFtvP9endAL90kBoFddkDP91PjpWNzQHe+nxovCXdAOrTIdr7BckA/NV66SRhxQI/C9Shcz3RAw/UoXI+seEBU46WbxIx4QL+fGi/dPHRAlkOLbOepfUBWDi2ynfV7QHnpJjEIGn5AxSCwcmjpfUBzaJHtfCKAQOOlm8QgNoBAsHJoke1fgEBI4XoUrk+AQP7UeOkmD4BA46WbxCBigEDLoUW288OAQPLSTWIQroBA7Xw/NV5xgEBxPQrXo5eAQFK4HoXrdoBAjGzn+6kPgUDZzvdT43WBQEjhehSuQIFA8tJNYhA5gUAj2/l+anaBQK5H4XoULYFAPzVeuklJgkBEi2zn+8mCQBbZzvdTO4JAKVyPwvVqgUC/nxov3WGCQJ3vp8ZLlIJAhetRuB4hgkAdWmQ736qBQM3MzMzMJ4NAf2q8dJPKgUAUrkfhepR+QM/3U+Ol5XhATDeJQWBxeEC4HoXrUQZ5QHNoke182XxALIcW2c7RfUAtsp3vp0p6QFYOLbKdW3RABoGVQ4s6ekCyne+nxq19QAIrhxbZRnNArkfhehRqgUDy0k1iELWEQOSlm8Qg5oRA/Knx0k0BhUB/arx0kzOGQP3UeOkm7YVAMzMzMzMghkAAAAAAAPyFQLtJDAIr3YVAhetRuB74hUAxCKwcWoeGQNv5fmq8hoZAGARWDi1KhkAj2/l+ameGQDEIrBxaR4ZAbhKDwMpbhkDpJjEIrFyGQMZLN4lBlIZAPQrXo3DVhkCF61G4HkuHQL+fGi/dcIdAVOOlm8RUh0BFtvP91HuFQMqhRbbzjYZALbKd76dDhkBWDi2yncGGQNR46SYxuIZAJjEIrBxph0A9CtejcDmIQDZeukkMqIdAtvP91HgdiECWQ4ts5yOIQIPAyqFFd4JAmpmZmZnjfUCPwvUoXEmHQKrx0k1imYVAWmQ730+tiEBxPQrXo9KHQDm0yHa+3X9ADi2yne+Kh0DsUbgehXl+QP7UeOkmTIBAw/UoXI9GgkCJQWDl0EyAQNrO91Pj7IVAdJMYBFbShUBI4XoUrp+HQL+fGi/di4dA2c73U+Pbc0B3vp8aL2GFQMP1KFyPqoVAYxBYObR2iED4U+Olm4OGQHnpJjEIDoFAaZHtfD8MiEAMAiuHFliAQKwcWmQ7TYNAtvP91HisgkAshxbZzqt2QNv5fmq8sohA9ihcj8JQh0Coxks3iWSHQG4Sg8DK+YdApHA9CtfvhUCDwMqhRb6IQPT91HjpLoJAqvHSTWLRhkCuR+F6FN2FQKwcWmQ7xYZAIbByaJFUgkD4U+Olm3uBQOF6FK5HxINAiBbZzvcIhUDfT42Xblx/QCUGgZVDn4hA76fGSzcBgUBI4XoUrjmHQGq8dJMY3YBALbKd76eOhEAbL90kBj2FQEw3iUFgZIZAGARWDi0jh0BSuB6F62CBQN9PjZduUHhARrbz/dRqg0Dy0k1iEO2FQC/dJAaBqYVAFtnO91PJgkAK16NwPZxxQPLSTWIQVnhAkxgEVg4Tf0ACK4cW2XeEQBSuR+F6/IVAbef7qfEPgkA3iUFg5aZ1QM/3U+OlsYNAu0kMAivHhECmm8QgsIuDQIcW2c73aYBAke18PzXAgkCsHFpkO0l7QMZLN4lBHIFADi2yne8LgEDn+6nx0tVqQI/C9Shce3pAXI/C9SgHg0ApXI/C9Tp3QN9PjZduCHFAhxbZzvezbECJQWDl0BJ2QFCNl24SX39AYOXQIttXf0Aj2/l+avJ4QAaBlUOL6YFAGy/dJAZzg0ATg8DKodWDQNnO91PjfINAw/UoXI/9gkDFILByaKV1QKAaL90kaoJA+n5qvHRPgkDdJAaBlXeCQKwcWmQ7OoJAWmQ730/UgUCsHFpkO+KBQB+F61G46YFAbef7qfG6gUBaZDvfT6iBQLx0kxgErIFAMQisHFqTgUAfhetRuCOAQCPb+X5qfYFAf2q8dJONgUAshxbZzkF4QFK4HoXrUV9ADi2yne8nWkDNzMzMzDxfQCcxCKwc1nlABoGVQ4tMcEDXo3A9CltpQESLbOf7dWpA30+Nl24ibUAOLbKd7z9hQAwCK4cWRW9AmG4Sg8CodUAhsHJokbV3QCGwcmiRBXdAtMh2vp9SYEDP91PjpcNkQDm0yHa+r1tA30+Nl25CX0CkcD0K13tgQNNNYhBYTWBAfT81XrrFcUD91HjpJiFmQDVeukkM9mJArkfhehRyZEBoke18P6FmQFYOLbKd53JA0SLb+X4wdkAQWDm0yEB6QIXrUbgeHXJAL90kBoEtXkDy0k1iEMBXQESLbOf76VVAFK5H4XpMV0AmMQisHDJVQNEi2/l+ilVADAIrhxbpVkB3vp8aL6VZQARWDi2yVVxAWDm0yHbWXUBMN4lBYL1gQNrO91PjSWVAjGzn+6nhYUA3iUFg5QhcQDeJQWDl0FlAy6FFtvPFWUCmm8QgsEJaQJHtfD81DlpA1XjpJjEgWkBt5/up8SpZQIts5/upWVhAKVyPwvWoWEB3vp8aL11YQJZDi2znE1ZAT42XbhKzVUBaZDvfT/VVQFpkO99PPVdA/Knx0k2aV0DNzMzMzCRYQI2XbhKDsFlApHA9CtfDWUBU46WbxNBYQKwcWmQ7d1hAzczMzMycV0CBlUOLbKtgQHWTGARWFmpAnMQgsHIAbEBvEoPAyuVxQH0/NV664WVA16NwPQq/U0DZzvdT45VRQHSTGARW1lFAVg4tsp3fVkCwcmiR7XxdQB+F61G4zktA+FPjpZv0SEApXI/C9ShIQHNoke18z0dAH4XrUbgeSkAOLbKd7+9QQBODwMqhqWFAZDvfT43HYkBOYhBYOXRbQM/3U+Ole1BA6SYxCKy8TUAX2c73U6NNQEoMAiuHtkxAtvP91Hh5S0Cq8dJNYoBIQJqZmZmZ2UZA/dR46SaxRECMbOf7qcFCQBfZzvdTk0FAbef7qfHSPkASg8DKoUU9QAisHFpkeztAbxKDwMoBOkDXo3A9Ctc4QNv5fmq8VDdAXrpJDALrM0A3iUFg5RAxQJzEILByaDFAZDvfT40XM0Dn+6nx0g0zQIXrUbgehTJAVOOlm8SAMkA3iUFg5RAxQAaBlUOLbC9AAyuHFtlOLEB9PzVeukkoQMUgsHJokSRAXrpJDAJrIUCuR+F6FK4gQBsv3SQGgSBAHFpkO99PGEDb+X5qvHQUQPYoXI/C9RJAjZduEoPAE0Dl0CLb+f4TQKabxCCwchVATmIQWDm0FkDUeOkmMQgXQNEi2/l+ahZAoBov3SQGE0A6tMh2vh8SQJZDi2zn+wlAzczMzMzMBUDFILByaJH1P8ShRbbz/bQ/z/dT46Wb+r/UeOkmMQj2vyGwcmiR7fi/", 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", 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", 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    " ] @@ -93276,10 +48060,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:31:16.277304Z", - "iopub.status.busy": "2026-02-04T19:31:16.276756Z", - "iopub.status.idle": "2026-02-04T19:31:16.331817Z", - "shell.execute_reply": "2026-02-04T19:31:16.331264Z" + "iopub.execute_input": "2026-03-20T15:45:34.678637Z", + "iopub.status.busy": "2026-03-20T15:45:34.678152Z", + "iopub.status.idle": "2026-03-20T15:45:34.760162Z", + "shell.execute_reply": "2026-03-20T15:45:34.757983Z" } }, "outputs": [], @@ -93302,10 +48086,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:31:16.336479Z", - "iopub.status.busy": "2026-02-04T19:31:16.336479Z", - "iopub.status.idle": "2026-02-04T19:31:17.465298Z", - "shell.execute_reply": "2026-02-04T19:31:17.465298Z" + "iopub.execute_input": "2026-03-20T15:45:34.764365Z", + "iopub.status.busy": "2026-03-20T15:45:34.763720Z", + "iopub.status.idle": "2026-03-20T15:45:35.741155Z", + "shell.execute_reply": "2026-03-20T15:45:35.739807Z" }, "tags": [ "nbsphinx-thumbnail" @@ -93314,7 +48098,7 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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    " ] @@ -93354,10 +48138,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:31:17.469307Z", - "iopub.status.busy": "2026-02-04T19:31:17.469307Z", - "iopub.status.idle": "2026-02-04T19:31:17.474261Z", - "shell.execute_reply": "2026-02-04T19:31:17.474261Z" + "iopub.execute_input": "2026-03-20T15:45:35.744917Z", + "iopub.status.busy": "2026-03-20T15:45:35.744338Z", + "iopub.status.idle": "2026-03-20T15:45:35.751993Z", + "shell.execute_reply": "2026-03-20T15:45:35.750200Z" } }, "outputs": [ @@ -93378,10 +48162,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:31:17.477269Z", - "iopub.status.busy": "2026-02-04T19:31:17.477269Z", - "iopub.status.idle": "2026-02-04T19:31:17.481848Z", - "shell.execute_reply": "2026-02-04T19:31:17.481848Z" + "iopub.execute_input": "2026-03-20T15:45:35.756334Z", + "iopub.status.busy": "2026-03-20T15:45:35.755731Z", + "iopub.status.idle": "2026-03-20T15:45:35.762853Z", + "shell.execute_reply": "2026-03-20T15:45:35.761206Z" } }, "outputs": [ @@ -93415,10 +48199,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:31:17.485857Z", - "iopub.status.busy": "2026-02-04T19:31:17.484864Z", - "iopub.status.idle": "2026-02-04T19:32:02.443094Z", - "shell.execute_reply": "2026-02-04T19:32:02.442084Z" + "iopub.execute_input": "2026-03-20T15:45:35.766733Z", + "iopub.status.busy": "2026-03-20T15:45:35.766272Z", + "iopub.status.idle": "2026-03-20T15:46:17.789141Z", + "shell.execute_reply": "2026-03-20T15:46:17.787318Z" } }, "outputs": [ @@ -93426,10 +48210,8 @@ "name": "stderr", "output_type": "stream", "text": [ - "c:\\users\\mspringe\\onedrive - nrel\\msp\\pvfleets\\repos\\public\\rdtools\\rdtools\\soiling.py:27: UserWarning:\n", - "\n", - "The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", - "\n" + "C:\\Users\\mspringe\\AppData\\Local\\Temp\\1\\ipykernel_35872\\2847556095.py:8: UserWarning: The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", + " from rdtools.soiling import soiling_srr\n" ] } ], @@ -93452,10 +48234,10 @@ "execution_count": 18, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:32:02.449095Z", - "iopub.status.busy": "2026-02-04T19:32:02.449095Z", - "iopub.status.idle": "2026-02-04T19:32:02.457295Z", - "shell.execute_reply": "2026-02-04T19:32:02.456285Z" + "iopub.execute_input": "2026-03-20T15:46:17.792470Z", + "iopub.status.busy": "2026-03-20T15:46:17.791988Z", + "iopub.status.idle": "2026-03-20T15:46:17.799026Z", + "shell.execute_reply": "2026-03-20T15:46:17.797692Z" } }, "outputs": [ @@ -93476,10 +48258,10 @@ "execution_count": 19, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:32:02.462291Z", - "iopub.status.busy": "2026-02-04T19:32:02.461299Z", - "iopub.status.idle": "2026-02-04T19:32:02.467436Z", - "shell.execute_reply": "2026-02-04T19:32:02.467436Z" + "iopub.execute_input": "2026-03-20T15:46:17.801747Z", + "iopub.status.busy": "2026-03-20T15:46:17.801414Z", + "iopub.status.idle": "2026-03-20T15:46:17.806438Z", + "shell.execute_reply": "2026-03-20T15:46:17.805299Z" } }, "outputs": [ @@ -93501,10 +48283,10 @@ "execution_count": 20, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:32:02.473443Z", - "iopub.status.busy": "2026-02-04T19:32:02.472441Z", - "iopub.status.idle": "2026-02-04T19:32:13.806873Z", - "shell.execute_reply": "2026-02-04T19:32:13.806873Z" + "iopub.execute_input": "2026-03-20T15:46:17.808838Z", + "iopub.status.busy": "2026-03-20T15:46:17.808515Z", + "iopub.status.idle": "2026-03-20T15:46:28.311846Z", + "shell.execute_reply": "2026-03-20T15:46:28.310459Z" } }, "outputs": [ @@ -93512,15 +48294,13 @@ "name": "stderr", "output_type": "stream", "text": [ - "c:\\users\\mspringe\\onedrive - nrel\\msp\\pvfleets\\repos\\public\\rdtools\\rdtools\\plotting.py:173: UserWarning:\n", - "\n", - "The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", - "\n" + "C:\\Users\\mspringe\\AppData\\Local\\Temp\\1\\ipykernel_35872\\3529624818.py:2: UserWarning: The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", + " fig = rdtools.plotting.soiling_monte_carlo_plot(soiling_info, daily, profiles=200)\n" ] }, { "data": { - "image/png": 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", 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", 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    " ] @@ -93540,10 +48320,10 @@ "execution_count": 21, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:32:13.810883Z", - "iopub.status.busy": "2026-02-04T19:32:13.809883Z", - "iopub.status.idle": "2026-02-04T19:32:14.037492Z", - "shell.execute_reply": "2026-02-04T19:32:14.037492Z" + "iopub.execute_input": "2026-03-20T15:46:28.315914Z", + "iopub.status.busy": "2026-03-20T15:46:28.315366Z", + "iopub.status.idle": "2026-03-20T15:46:28.554677Z", + "shell.execute_reply": "2026-03-20T15:46:28.552355Z" } }, "outputs": [ @@ -93551,15 +48331,13 @@ "name": "stderr", "output_type": "stream", "text": [ - "c:\\users\\mspringe\\onedrive - nrel\\msp\\pvfleets\\repos\\public\\rdtools\\rdtools\\plotting.py:233: UserWarning:\n", - "\n", - "The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", - "\n" + "C:\\Users\\mspringe\\AppData\\Local\\Temp\\1\\ipykernel_35872\\476338665.py:3: UserWarning: The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", + " fig = rdtools.plotting.soiling_interval_plot(soiling_info, daily)\n" ] }, { "data": { - "image/png": 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", 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", 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    " ] @@ -93580,10 +48358,10 @@ "execution_count": 22, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:32:14.040511Z", - "iopub.status.busy": "2026-02-04T19:32:14.040511Z", - "iopub.status.idle": "2026-02-04T19:32:14.055614Z", - "shell.execute_reply": "2026-02-04T19:32:14.055614Z" + "iopub.execute_input": "2026-03-20T15:46:28.559543Z", + "iopub.status.busy": "2026-03-20T15:46:28.558578Z", + "iopub.status.idle": "2026-03-20T15:46:28.579159Z", + "shell.execute_reply": "2026-03-20T15:46:28.577403Z" } }, "outputs": [ @@ -93723,10 +48501,10 @@ "execution_count": 23, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:32:14.059622Z", - "iopub.status.busy": "2026-02-04T19:32:14.059622Z", - "iopub.status.idle": "2026-02-04T19:32:14.189628Z", - "shell.execute_reply": "2026-02-04T19:32:14.189123Z" + "iopub.execute_input": "2026-03-20T15:46:28.583419Z", + "iopub.status.busy": "2026-03-20T15:46:28.583036Z", + "iopub.status.idle": "2026-03-20T15:46:28.726081Z", + "shell.execute_reply": "2026-03-20T15:46:28.724330Z" } }, "outputs": [ @@ -93734,15 +48512,13 @@ "name": "stderr", "output_type": "stream", "text": [ - "c:\\users\\mspringe\\onedrive - nrel\\msp\\pvfleets\\repos\\public\\rdtools\\rdtools\\plotting.py:273: UserWarning:\n", - "\n", - "The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", - "\n" + "C:\\Users\\mspringe\\AppData\\Local\\Temp\\1\\ipykernel_35872\\2137372672.py:2: UserWarning: The soiling module is currently experimental. The API, results, and default behaviors may change in future releases (including MINOR and PATCH releases) as the code matures.\n", + " fig = rdtools.plotting.soiling_rate_histogram(soiling_info, bins=50)\n" ] }, { "data": { - "image/png": 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iIpKGIURERNIwhIiISBqGEBERScMQIiIiaRhCREQkDUOIiIikMbsQUqlUGD9+PNzd3VG+fHk0adIEO3fulF0WERGZgNmF0IABAzBr1ix8/PHHmDt3LqytrdG5c2ccOnRIdmlERGRkNrILeNmJEyewevVqzJgxA2FhYQCA/v37w9/fH+PGjcORI0ckV0hERMZkVltC69evh7W1NYYMGaJps7Ozw6BBg3D06FHcunVLYnVERGRsZhVCZ86cwdtvvw1nZ+cC7Y0bNwYAnD17VkJVRERkKma1O+7evXuoWrWqVnt+2927d3U+TqVSQaVSae6np6cDADIyMvSuJU+VpbPdkD7JfBT2/gIlf4+L6qukzyG7L2PS5/9KadRsruNVmKLG0Zg1G/Ldlv9YIUTJHyzMiLe3twgMDNRqv379ugAgZs+erfNxERERAgBvvPHGG28Sb7du3Srx975ZbQmVL1++wBZNvpycHM1yXcLDwzF69GjN/by8PKSmpqJChQpQKBQG1ZSRkQEPDw/cunVLazchFQ/H0DAcP8Nw/AxTnPETQiAzMxPu7u4l7t+sQqhq1aq4c+eOVvu9e/cAoNAXqFQqoVQqC7S5uroatTZnZ2d+gA3EMTQMx88wHD/DvGr8XFxc9OrXrE5MaNCgAa5cuaK1b/L48eOa5UREZDnMKoSCg4OhVquxaNEiTZtKpcLSpUvRpEkTeHh4SKyOiIiMzax2xzVp0gQ9e/ZEeHg4UlJSULNmTSxbtgyJiYlYsmSJlJqUSiUiIiK0dvdR8XEMDcPxMwzHzzCmHj+FEPqcU2c6OTk5+Oabb7BixQo8fvwY9erVw5QpU/DBBx/ILo2IiIzM7EKIiIjKDrM6JkRERGULQ4iIiKRhCBERkTQMIR3S0tIwZMgQvPnmm3BwcMD777+P06dPl7ifZ8+eoU6dOlAoFJg5c6YJKjVPhozf4sWL0bp1a1SuXBlKpRI1atTAwIEDkZiYaNqizYi+45eXl4eYmBh07doVHh4ecHBwgL+/P7777jvNVUfKAkM+fydOnMDnn3+Ohg0boly5cgZfccWcGTKB6J07d9CrVy+4urrC2dkZ3bp1w40bN/QrpMQX+rFwarVaNG/eXDg4OIhJkyaJ+fPnizp16ggnJydx5cqVEvX1448/CgcHBwFAzJgxw0QVmxdDx2/YsGEiNDRUzJw5UyxZskR8/fXXonLlyqJixYrizp07pfAK5DJk/DIzMwUA0bRpU/Hdd9+JRYsWiYEDBworKyvRpk0bkZeXV0qvQh5DP38RERGiXLlyomHDhuLtt98WlvwV2bt3b2FjYyPCwsJEdHS0aNasmbCxsREHDx4s8nGZmZmiVq1aolKlSmL69Oli1qxZwsPDQ1SvXl08fPiwxHVY7gjrac2aNQKAWLdunaYtJSVFuLq6ij59+hS7n/v37wsXFxcxefLkMhVCxhq/l506dUoAENOmTTNWmWbLkPFTqVTi8OHDWu2RkZECgNi5c6fR6zU3hn7+kpOTRVZWlhBCiC+++MJiQ+j48eNa30vZ2dnCx8dHNGvWrMjHTp8+XQAQJ06c0LQlJCQIa2trER4eXuJaLHOEDdCzZ09RuXJloVarC7QPGTJE2Nvbi5ycnGL1M3DgQNG4cWNx48aNMhVCxhq/lz18+FAAEOPHjzdWmWbLFOMXHx8vAIh58+YZq0yzZczxs+QQGjt2rLC2thbp6ekF2qdOnSoAiL///rvQxwYEBIiAgACt9o4dOwofH58S18JjQv9w5swZvPvuu7CyKjg0jRs3RlZWFq5cufLKPk6cOIFly5Zhzpw5Fr1PWRdjjB8APHr0CCkpKTh16hQGDhwIAGjXrp3R6zU3xhq/lyUnJwMAKlasaJQazZkpxs8S6TuBaF5eHuLj49GoUSOtZY0bN8b169eRmZlZoloYQv+g78R6+YQQGDFiBEJCQtCsWTOT1GjODB2/fNWqVUPlypUREBCAI0eOYN68eejQoYNRazVHxhq/l0VFRcHZ2RmBgYEG12fuTDF+lkjfcUpNTYVKpTLqGJvVteOMLS8vD7m5ucVaV6lUQqFQIDs7W+c1kuzs7AAA2dnZRfYTExOD8+fPY/369SUv2MzIGL9827ZtQ05ODhISErBixQo8ffq0+IWbCZnjl2/q1KnYtWsXfv75Z6NPb2Jq5jB+lkrfccpvN+YYW3QIHThwAO+//36x1k1ISICvr6/eE+sBLyZ/Cg8Px9ixYy3iit+lPX4vy3/ewMBAdOvWDf7+/nB0dMTw4cOLWb18MscPANasWYOvv/4agwYNwrBhw4r9OHMhe/wsmb7jlN9uzDG26BDy9fXF0qVLi7Vu/qZk1apVNZPovexVE+sBwMyZM5Gbm4uQkBDN71pu374NAHj8+DESExPh7u4OW1vbkrwMaUp7/Arj4+ODd955B7Gxsa9VCMkcv507d6J///4ICgrCwoULi1mxeTGXz58l0ncC0TfeeANKpdK4Y1ziUxksXHBwsM6zawYPHvzKs2tCQ0NfOQf7mTNnTPwK5DJk/IrSoEEDUbt2bWOUaNaMMX7Hjh0TDg4Oonnz5prTjcsKY37+LPnsuLCwMJ1nx33//fevPDuuUaNGOs+O69Chg/D29i5xLZY5wgZYvXq11u8MHjx4IFxdXUVISEiBda9duyauXbumuf/XX3+JuLi4Arfo6GgBQAwYMEDExcWJtLS0UnstMhgyfs+ePROpqalafR4/flxYW1uLfv36ma5wM2HI+AkhxP/+9z9RoUIF4efnp3MsLZ2h4/cySw6hY8eOaf10JCcnR9SsWVM0adJE05aUlCQSEhIKPPaHH34QAMTJkyc1bZcuXRLW1tZ6/YyCUzn8g1qtRosWLXDhwgWMHTsWFStWxM8//4y///4bJ0+exL/+9S/Nul5eXgBQ5CVlEhMTUaNGDcyYMQNhYWEmrl4+Q8YvLS0N1atXR0hICPz8/ODg4IDz589j6dKlsLOzw7Fjx1CrVi0Jr6r0GDJ+mZmZ8PPzw507dzB16lRUq1atQN8+Pj4Wf8amof9/k5KSsHz5cgDA5s2bcfz4cUyZMgUA4OnpiX79+pXaazG1Xr16IS4uDqNGjdJMIHrixAns3r0brVq1AgC0adMG+/fvx8sxkZmZiXfeeQeZmZkICwtDuXLlMGvWLKjVapw9exZvvvlmyQopcWyVAampqWLQoEGiQoUKwt7eXrRu3bpA6ufz9PQUnp6eRfZ18+bNMvVjVSH0Hz+VSiW++uorUa9ePeHs7CzKlSsnPD09xaBBg8TNmzdL7wVIpu/45X/WCruFhoaW3ouQyJD/v3v37i10/Fq3bl06L6CUZGdni7CwMFGlShWhVCpFQECA2L59e4F1WrdurXNr8NatWyI4OFg4OzsLR0dH8eGHH4qrV6/qVQe3hIiISBr+WJWIiKRhCBERkTQMISIikoYhRERE0jCEiIhIGoYQERFJwxAiIiJpGEJERCQNQ4jMWps2bdCmTRvN/cTERCgUCsTExGjaJk2aVOZmsC2Jzp07Y/DgwVKeW9f7ZWwTJkxAkyZNTNY/mRZDiIzq/PnzCA4OhqenJ+zs7FCtWjV06NABP/30k+zSzNbKlSsxZ84ck/R9+PBh7NixA+PHj9e0paWl4eOPP4abmxu8vb2xZMkSrcedOnUK9vb2uHnzZqF9nz9/HgqFAidOnDBJ7cU1cuRInDt3Dn/88YfUOkg/DCEymiNHjqBRo0Y4d+4cBg8ejPnz5+PTTz+FlZUV5s6dq1efO3bswI4dO4pc5+uvv36tZ8w0ZQjNmDED7dq1Q82aNTVtYWFh2LdvHyIjI/Hhhx9i8ODBOHLkiGa5EAJffvklRo4ciRo1ahTa95YtW1CpUiUEBASYpPbiqlKlCrp164aZM2dKrYP0Y9GT2lHp+v777+Hi4oKTJ09qTSWdkpKiV5/FmQDQxsYGNjbm81HOysqCvb297DKQkpKCLVu2aE1qt3nzZkRFRaF///4AgPj4eGzatAnNmzcHAMTGxiIpKQkTJ04ssv+tW7ciMDDQLHaF9urVCz179sSNGzfg7e0tuxwqAW4JkdFcv34dfn5+WgEEAJUqVSpw//nz55gyZQp8fHygVCrh5eWFiRMnak0b/M9jQrroOiakUCgwfPhwbNy4Ef7+/lAqlfDz88P27du1Hr9v3z40atQIdnZ28PHxQXR0dLGPM7Vp0wb+/v7466+/0KpVK9jb22u+vH///XcEBQXB3d0dSqUSPj4+mDJlCtRqdYHHb9myBUlJSVAoFFAoFJopBoAX0yhHRESgZs2aUCqV8PDwwLhx43ROr/xPW7ZswfPnz9G+ffsC7dnZ2XBzc9Pcf+ONN5CVlQUAePr0KSZMmIBp06bB0dGx0L7T0tJw5MgRBAUFFWgbMGAAXFxc4OrqitDQUKSlpWk9Nj4+HgMGDIC3tzfs7OxQpUoVfPLJJ3j06JFmnb1790KhUCAuLk7r8StXroRCocDRo0c1bfmv8ffff3/FqJC5MZ8/H+m15+npiaNHj+LChQvw9/cvct1PP/0Uy5YtQ3BwMMaMGYPjx49j2rRpSEhI0PnFo49Dhw5hw4YN+Pzzz+Hk5IR58+ahR48e+Pvvv1GhQgUAwJkzZ9CpUydUrVoVkZGRUKvVmDx5conmRHn06BECAwPRu3dv9O3bF5UrVwYAxMTEwNHREaNHj4ajoyP27NmDb7/9FhkZGZgxYwYA4P/+7/+Qnp6O27dvY/bs2QCg+fLPy8tD165dcejQIQwZMgS1a9fG+fPnMXv2bFy5cgUbN24ssq4jR46gQoUK8PT0LNAeEBCAWbNmwdfXFzdu3MD27duxePFiANDMQ/SqeXP+/PNPKBQKdOzYEcCLXXjdunXDoUOHMHToUNSuXRtxcXEIDQ3VeuzOnTtx48YNDBw4EFWqVMHFixexaNEiXLx4EceOHYNCoUCbNm3g4eGB2NhYdO/evcDjY2NjteZGcnFxgY+PDw4fPoxRo0YVWTuZGb0mgCDSYceOHcLa2lpYW1uLZs2aiXHjxok///xT5ObmFljv7NmzAoD49NNPC7SHhYUJAGLPnj2attatWxeYxyV/zpylS5dq2iIiIrTmPAEgbG1tC8ycee7cOQFA/PTTT5q2Ll26CHt7e3Hnzh1N29WrV4WNjU2xZtXMn29l4cKFWst0Ta392WefaU0zHRQUpHNequXLlwsrKytx8ODBAu0LFy4UAMThw4eLrK1FixaiYcOGWu3x8fGievXqmnlyevToIdRqtbhx44YoX768OHr0aJH9CiFEv379CrwvGzduFABEVFSUpu358+eiZcuWWu+XrnFZtWqVACAOHDigaQsPDxdKpbLAbMQpKSnCxsZGREREaPXRsWPHMjEFvKXh7jgymg4dOuDo0aPo2rUrzp07h6ioKHzwwQeoVq1agTOXtm7dCgAYPXp0gcePGTMGwIvdSMbQvn17+Pj4aO7Xq1cPzs7OuHHjBoAXs3Du2rULH330Edzd3TXr1axZE4GBgcV+HqVSiYEDB2q1ly9fXvPvzMxMPHz4EC1btkRWVhYuXbr0yn7XrVuH2rVrw9fXFw8fPtTc2rZtC+DFLquiPHr0qMBut3x169bF1atXcfLkSVy9ehXr16+HlZUVxowZgx49eqBp06bYsGED6tevjxo1amDy5MkFZtbMy8vD9u3bC+yK27p1K2xsbDBs2DBNm7W1NUaMGFHkuOTk5ODhw4do2rQpAOD06dOaZf3794dKpcL69es1bWvWrMHz58/Rt29frX7d3Nzw8OHDIseEzA93x5FRBQQEYMOGDcjNzcW5c+cQFxeH2bNnIzg4GGfPnkWdOnWQlJQEKyurAmdsAS/OcnJ1dUVSUpJRannrrbe02tzc3PD48WMALw7cZ2dna9UBQGdbYapVq6bzBIqLFy/i66+/xp49e5CRkVFgWXp6+iv7vXr1KhISEgrdNVickz1EIXNW2tnZoVGjRpr7e/bswY4dO3D58mVcvnwZvXv3RnR0NLy8vNCnTx94eHhogvbkyZN48OBBgRBKSkpC1apVtY4jvTyddr7U1FRERkZi9erVWq/h5XHx9fVFQEAAYmNjMWjQIAAvdsU1bdpU5/sjhDCLkySoZBhCZBK2trYICAhAQEAA3n77bQwcOBDr1q1DRESEZh1Tf2FYW1vrbC/si1lfL/9lny8tLQ2tW7eGs7MzJk+eDB8fH9jZ2eH06dMYP3488vLyXtlvXl4e6tati1mzZulc7uHhUeTjK1SooAncoqjVanz11VeYMGECqlWrhilTpqB58+aa0Pnss88QGxurub9161Z4eXmhTp06r+xbl169euHIkSMYO3YsGjRoAEdHR+Tl5aFTp05a49K/f3989dVXuH37NlQqFY4dO4b58+fr7Pfx48eoWLGiXjWRPAwhMrn8v7jv3bsH4MUJDHl5ebh69Spq166tWe/+/ftIS0vTOpBuKpUqVYKdnR2uXbumtUxXW0ns27cPjx49woYNG9CqVStNu64ffxYWxj4+Pjh37hzatWunV2D7+vrit99+e+V6CxYsQGZmJsLCwgAAd+/eLbB70t3dHXfu3NHc37JlCzp37lygD09PT+zevRtPnjwpsDV0+fLlAus9fvwYu3fvRmRkJL799ltN+9WrV3XW1rt3b4wePRqrVq1CdnY2ypUrh5CQEJ3r3rx5E/Xr13/l6yXzwmNCZDR79+7VuZWRfwwof9dM/hfYP3+gmf8X/8u7eUzJ2toa7du3x8aNG3H37l1N+7Vr17Bt2zaD+wYKbnXl5ubi559/1lrXwcFB5+65Xr164c6dO5oz116WnZ2Np0+fFllDs2bN8PjxY80xMF1SU1MRERGBGTNmwM7ODgBQuXLlAsesEhISUKVKFQAv/lA4ffq01nvUuXNnPH/+HAsWLNC0qdVqrStl6BoXQPuzkK9ixYoIDAzEihUrEBsbi06dOunc2klPT8f169c1v3Wi1we3hMhoRowYgaysLHTv3h2+vr7Izc3FkSNHsGbNGnh5eWl259SvXx+hoaFYtGiRZrfViRMnsGzZMnz00Ud4//33S63mSZMmYceOHXjvvfcwbNgwqNVqzJ8/H/7+/jh79qze/TZv3hxubm4IDQ3Fl19+CYVCgeXLl+sM6YYNG2LNmjUYPXo0AgIC4OjoiC5duqBfv35Yu3Ythg4dir179+K9996DWq3GpUuXsHbtWvz5558Fjuv8U1BQEGxsbLBr1y4MGTJE5zrffPMN6tati549e2raevTogcmTJ2PYsGHw9PREdHS05g+ErVu3ws7OTus96tKlC9577z1MmDABiYmJqFOnDjZs2KAVrs7OzmjVqhWioqLw7NkzVKtWDTt27Cjy8kD9+/dHcHAwAGDKlCk619m1a5fmNHF6zUg7L48szrZt28Qnn3wifH19haOjo7C1tRU1a9YUI0aMEPfv3y+w7rNnz0RkZKSoUaOGKFeunPDw8BDh4eEFTl0WwrBTtL/44gutGj09PUVoaGiBtt27d4t33nlH2NraCh8fH/HLL7+IMWPGCDs7u1e+5tatWws/Pz+dyw4fPiyaNm0qypcvL9zd3TWnrAMQe/fu1az35MkT8Z///Ee4uroKAAVO187NzRXTp08Xfn5+QqlUCjc3N9GwYUMRGRkp0tPTX1lf165dRbt27XQui4+PF7a2tuLMmTNay2JiYoSXl5eoUKGCGD16tHj+/LkQQojg4GDRuXNnnf09evRI9OvXTzg7OwsXFxfRr18/cebMGa336/bt26J79+7C1dVVuLi4iJ49e4q7d+8KADpPvVapVMLNzU24uLiI7Oxsnc8dEhIiWrRoUfRgkFlSCGHko7REFuCjjz7CxYsXCz1W8bo4ePAg2rRpg0uXLqFWrVoG9fX8+XNUqFAB06ZNw+eff26kCov3vO7u7ujSpYvOi60mJyejRo0aWL16NbeEXkM8JkRl3j8vfnr16lVs3br1lZcLeh20bNkSHTt2RFRUlMF9paamYtSoUVpXMDC1jRs34sGDB5pr3f3TnDlzULduXQbQa4pbQlTmVa1aVXMts6SkJCxYsAAqlQpnzpwxeOuB9Hf8+HHEx8djypQpqFixYoEfspLl4IkJVOZ16tQJq1atQnJyMpRKJZo1a4apU6cygCRbsGABVqxYgQYNGph0UjySi1tCREQkDY8JERGRNAwhIiKShiFERETSMISIiEgahhAREUnDECIiImkYQkREJA1DiIiIpGEIERGRNP8PL2NILuzKWb8AAAAASUVORK5CYII=", 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", 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    " ] @@ -93769,10 +48545,10 @@ "execution_count": 24, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:32:14.193634Z", - "iopub.status.busy": "2026-02-04T19:32:14.192634Z", - "iopub.status.idle": "2026-02-04T19:32:14.431183Z", - "shell.execute_reply": "2026-02-04T19:32:14.431183Z" + "iopub.execute_input": "2026-03-20T15:46:28.731338Z", + "iopub.status.busy": "2026-03-20T15:46:28.730759Z", + "iopub.status.idle": "2026-03-20T15:46:28.979829Z", + "shell.execute_reply": "2026-03-20T15:46:28.978513Z" } }, "outputs": [ @@ -93952,10 +48728,10 @@ "execution_count": 25, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:32:14.434192Z", - "iopub.status.busy": "2026-02-04T19:32:14.434192Z", - "iopub.status.idle": "2026-02-04T19:32:14.584214Z", - "shell.execute_reply": "2026-02-04T19:32:14.584214Z" + "iopub.execute_input": "2026-03-20T15:46:28.984212Z", + "iopub.status.busy": "2026-03-20T15:46:28.983560Z", + "iopub.status.idle": "2026-03-20T15:46:29.274678Z", + "shell.execute_reply": "2026-03-20T15:46:29.273085Z" } }, "outputs": [ @@ -94090,10 +48866,10 @@ "execution_count": 26, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:32:14.588233Z", - "iopub.status.busy": "2026-02-04T19:32:14.588233Z", - "iopub.status.idle": "2026-02-04T19:32:14.593665Z", - "shell.execute_reply": "2026-02-04T19:32:14.592648Z" + "iopub.execute_input": "2026-03-20T15:46:29.277515Z", + "iopub.status.busy": "2026-03-20T15:46:29.277002Z", + "iopub.status.idle": "2026-03-20T15:46:29.283797Z", + "shell.execute_reply": "2026-03-20T15:46:29.281735Z" } }, "outputs": [], @@ -94115,10 +48891,10 @@ "execution_count": 27, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:32:14.596664Z", - "iopub.status.busy": "2026-02-04T19:32:14.596664Z", - "iopub.status.idle": "2026-02-04T19:33:20.336974Z", - "shell.execute_reply": "2026-02-04T19:33:20.336974Z" + "iopub.execute_input": "2026-03-20T15:46:29.287390Z", + "iopub.status.busy": "2026-03-20T15:46:29.287044Z", + "iopub.status.idle": "2026-03-20T15:47:33.926072Z", + "shell.execute_reply": "2026-03-20T15:47:33.924844Z" } }, "outputs": [], @@ -94131,10 +48907,10 @@ "execution_count": 28, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:33:20.340994Z", - "iopub.status.busy": "2026-02-04T19:33:20.340994Z", - "iopub.status.idle": "2026-02-04T19:33:22.719457Z", - "shell.execute_reply": "2026-02-04T19:33:22.719457Z" + "iopub.execute_input": "2026-03-20T15:47:33.930049Z", + "iopub.status.busy": "2026-03-20T15:47:33.929611Z", + "iopub.status.idle": "2026-03-20T15:47:36.288210Z", + "shell.execute_reply": "2026-03-20T15:47:36.286410Z" } }, "outputs": [ @@ -94269,10 +49045,10 @@ "execution_count": 29, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:33:22.724543Z", - "iopub.status.busy": "2026-02-04T19:33:22.723543Z", - "iopub.status.idle": "2026-02-04T19:33:22.729988Z", - "shell.execute_reply": "2026-02-04T19:33:22.729468Z" + "iopub.execute_input": "2026-03-20T15:47:36.292378Z", + "iopub.status.busy": "2026-03-20T15:47:36.291795Z", + "iopub.status.idle": "2026-03-20T15:47:36.303433Z", + "shell.execute_reply": "2026-03-20T15:47:36.300670Z" } }, "outputs": [ @@ -94302,16 +49078,16 @@ "execution_count": 30, "metadata": { "execution": { - "iopub.execute_input": "2026-02-04T19:33:22.733003Z", - "iopub.status.busy": "2026-02-04T19:33:22.733003Z", - "iopub.status.idle": "2026-02-04T19:33:23.599906Z", - "shell.execute_reply": "2026-02-04T19:33:23.599906Z" + "iopub.execute_input": "2026-03-20T15:47:36.310169Z", + "iopub.status.busy": "2026-03-20T15:47:36.309336Z", + "iopub.status.idle": "2026-03-20T15:47:36.973775Z", + "shell.execute_reply": "2026-03-20T15:47:36.972458Z" } }, "outputs": [ { "data": { - "image/png": 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Hjh1LcnLyGc1TnFtn47wQ/1x9+vShT58+J11uzZo1qFQq1qxZc1bLo1KpePLJJ087nyeffBKVSkV+fv5Jl63tmtqzZw8DBw4kKCgIlUrFwoULT7tMQogzT4I1IRqouXPnolKpvH9Go5HY2FgGDRrEG2+8QVlZ2fku4nmTlZXFk08+yebNm893UWolwaK40H322We89tpr9f5cnz59OHjw4BkvjzjzxowZw9atW3nmmWeYN28enTt3PuXjLoQ4eyRYE6KBmzFjBvPmzWPWrFlMnDgRgMmTJ9OmTRv++uuv81y68yMrK4vp06fXGqy9//777Nq165yXadmyZTXSXC4XK1euPOdlEeJ01eem/aeffqKysrJG+o8//ojT6TzDJau/5cuXs3z58vNdjPNq165dvP/++97XVquVdevWcfvtt3Pfffdxyy23EB8fL8GaEA2QBGtCNHCDBw/mlltuYdy4cTz++OMsW7aMlStXkpuby1VXXYXVaj2n5VEU5Zyvsz50Oh0Gg+GcrrO8vJznn3+egQMHelsVtmzZQrdu3fjoo49QFOWclkeIc+nbb7+lQ4cO3u6DeXl53HzzzTz22GPk5OTUK6+KioozXj69Xo9erz/j+V5IDAYDOp3O+zovLw+A4ODg81QiIURdSbAmxAXo8ssvZ8qUKaSlpfHJJ5/4vLdz505GjBhBaGgoRqORzp07s2jRohp5/PXXX/Tu3RuTyUR8fDxPP/00c+bMQaVS+XRjSk5OZtiwYSxbtozOnTtjMpl49913AZgzZw6XX345kZGRGAwGWrZsyaxZs2qsS1EUnn76aeLj4zGbzfTt25dt27bVWK6wsJCHH36YNm3a4O/vT2BgIIMHD2bLli3eZdasWUOXLl0AGDdunLeb6Ny5c4Han1mrqKjgoYceIiEhAYPBQLNmzXjppZdqBFEqlYr77ruPhQsX0rp1awwGA61atWLp0qXHPxiAv78/q1at4t577+Waa64hOzubu+66i1deeYXPPvsMlUp13M8ePnyYcePGER8fj8FgICYmhquvvrpGV7IlS5bQs2dP/Pz8CAgIYOjQoTX24V9//cXYsWNJSUnBaDQSHR3NbbfdRkFBgc9yZWVlTJ48meTkZAwGA5GRkQwYMICNGzf6LDd//nw6deqEyWQiPDycW265hczMTJ9lxo4di7+/P5mZmQwfPhx/f38iIiJ4+OGHcblcPsu+9NJLXHbZZYSFhWEymejUqRMLFiw44b49Ebfbzeuvv06bNm0wGo1ERERwxRVXsH79eu8yTqeTp556itTUVAwGA8nJyTzxxBPYbDafvKrO8zVr1njP8zZt2ngDkK+//tq7nk6dOrFp06Za98P+/fsZNGgQfn5+xMbGMmPGjBrn2dk4HzMzM7ntttuIioryLvfRRx/5LFP1TNaXX37JM888Q3x8PEajkX79+rF3717vcn369OGHH34gLS3Ne32dqGvvyy+/zBdffMEzzzzDH3/8wU033cSAAQP4448/iIuLO+7nqrp6/+9//+Oee+4hMjKS+Ph47/t1Oefrcv3U9sxaRkYGw4cPx8/Pj8jISB544IEa5wQc//nJY/O02+1MnTqVTp06ERQUhJ+fHz179mT16tXH3f6TefPNN2nVqhVms5mQkBBvN8VjFRcXM3bsWIKDgwkKCmLcuHFYLJbjbseTTz5JUlISAI888oj3+Nb3uAshzg3t+S6AEOLUjB49mieeeILly5czfvx4ALZt20b37t2Ji4vjsccew8/Pjy+//JLhw4fz1Vdfcc011wCeG7u+ffuiUql4/PHH8fPz44MPPjhui9SuXbsYNWoUd955J+PHj6dZs2YAzJo1i1atWnHVVVeh1Wr57rvvuOeee3C73dx7773ez0+dOpWnn36aIUOGMGTIEDZu3MjAgQOx2+0+69m/fz8LFy7k+uuvp1GjRuTk5PDuu+/Su3dvtm/fTmxsLC1atGDGjBlMnTqVCRMm0LNnTwAuu+yyWsuuKApXXXUVq1ev5vbbb6d9+/YsW7aMRx55hMzMTF599VWf5deuXcvXX3/NPffcQ0BAAG+88QbXXXcd6enphIWFnfCYqNVqn8DsREFaleuuu45t27YxceJEkpOTyc3NZcWKFaSnp3tvlObNm8eYMWMYNGgQzz//PBaLhVmzZtGjRw82bdrkXW7FihXs37+fcePGER0dzbZt23jvvffYtm0bv/32m7c8d911FwsWLOC+++6jZcuWFBQUsHbtWnbs2EHHjh0Bz430uHHj6NKlCzNnziQnJ4fXX3+dX375hU2bNvnUyLtcLgYNGkTXrl156aWXWLlyJS+//DKpqancfffd3uVef/11rrrqKm6++Wbsdjuff/45119/Pd9//z1Dhw496b461u23387cuXMZPHgwd9xxB06nk59//pnffvuNzp07A3DHHXfw8ccfM2LECB566CF+//13Zs6cyY4dO/jmm2988tu7dy833XQTd955J7fccgsvvfQSV155JbNnz+aJJ57gnnvuAWDmzJmMHDmSXbt2oVYfrfN0uVxcccUVXHrppbzwwgssXbqUadOm4XQ6mTFjBnB2zsecnBwuvfRSb3AXERHBkiVLuP322yktLWXy5Mk+eT733HOo1WoefvhhSkpKeOGFF7j55pv5/fffAfjXv/5FSUkJGRkZ3vL4+/uf8FhUP/erbvTr6p577iEiIoKpU6d6W9bqes7X5fo5ltVqpV+/fqSnpzNp0iRiY2OZN28eq1atqnOZj1VaWsoHH3zAqFGjGD9+PGVlZXz44YcMGjSIP/74g/bt29crv/fff59JkyYxYsQI7r//fiorK/nrr7/4/fffuemmm3yWHTlyJI0aNWLmzJls3LiRDz74gMjISJ5//vla87722msJDg7mgQceYNSoUQwZMgR/f3/8/PzqfdyFEOeAIsQFymq1Ktu3b1esVmvNN20VipK5qWH82SpOafvmzJmjAMqff/553GWCgoKUDh06eF/369dPadOmjVJZWelNc7vdymWXXaY0adLEmzZx4kRFpVIpmzZt8qYVFBQooaGhCqAcOHDAm56UlKQAytKlS2us32Kx1EgbNGiQkpKS4n2dm5ur6PV6ZejQoYrb7famP/HEEwqgjBkzxptWWVmpuFwun/wOHDigGAwGZcaMGd60P//8UwGUOXPm1Fj/mDFjlKSkJO/rhQsXKoDy9NNP+yw3YsQIRaVSKXv37vWmAYper/dJ27JliwIob775Zo11VSkrK1MGDBigDBgwQNm/f7+SlJSkbN68WenSpYty0003+Wx3dUVFRQqgvPjiiyfMOzg4WBk/frxP+uHDh5WgoCCf9NqOx3//+18FUH766SdvWlBQkHLvvfced512u12JjIxUWrdu7XN9ff/99wqgTJ061Zs2ZswYBfA5PoqiKB06dFA6derkk3Zs+ex2u9K6dWvl8ssv90lPSkryOS9qs2rVKgVQJk2aVOO9qv29efNmBVDuuOMOn/cffvhhBVBWrVrls05A+fXXX71py5YtUwDFZDIpaWlp3vR3331XAZTVq1d706r2w8SJE33KMXToUEWv1yt5eXmKopyd8/H2229XYmJilPz8fJ88b7zxRiUoKMi731evXq0ASosWLRSbzeZd7vXXX1cAZevWrd60oUOH+lxHJ/LII48ozZs3V1avXq307t1b+eOPP5RRo0YpnTt3VjIyMo77uarvuB49eihOp9ObXtdzvi7Xj6IoSu/evZXevXt7X7/22msKoHz55ZfetIqKCqVx48Y1juvxzsVj83Q6nT77tKp8UVFRym233eaTDijTpk07YZmvvvpqpVWrVidcZtq0aQpQI/9rrrlGCQsL80k7djsOHDhQ676rz3E/4W+wEOKMkW6Q4uKUvxve690w/vJ3n7XN9Pf3944KWVhYyKpVqxg5ciRlZWXk5+eTn59PQUEBgwYNYs+ePd4ubEuXLqVbt24+tb2hoaHcfPPNta6nUaNGDBo0qEa6yWTy/r+kpIT8/Hx69+7N/v37KSkpAWDlypXY7XYmTpzoU9t+bG0/eJ6rqGqpcLlcFBQU4O/vT7NmzWp00aurxYsXo9FomDRpkk/6Qw89hKIoLFmyxCe9f//+pKamel+3bduWwMBA9u/ff9x1+Pv78+CDD7J8+XIaNWoEQLt27Vi3bh1jx449biuDyWRCr9ezZs0aioqKal1mxYoVFBcXM2rUKO8xzc/PR6PR0LVrV59uVtWPR2VlJfn5+Vx66aUAPvsvODiY33//naysrFrXuX79enJzc7nnnnswGo3e9KFDh9K8eXN++OGHGp+56667fF737Nmzxj6rXr6ioiJKSkro2bPnKR3br776CpVKxbRp02q8V7W/Fy9eDMCDDz7o8/5DDz0EUGM7WrZsSbdu3byvu3btCni6HScmJtZIr+2cuO+++3zKcd9992G3270DzZzp81FRFL766iuuvPJKFEXxOUcGDRpESUlJjf07btw4n2e4qlqnT3SOn8jQoUPZuHGjt1tgREQEn332Gc899xxRUVEn/fz48ePRaDTe13U95+ty/dRm8eLFxMTEMGLECG+a2WxmwoQJdc7jWBqNxrtP3W43hYWFOJ1OOnfufErnd3BwMBkZGfz5558nXba2a6+goIDS0tJ6r1cI0fBIN0hxcQpvChP+d75L4RHe9KxlXV5eTmRkJODpwqUoClOmTGHKlCm1Lp+bm0tcXBxpaWk+N6VVGjduXOvnqgKQY/3yyy9MmzaNdevW1XhGoqSkhKCgINLS0gBo0qSJz/sRERGEhIT4pFU9g/TOO+9w4MABn2eeTtYF8XjS0tKIjY0lICDAJ71Fixbe96urflNeJSQk5KQ3g1dccUWNNI1Gw4ABA477GYPBwPPPP89DDz1EVFQUl156KcOGDePWW28lOjoa8MyFBJ6AoTaBgYHe/xcWFjJ9+nQ+//xzcnNzfZarCp4BXnjhBcaMGUNCQgKdOnViyJAh3HrrraSkpABH90lVd9fqmjdvztq1a33Sqp4Xq662ffb999/z9NNPs3nzZp/ng+rTZa7Kvn37iI2NJTQ09LjLpKWloVara5zX0dHRBAcHn/TYBwUFAZCQkFBr+rHbp1arvfuwStOmnuu/6hmqM30+5uXlUVxczHvvvcd7771XY1mgxrlwbJ5V12F9Ap7qevfuXWt6v3796vT5Y79f6nrO1+X6qU1aWhqNGzeucd7Vdr7Xx8cff8zLL7/Mzp07cTgc3vTjfX+eyP/93/+xcuVKLrnkEho3bszAgQO56aab6N69e41lT3Q8q38/CCEuTBKsiYuT3gyx7c93Kc6qjIwMSkpKvDeibrcbgIcffrjWVjA4fjB2MtVbRKrs27ePfv360bx5c1555RUSEhLQ6/UsXryYV1991Vue+nj22WeZMmUKt912G0899RShoaGo1WomT558Svmdiuo1/NUp9RjRsT7zTE2ePJkrr7yShQsXsmzZMqZMmcLMmTNZtWoVHTp08G73vHnzar0B1WqPfo2PHDmSX3/9lUceeYT27dvj7++P2+3miiuu8Nl/I0eOpGfPnnzzzTcsX76cF198keeff56vv/6awYMH17nsVY63z6r7+eefueqqq+jVqxfvvPMOMTEx6HQ65syZU+ugCWdSXYPB423HmTgnTtXJ1l11XG+55RbGjBlT67Jt27atV56n41QmlD72+6U+5/zJrp/Tdbxzx+Vy+ezHTz75hLFjxzJ8+HAeeeQRIiMj0Wg0zJw5k3379tV7vS1atGDXrl18//33LF26lK+++op33nmHqVOnMn36dJ9lz+f5KYQ4+yRYE+ICNW/ePABvYFZVo6/T6ejfv/8JP5uUlOQz+luV2tKO57vvvsNms7Fo0SKfmt1jRz+rGnVsz549Pq0OeXl5NWryFyxYQN++ffnwww990ouLiwkPD/e+rk9LTFJSEitXrqSsrMynNWPnzp0+5TufUlNTeeihh3jooYfYs2cP7du35+WXX+aTTz7xdoGLjIw84XEtKirixx9/ZPr06UydOtWbXtVKcayYmBjuuece7rnnHnJzc+nYsSPPPPMMgwcP9u6TXbt21Wjd2LVr1ynts6+++gqj0ciyZct8BrKZM2dOvfMCzz5btmwZhYWFx21dS0pKwu12s2fPHm/LFXgG5CguLj7jx97tdrN//35vaxrA7t2ebtBVg12c6fMxIiKCgIAAXC7XSa/7+jiV1s4zpa7nfPXlj3f91CYpKYm///4bRVF8trO2+RlDQkIoLi6ukZ6WlubzfbZgwQJSUlL4+uuvffKsrZtuXfn5+XHDDTdwww03YLfbufbaa3nmmWd4/PHHfbonn0nn87gLIWonz6wJcQFatWoVTz31FI0aNfI+ZxYZGUmfPn149913yc7OrvGZqnl1wBPgrVu3zmdS6cLCQj799NM6l6GqNrd67W1JSUmNm+/+/fuj0+l48803fZatbeJVjUZTozZ4/vz5NYaL9/PzA6j1JupYQ4YMweVy8dZbb/mkv/rqq6hUqlNqSTpTLBZLjcmEU1NTCQgI8HYTHDRoEIGBgTz77LM+XauqVB3X2o4H1NzPLpfLp0skeM6d2NhY7zo7d+5MZGQks2fP9umuuGTJEnbs2HFKIzdqNBpUKpVP19aDBw+ycOHCeucFnlEAFUWp0coAR/fBkCFDgJr74JVXXgE4pe04mernmaIovPXWW+h0Om+XwDN9Pmo0Gq677jq++uor/v777xrvV7/u66NqZMDzoa7nfF2un9oMGTKErKwsn2kjLBZLrd1IU1NT+e2333xGrv3+++85dOiQz3K1XX+///4769atO9GmHtex023o9XpatmyJoii17pMz5XwedyFE7aRlTYgGbsmSJezcuROn00lOTg6rVq1ixYoVJCUlsWjRIp8a1rfffpsePXrQpk0bxo8fT0pKCjk5Oaxbt46MjAzvfGWPPvoon3zyCQMGDGDixIneofsTExMpLCysU+3qwIED0ev1XHnlldx5552Ul5fz/vvvExkZ6RMsVs25NXPmTIYNG8aQIUPYtGkTS5Ys8WktAxg2bBgzZsxg3LhxXHbZZWzdupVPP/20xnNAqampBAcHM3v2bAICAvDz86Nr1661Phty5ZVX0rdvX/71r39x8OBB2rVrx/Lly/n222+ZPHmyz+AN59ru3bvp168fI0eOpGXLlmi1Wr755htycnK48cYbAc/zObNmzWL06NF07NiRG2+8kYiICNLT0/nhhx/o3r07b731FoGBgfTq1YsXXngBh8NBXFwcy5cv58CBAz7rLCsrIz4+nhEjRtCuXTv8/f1ZuXIlf/75Jy+//DLgaZ19/vnnGTduHL1792bUqFHeofuTk5N54IEH6r2tQ4cO5ZVXXuGKK67gpptuIjc3l7fffpvGjRvz119/1Tu/vn37Mnr0aN544w327Nnj7er5888/07dvX+677z7atWvHmDFjeO+99yguLqZ379788ccffPzxxwwfPpy+ffvWe70nYjQaWbp0KWPGjKFr164sWbKEH374gSeeeML7TN/ZOB+fe+45Vq9eTdeuXRk/fjwtW7aksLCQjRs3snLlSgoLC+udZ6dOnfjiiy948MEH6dKlC/7+/lx55ZX1zudU1PWcr8v1U5vx48fz1ltvceutt7JhwwZiYmKYN28eZrO5xrJ33HEHCxYs4IorrmDkyJHs27fPp8W7yrBhw/j666+55pprGDp0KAcOHGD27Nm0bNmS8vLyeu+DgQMHEh0dTffu3YmKimLHjh289dZbDB06tMbzjmfS+TzuQojjOLeDTwpx5lzswwZXDWtd9afX65Xo6GhlwIAByuuvv66UlpbW+rl9+/Ypt956qxIdHa3odDolLi5OGTZsmLJgwQKf5TZt2qT07NlTMRgMSnx8vDJz5kzljTfeUADl8OHD3uWSkpKUoUOH1rquRYsWKW3btlWMRqOSnJysPP/888pHH31UY/h/l8ulTJ8+XYmJiVFMJpPSp08f5e+//64xnHRlZaXy0EMPeZfr3r27sm7duhrDZCuKonz77bdKy5YtFa1W6zOM/7FD9yuKZyjwBx54QImNjVV0Op3SpEkT5cUXX6wxpD5Q65D2dRlK/lTk5+cr9957r9K8eXPFz89PCQoKUrp27eozpHiV1atXK4MGDVKCgoIUo9GopKamKmPHjlXWr1/vXSYjI0O55pprlODgYCUoKEi5/vrrlaysLJ+hwm02m/LII48o7dq1UwICAhQ/Pz+lXbt2yjvvvFNjnV988YXSoUMHxWAwKKGhocrNN99cYyj2MWPGKH5+fjU+WzWseHUffvih0qRJE8VgMCjNmzdX5syZU+tydd3fTqdTefHFF5XmzZsrer1eiYiIUAYPHqxs2LDBu4zD4VCmT5+uNGrUSNHpdEpCQoLy+OOP+0xvUbXO2s7z2s6J2oY9r9oP+/btUwYOHKiYzWYlKipKmTZtWo3pKM7G+ZiTk6Pce++9SkJCgqLT6ZTo6GilX79+ynvvveddpmro/vnz59e6PdWnwigvL1duuukmJTg4WAHqPJx7fZxsepKTnfN1vX5q+/5IS0tTrrrqKsVsNivh4eHK/fffryxdurTG0P2Koigvv/yyEhcXpxgMBqV79+7K+vXra+TpdruVZ599VklKSlIMBoPSoUMH5fvvv6/1+6j69Xg87777rtKrVy8lLCxMMRgMSmpqqvLII48oJSUl3mWqrp2qaSGO3a/HTsFSl6H763PcL/bfYCEaCpWiyBOo4sJUWVnJgQMHaNSo0Vnrv/9PM3nyZN59913Ky8vrNGiEEMJj7NixLFiw4JRaUYS4EMlvsBDnhjyzJsQ/lNVq9XldUFDAvHnz6NGjhwRqQgghhBANgDyzJsQ/VLdu3ejTpw8tWrQgJyeHDz/8kNLS0uPO0SaEEEIIIc4tCdaE+IcaMmQICxYs4L333kOlUtGxY0c+/PBDevXqdb6LJoQQQgghAHlmTVywpL+8EEIIcX7Ib7AQ54Y8syaEEEIIIYQQDZAEa0IIIYQQQgjRAEmwJoQQQgghhBANkARrQgghhBBCCNEASbAmhBBCCCGEEA2QBGtCCCGEEEII0QBJsCaEEEIIIYQQDZAEa0KIWh08eBCVSsXcuXPr/dk1a9agUqlYs2bNSZf9888/ueyyy/Dz80OlUrF582aefPJJVCpV/QsthBBCCHER0Z7vAggh/rkcDgfXX389RqORV199FbPZTFJSUq3LPvvss7Rs2ZLhw4ef20IKIYQQQpwn0rImhDhv9u3bR1paGg8//DATJkzglltuISQkhH//+99YrVafZZ999lkWLlx4fgoqhBBCCHEeSMuaEOK8yc3NBSA4ONgnXavVotXK15MQQggh/tmkZU2IBqrqua3du3dzyy23EBQUREREBFOmTEFRFA4dOsTVV19NYGAg0dHRvPzyyzXyyM3N5fbbbycqKgqj0Ui7du34+OOPayxXXFzM2LFjCQoKIjg4mDFjxlBcXFxruXbu3MmIESMIDQ3FaDTSuXNnFi1aVO/tGzt2LL179wbg+uuvR6VS0adPH59tr6JSqaioqODjjz9GpVKhUqkYO3ZsvdcphBBCCHEhkaprIRq4G264gRYtWvDcc8/xww8/8PTTTxMaGsq7777L5ZdfzvPPP8+nn37Kww8/TJcuXejVqxcAVquVPn36sHfvXu677z4aNWrE/PnzGTt2LMXFxdx///0AKIrC1Vdfzdq1a7nrrrto0aIF33zzDWPGjKlRlm3bttG9e3fi4uJ47LHH8PPz48svv2T48OF89dVXXHPNNXXerjvvvJO4uDieffZZJk2aRJcuXYiKiqp12Xnz5nHHHXdwySWXMGHCBABSU1PruyuFEEIIIS4sihAXKKvVqmzfvl2xWq3nuyhnxbRp0xRAmTBhgjfN6XQq8fHxikqlUp577jlvelFRkWIymZQxY8Z401577TUFUD755BNvmt1uV7p166b4+/srpaWliqIoysKFCxVAeeGFF3zW07NnTwVQ5syZ403v16+f0qZNG6WystKb5na7lcsuu0xp0qSJN2316tUKoKxevfqE21i13Pz582vd9ur8/Px8tk8IIcT5c7H/BgvRUEjLmrgoWSwWdu7ceb6LAUDz5s0xm82n/Pk77rjD+3+NRkPnzp3JyMjg9ttv96YHBwfTrFkz9u/f701bvHgx0dHRjBo1ypum0+mYNGkSo0aN4n//+x/Dhg1j8eLFaLVa7r77bp/1TJw4kZ9//tmbVlhYyKpVq5gxYwZlZWWUlZV53xs0aBDTpk0jMzOTuLi4U95WIYQQQghxlARr4qK0c+dOOnXqdL6LAcCGDRvo2LHjKX8+MTHR53VQUBBGo5Hw8PAa6QUFBd7XaWlpNGnSBLXa99HUFi1aeN+v+jcmJgZ/f3+f5Zo1a+bzeu/evSiKwpQpU5gyZUqtZc3NzZVgTQghhBDiDJFgTVyUmjdvzoYNG853MQBPWU6HRqOpUxp4nj87W9xuNwAPP/wwgwYNqnWZxo0bn7X1CyGEEEL800iwJi5KZrP5tFqzLgZJSUn89ddfuN1un9a1qu6hVZNPJyUl8eOPP1JeXu7TurZr1y6f/FJSUgBPV8r+/fuf7eLXUH10SCGEEEKIfwIZul+Ii9SQIUM4fPgwX3zxhTfN6XTy5ptv4u/v7x02f8iQITidTmbNmuVdzuVy8eabb/rkFxkZSZ8+fXj33XfJzs6usb68vLyztCUefn5+x51OQAghhBDiYiQta0JcpCZMmMC7777L2LFj2bBhA8nJySxYsIBffvmF1157jYCAAACuvPJKunfvzmOPPcbBgwdp2bIlX3/9NSUlJTXyfPvtt+nRowdt2rRh/PjxpKSkkJOTw7p168jIyGDLli1nbXs6derEypUreeWVV4iNjaVRo0Z07dr1rK1PCCGEEOJ8k2BNiIuUyWRizZo1PPbYY3z88ceUlpbSrFkz5syZ4zOhtFqtZtGiRUyePJlPPvkElUrFVVddxcsvv0yHDh188mzZsiXr169n+vTpzJ07l4KCAiIjI+nQoQNTp049q9vzyiuvMGHCBP79739jtVoZM2aMBGtCCCGEuKiplLM5IoEQZ1FlZSUHDhygUaNGGI3G810cIYQQ4h9DfoOFODfkmTUhhBBCCCGEaIAkWBNCCCGEEEKIBkiCNSGEEEIIIYRogCRYE0IIIYQQQogGSII1IYQQQgghhGiAJFgTQgghhBBCiAZIgjVxwZPZJ4QQQohzS357hTg3JFgTFyydTodKpaKiouJ8F0UIIYT4R6moqEClUqHT6c53UYS4qGnPdwGEOFUajYagoCDy8vKw2WwEBgai1WpRqVTnu2hCCCHERUdRFJxOJ6WlpZSWlhIcHIxGoznfxRLioqZSpB1bXMAURaGkpITc3FxcLtf5Lo4QQghx0dNoNERGRhIUFCQVpEKcZRKsiYuCoii4XC6cTuf5LooQQghx0dJqtWg0GgnShDhHJFgTQgghhBBCiAZIBhgRQgghhBBCiAZIgjUhhBBCCCGEaIAkWBNCCCGEEEKIBkiCNSGEEEIIIYRogCRYE0IIIYQQQogGSII1IYQQQgghhGiAJFgTQgghhBBCiAZIgjUhhBBCCCGEaIAkWBNCCCGEEEKIBkiCNSGEEEIIIYRogCRYE0IIIYQQQogGSII1IYQQQgghhGiAJFgTQgghhBBCiAZIgjUhhBBCCCGEaIAkWBNCCCGEEEKIBkiCNSGEEEIIIYRogCRYE0IIIYQQQogGSII1IYQQQgghhGiAJFgTQgghhBBCiAZIgjUhhBBCCCGEaIAkWBNCCCGEEEKIBkh7vgvwT+B2u8nKyiIgIACVSnW+iyOEEEIIIYQ4TxRFoaysjNjYWNTqE7edSbB2DmRlZZGQkHC+iyGEEEIIIYRoIA4dOkR8fPwJl5Fg7RwICAgAPAckMDDwPJdGCCGEEEIIcb6UlpaSkJDgjRFORIK1c6Cq62NgYKAEa0IIIYQQQog6PR4lA4wIIYQQQgghRAMkwZoQQgghhBBCNEASrAkhhBBCCCFEAyTBmhBCCCGEEEI0QBKsCSGEEEIIIUQDJMGaEEIIIYQQQjRAEqwJIYQQQgghRAMkwZoQQgghhBBCNEASrAkhhBBCCCFEAyTBmhBCCCGEEEI0QBKsCSGEEEIIIUQDJMGaEEIIIYQQQjRAEqwJIYQQQgghRAMkwZoQQgghhBBCNEASrAkhhBBCCCFEAyTBmhBCCCGEEEI0QBKsCSGEEEIIIUQDJMGaEEIIIYQQQjRAEqwJIYQQQgghRAMkwZoQQgghhBBCNEASrAkhhBBCCCFEAyTBmhBCCCGEEEI0QBKsCSGEEEIIIUQDdNEHa+Xl5UybNo0rrriC0NBQVCoVc+fOrfPni4uLmTBhAhEREfj5+dG3b182btx49goshBBCCCGEEPwDgrX8/HxmzJjBjh07aNeuXb0+63a7GTp0KJ999hn33XcfL7zwArm5ufTp04c9e/acpRILIYQQQgghBGjPdwHOtpiYGLKzs4mOjmb9+vV06dKlzp9dsGABv/76K/Pnz2fEiBEAjBw5kqZNmzJt2jQ+++yzs1VsIYQQQgghxD/cRd+yZjAYiI6OPqXPLliwgKioKK699lpvWkREBCNHjuTbb7/FZrOdqWIKIYQQQgghhI+LPlg7HZs2baJjx46o1b676ZJLLsFisbB79+7zVDIhhBBCCCHExU6CtRPIzs4mJiamRnpVWlZWVq2fs9lslJaW+vwJIYQQQgghRH1IsHYCVqsVg8FQI91oNHrfr83MmTMJCgry/iUkJJzVcgohhBBCCCEuPhKsnYDJZKr1ubTKykrv+7V5/PHHKSkp8f4dOnTorJZTCCGEEEIIcfG56EeDPB1VI0keqyotNja21s8ZDIZaW+SEEEIIIYQQoq6kZe0E2rdvz8aNG3G73T7pv//+O2azmaZNm56nkgkhhBBCCCEudhKsHZGdnc3OnTtxOBzetBEjRpCTk8PXX3/tTcvPz2f+/PlceeWV0nomhBBCCCGEOGv+Ed0g33rrLYqLi72jN3733XdkZGQAMHHiRIKCgnj88cf5+OOPOXDgAMnJyYAnWLv00ksZN24c27dvJzw8nHfeeQeXy8X06dPP1+YIIYQQQggh/gHqFaw1atQIlUpVrxWoVCr27dtXr8+caS+99BJpaWne119//bW3teyWW24hKCio1s9pNBoWL17MI488whtvvIHVaqVLly7MnTuXZs2anZOyCyGEEEIIIf6ZVIqiKHVdeOzYsTWCtfXr17Nt2zZatmzpDWB27drF9u3bad26NZ06dWLOnDlnttQXmNLSUoKCgigpKSEwMPB8F0cIIYQQQghxntQnNqhXy9rcuXN9Xi9cuJCFCxeyYsUK+vXr5/PeihUrGDlyJE899VR9ViGEEEIIIYQQgtMcYGTq1KlMnDixRqAGMGDAAO677z7+/e9/n84qhBBCCCGEEOIf6bSCtT179hAWFnbc98PCws7782pCCCGEEEIIcSE6rWAtNTWVOXPmUF5eXuO9srIyPvroI1JSUk5nFUIIIYQQQgjxj3RaQ/c//fTTjBgxgubNmzN27FgaN24MeFrcPv74Y3Jycpg/f/4ZKagQQgghhBBC/JPUazTI2ixfvpz/+7//Y8uWLT7p7du3Z+bMmQwaNOi0CngxkNEghRBCCCGEEFC/2OC0g7Uqhw8f9s5llpSURHR09JnI9qIgwZoQQgghhBACzuLQ/ScSHR0tAZoQQgghhBBCnCGnNcAIQHp6OnfddRfNmjUjNDSUn376CYD8/HwmTZrEpk2bTruQQgghhBBCCPFPc1ota9u3b6dnz5643W66du3K3r17cTqdAISHh7N27VoqKir48MMPz0hhhRBCCCGEEOKf4rSCtUcffZTg4GB+++03VCoVkZGRPu8PHTqUL7744rQKKIQQQgghhBD/RKfVDfKnn37i7rvvJiIiApVKVeP9xMREMjMzT2cVQgghhBBCCPGPdFrBmtvtxmw2H/f9vLw8DAbD6axCCCGEEEIIIf6RTitY69ixIz/88EOt7zmdTj7//HMuvfTSOuf3xRdfUFlZeTpFEkIIIYQQQoiLwmkFa48//jhLly7l7rvv5u+//wYgJyeHlStXMnDgQHbs2MFjjz1W5/xGjRpFdHQ0t99+O6tXrz6dogkhhBBCCCHEBe20J8WeN28e999/PyUlJSiKgkqlQlEUAgMDmTVrFqNGjapzXr/++iuffvop8+fPp6CggLi4OG666SZuueUWWrdufTrFPK9kUmwhhBBCCCEE1C82OO1gDaCiooIVK1awZ88e3G43qampDBo0iICAgFPKz+l0snTpUj799FO+++47rFYrbdq0YfTo0dx0003ExMScbpHPKQnWhBBCCCGEEHAegrWzqby8nG+++Ya5c+eyZs0a1Go1ffr0YcyYMYwcORK9Xn++i3hSEqwJIYQQQgghoH6xwWk9s5aSkkK3bt3YtWtXre9/++23pKSknM4q+Pvvv/njjz/YunUriqLQvHlzCgoKuPXWW0lNTWXt2rWnlb8QQgghhBBCNESnFawdPHiQjRs3cskll7Bw4cIa75eXl5OWllbvfHfv3s20adNo0qQJ3bt358svv+Smm25i/fr1bN26lY0bN/LHH38QGhrKXXfddTqbIIQQQgghhBAN0mkFawCvvPIKvXr14rrrrmPKlCmnldfrr7/OJZdcQosWLXjxxRfp2LEjixYtIisri9dee42OHTt6l+3cuTMPPvggO3fuPN1NEEIIIYQQQogG57SDtZCQEL777jumTZvGzJkzGTp0KCUlJaeU1wMPPIDBYGD27NlkZ2fzxRdfMHToUDQaTa3Ld+7c+bQDRCGEEEIIIYRoiLRnKqOpU6dyySWXcMstt9ClSxe++eabeuexb98+GjVqVOflW7VqRatWreq9HiGEEEIIIYRo6E67Za26K664gj///BM/Pz8uvfRSvv3223p9vj6BmhBCCCGEEEJczM5Yy1qVRo0asW7dOu68807mzZuHSqWq82dvu+22E76vUqkwGo3Ex8fTp08funXrdrrFFeKkMoospBdYSAwzEx9iPt/FEUIIIYQQ/xCnFaytXr2aFi1a1Eg3Go18/PHHjBw5kvz8/Drnt2rVKqxWK3l5eYDneTiAoqIiACIiInC73RQUFKBSqRg0aBALFizAbJYbaHH2pBdYsNhdpBdYJFgTQgghhBDnzGl1g+zduzeRkZHHfX/o0KGMGTOmzvktWbIEg8HAk08+SUFBgfcvPz+fadOmYTKZ+OWXXygqKmLKlCksXbpUBhgRZ11imBmzXkNimARqQgghhBDi3FEpiqLUdeH//Oc/AIwePRqVSuV9fcIVqFSMHj26Tvn369ePJk2aMHv27Frfv+uuu9i/fz/Lly8H4KabbuKXX345pbnczqX6zFIuhBBCCCGEuHjVJzaoVzfIsWPHolKpuPHGG9Hr9YwdO/akn6lPsPbbb78xYsSI477frl07PvnkE+/rnj178vXXX9cpbyGEEEIIIYS4kNQrWDtw4AAAer3e5/WZEhwczPLly7n77rtrfX/p0qUEBQV5X5eXl0tL1Rkig2gIIYQQQgjRsNQrWEtKSjrh69M1fvx4ZsyYwYgRI7j77rtp3LgxAHv37mXWrFl8//33Ps+oLV68mPbt25/RMvxTpRdYOFRoYVtWCYPbxEjAJoQQQgghxHl2xofuPx3Tpk3DarXy6quv1phUW6PR8OCDDzJt2jQAKisrGTt2LG3btj0fRb3o6LVq/sooJiHUzIaDRf+YVrb1BwvZlF5Eh8QQOieHnu/iXNSk9VYI8U9X/XsQkO9EIcRJ1WuAkcsvv7z+K1Cp+PHHH+v1mdzcXH788UfvwCFJSUn069fvhCNPNmQXwgAjv+7N51ChhdJKB5GBRvz0Wsx6DZc1Dj/fRTur3v9pH4eKrLhcbu7u21h+MM+iX/fmY7G76nVeSYAnhLiYVP8eBOr9nSiEuDictQFG3G53vSa5BqhrLGixWOjZsyfjx4/nrrvuYtSoUfVajzg1VTfDeq2ahFBzjdq+i12HxBAO5lf841oUz4fEMHO9zquMIgtLtmYTYNIByDFp4DKKLGw4WAQq6JQUIsdLiFokhnl+ayrsTuKCTd40IYQ4nnoFa2vWrDlLxQCz2cyBAwfqHQyKU1f9ZjgxxOxTs3e+brTOdUtK5+RQooOMpBdYyCu3yeTXZ1F8SP2O6Ya0IvblllNgsXFZaoQE0Q1ceoGF9EILABH+hlM+VhL0NQzSqn12xId4Kq0sdhd2p1t6GQghTuq0JsU+06644gqWLVt2vovxj5FeYCHQqKPM6jhvNXsZRRZ+3ZtPRpHnJm/DwSI2pBV5btbOkfgjgWqnpBCZ/LohUaC00kmJxUlWsZX0Asv5LpE4Ab1Wjc3pwt+oPa1raMPBItbuzefvjBI55udRVUDxTzoGx/4enU4e6w8WHjevxDAzZr0GvVZd5/VVDQK2ZGv2SZc/E9shhGg4ztgAI2VlZZSUlOB2u2u8l5iYWKc8pkyZwvXXX8/o0aO58847adSoESaTqcZyoaEyEMSZkBhmJq/MhvFI33k497V31W8I4kPMUNWweo4bWNcfLGTNrlw0ahV55TZAut2db52SQ9iTW0aASYteo0avVfPtpswG1+JyOtfMmbre6pLP2by2M4osbEovwulW2JtTRpu4oFNaR0aRhd05ZVQ6nOS6XOi1Dao+8R9Fr1Xz6758wvwN/5jWnGMD1PpcL1XX166cMsornVQ6XHRIDDlhT42tmSWUVzrJK7OddB2JYWZ+2ZtPQYWN//6RzqhLEo/7mRq/q0KIC9ppB2uzZs3ilVdeYf/+/cddxuVy1SmvVq1aAbB9+3Y+++yz085PnFhVd4y/MoqZtb+AHk0iyCiyEGDSkVdmO6s3dlV5V++/n1FkoVNSCBFHbg7OhaqyLN12mG1ZJVRUOunZNOK0unGJMyM+xMyNlyR6z5Vju9kB3u5yccEm7E73ebmp3HCwiPRCS51uuI51pm6qTpRP1TmeV27DT689KzdwVa30v+0vIC7EzKb0olMaXTW9wEJiqJlii502CcFkFlmxO/P/McFCQ2J3ujFoNWQVWVmyNfsfMaVL9d+jul4vVd12d+eW4W/Q8su+fMqtDgxaDbtzS2kZE1zjWfAV23P480ABpTYXLaID6lQ5GR9ipmlUAGv32rA73CcsV32fDxbin+JC7U58WsHa7Nmzuffeexk0aBC33XYb//rXv3jggQcwGo3MnTuXqKgoJk2aVOf8pk6dKs+snWN6rZo/DxYSbNazdk8eCaFmth4qpnFUAH6GM39jV/WcnNOteOd0A8+PGApc3SHunF5AVV1L9ueVU2yxY9RqOJhfzq5gk+diDjKC2wEuO7gcnj+1BjR60Bo8/8o5W2cZRRZWbMshv8JG32aR3ucFa/viPHaI612Hy8gtryQl3N9zU5Xm6S4XbNaRW1pJo3D/81OTfBqtwWfipiqjyBMoooLmMQE13q8K5FCgwub0Voycyf1UVf4RnRLIKLLQITHklPLRa9WUVjro0SSCIJPuvDxH2pB/zKs/z3e2KyhKrA725pZhc7pRVJ5KiYa2P8606s+TVdicdeoWX1WJZHe4yaiwoFOrqbC5KaiwU2HXY3cUEWzS4XS7vYMlFZTbKLE60WvVRAYY6JR04uul6pyMCzHRo3E4qE48KEl9nw8+2Xob4rVwtv2Tt/1idqG2Op9WsPbmm28yaNAglixZQkFBAf/6178YOnQol19+OY8++iidO3emoKCgzvk9+eSTp1MccQrsTjddkkM5VGjxtqzFh5opKLcR6qev9ebvdKQXWHC5FdYfLKRLcqinRjKnjIIKG5VO1xm/iayVoxLKsqA0i+Z5+9Hu2c09lkOY3AX4V5ZhyirDlF5K4KoKcNWhz7/eH0yhYA4Fcxj4RUBwAgQnQUgShCRDYDyoL94uXXUdFGL++kN8tyULvVbNzuxSEkPNHMy3oNWouLN3qk/wll5gocxSyd8ZOyjN2Enajl1YivKIap+IKl9L3OHDXGuz4KdxExuoRdlnx0+vgi0m0OpBYwCtEUzBYArxHBtzGATEeI6PrmYX61NRvTW4voNjnImbqvQCC34GLRU2p7f7VvU89Vo1S7dlk1tqo9zuIv7ICHRn8jqr2o5DhRVYKsrYc+AAxRk7aB1lItpfc7SiQ6U6WtGhNXqOgSkUdEbA833kcius3ZPHNR3j6ZQUwoptOewvKGdXThkDWkadMKg/E9u0Ia3I2xIJeEfLPTYwOhvzZR1vW6q3jqYXWii1OvhjfwHxoWZ+3ZdPk6iAM941OKPIQkKoHxlFFagU2J1bdm6+n8+zqu+e5jEBJ93WjCKLTyVSm7ggtmaU8Mv+fBS3QrHVTkywifwKGwEGraciNMKfPs0iKa10ACpvgLg1o8Rb0VHVKl29a2VWkRW9Tn3C7o9nWvVr4Xwc9zN9bdc1PxmJ+Nw4lwFx9ZHP4cIbgfW0grV9+/Zx7733AqDTeU5qu90OQFBQEHfccQfvvPMODz300CnlX1JSgr+/PxqN5uQLi1NSdcIOaxdLfIjZ+yUVH2o+K10B9+eV892WLAw6NTsOl2J1uCg4cgOSHOZ3Rmo7FLebwsz9pG1fz96/17Nn5zb27j+I1llO80AbLQLLaRWhITFIRahKRUd9EBXGaGx+4TgNcfxdqMJqCCAwJJKE6CgqFS06vZ5msWHkW93kl1qIMKsIMwAuG9jKwVoIlgLPX9EBOPA/KMs+WiidGSKaQ2RLiGwOkS08/w+IAZXqgq/FW7E9hyVbs/EzeL5SjrcNB/MrMGo15FfYaBUbxJ7DJbhKs4lTssn/aRXRpgJSyjLRVmTz0WebmPN7Me5jZv/4PEDFrGsj6N48CrfORKDejMFhBI0WXBooLfIcF2clOG1gLfYcH7fTNyP/KE9AHZpy9HhEtoCg+Hq1llYFKusPFvLJbwcpsTppHOlf5+vndI991c3l1swS1u7No2VsEOO6N/K+b3e6sdrdHCq0Yne6cDhchPnp63/j7aiE4jQozYRST2UHJRlQmkXGoTR6v7yFzBIHNidM72NgVG9D3fPW+YE5lAN/O/ns10JCw8PJjoqjV9eO5JhSOKRvQUahFafLXaM73ul0Q63VkfOtsNzuvWErszpqtNxWr6HNK7edkZvaY2t9q4L/9emFGLQa4oJM+Bu07M0rIzbIxK7DpdhdCjan29s12NOV1ES8oRJKPceH8hywFnmuhcpiz/9tZUeD6KreAyoNaA1UONUs/WArzRLCePDqbmSWmShTB3LYHkd8u/YQnOi5fi7CCqjqx7f669qkF1gotzmJ9DfSLCqAzsmhdE4OZUCrKDYcLKLQYifUT49eo/b2XKkaAdLudGOxu9h8qAiDRkXm4RxSA5wcKt1OZ5cf+cUl7DyQi0njZsfKdeQXl+FnNvHVL6EkRYbg5x+A0xiCOzie9u07EhcV6fNboteq2ZpR4u3FUJ9uyceed9R5Nt4z60y2gtQ1AKve+6fM6iCx8YX3e3yhqO34nq17IW8PE7gg5zQ8rWAtKCgIp9NzAxQYGIjZbObQoUPe9wMCAjh8+HC98ly/fj3//ve/+emnn7Db7SxfvpzLL7+c/Px8br/9dh544AH69OlzOsX+R3MrbtZ/fz9lQbGUBCWQZ1ORX24nsshIuL8RlUqF2mwnrdyOVW2kcLeRgnI7eWU2ogKNRASYUKFCpVLV+FetUh/3vap/V+7bS7nbQk6Zi+iwMA6WaiiyOHBrXazPPERgYDT+OcF1yrsk8yDpG9dxYOtm9u3Zx579mezJKiGzxIGj2mONoSY1qVFm7Oj4LLsci80BQEBwCHEt2tHu0h5MvP0G2jRO5Pf9hWzPKiGzyMrV7eNRgkzkFVpJDPXDHurH9n0FWA1u8vRaujeJ8JalVk4bFB+CooOQtxNyd0Dudtj2NTiOtNiZwyC2A4qxGX5BrThsaUd8cKsLrmtlfpkNl1uhwuaksNzOr3urPWdUWQL5e9m6biV88wP6jGyaqh0kbnIxs7UVPZ7j4d6vwuEXQ6VfPKWmGP7I2U6X1qmMHjkcV2A8hCYQFBTC/z3yKFf/ZyOdhg3mzZeeQ1Fr0WvVZBZZfVq0fL70g01gK4WKfE8QXZQGxeme4KNgL+z8Aexlno3RBxwJqFtCbHuI7QCRrTytdSewZlcuhwqtlFjtlFjsOF0KeeU29Bp1jRrz6s7UDUmhxUaJ1cGWQ0VkFB1tgdJr1Zj0ahJCTZgNWvwNWhKOBHg+63PaPTf15blQcshT6VC4HwqP/Fuahc9dm18EBMZBYBwH1SnsL1jPwzf3Z+P+Amb8/Bch182kXctmNIsNISo4ADQ6UJQjgbTd86/dUq2io5Al337CX+lFxBaVcuiPncz5aiUA39zoR5eWSVRWNMOd3xqad2KvM5LDhkYUWjwVhGdiUKKMIguFFXYqj4xqGWjUUWp10CExhMwiq08X0updWPPKbJRaHew+fHqtT1V5llgdvP/TPrQaNVlFVnZllxHubyAu2ITT5aZ5dCDOiiKaKQcJrDxEZEY24Zk52EvTae7II8iRB25btZxVYAz0tDAbgz3/GgI8LZxqnefYaHTgdoHLzv592Xy9PgvWZ9HEv5IbWqnQ2YrQHbLBhiNZagyeoC2i2ZHKjhYQ0QLCGp/0Wmnoqq7JFdtycLrdx712E8PM7DpcRn6F59qr/r1X1eJdZqlk798bMO3fxP6svewtzSE90Y9BqRp0lhx6lGejd5SgptrgbOshHOgP7Mp38eI7FScs7/P9DTza0x8CYggwxpBsiuOAM4xKSxhWYwo/u1vUq8tsVRfzSoeTQKPOO7hTVfB5rgZ4OlPP3h0bgOkjPKNw1vjdCDKQfeggyZUHoDSTLmGVqH/JYVd2NliLiDHYCKQcKktwOuy4nXa0ihO14gRU1Xp0GDwVtOZqPW7M4Z6KwJAkz3UTGH/BXyenq7bjW6/fQ1uZ5zfdWnSkEqrY83+HBVwOSioslJZbCDKqaK3WUWyDwAB/KA6Fzred1W0701RKXWetrkW/fv1ITk7mww8/BKB///4UFhby3Xff4Xa7GTZsGGq1mk2bNtUpv19//ZXLL7+cuLg4+vXrxwcffMDKlSu5/PLLAejTpw8xMTH897//PdUinxf1maX8bHNai3A+n4QRFT8edPDIahvBkSrUcVDSUuFvvZvKBhQnqFwQWwLR+Wr88lW486E0XyEz303ViNJqFSSGqIiMUGEKU+EOUrD7Q2mQQlaoQkn1690NlAKHgfQjf5l4bvQaA12BFE7pxq+uwasaFcmoaKWoaO+GDgq0d0PkkXxyVLBZrWaLRs1WtZq/NBry1Op6B8bV/3W5weFS0GvV6DWaEy5f37xVKhUWqwNzaTkJThuN3Haaq100Vuw0clUS6vIEY9d+YWHpPicpETqsLtif46B5iwAuvSGVgqBAcnUmXGoNMUFmbA43Pz++nMg20XQc14ms4koUVFhtLuwON3mr91G0dBfm+GAaje2CPdCETq1Bq1Hhp9eh06hRq9UEGDz/jw02n3gbgBB7BdGWIqItRURZCompKCCyogANCk6Vhhz/cLIDosgKiOZwYDT5fuEoai0qlYrMYit/Hig60o0PdBo1FTYXgUY9LrdCeICRELOey1IjKLE6KLI4CPMzEupnoNji4FChFZVKRVKYH6FmQ732/Z6ccuxOhcIK+5GRFBVig80MbBlNuL+RXYfLKCi3k19uJzbYRKLOTmDFYZKUQqJtefiXZuNXmo2pPAe1cvSG0aEzYw2MoTIgxvNvYCy2gGjs/lE4/MJAc7Scm3/fzF0j7uLpLz5CHRjMc6PHE5rShFFTHkerVtOzSQTRgeaTbs+DEx6kIL+Alz7+gDU7DmMuz2bOs8+SmXaIL/49mMaqLGJt6RQXFBL7SjkBBhUDWkcy/b6rMTXqRGBKZ5SQJFSqU7te1u0rYGNaMSqVisRQMxEBR0dC/HVvPha7y/scU1V31zKrgz8PFqJRq7kkJZTEELPP+/W5sV1/sJBN6UWsTyukvMJKcOHfhFjTaRpgJVmTS7SqiEBnIf62bPxdpd7PWTSB5GpjyNFEYzXFEBbbiDYtWh4JpmPBP9LzrG0dbd26lbZt29KiVWv27dnDG18so8wURZTRyYBYG9GuHE9lR/WKqPIjFbNqLYQ1geg2noqO2PYQ3RYM/nVe/9lS11r7quNwqMhKbmklOaWVTOiV6n3Guno+6fkVlGbvZ+fGn3Dmp1GSm0FZbia7D2ayL7uQtAIbtmqVh0FGFSWVCv1aRfLM7f0JiUtlXY4KmzaQUvxo0ySZ8PAoYiLC+HHTfrKys3hsws18/O0qgiIi+X79PhS7hYrSYpJNFWz+eSVLFy/lpYkjeOiqVlhy9+MqOIi27BAmeyEAbjQUmxKoDG5KbNOOnsA6tr2nZ0EtFYPfbsrk78wSDhRU0CjcD5vTjdXuosLupEV0IJ2SQs5a68TZ6Pr47v/2sTe3HLUKesW4IHMLpenb2L1jG4czD+G0ltEkyEWqv43kIIXkYDVJwWoCzEYshnDynH5UagIwBIaSmphAqWJmT4ENp0oHai3NYkMJNumOVkQ5Kz0Bg+VIRZS10BNUVK/wUqk9j0hU9ei4iCo76qLqGquqCKk67iVWh6dyMyGIzmH2o5WFJRlHenVU69lhK62ZsUrjCZQ1OirdamyKFkWlwaRVyCm2sDnDQsfkMOKn7zz3G32M+sQGpxWszZkzh9mzZ/PTTz9hMBj45Zdf6N+/v7crpE6n46uvvmLo0KF1yq9Pnz6UlJTw22+/UVZWRmRkpE+wNn36dD7++OMTjjzZEDWkYE1RFMqthajydvHK8y/w1HuLSA03sivHygv9DTzcw8yGylhmb3QSkdSY4MbtCWpxCYbwOBQUTDoNRp2aTskhKIqCguL91624a6Qd798FG9Ipq3Tib1BzTYdYft+6h+y0A5jz93Hgz03kZOWwL6OQvbmVVB7pvWbWQZMoEynxISQlxxLfNJWYVq0IbdUOrclc53UrisKe3FJW78zBrbjxc9nRHtjD7z/8xMEdB4lunMjA8dfSuVdbtmYUk1tWSUSAgVaxAYSY9SfN262461wOBYVDhRXszS0lwlVBB1URbSgiyZJLTGk2ZmclAGV6P7ICIsny9/xl+kdQavCr8zoyiy04XG60aogOMtavvFX/V9wEO6xE2cqJriwj2lZBtK2cCEsZw2flcUcHPXd30WNBzX6VgQydiRyjHwV+ARwymPj81b/BoKHT5E4UW+zsXnuI/C/2oDFpibq1KfZII/4GDQFGLRa7k4NPbyS4cwStRjWm0uGisMKGW1GwuZxoVODKspIz7yCOYjsBQ6PRdg7EpNficLnQqFU43W78DRpMejVatQq7yzMJLUe2R6tRoVFzwv2gV9w0dzpp63LRxuWkrctNU7cbDVAJbFerWGtVWLzfSVakmn0hKtx6FW7laD6goEJBo1EBCk6XpwyoQEX14+BZVjkDfY78FWiCmmaoMabD4e0K8UY1M3saCNd4uq65UTiAwi5c7MTNLtwcxM1hFDJRKDhSxjo5AHwMTATCgE3At8DtQEI9Cj4fsAK3VksrBN4BLsXT1ACE5EDRLGjVVs3Ov92M66rj/YGmI4srrMfFhmp/B+uzLdV4wvgj4Xy1wA5AUY5kqKhRH0lTqzz7tir4AxVqtRqDRoNGXXslQZQCqYpCilth/8/l5Kc7OJzr5EC+2+cmPyZITVyEhtAILX5ROhzhekqjjWSYdJSoNLjc4FLAqNUQ6mfAz6BFhQqHS8HhUjBoNRi0mjoFrxUZFfzx7z9o9mA7Dn62B5VWRfykttgUMBu0xAWbMem0Pp8LdDlJtFeQZLOSaCsnpbKM5Moy9IobN5Bl8Ge/KYgD5mAOmoJJNwfhUOtq2SfHL5f6mCC8vv9mFllxHqlMSQz1O27e6YUWnC7PICt/Z5Z6Klz0Km5qYiTJWYY6/zDh1kIydmcy8T+ZHC4/Wslh1EJ8iI6ESDOhEQH4RYZiDwkjpHEj9unDKHFrKdy6m6xFP2KvsHLZ+OuI6tyWfbnlxIeYCQ8w0j4hhLLCEp4YOpmQRgkUHTjEBz99wJ85lWQWV5JWYCHMz4DV7qZDQjC7Fy1l1SffcteUu7hq9FWoVCryy22UFhbTmHzsGfvwLzlEkjOHONth9JUlADgMAZSHNaY8vAnl4U2oiGiKwy+SvHI7fx4oZmtWMXqNBofTjV6rpazSQXyI55m71nE1e8DU9d8TnX/rDxSSVVxJVkklqREBtE8IJi7Er055e/JVUJVkoi7Yh6pgLz/9/BNTP1pBVkE52SUOLI6j36+hJhXxoSbMfn4UVLg5lF9K5ZGeNwAGsz+BEbEYQ6IJjIhhSPcO3H3rSLJdARwq9Iyk3SYhmMQjc7WelNPu6ZpclOap6Mjf4+ltc2xlR0RziGl/tGdHVGvvc70XotoC8Pd/2kdR1n50+TsY2EgLlny0FTnY8g8Q7com1J6F1lV5NBP/KE/lU1Dc0UqowDhPDw9TsG+PAZWKXYdyefY/P7B543oqDu0i78A2SvM9+zg2Npbdu3fj5+d37ndGNecsWKvN/v37+e6779BoNAwcOJCmTZvW+bN+fn7MnDmTSZMmUVBQQEREhE+w9sEHHzBp0iQslgtroseGFKxV9+yzz/Laa6+Rm5tLbGwsd918NVNvuIQxj77AFz/vwuVWcB75DYryV5MY7kdISBAxUZE0T0kgMT6BgNBIAoJCCAgMxmAyodLoPV+WioPU+Gj0Go6OpGgtYs7nC9m2ex9pWTlk5ZXQPVHLzF4KGjwR2b0/WPlws5NLU0No3iiOFs2b0bxtR5p36kNCyy6otWdmasBf9+azemcuxVY7PZpEcHX7OBRF4fOFPzDz6Rls3fgn7XsMoPWI+3GbwwgyaemQGHLGh69ef7CQWWv2YncpqIHOyaFHay0VxVN7nb0ZsjYf/dfqqS3FP8rzpR7W+MhfKgQleGrRTaE+z5PUqbbS7QZLPpQd9vyVH/Z04yzYCwV7oGA/OI50x1FpPLWCYY0pNSYQNOIVAEY/OA1Nq8GUVjppFRdEQoiJ8b1SAbj88suJioriv//9L7/uzff82O3cw4KXHmHv9r9oe809JPW+nt7NotiTU8bc+wYx/KZxfPbOiz4DdwBU2l1syy5Br9j5dvbzrF82n+ade/Dcq++gDwpn6d/ZuBWFYLPeu083HCzi78wScssq6dY43PsDW++aXHsFZP/lPR7Pzl3Mv77LADw3as2i/UhJiiU+pTmuqBaEtbiMTu070alRKJ//kc62rFJMOg2DWkVzdYc4lmzN5uuNhyi2OEmN9CfMX49Rq6HEYsdid9A6IYj4YBPdUsN8K0eclVB4EFXhfijYy9YNfxJDDuayNMKUYm9xu82xsavARanVxYBLmzPk5hvI1sVR6R/LQ0PbnXZlg6Io/L72d8aPGM/zX82jbasU/s4o4pmxd+PW6bn0wcdoGhPIzV0TT5rXtLunYbVYmTlnJgoKf2cWk1tayepPvuKPBd9x/YvTiGkUh/twFm/cNYVJ7z3N7o3bWDr7v9w2bTwjukRiyt1HVFkaceUZBNo9N6U2nZmi4EQKQxIoDE4gPziBMnMYikpVoxLH5nSTV2YlzF/PzuwSymwOSq0Ogv10BBm12J0ugvx07M8tQ69V43C5cCkKGhXY3W4cThc6jYrwAD0GrWd+QH+3jUsCHSQ6SwmxFBBqKSLMUkiYtQjDkZbnXItC1ItlpEbpSUjwxxAZhBITRq7Rn/JSJ5bDxVgPl1CZU4w1r8xbQa8P98eYFIZfSjh+zaIwhJoI9zeQEGpCQSG9oAKtVoWfXkNkgMG3AuY4/xYdLGLpw0vpPqMvNqeTDc+sJbxfMqZ+iWjUKiICDEQHGU56PNVuF4l2K00qy2lqq6CprYIUuxU9Ci4gTWdgl97ELp2RnXoju3VGLCpVvc8/n+viBJWGTpcbh8uNRu35ejz2fVwuomwuUnGToig0URQaA40VhcRq0X4hCrtV8PZvNj5bYafLNTqKQlUUhSgUGRUUNVRVvByttDmGDfge2IqnImIgUP0RwBxgVrXXU4DjNY4qwHJgHTAKaHbir7AoRUVHNHRGTWc0dEZD7JGV5+JmI26fyo70U6zsOGsUCEdFU9Q1/hqjxnSksJUoPPm7jReX2el+iQZNENgDoCgEDoe6KTapQaVCfSTYUxSgQgXFChQrKEWglChHXxe40TXX4X9rIIrCkYobFVq1Co26/j1SqgevwW6Fxi4nTZ1OmrsctHLYaeK0owMcwD6tnp16Izt0BnbqjezTGXGoNXWu3LA73dicVRXu2lMq56lUnOjcbnSFRUTby0lwWmhMJc9+sJd1eywUWz3XhUED7WO1tE4wEB1tRhsWgDE2nODUOEr8gykyBVLsgJwSGzanG1Bh1muJDjJhUqCiqIKijCLyDuaRn5ZP9p5s8g7mobgV1HotfomRRDaNJSApipDoENRlDuY+8dF5Hx+gPrHBGZsUu0pKSgr333//KX1Wp9PVOql2lczMTPz9z39XiouFoiioj9zQq9Vq3H5R0HkcG3Jf5rbxd/HaS8+zbtX3/PLzGrZs2UxhTjbFxSXsTc/hi5UbvS1exzPxEj1vDD5aG5RX4ea2l8qJD9aTEhVAZFgIL/8vDVdMf16e+gAExlK6+1kuMWWz5qefzuKWe/pKxwab0OvUxB0ZHU+lUjHqmmHcOHwoM157nzdmTmPHEzfSe+wjmC65gsIKO+/9tI8Ao47WsUEEmXSn3VVjU3oROo2a9IJyUiP98Tdqj/bfVqmOjCaZBC2v9qQpiqc7QFXglr8bDv0Omz8Dp/VoxioN+IWDIRC0RiLRYnRqABU2PRhULs+AG26nJ5C2V0BF7jGDcKg8AWF4E4jrBG1vOBIUNvGUSeN5UNtVVAS8gk6n44u3ZnLb0yn4xbUiu9hCo3A/7zM8drsdg8Hg3f95ZTYuaduc21es4pFHH+Pr/7xJyf4tOG/4PwKCQ3A7bKTGhPo8GF7VxWzJ1mz0Wg1BxkAGTvg37XoMYMFr/2bslb1488036duqD99uymJ7dj4ZRVbPzYwKiq0O3IrCur35WBNDvH3m6/XMmN4Pkrp5/oDKzVOJ/vM9Zs18jHX/+5FdO7ax90AG36/bg8P9HQBJwWqaxwaQEBlMakIMHdq2RGeN5svftBTb1bRwaCiyKyRjIrZSi8rtwGZ3YNS4cG6y0TjCjW5HyZFAOsfz3J0l31ukH9O19J9TSPvkUMYO701g065U+CURENecvM9uYNydw+jWrRs33HADqti9NL5mGAaNls/WldV78IHa5AbnAnB9h+40atSI1pEWyh+byfT7biEws5yOHfoR71dzJMdjhRpDsavt9EvpB0DzEE8gfdsrQ+i5tiN/zvmBof/3NqHqIACuaTsEXZ8J5O0o5L8vfc4l/13K0OHtSS+wEBBmJlBXDtlbMGRtJjp7M9HZW2D3Cs/KdH4QlnK0siOkEZmhSfy+rwT/qCQO2oNRAt3kl9kJCdWh1ahxKwoBBi2KAlddGsjunFJyS8pJNFSgKc/BVJmHwZ1LY2M5Uc48/EvSCbamE+wu8m6jyxyJJqIJ5REdydYn4B/XnPCkVjgsOngxlVZjXyayZVcCjFpig0yUVjqJCTJSYXN6R320Wq38umEr27ZtY/XPv5C1azPZX21CcbuJTGlBdLd+BF7anyJDJE30GppHBzKqa91HEfzrr79YylJeveJ5unTpwiPOabzy/DPcPuRFEhu3oE1sEFd3iKvvaeLhtEPudjTZm0nJ2kxK9hYG52zzdCFDBeFNIaad57nRsMYQmuoZBEhfs+wnqmg57mid/irPdVRSVRG1DyV/L6NeXsEv+4rZUqqgi1XTo52Zbh0boY9MpTKsMR8VB5GjSyAgtjn3DevKpcCa554j8PcXeWXmLp/1VM3RZtZrvIPP+Bu1hJh0FFhshPjp6JgYTOwMI7NnzeaByQ/QI3AQXcY9jtWtwa24iYjP5ClupNOwG3CVFjDv7rnEBpu8wd/irVlkFFowG9SkRvgRfZueqfdO4ufvfubdWz/DFJPoGWXZ7qTc5iDUX3/kRl1Fh8QQn0CyRFEor8jFkLsTU+4OLsvbRe/DOzDZPOdtucafg/oE9ukTKAhKoTw0hRx1CI1jgmgeHXjc4HlrZjG5pVb25ZXRKMKPCH8DLWNrX74qyN6eXUJ+WSVphRWEaB20NVZA3iEibXmkqkpIopiAshz0jqOV9hWmUEoDIin1i2CrfySlfuEUB0RSbgphf/Ey9Gu/p81jT3K4tJKsYguKxU6gw0WkToVeq8asV1NidXj2e5iBTr2CCTbr+GVPHg63G61aRbfUUL59fj6Zafm08L+GJlEBNIn0825DQYmFcqebQJOWAKP2lCscClD4WXHzk6KgcTuJsRSRWJFPYkUhHSsKuLIkHw0KLlRkmQJJM4Vw0BzMQXMQ6cZAbGoNiqJQYXNQbnNiNqgx6TTklVWixYVGBUFG/ckrPdx1r7RTuV1EOm3EOSqJd9hIcFSS4LSR4LAT5XJ46yDKVGrS1FqW/FVBuzYmOrfyI9ugIT3XyaYMG+t3VOL6tQLIA/Z7HgMM1KIyqECrQtGA262AUwGHgmJxo1QerQhRGVRoo7ToYnX4dwpAFatFFalGpbaT695PDvtRFDfm8KB/1tD91bndbkpKSqitoS40tG43ApdeeikLFixg8uTJNd6rqKhgzpw59O7d+3SLKo5wu93eLj0ajQaXy4Xb7Wb//v3ccccd6M0B9B42Cl3zAZRuzsR2uJQgjZq2fnpSw/0IooLLIuyY3RbKSoqwV1pRXHYUlZqJU18mPy4F7nvN+/C6vcACLzXh3U+/YciQIQC8/fbb3HfffaR2H8499wym3Go/JwF5fIiZZtEBJNjNR7rGHaVSqbh97C1c2rsfH7w4lQXvTOOS7esIuu3fWNVGSq1Oiivs9G0eddoXfILJzg8bf6RTjyuICzbTLOokw0WrVEemBUiAFlceTXe7PdMRlGR6gq7yXKjI8zyA67RRVFhCUalnAA23yUxksN/RgQXUWk8f74Doo3/+0Z4WuiMB2YlUVbD8+8W3+WH+p8x98l5GzfiIgLhUTHqNd1S1wjILDk+Vs898RofLnHz18Wxe7dWbx++/i8PP3Uafu57Gaa8kJizIO+Fy6ZGRueJDzHRIDGHNrlz8jVp6REawza8nT81byuo5zzN69GgGD7ua+CsnolFpyS62sj+/HBTILrEAakLMOrZnlXgflq8+MXt9j6fT6cRoNDF87GSGj53svUlUOyz8tGoJGdt+J2vfDjLT09mw4TD5a9IwaH+nV7KOYU00XNlEQ6OQIz9nOUf+jnCptLhUWuxFwZT5R6MNisaU2NVzfAKiIKQRWdo4flmwErgTXUQqk1/7hibtD5Mw5E5aat0UFhUTHBzMiBEj+PDDDxk3bhw3R8Wi6XAtBwsq2Jldyt19Gp9WwFZ1DlRV/sSHmHny3pv59duP+f3zNxl+5ZV1mljZ7XZ786jKp2r5F155jVtHXkP6hpXsVnvSCivhknA/HnzqVe4bOYinHhxPv59+9raYfrvHQaGlMaFBLenU9l5PXhX5kL3F0/2oYJ/nhj39dyjL4p0fK3l2rd27fp0azDrVkS6MoFGDRgVuRfF0O3QrqFQq+iRruKm1jiFNtBh0WsrtYZRqw8lUR/OzriUV/smUBSTRqGk7YiMjuaxxOH9VewYuPCIc+4EDADSKCMTP38A1HeOJDjL6TLicW+rpFmQymQiOb0L3hCaMvHEUm9KLUDksZGz5lZVLf2DtN3P48dO3CEpoRvwlg+h9z+2n9T017OY7mf/F5/z00Uw+mL+Y5IjT+I7W6o9072oPnY6kuRyermDZWzwVUdlbYM8yz+BEVfwiwC/SUwnlHwmGQNTlbmLQoeiMEOZXbWRLJ19/twG9VkVky1DClSLaWnIwVuaBvdpzLioNjsBEDqli+GJTEZe0b0GHJm05cPAQDy//HdXKXVw1oiPPT5+AKlfLoQMFhLuM3u8Ji8WC3mDkUKHFZwqFYwefAc8gTAkhZiIDjT5d5iZNnERyUjI33ngjBUVl9L//JZIiw9DneqY9GjzidiLjkymtMNA65ug1enlTszcwNGm0OOwaFny+gB49evDYXZN5e/4KIk0R5DoriQjVkV1kJb3cRo8mETQJi6l5XCJaQPIx91dlh8nf/Ts7N/1MaMl2epZvJLRkOaSDEy0lxjjCElt6gumAaM8x8o8gx+VPVrmKXoHJ/FJYhsbgJtyp5ZrkKGL9tdUqCu2eZ7qOVEDt272Tz+esAIeFoclurkux4q/33KOUqoNxBKcQltjd04skLPVIMJ+Cn86EH1DLVpGxOJsfjWu4pukYDhVaOFBQTnZJJUatBpfbTViApwJxT04ZJRYH8YFmRrf2TCOTrPfMCVpVObsxdA+Zu34lXnsTQQ4DrQOiQAUHf1vCK088xuuf/UDjxqlnd7RBRyXkbEOTvZmE7M0kZG2mR9Y2z3mvUnt620Q055AugZLARNyhqbRt3ZYMm4n0ItupVTC73Z7jVH6ksrDkEBTug4J9FB/aycA3tpISqebO7noaR5pRhaZAWCqlfsn8XBGKIySVoNjmdGndjOSKCpgaQKfhz1IY1Zk4m4sgm5OIAD1J4X4E6dxkHTpERcFhItUVlBXmoFPsFJaUs/1QPi7UaPV6EiOCiYmKxKINIDg8kg6tm3NF19Ykhvl+N1Wv7DVpjzRNn2SewobotII1h8PB888/z0cffcShQ4eO2yrmcrlqTT/W9OnT6d27N0OHDmXUqFEAbNmyhf379/PSSy+Rl5fHlClTTqfIoprqN0ZqtRqXy0V2djZWq5XU1FTvcolhZrqlhqPXacgvt6FRwZ7ccppGBfCHVc/gNjE0OebiD3vnCxwaE4Q39qa5itMBfKZiuPfee9m3bx8TJ07EogumoLiU6Iiws7nZPtt1vJGmPF9mMTzw1Ot06TWAp/7vfnLSxzJhxiyspihCzXoq7M7Tnodu97oVfPvaY7ROjiYxtf+pf4Go1Z6RpoLia33bUWRhV7UBDziDNUre61uj5+Z/vUbuA7cw/9l7GfPsf1i02UaX5DDyym3YbHYq3Uf70hy7/7v2HsDUj77nrSkTWf7C3bhcTkwmk/f96j8ydqeb9gkhVNicBJl0NIkKwE8fQqdn3+KmkSO46667+G3dL1x262O07t6fnIIStu/agy6yEVEBGtQqUKtV7D5c5pknLcBwyiMyulwutNW651YPMOKjRzNrdTcS+7ixZpcyyE/PoQP7cBzcwIY//8fKZVu4f4mLpORkOnS5lNDG7bFHtkLlF0KHpDAKrQ7Ps0YaNR0SQ9iaUUx+uY0WoYGkBPqTGOzZh8Vl5QD89ttvfPfdd4y/7wH2Pnc7h3pfS1F+LkFBnpao/leP5PZJO/jwjRfoNSEAfbMeJIaZ2ZRedEaDtSovvvgiHTp04If58+h59S0nDdiO3ZfVjb5+OP8ddjU/znmZ/mMf9Cyv0pFeYKFpQhTXPPQi/3niVv7vkYd5/c23WLI1m5wyGyUWh2ewkKqpFPzCoXE/z191jkqKDk2gccYaXn9iPHsOpLMj7TCK04bDbseoUSi1uQAVOp2OhLAA7IqKnJJK/vxrDyPm78doMpPUqRetB4wkIbUNZTYnJq2GSqcTg1ZDRlolo2OPzvNT/fyveta7aWwIV/X1fG9W3WQ0jQwgt6ySAJPOW/mRXuj5N8LfwOA2MaQXWLii42iGXXs9f+w9zMZfVrP6u/nsWPgOt337Dh/1HcDVo8Zy3VVDatzQHPuw/7GVrqkxwTwy/QXuu2U4O39aRI877qj9RDhVGh3EtPX8MdqTpiieARoK9nr+SrOOVkSVZmG37CDAaiHI7cCocsBBlafiSa0FjY7731kPwKDWobwwtjvhsT0o9o/GaggnOCqRiLhUCE7iz4OlrNm8F1hKQM9xDLn2GjRqFSHqSlYu/C/ffvohzb+Yx7Dh15LafzSGkMZsSCvyBmsBAf6UVjqodLpJL7AQ4W/gssbhPud4RICBEquDA/nltU4Yf9VVV7F48WIGDxmC3+zHuO/Lr9i7xRO8Bwf4Uel0eeeHqlL1PVO9BdHPz8yXX35J+w4dmD3zX7z34UeAp7XvUKGFED8DGUWWunf9Dohmd1B3Mtt2YElGMU5FgbJc/Ip3EunIpKU+ly72Ykx7lnmOy5EBH6KO/AG0rZ7fBo7PEMjijSr++8shmsUG8dnvJYzXaYlr0pqoS4agb9qLRHMQTdQBtA8IplNM3QbusdlsmIxGzHoNof56EkIjqbAd6UFS9XsIrNiWwy/78zFqNazelUvTqAASQj2VugA/78ljX7ETm7UCp9vtmY5hbz7BJh0Z+9IoLirgX/eN5b/frThpmU6LzgjxnTx/VZw2T+VT9hZvj5s7nvuSMouND68yQoSGeJWaeHOYp8LDFHxkvksjaPVYHArWykrMWjBp3EcqPVyeQVLKczx/1XvdqNSewWnCGnPIvwN/Zm7mz0wXH2520q57NybePYFbrr2av9NLOVxoYVt2Ccp+B2sP70Zl9VTAuLUGuqaE8ceBAkL9dfgbdDSPDqTC5qQkOgltWALppZUM6htNTJCJ3LJKOlXY2ZNTRkyQkZzSSgotDsx6LRbAZghlU3oJGUWVPqN8At7K3h5twi+o1rTqTitYu/POO/n444+59NJLGT58uPeG4FR17dqVxYsXc/fdd3PrrZ4nzKvmaEtNTWXx4sW0bdv2RFmIeqgerGk0GtxuN/v27QPwCdaq33xWPfPTJCqA3TlldEkOrfUGV6/X43A4fNKqbuqPnTfvxRdfZP3WnUy5fzwBgUE0bnTFmd3Q4zjRhMTVa2N6DBjGxv7dGT58OM/dfS3/fnEWsR16siGtkN059e9GVv2HsqzM09r1n5en8H+3XUtAwNn5Itm54VeiIuNxm898jV/VjbpJr+OyFomkzP2S8dcP4ZMn76LXQ+/w2z6FwgobdrudsMCjD/Qeu/8Tw8y0apLCm58sZNFHr/Kf2W+QZvWMinVsTWXVjW6F3emZO0UBs16DXqsmtn0fVvzyJ08+OplFrz6M68BIbLoAVs//kJi2Pbnmrv/jih4dySiyeG9+9Vo127JKar2ROhmn03ncACM+xMw1HeP5ZmMGHRKDURS4olV31qe1oFn/GwnWOrClb8WatoW1a1azd/7noFLhH5vKHy0voW3XHqS26YTNYGJrZjF/pnnmPTpcWkl0kMnzHB9QWl6GyWxGrVZz9dVXkxvUnI9mv82fX78L4P1uTi+wcMOEB9j09w5+nfMU1017HzdBHCqysv5g4SkHbMcL1tq1a8d1N97E4o/fokXPYTRJiDxhQOx2u487r2ZGkYXxj05n1cBu/PKl52Ge4AA/77kwsFc3bJOm8OnLUwhNbUfHvkOxO104FbdnCoVjbnZr0BlxaU0Eh0cxZPwU7zqXbM2moMJOmdVBlFZNuc1Fy5hAxvVo5PPxn/7cwqwP/8OyhV/y1dofiGragb4j7+CyQVdwsMBCfrmNmCCjtyX/2PO/KljrlBLpHX2y+k0GeOaUyyu3ERdsIjHU7K0hrp5XeoEFtVZPVJuevHXttew4cIjfVn7Pmm8/53+33cCM6ARa9x/BLbeMoU1qnDdYL7E6jxu0x4eYuffmq/lj+a089thjjBgxguDg4BPvz9OlUoFfmOcvsWuNt9dXa5ms7dlT7YN64pu04Y/cw3T8vyX0ueZmWg26isiYWForQXTShJB+sBS9Vo3W7dn3l7dJpG18sHcS9H//6wlee/rfvPL2u7z56sss+noB7XtdQcjkx6F9HBaLhUB/Pwa3iWHFNk8rzPGCql/35qPT+NfoyVGlT58+/PD99wwbNoz7xt3EmDFjAGiVGIHWHHjczx17HjVp0oR33n6bsWPH8sctI7mkr+f3tHVskLdF8PM/0ql0umkTG1TjWvzPf/7DF198wQ033EDPnj1JCPWMU5wa6U9mkZXduQbyAyJZV1zJNqOWr9Qq2jcJ8UxY76+CinxyDmeQW1hCWXkZTrsNW6WFQD8Ter0evd5Aq/gwb1CNKcTTKqf3I2fGs5iWPs+jX2xi3759/G/59+xYu5SDc59FY3ydfa17sKN9X0ou7+d9ZvNko67abDbMJqPPOVLbhOfNogPIKrayO6cMu8Pt/U2pqkzZvbYMjd6M01pBn6aRVDo8A1bpdWrMGgWjyUxeZhoPTbqXBV98RkLoORy8Qms4MvJqB29r9cHnmrE7YzftP7DzfxNGMvXmPmhthZ4eN9bioyNXVpZit9iwu1QUO1WYjEaC/YMwGw2eYC718mq9bmI8j0b4R3lHrHRu2gTMYezM/7B753bSfl7I7TeP5OGJYVx5zXXEdezPfnU0FieUVzoJcXqeuU+NCadXkwj6t4jy7Mcj11ximJnDJZW8umIXLkXhu7+yMOk06DQq/A06OieHsv5gIcVWB4XlNvIVG5ckh3qP018Zxfx5sJCIAANxwWYSQ80YdRqM+gt7vubTCtbmz5/P6NGjmTt37hkqjmcQgl27drF582b27NmD2+0mNTWVTp06HX8+K3FKqj+zVtUNsmqkzUaNGtVYvlOypwVCr1WzKb2IoORQNGpVra1BOp3Oe/NR5XjBmkaj4YM5H3P1kIHs3Lq5QTyXmF5gweVW2HqomMYR/jRJbsJvv/3GmDFjePyeW7n6nn/jatYflxt255SSWRxX5yG6X3jxZbSBEbS4bADZBZ4uagUFBUx++P+4/ZEZZ2Vi7DvuuAMXat747xLgxBO91lfVjXqr+GDPjV5yKK/P/ZLbRwzm13ce5YpH38ao0+B2OnyCtWMd7RqppceoSTTtdyMBwWG13twfW6tc9eNbNXDJoSIb4558mz6DhvLk449QWlpKaHQ81sN7eW/SNRSNGc+TTz7JLwfL+WVfPlq1Cq3aUxvXObl+2+90Oo8bYADem9/qLRcBRt3RobHb96L10CsZfve/Wf7HNn7/5ScK9mwg/Y/l7FrxGRqtjsjGbQhv0pHmbdriCk2iTdMUVu/MITzASJu4IDROGwHVrpvB7RJo9fRUdFMm8c2nHzF48GDgaJD75jvvMvraIax883FGP/9fAoOiTqt1reocqP4dXXVsrhhzP4u+/or1388jeuwk9BHHD5pcLleNgK+K5zm0aG6772FmvfQUAH1ax6PTHe2qO/OJB8jbs4V5Lz5BQuMWdGrTytsSdbyb3eqqjmX1G//BbWJYsjWb5HA/DhVYsNpd/Lo/D1R4blCPnJu9urSjV5eXSXv6Saa+Podln3/A50/fy7qv2jNgzINEN29P67gg7/flscFF1felXu+5CaqtRbmq67Dd6T7uM2OJYWZ++CsLzZGJmNvGR9Okzwg6XHEjq/73M1uXf8kv/32TX794h6RLBtD/ujFc0787JdYStEfmBKxy7G/uc889x4IFC3juued47rnnztoEtnVxbMtk9WdP44JNOB0Oeg8bgSP5Mnb++AVrl3zK6m8+JeXSK7jsutv4Liwek1ZDsJ8OS1ExAOHBgT75Vm1Tn6tvJqnbML5d8Dmr//sOk66/nM233caBAwcwm80n7FZ/vPJWV7Ufm3a4lO+++45hw4Z5pzxqHBdGboXnZtZn/srjyCiy0PiyIfS/YgiTJk1izvdrUelNBJl0DG6Tyq9787E53OzLLSOvrJK4EJPPdb9q1SpWrFjB4sWLATCbzURERBAREUFoaChG/0DsGjNOrYm/HDr8Q6M4EJ3AtoNN6dc2mSCTicSodoREwf5qgdThkkrWpxfRISEEjvM9k1tUht6gx+ly06dzG1JTUikYfRf5Gfv5beX3bP7fYjauX8bf/w3kx8sG0bb/ddiCEkgJ9z/acn6MyspK77PSJ6qgTQwz0zouiNgQU61zyfVtFskWf39cNgtRZhUpMZHe1psdZRb8g0PpPOIelr75BK+8+jqvPvXEcY/RuWBzOOlx9WgUjZZn3vmYpb/vZs6cObTq3arGsuVHKqVyymwEGXX1mpqh6r7Oho6B195CyZAbyNy3k7zNP7Lk++/I+/A99OYA/Bq1I6JZZ0pDPPl2SI3xrqP6RO5V10j/FtGs2ZVLZrGVnJJKjDoNLWK1xAabGNEpgRU7DlNqddA4wh+TQcOenDI0ahXbs0uwOd0UVtjolhpOp6SQMzq5+vlyWsGa2Wzm0ksvPVNl8dG+fXvat29/RvKy2WxMnTqVefPmUVRURNu2bXn66acZMGDAST+7cuVKnnnmGbZu3YrT6aRp06ZMnDiR0aNHn5GynU/Vn1lTq9W43W7S09OJjIzEZDLVWL76DXJkgPGEtVk6nY6KCt+JPI8XrAE0jY9g9fIldO/enZSUlDOxeadFr1VzqNBCoEnHpvQiooOMxIcEsGDBAibcO4kP35pBy8FpxA8YS3mli7V78oC6BUFLv/qMAwf2MWXW5+QWlBAXF8dtt93Gww8/THFsV1q168SE3iln9EvF4XCQlZXF1Afu5INP55+xfOHoca1+k31Zx9a89tEXTLxlOLs+fYprX/0QxeXw3ogeT9UNTYfEEDKPnGMn6hpaW+vctqwSKp1uDhVa6TrwWv6+cjB33jORlp0vo8eQEcx9722+/mQWv61awoAJUzEltyOv3EZskAl/Y/2/Ek/Uda+K3emmUfjRWvWqio/YnDLKK53eAVCaN25E59ZNQLmdTYcKCbHn8fsvP7Hlt5/ZsfJztn73AQDf+QcQkdgEbXgSofEpaHJ2+lRyHL1WzQy77UHsOnON/fXZ558zoFc3lr49hesef4Mw/8BTntC5qttc9XOg6gcyPDKWa28ex7dffETPq2/mm3zP90JtgeGxLWvVg4Gqc2P0+HtY8s0XpB/Yy+EyO4cKS0gMOzp09r+efZm/Nm/iP89MZu43y9njdBHmb6hTF+OqY1n9x/2yxuHeboaNI/z5ZmMGoGJ7Vkmtz5gmhQfwzIN3cM0117L595+Y+/pMPnjsVroNHE7o3Y95W+PtTrfPDcSxwVptN5YnmyS4an/1aBLhPZZBJh2BJh1r9+TRvF0XwlPasDctk5z1S8j843ve/+V7fr+kB60H30xg486gQMfj9O6OiYlhwr3388qrrxDWZRj4h5MQevTcOpcO79tO2p49XHbkkQm9Vs2v+/IJ8zcQE+gJ4K1OFUF+ZjpeOZb+I8bwy3efs+GHefzn1x+IbNmN6K7DiG7ZFX2xZ7CeAH//Wm/sqr5X+l51Ax36DuOvFfP573/eobykiJat25BRZPE8m6biuF3jTxQoVF9nv379+Prrr7n66qtRqVSkRofQWKXyzvN37A3nsQFzeoEFq8PN3Y89zeghPfjyvZcZ9+A0n+C/dVwQueWVBJn0tVbSdO3alfnz57NhwwZ2795Nfn4+eXl5FBYWUlRUSGHhXg7nFVBUWIjNevR3/p2QKJq07kCzth3p2q07saktKbd7fh+O/Q6sjUmjYNAb6JAYgt3pPtJt0Yw59RLuu7YP6w88weKffmPtsm/Z+esS/loxn+CkFnToN5xBTcbz615qBLM2mw2j8eTD3p/o+ACkRPhzz83Xcs/C2Xz71jQ++eQT7zWcUVCKWqOjx8CrceXs5a3npnHNgB706tXrpOs9WxwOF061jqZDJtBn4DC+eu1ftG/fnsmTJzN16lQCAo6ep8c+B16fxzGcTk/3yKTwALRqFYeLregiGhHd7zbueOAJVvxvLbs3/Mr+zevYs/BNFLfnfEiNPRoMVnXTrZoKIa/MRqifnj7NI/lxZy5qtWfU3k6JoUQc+S6vug/NLraSXVLJjqwyyiodBBh1RAQa6JIcytXt4+p0bV4ITitYGzVqFN9//z133XXXmSoPANu3b2f//v0UFRXVOmBJVRfJuho7dqx34JImTZowd+5chgwZwurVq+nRo8dxP7do0SKGDx9Ot27dePLJJ1GpVHz55Zfceuut5Ofn88ADD9R72xqSY7tBulwuDh06RGJi4gk/l15gwc/gGemq+pdb9ecedDpdnbtBVomOjmb37t0nbKU4E+pSG2x3umkbH8xfGcUkhft5fyDVajXjHpxGpS6IT998Fn93OfE3PoRGrfJ2yzgZxe3E6XDw+mN30aZtO/z8/Jg0aRKvzPqQVR88jf/Uj+s0GEN9uN1uOnTtzpY/f+btl56h66zXzki+VXmD73GNDzFz+zX9sbwzl/tvu5EZ/3qUckslVteJW8er/2DWt4Wr6vOD28R4u8Z4fnTM/PvVD7w3uqPG30+Xy4fywzvTee/xcTTpNZwet0wmMTSMUL/6T0Z6om6QVY69ya7azmPTq36I0gssmPUaSiuDubL3JcxbN4KCcjuu8lz8yrP466+/yD6wm9zdmzj4y3e4XU66dq3ZVWzF9hz+PFBAeICRCb18KwC6tmnGky/P4qHbb+Snrz/GdOMd3mdx6qu2bpBV29E8JoDLnpvOoi/+w8ez32DguIeP24p3bMvasUFTVevp+Ckv87+li9iYXoyfXuu9PjOKLOwqcPDg87OZetvVzPz3I9z6f89TWumosa7auFwuNBrNcY9XlUVbMgHVcbtWVi0/vONN3DbyKl54YzZzX3+W9T+toOM1d1AwfDQjLmnk3U+A9/vyRBUaJ7uhrNpfVa0oVX7dm0/b+GAOFVnomBRCTLCJ7OTxqK67jcDDG1nxxQd8Nv1uguNSKRp1B21u6H/cdQy9eQLvvfceLz87naETn0EFmHSaUw70T9V7773H+++/z4bdh5g86T7sTjcGrYbySif7DxcD0CgqCI2/gR5NIogIMKDVj6PtwBvYsnoRu1Z/xV8fPcG+sBhCU9oAsCXbSpMWR58prC4ywMju3DIyy5xUNBnEVc9eTvGfi+javpX3N7HC5vS25NZnXxx7vg0ePJj58+fzzTf/z955hzdZfXH8m6Rt2nTv3bL33lMKskEZsvdSNggCypAlyEYEBEWQJRtBREVUBH4CCoqAskEoZRRK90ibtkl+fxxvkrbpTpu0PZ/nydPmzTvu+9773nvOPeMe1U2oZqeoZ1Yude9dnapYsGAB5syZgxlTJyHgP4uGKFd0Uioik1RZXL+FzOXj44Nu3bplu07un6HR+ObaU0RGRSP++WNcv3UHaREP8OLhDdy6tAaHPvkQTm4eaNCyHeJe74k+PbrhWVyqTtA2NgbLpRooFHY6dzjDew6LUuLGs3hYeZRH9dfGwu/VEXh27Rzirv2IsztX4tcv16BOi/Z4pVsftG7TDnGpGrjZ2+BpVDxStdIc22d25ck8WYRq1bB246eYOGY46tWrh4FjJiIsSgk3WynsbOWoFeCMwRs/wqBn99Gjdx+s2fs9OjauYRZrjlSihUJujSo+jvBzqY9pnxzFkV2fYsPGT7Bnzx6sXr0aAwcO1LUvEQeeWa7LDSHXxanUuP84FmqNBompqXCwkeL0nUj069oezm90gY2VFHfDXuDU6dN4HBaK8y+t4eCtb7MX/o1EulaLx1FKVPFxREqqGulqDQY3Ccow8STagpMtTchU93VCeGwyjl97hlS1BjFKFQLdFXCzt9HJpCKTdOYYz5JkZSuUsrZy5UqMGjUK3bt3x6hRoxAYGGhU0G7QoEGezvfvv/9iyJAhuHTpklElDSC3jPwoa5cuXcL+/fuxatUqzJgxAwApe7Vq1cKsWbNw4cKFbI/duHEjfH198csvv+jM6GPHjkW1atWwY8eOUqWsiQQjYWFhCAzUr2JrrGEbdqCG5uujfz1BcroGoZFJSNVK8uwGaUhRK2pA1sHNGGJArOjloBs4BMEe9pgwZRqa1KyA6RPHQpOWglfHLoK/a1ZrpDHS09Px5ptv4uTJkzj7y89o27YtrKyssPyjjRj6+qu4ceoQfN1G4KcbL1DVx9EknYpWq0X79u3RIqQDPlmxEN3btkC/fv0KdU6BMcuawLZ8fTQePBOXdi8HADyKSc2yj6kwbKuGLmKGM9JihrxipUpYue0Q9uz8Al+s/QAJoX+jzspPAfca+DM0WlfneXnu6enpUGslObooZSdkZ95uzJIith396wnUbsF48NIDnq1qoGIHa8ikgFwKNPVIQ/dGlZCZh5GJeBSVjOQ04zPyFeu3Qqtew3DhwCdQVGgIVYO6eXbnNcSYspbx3hToP3I8dm/ZgJodB6B99YZGzpLVsmZMQA1yV8CzfHWMnF4nS1yJbhD3K4/laz/G2+PfhGfleuj8xsA8ucAIZS0npahROTfdjHpeXCuD3B0waOgI1G/VEZ+uW4ZL+zfgztlvoHlvCfq91hkn/glHgKsCdx+SdT4363PO1zIu0IushJW9aWa5aXl3PI5RorK3I/xdaqDza73x46lT+OXQNhxYPRvSp38DyOoGCQDVgrxQs/to/LFnJULvDEY132ZG21dRIzxD1ix8F6mwRvnmXXHzeRxq+LrAy4HakJO9HZpU80aSiuLxAtwUkMkkaNK1L9r1HAjZy/v49uBOXD17ApBIILOj/j6zC5hQxqp4OeLu8wRoAEhsFHhr6kxdggrDGNr8Pgtj7a1Hjx7o0aNHjvsA2U8EAcCUKVOwceNGvP/++zh48CCAjPHYLX08Cuz6nJquQXKqBnFqOay8K6NzldpITlPDzd4GUYlKxIXeRNK9S/jzfz9j5vGDWDvfF8OHD8eECRPwV6QUYdFk8TC8p5SUFEhk1lkmaAQ2VlL4u9qhsrcDHkUlobrfa5B2ew2+1in47shB3Pzfcfw1cxQ+dXKHb8MO8G/cEaGPXsJeI8uxTrKTCYxNFrWoNAyP79/Ce++9hxYtWqBly5bYKZfAw9le53I3dtF6TOnXCbMnjMTzNbsx7JUqxa4YSKBF7QBXtK3qhTsvEnD+YRyC2g3Bwq698efB9Rg8eDA+++wzbNy4EbVr10aQu0KXFdlwDBTPIbuxTVjW3B3sEJUM2NhYIVWjRYJKjZT0ZFx/FoeBTWjZEB9nW9yIbAVp+ca4/TwB1X2dde21srcj5FbUlzcMdsWJf8KRrtHiSYwy24lrEd9270UCmpR3w7UnsbCX0xJg9jZWuBIWAydbazyOJvf1l4mUmdVwgq+kUChlTaVSQaPR4MSJEzhx4kSW37VaSmuc12yQY8eOxT///IN169ahdevWcHXNf7B/Zg4fPgyZTIa33npLt83W1hajR4/GnDlz8Pjx4wzKiSHx8fFwdXXVKWoAYGVlBQ+PIkzLWoxkjlnTaDR4/PgxOnbsqNvHWCdmOBgIQfjGszgEuinwR2g0qpRzwz9qSb4ta8VFbq5EQO4z2C8TVAhu2hkfbtyGOZPfRHpaGoIXrPvPXTJ7FxWAZtD9/Pxw7NgxtGzZEla2ZC0IadkUPQcMx/dfb0WFJh1gYyVDoJvCJJ2KRqOBi8IGk8dNxd0bf2P4iBEIDAxE8+bNs5QTyLlzNnZuwLiyVj/IFZ3eGISoZ2H499RePI6ML7IZ+OwG3MwxKMKlLchdgbkzpqBNSFsseectzBr2GnqOfQ+NuvZHgyDjiXOMoVaroYbEpD7xmdufEKjO3IlArDIN9nIrWEkleLWGt25x78w8iVECWgm8nOQIdFMYnZG3l1thyMT3cOPi/3BpxwcILr+zQNa1nNqAYMaM6Ti4ayuizh2A82vG3eczW9aMvYeZ6zBzXev+1h6EU6fPYv+6hWjXqhmCKjXO9T5yiz80vE5ufUjm/QE/bP7kE6zd9zp+2b4Cq6YMxo+HO6NGr4mQ2LsjIImSDRVGWTN8Xsbc45SpaiSp0hHopoCtjUwn0JT3cMCQXt2waeZwlCtXDvHx8UbPL845YewYTPt5LyL+tweOnVrpYnuLE61Wixp16sM9uCo2Lp6B1m8qUbV5JzjIZfBUkGjj5+4IhY0MSanplKwlJQ0Ng91w7l4kXsSnwM4hGP1nLMeAyfPw6MF9NKkebLRODa3E0UmpuBkejxq+TuhRTz8plHnWvrjIaayytbXFwoULMXr0aPz1119o0KABLofGICJehbBoZbYW0bzkBwhyV6CGrxNsbaSwkkigkFtBqUrHjWfxiEpMhZ9XdVSt1gAfrVmF639fxcbNn2PDJ5uxavVqVG/RCeXb9ke9+vXRsJxe2Y2OT4K9wjbDBIzhfQ5sGqTzmqjm44Rz917Cyc4a8clW6DZkLBwb90JM2B2EXTyBxxe/x8PT+yGRWaFCnWY51klOkxzGtn/wwQf49ddfMXjwYFy7dg0qlQpyuVz3jrm4emD4/I3YPHMI9q+dgzY1dha7YqDRaOBiT5lJ7zxPgFRCroTtm9RC3eobYF2jPc7tXo369eujTc8hGDftPcSqrRGVlIoDf4QhyE2B5hU8cs2ULOS6QHcHuMndkK7RQqlKx81n8UhQpePhyyTdmBIWpUSgmwKJqnTU8HPO8FwbBrvqPEtEHy8mFQyvbaxfk1vJILeS4bU6/kjXaBDgqoDCRqZzp7X9bwmhxJR0BLkpjLYvS6dQytqoUaNw9OhRDBgwAE2bNi10Nsjz589jzpw5mDx5cqHOY8iVK1dQpUqVLKuDN2nSBABw9erVbJW1kJAQrFixAu+//z6GDx8OiUSCvXv34s8//9TNUpVkMsesGbOs5SaUBLkr8NONFwiLUcJNYYNa/s5IUKXDxib/bpDFRW6KWE6IWUkRiNuqfTds3b0Pbw4biM8XTEK1z3ZmGLTF4qiGnU1aWhqsrKxQr149nDp1Crdf6JWMxR8sxo/fHsXtb7eg6tQPTLI8AKC3oj6OTsbURWvw4vlTvPbaazh//jyqVq2Ky6ExupnO/KaxN+YGKWhUzg2Nyrmhe+2PMXeJP0I6di2yGa3s2qox65Xh9wEdmqLnpYt4Y8R4HNqwCFcu/oohMz9Et0aV83Td9PR02MltinwAEG4qlb0cdYl+Mlt9DQmLUqKmnxMC3eyMzkyK5+Xj7oQZH27AvFE9cfHoVni7TM23dS0vylqNYF+8PX0Gli9ZiIXz3gOQVcEUlq2Cknkiaey7H+DW31fw/pTRiNv0FZpXC8zRkpCX+MPM18lruQBKxV+nXj2UW7YTto8uYPWS+bj+e1/U6j4SynLkFlkYZc2QbN3j/kvGI/ooIdAYtqPsPFvEOav4umL+/PcxfeJYfH3qHBo1aGAQ21s8QlBiShqS0zTo9NZcPAyPwq+fL4DE2gbNK/XBo5eUHtzPzTFLpkgAiE5MxdUnMbCzliE1TQMvF1e8O/z1bMtuWN8danqjqo8jbKykOHblaYbY7cKMLUXFsGHDsGrVKsyfPx/ffvstIAGc7Kxhky6FvY0V9f0Gwm92dS8wfJYiI6pI7HTs2lMo09SQW0mg1mgQ6KbA4+hkpLqUQ40+0xDQaTSunfoaN3/aj+v/+w5/1WyCxJHjUa1RKzgpbBAdnwQne+OTT0DG9TkfRibqXHs9HOUIjUqCq70NVH6VUaVXZTTuNwVP/rmAqGu/oFPH9vl2gRTXM3aclZUVvvzyS9StWxcTJkyAVquFXC7P8I41LNcV6rg12DR/EnZtWoOWHxVvQh5Dzyk3BxtU8nKAjbUUPs62OPrXE7hVbYLByw/g/plDOL5jA37/6Ru8MW4W4gNaQAMJbj6LR1UfJzQs55qjDCgsa13qBuhkxycxSlwOjcGfYZS9WISIiHMI7wRDjI3ThpNyAmP9mohJy27coolL5LiPpVMoZe3kyZOYPHkyPvroI5MUxsPDo9AKX2bCw8Ph65t1qUSx7dmzZ9ke+/777+Phw4dYunQplixZAoCSqnz11VcZ3BMyo1KpoFKpdN+zm6U0N5lj1qKiopCUlJQhZi3zC5S5swlwVSBdo4GzrQ0iE1TwcbaDUpWGmGQNlCmqDNezFGWtMAg3q7jkNAS5K2BjJUWVRm0wfeVWrJn1FsYPH4hvjx9DRBK5SUUnpiJCk5IhLiA9PV2Xwa5Zs2YIyPBMPTB3wSLMnfE2WnQfgGiPpgWKgciMqGvR6e05+BX6d++Izp0748KFC4hWpiIsOgkOtla5ds6ZyckNUtCkgge2r1lYpLPOBRWURJueNPdDSPxq4afPFmHdxDfgv+kLNCrXMct+mQdatVoNe1ubol0IFcgibOdlf/E3JxfMJzFKeDo0w2vDJ+L4zk9QqdEr+MnTHlW98+6CmxdlDQDmzJyGbZ9uxGcfrUDLXbuMnie3cwD5c2X+YvdedGzTAtuWz0HKe6tzdHEtrLKYW5lFnMWQZsEIcK2Lyk3aYu3ypbj89RbcsCYl7Xp4Itq4F3ytSUPXdCD7BD05vS/ZCeyGEyLp7V6Hq+9S3Dj+Bex8KukE6eJU1mQyKf59mYRWY+bjvCYN5z6dCyc7OY44+gBAtlkAR7Yqjycx3rmmfTeG2G/fxTA8jEqCv4tdtpkILQErKyvMnj0bw4cPx/Xr19EwuAI8HfSTPfl13TT27gn38joBLgiPTUY5D3u4KGzgZm+DIHcF7jxPQJIqHZEpUlRt1w+uDbsh7tZ53P5pLz6aMRJegRXRuvcwaFKVkMvlOSo1og0aWk2uP4lDWroGCrkMVX2dkKxSw8NRjpZV30D96WOgyCFte176EmOUK1cOn376KQYNGgQAaNOuPS6HxiBamYqXiSo0DHbF4IH9oYx8gi3rlqNt03oIatQej6OVuPEszqQx6cYw7EsbBrsiIl6/TmOryp44d+8lWlX2RJsaU+HX4FX8eWgjdq+cjUqNXoH/6+/Azc0N/zyNM5oZ0xChrGWOWQ9wVWSRJcT27JLlZMZYH5VbPHFez1PSyH1UzAEnJydUqpQ1TqKgjBs3Dl9++WWe3SbzQnJycgY3RoHIDpScnJztsXK5HFWqVEGfPn2wb98+fPnll2jUqBGGDBmC33//Pdvjli1bBmdnZ90nO8uducmsrIWGhgJAjuU17NgE9YNc4WxnhVaVPRHkpkCKWg2VRoLEZBWexChx4X4knsQodfWal5lrSyXIXYFANwUGNAlCj3r+utgVq6B66DR9Le7/fQldXuuF83fDceUxCQKZM2AJy5og4D83NtGZvPv2JARVroFjm5bgwYuELM+7IGg0WoRFU1tvUckDtcr748SJE0hLS0PXrl1hq1HBxY4UbrFPXju3nCxrhmS+T0tBtOknMUrUatkebWZthbWjK8YP7I6PPvpIJ7gaa/tA3hKMmILMz8/w3crL/rmdd/bsOfAMroKfNr2P3b/exb5LYbp13HLDWDZIQ0RZo1XAsAnT8eWXX+Ldz7/FsatPM5Q/r8pSkHvurizivlo3qoNpi9fi2tnvcfG7/fj7SSw2n76PP0OjsxyTVzfIgiD6DiGkPYlRQmHviH6T5+K1+Ttg51UOVrb2uBmR/ZiUF0Q7FbFXov6Ntd/c2lBmdzjDNlXB2wl9Rr+NJ9d+havyMR5HK3Nfy86EKGyksLOxQp+GgWgQ7I55qzejTvMQfPfRTIRePQcg92QtPer7o0c9/3z3SWFRSurTtYCNTFpkE1D5Iae6HDBgAAICArB69WpdHTb6b22q6MRUXHkco6s7Eb6SHcbePWEFeaWyJ2Z2roam5d2hsJYhIj4FAFl2qvs6oVVlD1jJJKgR4IbyTdqj69wv0HD8Ojj7BuHI+oU4+d3xDO6ExsY9w/K3qESp2eXWUvi5KtCigic61fDBK1U90aqyB9pW88q1n8hLX5IdAwcOxODBgwEAz19EICxaiT8eRuPcvUhcDo1BkLsCYyZNR+9+AzBixAhc/P13/HjzOR5FJeHEP+H4MzQ6x/evMIj4X0MLetB/lqgutX0xvm0lpKZrcOFBJLz8/PHuik3Ysf8rhN/9G1fWj0Pkwxu4FhaD/ZfCsO9iWLZlzEmuy24Myu8zN2zblipHFDWF6lnffPNN7Nu3z2TKVZUqVaBWq1G3bl2sXbsWhw4dwpEjR7J88oOdnV0GK5cgJSVF93t2TJo0CcePH8f+/fsxYMAADB48GD///DN8fX0xderUbI+bPXs24uLidJ/Hjx/nq8zFReYEIw8fPgSAHLNBGnvJfJxtUdPPGZ6OpBRLIIFMZgV1enqGTjc8llL8vkxMLapbKnIydxTiebSq7InK9Zqh1fjleHDtN3wyfyqexyQCAJJU6XiZqNJ1dsKylt3gKpPJMG72Ejz/9wb+Pv01Tt9+gbjkvGWzy450tRppGm2GwS8oKAgnTpzAgwcPsPn9CZBq0pGq1uDyo7wJ6IK8WlUsCcNnL+qwfpArPBzkqFSpIiau2o1uA0Zh+vTpaNa2Mw6eu4kL/0bicUxWy2BRCvg5kZNAUxA0EhnGzV+DhJfP8PCnXbj3IgF/hkVnUaiMHmtknbXsylquRXc4evhi/+bVuP4kDif+CdedP6dFsQ3J74DdtF03vNJzKI59thyXLv0BmYzWisxMUVrWMpdZxAx62MtRt15d9Hx/Gwau/QblPAvnXZKdIGRsu7E2lNf1TANcFdi8cAoqVq6CP49+jgA3Wly7KARPY9hZy+BkZ4MutX0xo1M1vBlSFYcOHkC1Bs1x/cgGAEBMSu4JYApCkDulv29c3g1VfCwjHXhO/YGNjQ1GvDUBe/buxR/X72U4JlGVDlsrWZ6S5QDZv3uG24PcFYhPSdNZchoGu6JhsCtaV/ZEq0qe8HG2RZdavtAAKF+nMUImLsey/b+g04AxqPFKd9hYSfMszAe40uRpu6pe6FDTGz3q+2Nky/LoUc8fPs55S9lfGOF/wwZqaxpI4GBrBQ9HOVwU1oCEzt2ysidWrPsE5avVxrxJIyBJikR4HFm5roTF6Oost4mT/CLku8yTNwC5rV5+RKEPUQmpeBajxN2IBLzasTNOnfsdvr6+OL9uEp6eP4rH0UkIi1Zm6KcNMWZZy438PnNTj3UlkUJNB9eoUQPHjh1DgwYNMHz48GyzQfbu3TtP5+vfv7/uf5G5MTP5SVgCkLvj06dPs2wPDw8HAPj5+Rk9LjU1Fdu2bcOsWbMyCKHW1tbo0qULNm7ciNTUVKMzd3K53Kg1z9IwnEETbpBWVlbw9vbO9hhj5mQR75SSpoattQypaWqkqIHUtLQMrjh/XSRl7UVCyVXWMmP4PGoHOGOfiwLWUOPUxvfw9cfz4DVvDdzsbTLErQnLWk7uF0N7dsLJQ73w486P4FazNQ7Hp8DTUV7gzF2AFnLrrOun1K5dG8eOHUPnzp2RsOodNBn9AaKSUvHgZSLSNVq0reqV6zXz4gZpaRjL8gXQxINwjao3/X14VamPPSvfxZher6LLlOWoUqcBLofa4KebLwAAbvY2SExJhdwM1uL8JrnIy/kCKlRB675v4teDn6Fis464b2+NqP/e15wG1twUdsOy2lh5o8vwyTiwejZePLiBis2b6t6BnBbFLhQSoN2w6Xh46xqOr5uFocv3IaBCVlfDvMasmQLxTGgtKS8EuipQ3sMhR5etvJCdy092LkUiA5xhoonc4pYEMpkMixcuwODBg/Hk7nXUrt+g2FwhjVmAKvq44vLZH9Dy1S7468IZPIgumrEmv+5cxUFu/cEr3Qdg7cpl2LhpE3Zu+kh3jIj3MTwurwp7dmSONzKM2RRZKFtU8kCaRos/HkYhTaNFtMwV3u3HwNXb0WhGzoJQUBfH/ODq6oqvzl5BmlaKQG9HdKjhrXND3n7uISKTVFCq1Kg9fDGeLBuDY8snY8nWI0hITkOAqwJJqnQkpaYbjW8vDIahD5mThylT1YAWcJBbwd3RBkkqNVTpGlwOjUGP+lXx95+/YeSEt7F32wYkhf0Dv+Fz8eK/sTFz2bKzrJkyPs/UY11JpFCjkqmVq9OnTxemOEapV68eTp8+jfj4+AxJRi5evKj73RhRUVGUkttI2dPS0qDRaEzqrmkOMlvWAFJe8z2z/F+/7uEoh5vCBinpasjlciiTEhEWlYjeDclSJwUJdHIba9PcgAVSxdsRT5q3g1y6DN9//B6OfbIQksmLUNXXGdV8HaHVanWWtew6INHJDXt7Dn47/QPOffU5Xh02Hbt/C8XT2OQCBchqNRpU9DIe6xQSEkKLsPbshRfx76LqoPdx+5kN0jVanLkdgUntKqNL7axxn4K8ukFaErklIxEB0s3bdoRP+SrYPH8yDi0ajdYDpyD5tWF4GqNEUqoaNfyckahUwd61eDPhGZbVlOfrUtsXVd6fi2F/nMLNA6tQe/x62Fpb5bqGYG7KWuayThwzEhePfoHzBzfj1Vda6Oohr5a13MgsKIiYjbcWfoylb/bAD5vnw3bGR1kmQIrSspYZw7aWXaKP4iiDSDABLbIoa3kR2vv374/5Cxfhpz2b0KTJ9mIrf3buera2tnjrg0349vg3sPPKec3QwmJJQmRu/UH1ct7o3LMvTny1F2kfr4S1tbXRY/KqqOe3PCJm87FBFsoONbwRmaBCVJIKkUmp8HWxhY11/t1Ks1PKspuMMDVNalfJEst/4X4kbobHI02tQUR8CuSOrmgzaQ3OfTQBG+aOw6gPtiLV0VZX/nS1Bg62VlnWvSsoQr4zrAfDBaJFPFngfxZxW2uZTpazsbHBnq2bEFS9AT5eMB0nl46EatIq2NvUz3Kd7CxrplSUS0PMWWEplLJmauWqTZs2AChBx19//YWIiAi0bNmyUKny+/Tpg9WrV2PLli06hVKlUmH79u1o2rSpLj4rLCwMSqUS1apVAwB4eXnBxcUFR48exeLFi3UWtMTERBw/fhzVqlXL0YWyJJA5Zg2A0WQsuZE55eqfodG4ULURVPs/wa6dO/Egsi/cHeSIiKdYDI22cLN2lopwa6oX4Ipafr1RzdMWa+dNhY2tHSRvzQag79iyGyjFeZSparh7+mLIm5Ow69OPIes9BHZe/giLUhYomN1wmQZjdO3aFbNWfYbl77wJ9b4lqDZgLlI1UthYSbD2xzv47UEUmldw1y1KaXj9kmhZy63zFy4iDrZWUNu5Y9AH23Hp4Cb878uP8OLOX6jUdyZcXD0QlZiC5NQ0pJbseRsd4plMmLcS743qicDL36Jp/1G69NrZkR9X2LAoJVRqoEWfsdi7YgbuXLuMhsHtceF+JFSp6SZpR5kFBaGI7k9OQ9dJS3Bk+RQ4Hd4OV4dxGZQ1c7i0ml0QkWT8m1+rikwmw+Cxb2PxjAl4cOs6PB1oDb2ividjyWiE4qtUS1GtReci75PMXnf5IMBVgYWz3kadL7/AsWPH0KdPn2K9vlDAxJIRwquhircjwqJlsLOSIVqZCqsC1FlOk2/FYV3Lzmpdw9cJkUkqNAp2xa3weNTyr4uaSz7F2mlDsfmDd9Bu7GKoJRJ42Mvh7mCTJb69MBjzUhAyisJGhudxKbjwbyTcHeRoW83L6ETRxFGD0KB+PUwcORA/rBiL5Emr0bqyZ5YJLiCrZc2SJjJKAwXuyVJSUnDt2jVIJBK0adMmx09+WL9+PXx9fdGqVSv07t0bf/9Ni3NGRkbCw8MDX3zxRb7O17RpU/Tt2xezZ8/GrFmzsGXLFrRr1w6hoaFYuXKlbr9hw4ahevXquu8ymQwzZszA3bt30axZM6xbtw5r1qxBkyZN8OTJE8ybNy9f5bBEjClrOblAZkdm/+PUdA0aNWqCKs064NSeTxD6IgZ/PIzCkyiK4Qp0L34rhCnIyadczFglpaajQ01vvPlKRayeMxnL1qzH2aO78cOXn+D6kzh8d5XiF3NytRKxJQ3LuWL9sgXw9HBH2I9foHkFDwS5Z10vKy8YLtOQHeOH9cOExRsRef0c4n5Yh9p+dB21Vot/IxJw7t5Lo37jJdGyliv/TS5HJqgQ6KaAg60cG9atwUfb9uHJnWu4sGoMvBPvoYafC+KVKjyNVxVbrE5RExalRMMmTdGi+0BcPfoZAq2TchVy8qqsGb4n7br2gHdQRezetAYn/glHWIwSKWlpJmlH2SVBqOztiJD2nVG321BcOrgRf/7+W5YEJyU5AVJBEPFEYnFnIP/WlZHDBiMguDwObl1XbLElxixrQjBXa7QIclPATWGaZRBKC7Vr10aLFi3w2Wef6bYZG9cK6wZpDCEnNAx2zfBuNixHbU9hawWJRIJnscp8t5+cYqAKk0CksFT1ccTAJkEY0rwcejUIQHxyGsrXbICBs1bi/u8/4qdd66BK1SA5NR0eDnIkpaabrJzGJjOC3BW6GPpvrj3D3RcJuGokdlcQ4KpA33aNsP+bk3D1K4/TH03B6m0HMrQVMQGdud8sq4lAiooCK2u2trZ49913cefOHZMVZvv27Xj77bfRuXNnbNu2LcOA4eHhgXbt2mH//v35Pu+uXbvw9ttvY/fu3ZgyZQrS0tLw7bff4pVXXsnxuLlz52LPnj2wtrbGokWL8P7778PJyQmHDx/WZQAqyRgOduKl9vHxKfR5RfD1tNnzkRwfhVunDiJNo4X8PxksoIQqazkFuYoZq8xWr3enTcKEGXPxy55P8P2hnYj6z7oYr8p+9sywk7O3t8eMuQvw7ddf4acz/4O/i12BOr+8pEQPcFVgw5yxWLZhK/45dxL/7FuBzjW84KKwhqOtNTwcjQ8mJTHBSG4IAaJtNS/UCXDB+LaV4ONsizS/ehi26gCcfYKwdtpQHNz0IRISk6BMQ54zJ1o6QrhZunQpnJ2dsX3NQqw+eRvbzz/MViHNLRukwPA96VTbDxOmv4vrl/6H5/f+RkJyGmQS07Sj7AQFoZRMmvk+fCrXwXcfv4dfrtzX/V6cbpCWgrFnlV9lrZynEz5YOB+///IDnj24XSyCsTFlTbTdkKpeVNe5WITLIuPGjcPPP/+M+/ep3Wce10zlBpkdmdub+N62qhcCXO2yLJZs6usVF5mfa2q6BnUCXCCTSjBlzFB0GDkDD3/ZhztnvoJMJsXT2OQMrsiFxdiYH+CqgKejHPY2VtBqtVClaWBnY5Uh0UlmnsQoYWvvhE/3HEH5Ok1xePlU7N53SPd7aViSqSRQqCnEWrVq6dK9m4I1a9agR48e2Lt3L6KiorL83rBhQ6xfvz7f57W1tcWqVauwatWqbPc5c+aM0e2DBg3SraNR2jBmWTOFsqZzCajvj+tjx2L7zi9Qvnl3XA6lOn2RoEIBvC3NTk5m/Zx+G/TWVNx48AT/271Kt85STHLe/ebKN+8K18AqOLBhKaTeVQoUt5bX9asAoFWH7pizajM+nDkeEokUg2cuw92IJCT9F5ScXYBxaVLWjLm1XLgfSesSyZzRecZG3PppH37dtwEadTrc/IL07mQlHP29e2Dj+nXo378/nOp1gneN5nBT2Bhtd7llgxQYvicBrgqMGDIQ2zaswVdb12HrvqNQpaZDmVY0GfwA/b0FuStwfeYqfDatLxa9Mx4hP59EkLtDmVTWciI/FpbBgwdj8eLFOL5zI4Z1P5T7AYXEmLJWktwSi4K8JHXo06cPpkyZgu3bt2Pp0qVGx66isKzlRqNyboVIoGV5ZH6umde9nDh5KlJjI/C/fWtQpXwQZHVa6cYQw7USc1oXMieyG/NFuXrU88fTmGRAAvi72GUbLyuUTi9XJ+zaewDjxozAvMmjEZ2gxNS3hiM9nVzXzdFmyhKFkq6WLl2Kzz77DD///LNJCnP//n106dIl29/d3NyMKnFMwTB8mcWLZgplzZD58+dDo1HjwpGtwH8zduFxJTMbZE4zdDn9Fuxhj6lzPsArXXri5OcfAgBs5eSek5d0vVKJFJ1GzqB1T/53AtefxOGnGy/w+f/+NbpWlDFyi1kzJMhdgS6v9cLHn27FxZ+OYefKOYhTqvAsNhkPIhOzXLdUukEaIOrIxkqKWv7OCKnmhSYVPTB83GT0+2AnvMpXh19wpQxuZKWFvn37oknLNriwezWUycm4nE1q9ry42QLG1opLwbCJ7+Da7//Dnxd/g0ajRoKq6AMAA1wVaNugGl6bugwPrv2GoZPexZ+h0WZbhsGSKKjQZW1tjblz5+Lw4cO4fv26iUuVlfz0aWWFvKQ4t7OzQ79+/fDll19Co9Ho3kmAJqSSVIVbJoYhsrMgiu8Ng13xwYcrENKxKw6tngmPpEe6MSQsSonH0Uoc/esJwmLy7xYKZJ+sSZSjUTk33TqDYs263NxIXySmo9mohQhs3AFr5kzCZ1u3c59ZTBTKsrZx40a4ubmhU6dOKF++PMqXL58l6YZEIsGxY8fydD4XFxdERkZm+/vNmzdNrkyUZQyVtdjYWACmV9a8vLwwedoMrF3xIV4ZSPFwQZ4l0w2yoAS4KhDQUIHuXx9As7ad8Nf507jxPFEfDJ9L8HPDcq7wHNoLt385iL+Pbkanbq8hMkkKCSS4EhaTp9nIvArTuvK6KtCi0gi42Fph2LBhSFUDjQbPxM3weMgkEvz+IArjQyqhUTk3i7OsmTJlMGCQ6hhAj/r+Gc5f278z2rVsivpB+c/QWRJ4GpuMt+cvx9Bur+Dp2f2oN2KK0baaH8utITZWUgTUD0GlqjWwZ/NqaDUauNrnvjaSKWhYzhXo3R1ht67gfwc2Y2+TZmUyZs0YBXWFGzp0KD744APMXbAI767YbLJ30Bj56dPKCjZWUtx4FpdrRsEhQ4Zgy5Yt+PXXX3V5BUQ/pyyGyRJG76Hy/qpNmDFmID6YPBQ1A79DwKutYWMlxd9PYiGRAP88jkWlAshMBe2TjZVTlPWnmy8QnpCKoJ7ToZFaYem7k9GoSTPuM4uBQtXk33//jbS0NAQFBUGtVuP+/fv4559/snzySteuXbFlyxad4mDIjRs38Pnnn+P1118vTJEZAwwHu5cvXwLIqKyZapHGhXNmwcvLC38e2wEACHK3jEVEi5sXiWl4Y+ZqNH5jLPwq19EJ/LkFP4uZsHVrViEhOgKJl79B26pecLbLW5rfvMYTGWPIkCFYs/FT/P3LUfx1YC3S0tT492UiUtUanL4dAcDyYtZMtYCmoUXNsI4Mz9+onBvefKViqXLfMSQsSgnPgPLoOXQs/vxmB9w1MbCxkmbpFwoqGKSma6CFBHVeG41zZ88gMuJ5sabOb1jOFX1HT0FgzSbY9sE0PHsRgeQidMMsKRRUWYtISke/0ZNx/OhXuHXrFi6HxuDYlad5Wli9IGVkZU3PkxglroTFwNHOOteMgi1btkS5cuXw5Zdf6raJsUghlxX7czX1gtCWRnb3FxalhFpqgxELP0FwpaoY1Ps1XL16FU9jk6GwscLzBBUUciuKZ8snplLWDHGzt4G/iwIKWxs0Gvwu6nbshz8u/saWtWKgUDUZGhqKhw8f5vh58OBBns+3ZMkSqNVq1KpVC/PmzYNEIsHOnTsxZMgQNGrUCF5eXpg/f35hiswYYOhGEhFBgrehsmYqoVehUGDMtDlIiI8DUHrd5XLjcmgMtDJbdBoyEY2rBelmnfMa/NymST0MG/Um1q9ZhejIl6jp5wwf59ytEIVVpqZNeAsrP/4EV04ewuUDH8HXUQ4pJLCSSTKc31Lq1VTZv0T7F778YVFKPInJm4JdWhD3+uHi+fD18cahDR/gr0fRWVxzCioYBLkr8DhaiaCGIXALrAy1Wo34lOKb2Q+LUsLGxhrjFqyDVGaFyBfPkZRWtAkWLB1DQT2/QntYlBIhr/WFu7cvDm5dD0iAsGhqK6bOEMnKWkbEOmYJyWm59k1SqRRDhgzBwYOHcPrGE90aZC0qecDOuvj7cVPJGpZKdvcn+tfm1QLx0RcHUL5iRbRt2xY3Ll9EQkoaohNUeB6XjLvPE/AkRplnpbYwE7Q50TDYFZ1q+qBTTR8Ee9qj+7i5GDZuSoZM6kzRYBlT4f/h5+eHy5cvo3Pnzjhw4AC0Wi12796N48ePY+DAgfj9998LteYakxFjbpCGqftNKZSOGTkMVWvWAWA5Qn2xIwGc7KzJV7yef4Hcg/qMngotJJg9bz6uPYnFiX/Ci6XjnjF5PCa8vwLXfzqIvw6vh6OtDDfD4/DRT3dw7u6LQp/flJgq+5dh+8/srlpWUhIHuCpgYyXF2QfxmDx3CX756SR++O44fvvP4igoaPxQgKsCvRoEQKMFmvUZCwBwcyweN0iA6jjITYGalQKx8pNtkMlkcHcq/fWaGwW1rAW5K+DioMDb78zEz98egWtaJILcFAVeciS3MlpKn2MJBLkrEOhG6wnmpW8aMmQI4uPj8MuPJ8yuJJX2CbDs7s8wfqxj/Qo4+8sp1KtXD4snDsLdiz+jnKcDlKlqBP43BuVVqS0qb5cAVwV61PdH30aB8He2Q6pag1o9xuPIyTMmvQ6TFZM4mp49exbfffcdHj16BAAIDg5Gt27d8r3GGkAxTlu3bsXWrVvx8uVLaDQaeHp6cqdcBBibDVcoMq5LZCqBNMjdAbu3b8X69et1C4yXNfxd7BARnwJ/l4Ivpi6xc0KVzsNw5chmfNusB14LaZLrYp95zdSXG7OnTUJckgp71s5HulqLGr0n48ydCKTrsnymIrBQV7AsMrf/srrA55WwGMQlp8OpanM0aNkWp3asRs/KjbD5zH20reqFCp4OiE5MKXAf3aicG57GJqOi52tIffgnurYPMe0N5ECGOq7nj8peP6NixYrFdn1LpaDKmnieDSaNw6aPVmHD2pWY9sHHRRK7xjFrGcnveF21alXUbdAQZ78/irEj9EsRmcNiWdqzeOb1/lxcXLD0072YNnEsjq6ege7DJ6H94In47X4kLstkSIcGjnJrvF7XL8fzFIWyZhirHRalhCpNg9CXSYiIV2HfxTAMbBpUquvQ3BRKWUtNTcXAgQPx9ddfQ6vVwsXFBQBZadasWYNevXph3759sLa2LtD5PT09C1M8JheKwqc5Jxo3bozdu3cX2/UsjdR0Dcp7OOQaT5ATT2KUqN95AO6eOYrb32xC2+YN8DJRpXNjMYapOu4AVwWWz3sHvk62WL1wFtLVGri1HwNZYgoAIDwupVDnt2RKuzCRE/WDXHElLAYBrgqMfmchpvR9FVe/+xINeozG6TsR8HG2Q1SiqlDtq2GwKzwd5Oj9xTazPueQkBCzXdtSKIwbpECswzpt+nRU7zISDWtXN3m9shtk4Rk2eBBmz54NRylngLQUbrxQouPEJbDzCsZ3uz5B6O1/UH/YPDxMkMDWWobKXo65yhBFkfTL0Kon1tJVqTV4HJ2Eh1FJuPwopsyOkcVBoWpy0aJFOHr0KN555x2Eh4cjOjoa0dHReP78OWbMmIEjR45g8eLFpiorY2IMB7uOHTvC0bFsJv4oLkzh6lE/yBUBHk5oN2waHlw5j8R/L8PexgqXQ2Oy9WU3pf96gKsCqxbMxJJVH+HfM4cQe2YH0tJpYAh0ty/0+RnLQyRRcbazRpWqVdFvxFu4c3I3pMpoBLnZIyk1Hc62skK1L+FueeKf8DwvR2FqSnuSg/xgioWRu/QZDIWTKw59sQEPIhNN/mxZWSs8ffv2RWpqapaM3fxcTUd++5UAVwWexaWgy9AJWLPtAB7f+RtfLxyO1BcPYC2VwsNRnqsMURSWNUP5RbhDvvVKBdT0c4afix1QtkN9i5xC1eTevXsxfPhwrFy5MkOsk5eXF1asWIFhw4aVaUuKpWNoWTt58iTi4uLMXKLSjSlinRqVc0Pnmr6YMmow6jVujt0fL8H957GIVqZm68teFB333BlvY+y7i3Hv5314fu4ggDIci1hGEIP1W1Nmwk5hj39PfI5qPo6IiE+B1gQuacLd8kpYjIlKnD8uP4rRfco6plDWXiq1aN17FO6e+w7Xbt7Nc4xtXuGYtcITGBiIli1b4sCBA7ptpqh7Rk9+k6c421mjYw0fuNnboG/Pbrh65S94eXjgr42ToAg9izdbl89VhiiKMd+Y/PL8P28afxc7WgqFKTIKVZPh4eFo2rRptr83bdoUz58/L8wlmCIksxskz6aVDILcFbCXW2HpilV4cPc2zhw/CGiRrdXOVDFrmfl0+fuYs/ADPL1zDQDwNFZl0vMzloUYrG0UDug3bgbOfncEJ0//DxEJKjyOTiq0YFA/yDXPy1EUCdpMf5lCEeSuwIhRb0Lh6IL7P+3Bk2glHO2sTZbMgmPWTMOAAQPw448/IjraPBbt0k5+PWoME8UAwLN0B+w8egLd3hiIrz6ej7lvj8fdJy9zXBKjuDI0XwmLQXxKOu6/SCjS6zCFVNYCAgJw5syZbH8/e/YsAgICCnMJpggp7pg1xjQIoblr25Zo270Pvt2+Do8jIrMN4i/KddCWLpiHIRNnwtbeEammyVfEWDhB7go0aN8LgZVr4vsty6HWaExi5TD3mnUNy7miYbBrkc8QW7q7pSli1gDqp/q1qIRR4ybj95NHUNlehaD/3F1Ncf/sBmka+vTpA41Gg6NHj+q28XM1Hfn1qDHcX1jlJDIbfL1vBxZ/9CkOHPoKLVs0x/H/XcK5e5H46cYLo+teAkWfobl+kCvUag0C3RRmzyha2ilUTQ4fPhwHDx7EuHHjcOfOHajVamg0Gty5cwfjx4/HoUOHMGLECBMVlTE1PNiVfFYs+xCpKUpcPrZd11lmFgaLas0VwSv9xmLhwd/wIqn41sdizIuPiz26j52NFw9u4OGF7+HrbFviJ36Ka0mGkrCmlCld4V4bMBwOjo74ZtdmtKjkgdR0jUnun8cv0+Dj44M2bdroXCHZDdJyyGyV82nQHv2X7IJao8HOdwfjyplv8TAqKcv7VFzKWqNybhjfthLqBLiUyUzJxUmhanLOnDkYNmwYtmzZgho1asDW1hZyuRw1atTAZ599hmHDhmHOnDmmKitjYtiyVvLx9fdH7+Hj8f2+bUAiLWx+OfS/2JtQir0p6o67fpAr3Bxszee+xhQrYVFK2Mut0KldCNp364XvvlgDrarwbpBlhZKwppQpBfZqQV5o3280vjn0Jb777R+T3T/HrJmO/v3745dffsHLly8BsGXNUsg8gVQ/yBXlKlXBW2v2o26rDji1aR5+3f4hZNqMC6EXl7JmrIxM0VCompTJZNixYweuXLmCJUuWYMyYMRgzZgyWLl2Kq1evYvv27dyZWjCsrJV8wqKU6DLoLdg5umDEhLcx/eBVnL0bgfiUNOC/8baoYtYE5nZfY4qPJzFKvExQISk1HQ3LueKLzR8jMSEBq1at4r4kj1i6cGMqN0hBgKsCdTv1h5WNHWbN/wCXH8WYZN01jlkzHW+88QYA4OjRo2xZs2AalXNDwyA3+Hu4YsKCj/DukrX47YcjmDKoOy78dUPnTVOcyhpTPJgkyKRu3bqoW7euKU7FFCOsrJV8gtwVuPHMGo36TMDpLQvxa4NfUaFWQ/g626FhMFm6uONmTIWwqilsZCRsuyrw3nvvYcGCBXj27Jm5i8eYCFML7AGebqjeYSD+/nY7LlybgIj4QHSp7VsohY3dIE2Hh4cHfHx8EB4ejuRUNWKVqTmu3cmYEQkQn5yGlHQ1+gwejmq162H2pJEY1as95i5fj6ED++LKv2Qh5TG/9JBvZa1OnTr52l8ikeDatWv5vQxTDPDMZMknwFWB+kGuCOvcE9d+2If7325G02a7UMXHUTfQFnXMGlN2CHJX6BZFFcyYMQMLFiwAABbwSgmmVtY61PSGfNpUvPnzPlz4+gvUn7MEl0NjdG2pIG2GlTXTo9VqoUxNh0YrQVgUv8uWiL+LHX659QJ2NjKcvh2BIJ+KmLDuEE5sWog5E0fg2p+/o/vAUQB4zC9N5FtZc3Nzy1MH+fz5c9y5c4c7UwuGff5LB6npGrSp6oPkd+ZjzdTBeHL5Z/i3ekv3O1vWGFMR4JpVsFYoFFi/+yiuXv6DBbxSQFGM2QGuCgx6pTouT5yMjetWY/TEabDz8NIlRiiossZ9mumxs5ZBKYVFx1SWZVLTNfBytMXTWCVUag2exCpR3ccVqzbvwJ/f78U7M2bg1E8/AuAxvzSRb2Utp1T9AClpK1aswGeffQaZTIahQ4cWtGxMEcNukKUDYe0Y8HpnnDzQHr98+TGqNW+Hp7H+aBjsCkkRx6wxZZMnMUqdZaRXt45o2KwVC3ilDFP3GR36jsCnn6zHj/u3YuWqVVmstPmBPUNMi3iWdjYyuChseNLFQglyV6CWvzNsrKVQpWsg0QIyqQTBHvZoOXUqntv4Y9P8yQCAiw9jUJO9HUoFJpPUX7x4gWnTpqFixYr45JNPMGDAANy+fRtffPGFqS7BmBhW1koHImFBo3JumDhrAZJiIvHLgS8QFkXCNFvWmKKgJKSgZwpGUSWZqFXBD/2Gv4Wje7cDSdGFSrTCbpCmR9Q7P1fLJcBVgR71/TGwSRBq+zmjVoCzbgHtY1eewqtSbby+aBca9pkAjWcV7p9LCYWW3p4/f45p06ahQoUK+OSTT9C/f3+dklaxYkVTlJEpInhmsvTR/ZUG6DHkTVz5dgfuPniAiw+jcPJ6OABW1hjTYpiCnRW30kVRKWsBrgp8/OF8ODk6YtrMdwu1ODYra6ZFPEvOBlkyEEpbj3r+CHBV4PKjGJy7H4kX8Slwd3NH+wFvwd5Bwd4OpYQCS2/Pnz/H22+/ncGSdufOHXzxxReoUKGCKcvIFBFpaWmwtrY2dzEYEyAWwgaAnRtWwNHJBSe3rca9F4m4/SwOABCVlGrOIjKlDMMU9CVh7TAmbxSVAiT6qHi1FRYvXozD+/fi7PmL2H8pDMeuPs230sYxa6aHLWsllwcvExEWlYQnMcnwcbaDTCJB26pe7AJZSsh3TxceHo6pU6eiQoUK2LRpEwYOHIg7d+5g27ZtKF++fFGUkSkilEol7O3tzV0MxgQYWjYcHR0xYtpc3Lv4M17c/gNhMUkAgHsRSWYuJVNasfS1w5j8URRCu2EfNXr0aFSpVh1b1yzCP09jcfL6c1x+FJOv87FniGlhy1rJJl2thbPCGnbWUsikEtQOdEFqusbcxWJMRL4TjFSsWBEqlQr16tXDnDlzUL58ecTExCAmJvuOtkGDBoUqJFM0JCUlQaFg4ao0kDml+rRxo/DDoS9xbvdqvDZ9FQCeLWVMj2GSEVbUSg9FIbAb9lHPE1IxduYCvDN6AHwvnUHlpu2AfF6S3SBNDytqJZe21bwQq0xFoJsCvs528HSUs6dDKSLfylpKSgoA4MqVK+jXr1+O+4rOVK1WF6x0TJGiVCpZWSslZE6pLpFI0Gfy+1jyZg9cOr4HAFDNz9lcxWNKKYbWElbWSgdFpQAZ9lEX7keiTrMQVGnYCjePbULXrp3RsJxrvs7HypppMXyW/FxLHo3KucHH2ZYnz0op+VbWtm/fXhTlYMwAK2ull7AoJfwqVEPVkF64/ssRAICPM9c1Y1qMLZLNlB6KSmgX7WbpitUY1OUVvDx3EGg9DxfuR+ZZ0OSYNdOj1WrZulaCMbYOJlM6yLeyNnz48KIoB2MGOGat9BLkrsCNZ3EYPfU9LPjzFJTxsXiZoDJ3sZhSBgsHpZOiFth17aaSB06MnYwN61YjtXxLtG5UW/d7bnDMmmlhy1rJg93Qyw48LVVG0Wg0SElJYctaKSXAVYEutX1ROdAXnUdMAwBEp/CMKcMwOSORSIrVutLg9ZGwd/XC8c1L8DgqCS8TVXnKDMlukKaHrWolC14ypezAyloZJTk5GQBYWSvFBLgq4OkoR5+BwzB11Rfo8EozcxeJYRgmA00r+6LPxHl4/M/vuPbrD3gWm4wT/4TnqrCxsmZaOBtkyYOXTCk75NsNkikdKJU0ELKyVroRnXjr0f3ZTYJhmDxRnOttNSrnhm3zx+Hm2WM4tnkZUrxqon3dCrkmreGYNdPD66yVLNgNvezAPV0ZJSmJ1txiZa10w+tfMQyTX4rKuiIWxs5sNXsSo0T7Ue8hNUWJm0c/weNoJWyschZP2LJmWtiyxjCWCytrZRRhWfs3OjVP8QEMwzBM6acoFaDsYmzCopSoVbk8Oo6agVtnv8HzW5dw5k4Etp9/iGNXnxodozjBiOlhRY1hLBNW1sooQlmDlS0HpzIMwzA6isodLrsYmyB3BQLdFBg9egxqNW6Jw+vmIy4+ATefxSMsSml0jGLLmmnhbJAMY7mwslZGEcqai5MDB6cyDMMwOorKwpKdW7bY3qicGxas+BipSXE4vXsdYpNVSNdojY5RHLNmenidNYaxTLinK6MIZa1VdX+OZ2IYhmEAmNeqEuCqQLN61TFuxjycP74XcQ/+wfWnsfjnSVyWWDe2rJkWtqwxjOXCyloZhbNBMgzDMJbG5UcxcGv0Gvyq1sOJzQthL1Pj3L2XWWLdOGbN9LBljWEsE1bWyiiPI6IBANEqMxeEYRiGsSjMmsJdC8Sr1Og3bSlS4yLx1+FP4OEoR1JqegZ3SLasmRZ+lgxjubCyVkZ5+jIOEokELxLV5i4KwzAMYyFIJBKzWlcalnNFq0oeqFOrOoZNnYPz3+xB6qNrgJayRgpXSI5ZKzpYcWMYy4J7ujJKemoKbGztILeWmbsoDMMwDAOA4tZ61PdHVW9H9B06BnWbtsaaeW8jMSEWylQ1LofG4ML9SKSp2Q3S1LAbJMNYJqyslVEiYuJhI7fD09hkcxeFYRiGsSAsQWAPclfAwdYan2/dhmRlEtYsfA+PY5SABFCmqpGals7KmgnhBCMMY7mwslZGUSUnQ2Zji7vPE3hRbIZhGEaHWWPW/kOk8/f190e7Ue/hyulvsWvPPtjIpFDYyCCTSlipMDGWoKQzDJMVVtbKKM42Gtgp7BDoruBFsRmGYRgAlmdVCYtSonOPPvCr3xa/7VqJExdvIMhdAZkEHLNmQkS9s8LGMJYH93RlFJkmDZ6uTghyVfCi2AzDMIxFEuSuQN1AV8z7cA0kMit8s3Eh/gyNRkqaGteexOLP0GhzF7HUYAkWVYZhssLKWhklKSkJLo4OaFHJgxfFZhiGYXRYktAu3CHrVgpE90mL8OjaeRzZsx0pqelITdfiSliMuYtYKmDLGsNYLlbmLgBT/DyJUeJxRCyk1nJzF4VhGIaxIMyduj87gtwVaPrKqwi72h8HPvkQVjIZ5NYy1A9yNXfRSg2WWO8Mw7BlrUwSFqWEUqkErFhZYxiGYSyfAFcFBjQJwrLlK+EfEARlUhIqezuhUTk3cxetVMDZIBnGcmFlrQwS5K5AmioZ7i6O5i4KwzAMY2FYqoUlwFWBKgEeaD9hKaRW1ngcl2buIpUqeJ01hrFM2A2yDBLgqoCVNg0eLk7mLgrDMAxjQRi6QVqihSUsSgkrz/LoNHsr6taubO7ilBrUGuBZbDJS0tSwt8B6Z5iyDCtrZZAnMUpExSZALbU2d1EYhmEYJs8EuSvQuJwbyns2QduqXuYuTqkhVa1BWroGKWlqcxeFYZhMsBtkGSQsSolEpRLPEjW8IDbDMAxTYngel4J0jQZtq3pxvJoJsbGSwkomgdyKxUKGsTT4rSyDBLkrkKJMgqODPS+IzTAMw2TAkt0gr4TFIC45nVP2mxhrmRS+zrawtZZZZL0zTFmmTChrKpUK7777Lvz8/GBnZ4emTZvip59+yvPxBw4cQPPmzWFvbw8XFxe0aNECv/zySxGWuGgJcFVAnaaCj5szL4jNMAzD6LDU1P2C+kGucLaz4pT9JobXWWMYy6VMxKyNGDEChw8fxttvv43KlStjx44d6Nq1K06fPo1WrVrleOzChQuxePFi9OnTByNGjEBaWhquX7+Op0+fFlPpTY9Wq0WyUomawV68IDbDMAxTYmhUzo3dH4sIS7aoMkxZptQra5cuXcL+/fuxatUqzJgxAwAwbNgw1KpVC7NmzcKFCxeyPfb333/H4sWLsWbNGkybNq24ilzkpKSkAAAUClbUGIZhmIywdaXswQoaw1gupd4N8vDhw5DJZHjrrbd022xtbTF69Gj89ttvePz4cbbHrlu3Dj4+Ppg6dSq0Wi0SExOLo8hFjlJJcWqsrDEMwzCGWHrqfqbo4HXWGMYyKfXK2pUrV1ClShU4OWVcU6xJkyYAgKtXr2Z77KlTp9C4cWOsX78enp6ecHR0hK+vLzZu3FiURS5yWFljGIZhzMmTGCUu3I/kjMQWgqFizko6w1gWpd4NMjw8HL6+vlm2i23Pnj0zelxMTAwiIyNx/vx5/PLLL1iwYAGCgoKwfft2TJ48GdbW1hg7dqzRY1UqFVQqle57XFwcACA+Pr6wt2MSIiIiANAsmqWUiWEYhjE/arUaajWttZWQkFBkY8St0Cgo09RISkiAk8y9SK7B5B21Wg2VSoX09HSkpaWxbMAwRYx4x/JkzdaWcipUqKDt0qVLlu3//vuvFoD2o48+MnpcWFiYFoAWgHb//v267Wq1WlujRg1tQEBAttdcsGCB7lj+8Ic//OEPf/jDH/7whz/8yfx5/PhxrrpMqbes2dnZZbByCUSSDTs7u2yPAwBra2v06dNHt10qlaJ///5YsGABwsLCEBQUlOXY2bNnY/r06brvGo0G0dHRcHd3N4l7QXx8PAIDA/H48eMs7p2M+eH6sVy4biwbrh/LhuvHcuG6sWy4fiwbc9SPVqtFQkIC/Pz8ct231Ctrvr6+RtPsh4eHA0C2D8nNzQ22trZwcXGBTCbL8JuXlxcAcpU0pqzJ5XLI5fIM21xcXApS/BxxcnLil96C4fqxXLhuLBuuH8uG68dy4bqxbLh+LJvirh9nZ+c87VfqE4zUq1cPd+/ezeJ/ffHiRd3vxpBKpahXrx5evnyJ1NTUDL+JODdPT0/TF5hhGIZhGIZhGAZlQFnr06cP1Go1tmzZotumUqmwfft2NG3aFIGBgQCAsLAw3L59O8Ox/fv3h1qtxs6dO3XbUlJSsGfPHtSoUSNPpkuGYRiGYRiGYZiCUOrdIJs2bYq+ffti9uzZiIiIQKVKlbBz506EhoZi27Ztuv2GDRuGs2fPZsjKMnbsWGzduhUTJ07E3bt3ERQUhN27d+PRo0c4fvy4OW4HALlZLliwIIurJWMZcP1YLlw3lg3Xj2XD9WO5cN1YNlw/lo2l149Eqy39KyCmpKTg/fffx5dffomYmBjUqVMHH3zwATp16qTbJyQkJIuyBlCa+1mzZuH48eNISkpCvXr1sGjRogzHMgzDMAzDMAzDmJoyoawxDMMwDMMwDMOUNEp9zBrDMAzDMAzDMExJhJU1hmEYhmEYhmEYC4SVNYZhGIZhGIZhGAuElTWGYRiGYRiGYRgLhJU1hmEYhmEYhmEYC4SVNYZhGIZhGIZhGAuElTWGYRiGYRiGYRgLhJU1hmEYhmEYhmEYC4SVNYZhGIZhGIZhGAuElTWGYRiGYRiGYRgLhJU1hmEYhmEYhmEYC4SVNYZhGIZhGIZhGAuElTWGYRiGYRiGYRgLhJU1hmEYhmEYhmEYC4SVNYZhGIZhGIZhGAuElTWGYRiGYRiGYRgLhJU1hmEYhmEYhmEYC4SVNYZhGIZhGIZhGAuElTWGYRiGYRiGYRgLhJU1hmEYhmEYhmEYC4SVNYZhGIZhGIZhGAuElTWGYRiGYRiGYRgLhJU1hmEYhmEYhmEYC8TK3AUoC2g0Gjx79gyOjo6QSCTmLg7DMAzDMAzDMGZCq9UiISEBfn5+kEpztp2xslYMPHv2DIGBgeYuBsMwDMMwDMMwFsLjx48REBCQ4z6srBUDjo6OAKhCnJyczFwahmEYhmEYhmHMRXx8PAIDA3U6Qk6UemUtMTERq1atwsWLF3Hp0iXExMRg+/btGDFiRJ6Oj42NxaxZs3D06FEolUo0adIEa9asQYMGDfJcBuH66OTkxMoawzAMwzAMwzB5Co8q9QlGIiMjsXjxYty6dQt169bN17EajQbdunXD3r17MWnSJKxcuRIREREICQnBvXv3iqjEDMMwDMMwDMMwZcCy5uvri/DwcPj4+ODPP/9E48aN83zs4cOHceHCBRw6dAh9+vQBAPTr1w9VqlTBggULsHfv3qIqNsMwDMMwDMMwZZxSb1mTy+Xw8fEp0LGHDx+Gt7c3evfurdvm6emJfv364dixY1CpVKYqJsMwDMMwDMMwTAZKvWWtMFy5cgUNGjTIklKzSZMm2LJlC+7evYvatWtnOU6lUmVQ5OLj44u8rAXi22+B0aMBjQaQSICPPwZeew3Yvh1YtChv55BIAK1W/78hs2cD06frv6ekAA0bAi9e6LfVrw989BFQvjx9/+IL/bUlEtN8xLmsrYGKFYGaNYFatehv+fKATGb8vmxsAKtS9Iqo1cbvtbCkpwMdOgBNmwJLlmT/zBYvBjZs0LeXli2B996jNmBjA2ROXTtlCrBvn74epVIqf9u2wNSpQKNGpr+XgnDkCDB+PN2XVKr/yGQZv0ul9Gz8/IBKlehTuTL9rVABsLUteBlCQ4FRo4Du3YHhwwF3d/1vU6YAX30FBAXRO96kSaFvOQuPHwOtWwNJSXSfU6YAc+Zk7RNyY+1aYPlyek4yGf11cAA++ADo2VO/X1wc3Ud8PBAYSMfVqUN9DEDvuo2N/m9e2bqV+i2JRF9/hvUIZN0mk1H9dexI70GlSvm/bwBQqah/fPmS7lt8rK2pn6pdmz61agHVq2dtL9HR9C4K5HI6XioF7OzyV5bISHqffXyAHTuonZY0Xn8dUCqBwYNpXHNxyb5vUquBZs2A8HBAoaDn26sXHWf4LmXm9Glg0CA6Hsj4rhv2W4Z/AarPceOAHj1yH2Oio6ku4uKorRm2TamU2vegQTTW5iFRgUXzyy/A0KF0H61a0fvUrh3g6Vnwc546BQwZQnJO5nfa8K+XF9VL5o+fX9axqSTw0UfAkyfAG29Q2y6qe4iOBl55hfrAYcOAbt1y72/atAHu3qU+ytaW+vA6dehTuzZQo0bhxkNjpKUBYWE0VlatCuSSfdHSKEWSqOkJDw/HK6+8kmW7r68vAErJb0xZW7ZsGRblVdkxJ//8AyQmApMmAZ98Apw7B9StC2zZQi/b0KH6fdPS6GMohGi11MlpNPRdIqGXz9GRlK5LlzJeLyoKuHmThK5y5eh8X38NNG8OLFwIdO4M/PgjXbt3b71Qr9Vm/eRnu9iWmgo8fAj8+isQE0Pb7eyAevVISGrUiO7f2pp+s7UFnJ0BJ6f8CXyWSHIyEBEBuLmZfkBPTATOnKHP//4H7N1L9ZuZ8+fp+l26UN0fPw60aEGD8ZQp1A5sben5W1vT+apUISE4PZ3aV2oqcOAA8OWXdOzUqdRWzKlUX71Kz3fkSGpnGg19tFoS4sT/AH1//hw4exbYuZOOA+jeAgJoMqFSJaBaNRLKa9QA/P0zvneGEySC338nwfHcOVKS+vUjYbB5c+DkSaqP1FR6ZosWkZJsSsU9NBR49IgURqUSmDeP6mzBgvyd588/STkbNoz6C5UKuH+f6njZMmDWLLr/R49osB87lp5/69akpM6eTe07IYGerUJBgoB4p/NyfZmMhN/UVL0CrlDQfQllSKWiNizq+N49aovp6XS97t2pDlq3zvtzDg8HbtwgJcPfn86rVtM5X74EDh0CVq2ifWUyUqCE8lajBn03FGpjY+kerK1J6XJ2zmstUFkePKCPGBOGDMn78ZbA8eP099Qp6uc7dgT696f+x8kpo/AaE0N1378/vYe//UZtWSolQbR3bxoPMz/Dy5dJiZo9W/+8xcSgUAQA/fur0dB+Fy8CffqQIjBrFrXjzMJpairwzjvUZ96/D8yYQe0wNpbOK5TxiAh6NzZupPduwoS8t3dTkN1kbUG4coXe+169qD/bto22169PiluHDlQf+RmPr1yhZzZvnr4/1mj0/4t37Plz4M4d4IcfMk4o29gAwcHUh5YvT31DmzaFv9eiZvNmajdr11I769WLFLfWrU07Xj5+TP3WjRv0zjk4UP/XpQu9c5k921JSSE544w1SmlJSqJ85dozKCtC7ExxMz7tcOfr4+gKurvQREy9iAkStpj4/Lo4m8F68oHI9fkwKq/grZFV3dxo/3NxM9xyKGFbWciA5ORlyuTzLdtv/OtVkIWhlYvbs2ZhuYFES6TktDrWaXqyhQ4E9e/TCwY0b1EmOHEn7paWRkmNjk7WTTE/Xz/ap1fSyODuTMJqURL9bWZHgFBVFx3TvDrz6Ku0/aRLw7rs0EP31FwklderQNoExRQzIaDkT3w3/ZodWS9e5fRv4+29SKnftosHOxYUGhK5daTbq+XMayF1d6b6KcxA0Ja+/Th3V4sU0a+zqaprBFdALsKNGkbJdrx5ZKP6L89SRlETXnjiRhN1Jk2j/jz8mBb5NG7JQ1alDbSYykhS5oUPpWJmMBJpp04CffgI++4yEKz8/Eu7HjCFlp7hJSaFOf/JkEqayQwgFhgLCixc02xcWRgrI48c0mbBrFwlrAAmWwgonPpUqAd7e9LtEAty6Re/m+fNk6du7F9i9m4T5R4+At94ihXjRImD+fHruBw5kHUgLimgDAwbQIOvjQxMwTk5UX3klLY3ub84c6nNSUuh93bWLFMybN0kBfPyY9n/7bdp/0yb6/ccfqV20bk2Dc0IC9Tve3nlr76mp1J6mTycBz8WFzmFjQwK/RkP3lphIfYhKpZ/8iIgg4f3PP8lrYfNmum7fvsCbb1K7zomkJPor3gUhvMfE0DN1cCBB5MYNmmgTn48/ptltgNpFmzZkta5Zk9qjVErKl0RC9ZEXRB/7yy80qTB0KPDHH8Dq1ZbTB168SErV2LFZZ/KFpWvrVuoTjh0jQfLYMXoGbdvSc+7alQQ38fzGj9cL4uHhwDffAIcPkyI+cyYdM3o09UtSKR3n7U0K18OH9Lw1GmoX4p0QQqWYhEpKom1Xr9Kk0zvvkBK+YAH1oUK5v3ePxiTBBx/QfT18qB9z3dyoL3//fXq3p08nz5itWwvuefDjjzT+e3qSQqhW00RFfDx9EhL0/4vvajXdu709vTMBAfQpV46U/Xr16P/c3sHERKoPcd9PnwI//0yfXbuAlSvpfevUiayeXbsCHh65n9PNDZg7N+/PICmJJqAePqSP+P/oUVKATp3KuL94RpZk2UxPp7bati0pvseO0aS8pye14zfeoHZc2PdZjFM//kh1f/w49X/799P2evWA9u2pHK1akYwI0HjduXPGcyUmAtevk1x2/z4982vXaFJfyI95QS6n9ufnR38bNKB+28+PyhgdbTn9WB5hZS0H7OzsjMalpfznamOXjalXLpcbVfIsDmEps7WlwUSrpZdDq6WXSiCTUcOOi8vqjmA4QyOT6YUbrZaEjNBQOjYlRS9gOTlRZ2hjQ53cypVA48bA0qW0X9++esuXmNk2VMTE/5mVOEFmq4NWm3WQsLamQaRhQ+o0pFISeH/4gT6HDtG99u1Ls6oqFd2/uzt1yKaySpw+TQP95s1F69Z3/Topnteu0aDfuzcNcqmpdC+FsRwKoaRePRocli6l5/bWW+SKIRSYpCTqONPS6Bmq1dSJd+hAHf2GDSTst2tHik98PLVNlYoEEoDaR2QkzbR++ikp3AcP0uC+fDm12xEjyKphbOBMT6fjhYuctbXe3aygpKbS+VQq+hi6sBnOrstkWduNiwvNLgqEZS41lRS4O3dIaLt/nwawr7+mawB0f0Jxe/KEBBIXF5pkGTqUlL49e+hcbm70Tr33Hj3zgQOpvR05Yhq3SEM3MJmM6i8piYRHe3tqC3lBtKXUVDqX6E9Gj6bnNHUqKSv9++ufn7he06ak5L3+OtW/cMOMjqY2mBdFRdSlQkF1ERdHbS8ujupFoaB6dXEhBSE6mp6rRELCQNeuJOy//TbN3J46RcL+xo00+fPWW1R2Y0q9Ukl/vb2pnQtPBUA/I+zkRNbS5s31x2m1NDP944804XXxot4iERBA9duqFdV37do06ZTXiZrERHrPmjShZ3/rFrnUWoJQum0b8Pnn1MesW0cCqLgvofgqFOSeNXYstaEHD0gBPXmS3hMbG1Jsq1Sh/VUq6ietrakt9OxJroo3b5IAeuwYCaFBQTRu3L1L7UOMRcJ9XvSnWq1+giY9nSYtNRp6J5o1o35s1Ci6j7feookG0VbEGLhyJbU5W1t6FwBqB2lpNEGQmEhj1eefk7I5Zgy9C/PnkxKXX/e3PXvoXj089BY8e3tqN87OdC1HR73XiaMj7adU0icqipSsu3eB77+nSQ2AnlObNtS/t2tH1uDM7TAhIWPb8vMji+6gQfTc/v4b+O47Kt/w4XTdZs3ovevWjfoIQ/kAoHfU3p6ek8DQRVX0WYZ9s709TXbUrJmxfJMn05idmS+/pPpbtozefUtwmxQT6c2bUzubMoXGkjNn6Bl+/jn1Y6+/Topbx44Fcz0U41F8PNVX//5UX3FxNJly7hw9n9Wr6blUqkT7u7rqZVDxsbenttusWVaZLj2dJtBiYuiTlqaf9NRq6VhbW3r3xCSD4bgkxnpra711ugTByloOiEySmRHb/Pz8irtIpsVQIBAK2bVrJNiJFwrQC03JycYVH0OkUurEHR3pZZVKMwpAAP2fnk6DgXihRo8GQkJImOzQgQbDzD7/QMa/xpS1nJQ3Q9dItZpedpWKyqdSkfvSW2+R5efff0nI2ruXZu1feYUG94YNaYByd6fOoSDWKeGSKZcDFy7QTHyrVqSwCWumqVGrKXbjyRNykzl7lmZyRacmBl07u/zfkxCwra3JVWHNGupwly+njnr/fhISk5L0M+A2NhQjkJhIHWeXLjSAC8tIr160n7d3RtcjhSKjoNu8OV1rwQIagL76ioSVqVPpnH370oxeUhJZUBs00A8uwo1XKG1OTtTZC0Urr89BtG9XV7o/pZLeLTG7bijIGQoImeMqBWIf4XbTubN+P7Wa6vDePfrcvUuC5L17NMAZPpvu3emTkED3KYSmwECyTI4ZQxaoTz8tfLsTg6K9Pd2/kxNNQiiV5I5pb0/tLy/PUqOhwVgup+cqJnZataL6HT6cFDEgY9vw96cYx59+ovr/6SeyhnTvTvcul+uVn5yuLwZ1Ly/6npBA13n+nKxbArmcFDRHRypvfDwdJ4TNOnVICRg3jt7zgwepn5s+nSxtkyZRPycQgrinJ137+XP9JIJQ1owhkdC9v/46CbaOjiSg/vorvU8//URKOUDladuWhNu2bbNXukSfGRdH7W3wYHLN7dmT3tPvvqMymhO1mhQxPz+afOrYkSZ8qlTRK2t2dvrxSyaj7xUqUD//8iUpbidOkOAqkVD9xsToxyVra3r27u5Ub+PHUz/y7bfUvymV5CUi+oDYWKoz0dYkEuoL0tKoPMJFUqWiv3I5CdIrVpCQu3w59WmjRpESCdDEi7CAK5XUR8XE0L24utK9Pn5M43adOlS+Dz8kS9vFi6R8icmuvKDVkiJ18CB9F/2Y6CtFzJy9vd7dU0xKiX5A9GFaLfDsGSlZly+T+9uMGfS8fH31StYrr9B9RUfTfT15QtdUq/X9p0ZD7XXAAHpWL1/SOHb6NMVKz5tH71NICLXt+vWpfOHhVDePHmW9V0NlTdSboSu+jU3G/tnbm7whMstBYWFU1nfeoXdj507zx0Slp1P5RZtxdNT3SRMmUJs5dYosYbt2Udvv1o28VDp3zrsyIyxr1tZ0DSsrehZyOfW9nTtT+3/8mKzzf/xB17KyIuOAsfwCAmMT71IptXXhzipyLgD6tii8cIxNqhvKjSUIVtZyoF69evj111+h0WgyJBm5ePEiFAoFqojZuJKK6IDj4/UJHi5fJoE2swApOuboaPpNoaCXQQgRmV9sOzvq5A1nasSApdXS746OGYVLX18S7osbobilpVHHk5REyur06TSTdvYsuZWMHEmD2PDh5Ibh7U2dRn6tUn360AC2eDENJBUq0IA/ahQNtOvW5S5UFuQeAwNJqdm9m9xuLl6k761bk7UpOpo6UWdnqu+8Wg+FsubsTAODiHesW5eU78aNyRfdUFkTHaqYnU1LI6GmXz8Sun7+maxIDRuSwKhW6xN0iIFVKFRCGBs8mD4PH5KgcewYKdxeXjQxcPMm7Vu7Nj3vNm3of4Dq/elT/fllMmqbdnbUhnOqD5VK7yYnfOrFTKAQODLHR4jZdvEBMk4qGG7LPNng6Un306xZxvoFslqkraz0M/3CRUsk4di2jYTEUaPI4rB4ccFdY8X1ra31ligHB5rdVyrpnbG3z5gkxBiiT4qOpv7B15fOHR9PxwcHk9V77FgSmkT/YugaPWgQtaFp00ipO3aM2rmtLZ0vJyEkLU0vkMrl9I4/e0b3YEzZEwK+QqF3rxGJIOzsaHtaGgmPLVvS+374MMWArV1Lz2PaNIolFAqGoyP1K6mpdD4rK/pra5v7zLeoPzc3sgj16EH1fe0a9WN//EGufZ99RmVs0oTehVdfJSUh8/0JV6GnT8nKcOoUuZ+1akWKjjkFUo2G3oVNm+jeVqyg+L1p08hyDOj7G2FZdXWlScfERHquffuScKpUUt0YxtqKyUzxzghFrFUrUgRmziQrRf36esXO35/6g6QkageiH/Dy0reF5GT9OCPCBBQKah+7d1N7/egjivsGMipaGg3Vkaur3qrr5ETXiYykc3p5UXtv1ozehVdeIaX9v1j7fGHY5jUaKr/4+/Jlxnh1qTTjpIJ4zzQaUhCqVqXyJCeTBfjcObJwbttG9dSyJSlpjo56mUQohsYmbR0daewcOZLOee4cjRsnT5LyIdxdHzygccaYwmoYv5aeTvUs3O2EwubgQOWTy2lMi4ykSZFPP9VPdiQmUtvZsoXaU+3a9LvwADAHajX1Fx4e+klRmUw/4eTvT+P02LFkof3hB3Lz7NaN5J/Jk2lsMJygMoZQ1tzd9XG9hmO1kPXc3cn7ZswY/RhnLO9AdoqUYRvIPOlpiDi3Wk1lMxx/hZJtZ1fikseVrNIWIeHh4YiLi0PFihVh/d8A1adPHxw+fBhHjhzRrbMWGRmJQ4cO4bXXXisZro45IQRgGxt6qdVqUtaMzYBbW+tjZJRK6rCkUuoExAyara1+cLS11QuFAiHUa7V0vvxmKCsqDGdiAOpUhPIQH0+K2auv0uzgtm0UT/fJJzQ7/sYbNAhmDljPib//pgGkc2cSqsqXB9avJ8Fp4kSKQ/n669x98fODqOvAQJrdb9SIhPNRo8ht8L336P6TkvSCsa9v3pRGw9gMHx8SouVyusbevaQYTpxI+4g6N3xWhq5DDg4k9PbuTc9duBcKpVgIOioVtT2tlraL+pNI6Hm++y5Zdq5eJavCsWM0I9uwIQlY27aRsOzsTHXbrRspb9bW+o49JkbvMunmln3Mopglzxw/KQb7vJCThTinxDmZz2E4UAm3q5QUvYudeEcVCto+cyZZJpYsIUFpy5aC+fKLNiCTkVAkl5MA4OBAs/zJySS4fPstWc6zIy0t40SQVErnS0jQC2hSKSnjIvbBEFEHHh4k+PbvT5at3r3JkjVrVs6Z5YRlTZzHwYHa9NOnVLbs3nGplMpmb0/vUGwsPfOEBDqfrS2dy8mJLAujR9OM9t69euFfTByIe/Tw0LvNpaRQGfz8jPebOSV5sLUlIdPDg2a67e3JlfTaNbLqb95M9W9nRxM3r75KE3YAtSPhMvzyJT27X37RW8LPnKEymQND4atbNxLMN22iGL5PP6V9xGSgqDdh+RQKcUIC1ZVEQn1jQgK1XamUnr2Njd5tWyhICQl6xbljR701HaC+S1iYxHuXkED1bm+vL7uYIExNpXacmEj34+xM429ICE3aPX5s3EvE3Z3ak1DYrKz0VrYnT6iu27cnBaZDB6rXs2dJQM/Lc5VI6LkIbwMhHGc3HmT2HjDso4R8IHB2pvrq1o2237tHyuSPP5Lbd8+etI+hQC/cSDM/C8O+sWVL+sybR+37zBmyut28SRY8MZGVGcOskMLlUyaj66Wm0hggZJa6dckKO306TawePEjvblIS1Ue7djR+jxtH483Bg2TtNcc7Iia+vLyovSQn09ielKTv5+Ry2s/eniY4xowhV+etW8lKuGQJyQbjx2cvrxnGVovEcSqVfqxOScloIRV9lKHiBWSfcyBzQq3M46BhAq/MFjapVD/ZKuQE4QrJMWuWx8aNGxEbG4tnz54BAI4fP44nT54AACZPngxnZ2fMnj0bO3fuxMOHD1Huv9m1Pn36oFmzZhg5ciRu3rwJDw8PbNq0CWq1umRke8wNkcrdxYUa87Nn1NGLgdoQw+B04fObkkKDgqMjvZixsfqZYBGnZoiwrDk75z3g31wYzqoJpa1hQ+qsHz+mDvj990m4ffNNmk3z9s6bz3dKCilJfn6kMHh7k4vG66/T7GOfPjQr+v33+liKwiLq2taWBmwrK1JYjhwhZerHH+lvmzb6eMOYGOroc1NCDd0g3d3pOuHhdB5vb4pha9qU/PkrVMhd6HVyoueekEADpbDWiMFCDNxiJlTEE4mZQxFXJJHQQFq/fkar0aBBdOyVKzSY//ADPQeFggbbzp1JCBMudikp5JIWH0+WhMyWVOECVRgf+LwmxykI6ek0eIokAYbPyd2dBmg3NxJynj0jy09+Y5KEZU0Mkh4eVP8REXSulSspZqJHD5r5bt3a+HnS0qjuDAU/hYLqIiaG+ioXF72bTUoKtYvslJXu3cmCPHs2uecKlzfDmC9DhHuyIU5O1L6eP8/ZHRHQK20ODnSu5GRqx0JoF65W/v40oz1sGCk/u3bRB9A/exsbUo4eP6ZtiYlUP/7+WfuZ3Nx6bG2pv3n2jIS12rXJStmvH9XVgwdkNTt1iqyRr71Gxzk7U5tRKOgdFK6e33xD+7RtS0JxQaw2hUUo8y4u+knDd9+lNrZ6Nb3bwlXT2LsprEbOznR8dDS1XSFg2tvT+y5SvtvY0Lb4eLK+KJX0XaMhRdYwFlC4Cdrb07uV+fqGE4SOjvoxJjaW3oHAQOqPk5NpbHBxyWrhEG649vZ0feEaaWNDE2YpKTRxde4cWdc6dSI3xNwy4In79fLSWxTF9YTCJDwJDNtdcnLGGCTAeH9maBkBqB2OHUsKQVQUnUPEFBlb9kCcw/A3wzqWSMhS3aoVWfbFpJHozw2VSTGxJRRntZr6StGfiVhBEbqRkkJj81dfkTLTsiUpNomJ+vpxdSXX/zfeoD6venWy+r71VvHGSQmrrUSScZJC9EtxcdSGhQVOKqU26OtLY/Z779Ek8qxZ1Hd++CFZ4jLfgwgrEJNSok0D+rFaWLcMPUwMPUuMTURmnpTMbFHLbokcQ1dIYZUtBZQJZW316tV4ZOCvfOTIERz5z4d/yJAhcM4mpbFMJsP333+PmTNnYv369UhOTkbjxo2xY8cOVDVMClBSES4/Tk70Ml+8SNsbNsz5OFtbGiTkcr0ALQKQDYWSuDjqfEW8gFDW7O1zzppnSQiTuZ2dXmCUSmkgnTKFOrP580kAnDCBXDI8PHJ2IUxOpmcwdizNZonZnogI6ihPniSFolkzsrAZWT4i3xiusSYsYFIpWR6aN6fOedAgEt4WLKA2ERVF++Zm4RP1Ks7v4kLP7flzfcB4nz4005tX10oR+6hQkHBpKEALa7Bw7XN11WfjErPUIuBYzJ5l9oO3siJXj6pVSVkR/vs//EAWGBsbmt3u0oVmpl1dqe7j4uh5GJ5PuEFa6qAgXEaF4Ciek0gE5OBAs8Du7hQc3749tUEXl7xfwzCQG6BnIdpNRAS1p7Vr6R3p1o0EfGOTQqJPSknJ+EydnanM4nexZIhwu808a2uInx9NFHTponf7nT6dYnoyzxanpRmPRRVjRF4D8IUbpVAGhAKQmKhPxCD26dqVlMq//iJlylAoF4qfSkX1ERtL75WfX8ZJg5wsawI7O1L0wsOp7l1c6N0KDyehfsYM+ohlHgB6zr6+VIdqNd1LcjLVweHDZLEUFjbheVFcCAuQsIpFRpKwWakSWQujovT1ldNzEZNBTk60n7BIa7VZFXehHIoU+tHR+sQz2bW/3Pq8zGNMXBz1NcLSJpIiRUZmdcUVk6gKBR0XHU3tTCxfkZpKStePP5Ly8vrrNDmQF9d9JycaJ4R1PjGRric8MCIjM96b6IszC+ACQyFcCO6G8eMajd4C7eamz2SaWbkzFuebE/mJrRQeCSIsQqnUKzaiPYj47l27KMPk4MF03w0a6MdZiYTG0g4dSNkZP56SbHz6KbnqFgfZrasqxk4nJ731NzaW7lO0RTFGzpxJLuwff0weOJ9+SglwDGVEw5i1zIixmik0xajmm4/Q0FBotVqjH2FF27FjR4bvAldXV2zduhWRkZFISkrCmTNn0MhSFuMtLCJDjlyuD8R1dibrR05IJPpsaIZYW9PxAQHUUSmV1JlFR9MLLSwwpl7ssLgQMS/BwdTRBQRQbMGPP9JM9ezZpPh8/rk+/sQYKSk0EIk4FHt7qgM3N/0s2L59FAzcvj118oVFzEILZDISrvz86DqbNpFA+8MPNFt+8iSVMSLCuLuZIYZukAJnZ70FLyaGOn9h8QoIyLvlxtpa71qUHeKZiToJDtYnxImNzbhQcFoaPXchZLm70zG1atHM5969NPs8bRrd+7RpZE0dOJD8+W/cIIHacNmOzK5zloxMRs/e35+C8Z2d9ZafTp1oAeS7d8nCKhKS5AXDmWhDNxcPD7IOJSTQs16/nvqXzp3J5SkzaWn6mBzDWVERc2T4XsnlJJwbc4MxRCiOjRvT5MeECSR81K1LdW2IsJIac8VxcSlY3yWUMvFOlC9PbdTTk34Trnjly9P7ntmCIJQ1rVZvBXrxImO7Ntw/J4SFzc6OlBkxBjx7RsJ35vhJiUT/jgjXOFtbfaKfffuof+jYUZ/+vrgQFiBAbwXz8dFbSXx8qEwqVd4micQMvY0NPeecJitEgqSgIGqXIntpYbG1pX5ZnDc+nu7HxUU/GWqsjq2sqJ4CA/WWRpE86skTamvffEOue2+/nXMZDJVOEePk4UFtNjiY2rCfn34sFO05KIj28/KiZ+/rS/uJj78/fUQfXaECfTIvQl2uHI2FwqIlEv5kF6NkSmQyem4ODtQH+ftnXOfL2lo/IW1nR4rLrFl6b4XQUHqPhLLv6krywOnT1J/Wq0exYMXxrmSnrAmEYubuTvcXHKyf+ExOpuegUNB9L15MSVNiYqgfHT1aH9snlDVWyoqUMqGsMdkgYoUAvaBds6ZpOsPWrckV4LvvaEY9MVEv4JYwX+EsKBTUiYvFdn19SQg9cYIGrPHjye3v0CG91ckQlUo/AKpU1AGKDk8kqbC1pZgFsRjr6tWFK7OxjlvMEvv60gDauzcN6PXrk+IyaZJ+Jj+nwcWYsgbQPQrFTChNEklGi5epEW5zfn56ZSQpiZ6x8NW3t6e68/XVu9UFBuqFkfr1yery/fc0yM6bR+detIisCN26kYvIzz/r0/WXFGVNIOrBz4/u2c6O6qhePcoe9/QpvcNPn+btfIYxa4bPQSolQdHdnQRPb2+K9xTrGYrlPAzPI5PR/pljy4TFVlxLLtfP+ufmBiiX610zp0+nd9PVlaynM2boXbaLQ/G2sqJ3w9NTLwh6e1MdGLu2cIETcXsuLqQghYfrJ1JysixmRrhh+vjo3ZTs7Og9/y9UIMvzFAq+sChZWemTNuzaRe2kc2eq4+LC2ASUhwe9ywoFlcXBIet+pkSMBUFB+cu4mNfzijEmJobaaG6xNmJC0c9Pb72ysaG6rViRxqnNm2kttuzIKcGD6ONF+xXJdRwcCracjUggIiaNxULfloTwSnB31y+OHRBA952aSuPz3r2ktAE0kfLoESnJ8fFUByEhFMu2fDkpPWJtSGMTLqZCuEHmBaGUCwVcTLQmJlL5HR3pHo4epbHv0CHKDrt1q34NVFMtZ8QYhZW1soyhAC8GgOrVTXf+Xr3oZd61i2aXRGrq0jADI9xPgoKog9NoaGDdtYvcg+Rysi62bk1CvRgARayViDcIDtYrbSJeQSRScHUlRWHcOHJHePfdgqeczWmWTSKha4kZz1WraEC/dIlctI4ezSgYZsZQUM+MXE6Cg5ub3s2iuJQaobSVK0fP2spKP8vu7EzP3VDwEdYPBwd9/TRsSO4fmzfTgtNr1tBAtm0bKRvBweS+JpISlDSE5SYgQJ95sVw5mmiJiaH2++BB7ufJ7AZpiFSqD3IXcX+ffkptuWNHmokWCDdHa+usrtIiq5iwrslkdA6lMm9ugCIbYFISWdW2bCG3yA0bKBnOlSv66xcXUindp4cHPXdjiQgMYwBFvKdwyY6I0Fvd8oOwDAmhLCVF74InXMGAjM9TuFEKd0ytVj/Zs307WWS7d9cn2yhqRNKkzCgU1Ma8vbPGUBUFYizIJpyi0OcNCtJbNlNTc69rkZQnIIDqLDmZ/r58SW6QI0dSwidjlm0mZ4QbqJjgK1eO/rZoQe9ucrI+iVNSEqX0Dw3Vr8U4Ywa9Jz170mRogwbklloUZPd+5IZYhkZMXgp3SZGhc+JEChlo1Iji9RcsKPkT8CWAEihdMCbDUIAXf02prAE0MKxdSzN6e/fSttL0YgsrQFCQPrtYrVqUfXDHDhJqOnQgF7M//tAH44q4A0O3F1dXvf+4SAXt5kaBzDNnUpKGUaPyPxsnZt1z67jFbK6rK8U3nDpFZZ89m+Lr/vwz48KiguwsawIRI+fuXvyKuqGrh5gVzWuWTaE0BwXRx8eHlIu1aymj5/79FAfl5kazjCVRWRMYtmNHR7rXAwdIOAwJoUW5c8KYG2Tm8wuFLSGBZvk//ZQUtS5d9BM5aWnZB4ULq5Lh0gZyOSkY4r3KSSgXbpkiU62TE6VuP32ayt20Kd2nuaykInbVGPb2evc2sa+bm36SR5Dfctvb0ztvZ0fPUSgc4nlmxtqa2oanZ0YXvYoVaULur79oki67401JThYzmYzK6O+vz65ZUhFJwIKC6H4Ms0rmhOjPRZyqWMT93XdJkRsyxLjnR14ttIx+gk8obmI9PBHf5+hIz/PpU7K2RUZSXW7dSpOhDg6UfbVDB/puKoRreGGslFIplc/fn8ZOkUQoNpba4CefkJXQzk6fNZQpMkpwD8YUGkNlTSz+bWplDaC4n3nz9AlMSvqSB8YQlpigIPo/NlZvVVu/Hrh9m4TBfv30+xtiZ0edoWGsgkiUoVCQn/vSpZSOvFevjDFTuWGYqS83hDAmMpitXUvXDA2l7G/Ll2cUDoGM2SCzQyrVxzqYCzH45FXYMTzO0ZEG5KAgGpSSk8nqtmQJzYwOG1ayBUKBiGny8SHlavduGvjbt89ZYRNtIKeYkswKW82aZLG8c4dm/FNS6Dw5KUsKhX7hbVHe5GR9XGRuQqaNDU2OiAkMuZzK8/PPNCkilDhLE1aF9VtYhwF61vb2eVdWs0PUubOz/t3OyXoj6tHXV++G6uKiX1vqf/+jxEXGFAFTYrgYbnaUhMzDecXaWp99OT/H+PjQMxCZU9PTaeLvyhXqvzLDylr+EZOCIrZPuOIqlXrXe5F0KzSUXCQrV6bEPEeOkPzVtCllMj1/vvCLNhtOnpkCW1t9bJuYWNZoaAz85huaiC8NHlMWTCmQLpgCY6isCUGsKJQ1gAJUJ02igcaU64dZEmImTcRDpaeT0tWzJ/Drr/QM/vyT9s0uG6aY6TaMVRCueyNGkJ/7Tz/RTFxeg5Tzo6wB1MF7e+sXN65fn1w7+/Sh9L1t2ugVbyB3y5ohJVmhMVTahFtSTAw93+J07yxqhNtdQADd6/btJHB06JC9wiZcbnJ7DoYKW2IiDfYbNwK//04ZKUVbz+4cIs5SuIOJhBBiDaW81IGIt1Eq9YphbCxldb18meI1LbEuhfuVoZuhtbU+NXZhsLEhoV5Y1nITFkXiEX9/un5iIim5jRvT5NT339MERmHLlRNFGYtWmhAWZT8//dIUVaqQO9uSJdTmGdOROdmVm5t+MXSR9VOppHjdR48oKdn582SlunWLvFoaNiQ37YImIjGcPDMlIkGViG0LDKR+o1w5fheLGH66ZRlDZU24IQUHF821JBIaxJ8+tbwAYlNj6FIm1ilSqcgl9Px5yiDZrFn2x4tYBdERpqaSMKnRUEzIl1+SG15ISNYEDcbIKZ4op3vw9tavaRUURNbR3buprbRuTe6RKlXW1P2lHREzFBSkX2zUEoX7wiIEjipVKEYvJYXcQO/dy7qvWp2/YHZvb3p2SUkknKxZQ8mIwsNzd0N0cNDH4ojvMln+XO/c3PQxdPb21IafPyflw8HBcuvTySnjMihizSjxjhem3CJZUuYF63NCZLiUSqmPcnCgfmn1aloQ+K23cl+brqCwspZ3hGVWJB6RySjeqEoVyuxn6FrPljXTIJJdidh0Hx96tmJpI2Epj47WJ3T67TeyVPn5UaIyHx/yaNmzx3gIQnbkZwK1oIhlnwyTVDFFBvd0ZRlDZU24hhXl4CcsT2UF4V4UGEjPOSaG/nbpkreOTaxxJuKIxELkLVrQopzPnlF2wtu3cz5Pfi1rhtcXLpEioLpVK8oENWYMJSKpX58GGLF/WUK4GPn5ldwEI7kh2nCdOqSwKZWU9e/WrYzWF8O+JC+CnlSqV9jEOZcs0Qfw52adc3HRZ3AE6P3IT/YziYSsa46OZD0WywIUV3KMgiIWnBXlFMpafrJB5oRIkZ4fRIIakSnSzo4SE334IfDFF5QqvrBuXcYwTN3P5A3DJVWkUuCDDyhL4bJl+n0MF6RnTIPIRmsY+yW8Mpydqf9JT6fJqipVgM8+I/fwVasoRf6QIdRf9elD429u/VRBx/yCkl2sMmMySqF0weQZQwHr9u3chX4m/wgrWXAwCaepqSQU5kd4EVnYfH1pRj0uDqhRg3zdExPJ2nH5cvYz2IXpuMW6aAoFlUPEM02YQFkiAX3cQ1kUnCQSUmYDA0unsgboldKGDSkwPiGBYsxu39a3ufT0jIvW5gWhsHl4kPDRpw+5AvXvn/s5HB3Jdc8wfis/1waobXt50f0lJ+uzHAq3VktEIiHhztCaBphWyRQKoPg/L9jaUh8l4t5sbKg+58+nbJtz5piufIK8xKwxWXFw0K+1V706uat++CElhykKpZrRY22t97rx99e70iuV9A65uenXj1SpyJPmm2+AmzeBhQuBhw8p7t3Tk9zGjx41Hr+eU4ZmpkRSSqULJk8YKmsBAUDVquYtT2nGyoo6WOE6l98kK1KpftFTOzvq4IODKeukVEoz2efOGc8UWRA3yOwQgru7Oy1geuQIJT9p3pyEAKZ0ImLNmjUja0lMDAXD376tX8+pIJZVkdbfw4OEjgYN8pYARixcLASVgloD7Ozo+qmpdA8KhT49vqVib08TQIZuUWIhaFMpLwUR2oUbpYcHCZsyGTB8OGWyXb6cEiSZEnaDLDhiAtDRkdzt3N0phi0qit0giwNra3KDFKn/bWzonRFLYhguyv7iBW3r1w/48Ufg+nWa/Lh9m9ZG9fIiy9vx4/rJq+Jwg2SKFe7pyjJiAVqm+LCz0ytsBUGsIeTpSRY6V1fg66/pb8+e1Jlnjt0xdWYoEXMkFtWdPJmy+nHq3tKNREKCeOvWtJ5gVBRZT+7cIUUhP26QhhgqbPmJvXJ0zLhIdkFxcqJrJySUDOHfcAkDtVqfprsorCL5rUuh1Pv46Ne/mzCBPvPmUbyuqSjoOlIMYWNDFjZ/f2DuXErys38/K2vFiVjzMyiIFDdXV+rPoqOpP5LJaJujI7X38HDaNmwYZV29fp0W4756lbwdvL0pEdmJE/rzM6UC7unKMgWdDWcKR2HjAYT7VkAACSvW1uTHHhRErhHHjmWcdS8K/3Vh6fP317vCsbJWNnB2piQSu3dT3OSAAZTopjCCs1DY3Nzy3ifZ2ZE1Nz/LWBhDZDYU8WslAXv7jAuEmzLOyNANsiCIvsHXl5T49HSyro0cCUyfTvE4poAta4VHxCX36kXvX27rKTJFg1iGw9dXnx7f0ZHen+ho6uNsbKh/VCjovX/8mMbcCRMoDOL6dWDqVFK6R42i85amNW3LONzTlWUM3SCZkoWIhQsIoFl2iYSsHbVq0czawYN6l4qiSuMr4md8fWkAKaqsb4zloVDQ2mt79lAcxbZthe9LpFKa6ff2ztv+ov2lpxc+fklYhEQCJEu3LAjrmnBBNXWK/PzGrGVGZB8UkzkqFcWv9e9Pbne7dxe+jByzZhpE2xdLb7BlzbyILIv+/qS4BQRQ2IRSSYpbaipNUgk3yfBwWrvNxYXWivz7b+DaNXI7btzYfPfBmBQ2q5RlWFkr+cjlpCzZ2gIvX5I74vTpwLhxNPs2cGDRp9Z3ctKvd8WUHWxsgE6daEHUAQNoW2EXQpZK8xfPaW+vXxg7p/XZ8oKdHc1cW3pGSIG9PX0Ke9+ZKaxlzRCx1EB4ONXR8uWUxXPkSHreffoU/NycDdJ0SKWsrFkiNjb6+NyUFOqb4uIovg3Q91lpaeQ2GRND/adwh+SEMaUGVtbKMqyslQ6E25GtLRARQWtWzZsHTJtG7pBt29J+RVnXnFykbGJlBXTrRlnJ/vyz+IUDmYyElcePTdO+3d31lmpLRywQ/uSJadc4Kkg2yJywtycrwfPnNIH00UckeA4aRP3TiBEFOy+7QZqWzEp6SXgHygoSiX5BbVdXUtoSEuiTlEQKmlgfUqWieGKAJkuYUoHFKWtJSUk4e/YsHj16BAAIDg5GmzZtYJ+XDGFM/khJyX9WQsZyEUKRXE4uEAoFZY0aNox+Z8GGKQqkUqBDB6BRo8Jb1gqCgwO1fVO5ApakCSx7e3rfU1NpBt6c2SBzQiz78fw5KWiffEIuWyNHkqI9b17+yy6UNVYqTIPhmn38TC0XqZT6PAcHmlxKSqKQh7g4+k2hoEmcmBge80sRFqWsbdiwAfPmzUNiYiK0BoOFo6Mjli5dikmTJpmxdKWQmBialWZKDzY2FDAulwMLFpCQtGsX/VaShFCmZCHWmzMH1tYkoJQU90VTYm1Nn5QU07khm9qyJpDL9QpbXBzw8cf0ff58ICyMXLjzk/CKLWumxVBZY0oGhm6SwkUyMZE+hhl6mRKPxShru3btwtSpU9G8eXNMmTIF1atXBwDcunULGzZswNSpU+Hs7IyhQ4eauaSliOhoMqkzpQvhFimXA++/T4Lsp5+yYs6UXtzcym4Mk50d9eWmpKgEdrEWm0xGZX73Xfq+aBHw4AFltc1rP8UJRhiGMLS2paSQsiYsbUypwGKUtbVr1+KVV17BqVOnIDMYcOvUqYM+ffrg1VdfxZo1a1hZMxVaLVvWSjsODrTg5ty5lJqZFz1nSityObkAl0UcHCw7Zi0zIl28TAZERgJDh1LGu+nTKXvdsWOU1TY3eJ0108JukKUDW1v6lJTYWyZPWExPd+fOHfTt2zeDoiaQyWTo27cv7ty5Y4aSlVKUSjKTs7JWuhHZIuvVIwsbwzClC5EV0lTrrBUHUing6UlZ65KSgDZtgMOHSZFr1owS1uQGW9ZMCytrpQsrq7LpaVBKsRhlzdnZGaGhodn+HhoaCifObGM6hNsMK2ulH7GODr8/DFM6cXCw/Ji1zBgunp2SQmtKHT4MtGoF9O5NsWw5rd1YVt1eiwpW0BjGYrEYZa1bt27YsGED9u/fn+W3AwcOYOPGjXjttdfMULJSilDWOGaNYRimZOPmRq6FpqK4kkyIxDT+/rS4uVxOmSKnTgWWLAFee43c9Y3BCUZMS2bLGitvDGMxWExPt3z5clSoUAGDBw+Gv78/QkJCEBISAn9/fwwaNAgVKlTA8uXLzV3M0oMYANmyxjAMU/LJTybFnDDloth5xdmZMkNKJLT8w9tvk9J24QItCXHtWtZjWFkzPVotu5cyjAViMT2dp6cn/vrrL6xduxa1a9fGixcv8OLFC9SuXRsfffQRLl++DA8PD3MXs/TAbpAMwzCMMcyRvt3RkSxs1tYUU921K7B3LyVPad4c+PLLjPuzUmFa+FkyjMViMdkgAcDW1hZTp07F1KlTzV2U0k90NHXOzs7mLgnDMAxjKUgk+lix4hbgFQpS2J4/BxISgBo1gB07gBUrKGvk778Da9dSfB5b1kwLJxhhGIuFe7qySnQ0KWocoM0wDMMYYs6FkW1tySXS2ZkUNk9PYMECimHbsgUICQGePmVlrShgZY1hLBKzWdbatm0LqVSKkydPwsrKCu3atcv1GIlEglOnThVD6coA0dHsAskwDMNkpLiyQeaEjQ1libSyAqKiKNtlr15AtWrAlClAgwZAcjIra6bEHLGKDMPkCbP1dFqtFhqDtLwajQZarTbHjyanNL5M/uAFsRmGYRhLxcqK1mHz8qK12ORyoGZN4KuvSGlLSGBlzZSwGyTDWCxms6ydOXMmx+9MEcOWNYZhGCYz5oxZy4xYPNvaGnjxgr67uVGmyJMngSZNzFu+0gSn7mcYi8VipqX+97//4eXLl9n+HhkZif/973/FWKJSDitrDMMwTGYszR1OIqH1QAMCKMY6PZ3i2rp0ASpUMHfpGIZhihyLUdbatm2Ln376KdvfT506hbZt2xZjiUo50dG8IDbDMAyTFXPHrBnDwYEyRdrbAykpFNeW3YLZTP4xtKwxDGNRWIyyps2lg1CpVJBx5kLTwZY1hmEYJjOWZlkzxNaWFDZ3d1LY1GpK988UHo5ZYxiLxazrrIWFhSE0NFT3/fbt20ZdHWNjY/HZZ58hODi4GEtXyuEEIwzDMIwxLNGyJhCJR6ytKVOkpSqWJQ1LrGuGYQCYWVnbvn07Fi1aBIlEAolEgqVLl2Lp0qVZ9tNqtZDJZPjss8/MUMpSSFoaZdJiZY1hGIYxxJItawKpFPDwIEubjY25lO2JOgAAgUtJREFUS1M6YMsaw1gsZlXW+vXrh1q1akGr1aJfv36YMmUKWrdunWEfiUQCe3t71KtXD97e3mYqaSlD+PlzzBrDMAyTGUu2rBni4GDuEpQeWFljGIvFrMpa9erVUb16dQBkZWvTpg3KlStnziKVDaKj6S9b1hiGYRhDSoJljSl6WGFjGIvBrMqaIcOHDzd3EcoOrKwxDMMw2VFSLGuM6WDLGsNYLBajrAFASkoKvvrqK/z111+Ii4uDRizM+R8SiQTbtm0zU+lKEcINkpU1hmEYxhAW1MsmrKwxjMViMcrao0eP0LZtW4SGhsLFxQVxcXFwc3NDbGws1Go1PDw84MD+6aZBWNY4Zo1hGIbJDFvWyh7s/sowFovFrLM2c+ZMxMXF4ffff8fdu3eh1Wpx4MABJCYmYsWKFbCzs8PJkyfNXczSQXQ0YGdHmbQYhmEYRsBCe9mELWsMY7FYjLL2yy+/YMKECWjSpAmkUiqWVquFXC7HzJkz8eqrr+Ltt982byFLC7wgNsMwDJMdbFkre7CyxjAWi8Uoa0qlUpcJ0snJCRKJBHFxcbrfmzdvjnPnzpmpdKUMXhCbYRiGMQZb1hiGYSwKi1HWgoKC8OTJEwCAlZUV/P398fvvv+t+v3nzJmzZbc80sGWNYRiGyQ5W1soemS1rbF1jGIvBYhKMtGvXDseOHcOCBQsAACNGjMCyZcsQExMDjUaD3bt3Y9iwYWYuZSkhOpqTizAMwzBZYcta2UQoZ1z3DGNxWIyy9t577+GPP/6ASqWCXC7HnDlz8OzZMxw+fBgymQyDBg3CmjVrzF3M0kF0NFCzprlLwTAMw1gahsoaW1fKDqykM4zFYjHKWlBQEIKCgnTfbW1tsXXrVmzdutWMpSqlsBskwzAMkx0stJc9hLKm0bCSzjAWhsXErOXGnTt3MGrUKHMXo3TACUYYhmEYYxgK6iy0lx3YosowFotFKGsvX77ExYsXcffu3Sy/Xbp0Cb1790bNmjXx5ZdfmqF0pQyNhmPWGIZhmOxhyxrDMIzFYFZlTaVSYejQofD19UWLFi1QvXp11KtXD6GhoXjx4gV69uyJ5s2b48cff8T48eNx584dcxa3dJCWBgwZAtSqZe6SMAzDMJYGW1jKJuwGyTAWi1lj1j788EPs2bMHzZo1Q6tWrfDw4UMcOXIEw4cPR0REBMLDwzF//nxMnjwZbuy2ZxrkcmDnTnOXgmEYhrFU2LJW9uBFsRnGYjGrsrZ//3507NgRP/zwg27bmjVrMHPmTNSoUQO3b9+Gj4+PGUvIMAzDMGUItqyVTTJng+S6ZxiLwaxukI8ePUKPHj0ybOvVqxcAYNasWayoMQzDMExxw5a1sgcr6QxjsZhVWUtNTYWzs3OGbeJ7QECAOYrEMAzDMGUXFtrLJhyzxjAWi9mzQUqy6RSy284wDMMwTBHCljWGYRiLweyLYo8ePRpjx47Nsr179+6QyWQZtkkkEsTFxRVX0RiGYRimbMGWtbIJ1zvDWCxmVdaGDx9uzsszDMMwDMMwQkFjN0iGsTjMqqxt377dnJdnGIZhGMYQtrCUTTJng2QYxmIwe8wawzAMwzAWBAvtZY/M66yxos4wFgMrawzDMAzDEGxZK5sYKmsMw1gUrKwxDMMwDEOwOxzDMIxFwcoawzAMwzB62LJW9sjsBskwjMXAyhrDMAzDMARb1somrKwxjMXCyhrDMAzDMHpYWSt7sJLOMBZLmVDWVCoV3n33Xfj5+cHOzg5NmzbFTz/9lOtxCxcuhEQiyfKxtbUthlIzDMMwTDHDQnvZhC1rDGOxmHWdNUOkUikkuXQQtra2CAgIQNu2bTFz5kxUrFgxT+ceMWIEDh8+jLfffhuVK1fGjh070LVrV5w+fRqtWrXK9fjNmzfDwcFB910mk+XpugzDMAxT4mBlreyROQsoK2wMYzFYjLI2f/58HDt2DDdu3ECXLl1QqVIlAMC9e/fwww8/oHbt2mjXrh3u37+P7du3Y9++ffjf//6HunXr5njeS5cuYf/+/Vi1ahVmzJgBABg2bBhq1aqFWbNm4cKFC7mWrU+fPvDw8Cj8TTIMwzCMJcOp+8s2rKgzjMVhMcqan58fIiMjcfv2bVSoUCHDb/fv30dISAhq1KiBVatW4d69e2jevDnmzJmD7777LsfzHj58GDKZDG+99ZZum62tLUaPHo05c+bg8ePHCAwMzPEcWq0W8fHxcHR0zNX6xzAMwzAlGhbYyx5CtmE3SIaxOCwmZm3VqlWYOHFiFkUNACpVqoSJEydi2bJlAIDKlStj3LhxebKKXblyBVWqVIGTk1OG7U2aNAEAXL16NddzVKhQAc7OznB0dMSQIUPw4sWLHPdXqVSIj4/P8GEYhmEYi4cta2UTrneGsVgsxrL25MkTWFllXxwrKys8fvxY971cuXJQqVS5njc8PBy+vr5Ztottz549y/ZYV1dXTJo0Cc2bN4dcLsevv/6KTz75BJcuXcKff/6ZRQEULFu2DIsWLcq1bAzDMAxjcbBlrexhmGCEYRiLwmKUtZo1a2Lz5s0YOnQovL29M/z2/PlzbN68GTVr1tRte/DgAXx8fHI9b3JyMuRyeZbtIqNjcnJytsdOnTo1w/c33ngDTZo0weDBg7Fp0ya89957Ro+bPXs2pk+frvseHx+fq6slwzAMw5gdtrCUTbjeGcZisRhlbfXq1brEIj179tQlGLl//z6+/vprpKWl4YsvvgAApKSkYMeOHejSpUuu57WzszNqgUtJSdH9nh8GDRqEd955Bz///HO2yppcLjeqIDIMwzCMxcPWlbKHRAJoNByzxjAWiMUoayEhIbhw4QIWLFiAI0eO6Cxetra2aN++PRYuXIgGDRrotuXkvmiIr68vnj59mmV7eHg4AEpskl8CAwMRHR2d7+MYhmEYxqJhCwsDcN0zjAVhMcoaANSvXx/ffPMNNBoNIiIiAABeXl6QSgueB6VevXo4ffo04uPjM8SYXbx4Ufd7ftBqtQgNDUX9+vULXCaGYRiGYRiLgWPWGMZisZhskIZIpVL4+PjAx8enUIoaQGukqdVqbNmyRbdNpVJh+/btaNq0qS6WLCwsDLdv385w7MuXL7Ocb/PmzXj58iU6d+5cqHIxDMMwjMVhaFFh60rZwVBZ43pnGIvCoixrMTEx2LdvHx48eICYmBhoM83wSCQSbNu2LV/nbNq0Kfr27YvZs2cjIiIClSpVws6dOxEaGprhXMOGDcPZs2czXDM4OBj9+/dH7dq1YWtri3PnzmH//v2oV68exo4dW7ibZRiGYRhLgwX1somh+yvDMBaFxShrJ0+eRJ8+fZCUlAQnJye4urpm2aegC1Lv2rUL77//Pnbv3o2YmBjUqVMH3377LV555ZUcjxs8eDAuXLiAr776CikpKQgODsasWbMwd+5cKBSKApWFYRiGYUoErLiVHdiyxjAWi0Sb2XxlJmrVqgWVSoUjR46gdu3a5i6OSYmPj4ezszPi4uKyXZuNYRiGYcxOx47ATz/R/3fuAFWqmLc8TPHQoweQmAiEhQHt2gGbNgEymblLxTCllvzoBhYTs3b//n1MmTKl1ClqDMMwDFMiYQsLwzCM2bEYN8jKlSsjISHB3MWwCNRqNdLS0sxdDIZhLAhra2vIeKabKWpYQSubZHaD5HbAMBaDxShrS5YswcSJEzFo0CCUK1fO3MUxC1qtFs+fP0dsbKy5i8IwjAXi4uICHx+fAsfvMky+4HZWduCYNYaxWCxGWTt16hQ8PT1RvXp1dOjQAYGBgVlmkSUSCT7++GMzlbDoEYqal5cXFAoFC2QMwwCgiRylUqlbf9LX19fMJWJKLTzulE04GyTDWCwWo6xt3LhR9/+3335rdJ/SrKyp1Wqdoubu7m7u4jAMY2HY2dkBACIiIuDl5cUukUzRw4pb2YEtawxjsViMsqbRaMxdBLMiYtR4SQCGYbJD9A9paWmsrDFFAwvqZRNW1hjGYrGYbJAMwa6PDMNkB/cPDMMwDFO2YGWNYRiGYRiCJwTKJoYxa9wGGMaiMJsbpFQqhVQqhVKphI2NDaRSaa6zxhKJBOnp6cVUQoZhGIYpw7DQXnZgN0iGsVjMpqzNnz8fEokEVlZWGb4zTF4ICQkBAJw5cwYAEBoaivLly2P79u0YMWIEAGDhwoVYtGgRtGUgw1Xm58EwDFMgeBwum2TOBsntgGEsBrMpawsXLszxO1O6+Oeff7Bo0SL88ccfePHiBdzd3VGjRg28/vrrmDx5srmLZ3JGjBiBnTt36r7b2NggODgYAwYMwJw5c2Bra5vvc968eRMHDx7EiBEjyuxahAzDFCMssJcdDC1rDMNYFBaTDZIpvVy4cAFt27ZFUFAQ3nzzTfj4+ODx48f4/fff8fHHHxdIWfvxxx9z3WfevHl47733ClJkkyCXy7F161YAQFxcHI4dO4YPPvgA//77L/bs2ZPv8928eROLFi1CSEhIFmUtL8+DYRgmV1hBK5uIemc3SIaxOMymrO3atatAxw0bNszEJWGKmqVLl8LZ2Rl//PEHXFxcMvwmFvnNLzY2NrnuY2VlpXOzNQdWVlYYMmSI7vuECRPQokUL7Nu3D2vXroW3t7fJrpWX58EwDJMvWGhnGIYxO2aTZEVcUX6QSCSsrJVA/v33X9SsWTOLogYAXl5eGb6np6dj2bJl2LFjB548eQJfX18MGjQICxYsgFwu1+2XlxgtYzFrEokEEydORPv27TFv3jzcu3cPlSpVwpo1a9C5c+cMx585cwYzZszA9evX4e/vj1mzZiE8PLzAcXASiQStWrXC77//jgcPHuiUtUePHmHFihU4deoUwsLCoFAo0K5dO6xatUpnQduxYwdGjhwJAGjbtq3unKdPn0ZISIjR5xEREYHZs2fj22+/RVxcHKpWrYrp06dj+PDh+S47wzBlBFbQyiacYIRhLBazKWsPHz4016WZYiY4OBi//fYbrl+/jlq1auW475gxY7Bz50706dMH77zzDi5evIhly5bh1q1bOHr0qEnKc+7cORw5cgQTJkyAo6Mj1q9fjzfeeANhYWFwd3cHAFy5cgWdO3eGr68vFi1aBLVajcWLF8PT07NQ1w4NDQUAuLq66rb98ccfuHDhAgYMGICAgACEhoZi8+bNCAkJwc2bN6FQKPDKK69gypQpWL9+PebMmYPq1asDgO5vZpKTkxESEoL79+9j0qRJKF++PA4dOoQRI0YgNjYWU6dOLdR9MAxTSjEU1FloLzuwssYwFovZlLXg4GBzXbpkoVQCt2+buxR6qlUDFIp8HTJjxgx06dIF9erVQ5MmTdC6dWu8+uqraNu2LaytrXX7Xbt2DTt37sSYMWPw+eefAyDXQS8vL6xevRqnT5/OYFUqKLdu3cLNmzdRsWJFAGSpqlu3Lvbt24dJkyYBABYsWACZTIbz58/Dz88PANCvX79slaPsiIyMBEAxa19//TW++uor1KpVC1WrVtXt061bN/Tp0yfDca+99hqaN2+Or776CkOHDkWFChXQunVrrF+/Hh06dNBZ0rJjy5YtuHXrFr788ksMHjwYADBu3Di0adMG8+bNw6hRo+Do6Jive2EYhmFKKZmzQTIMYzFwghFL5/ZtoGFDc5dCz+XLQIMG+TqkQ4cO+O2337Bs2TKcPHkSv/32G1auXAlPT09s3boVr7/+OgDg+++/BwBMnz49w/HvvPMOVq9eje+++84kylr79u11ihoA1KlTB05OTnjw4AEAQK1W4+eff0avXr10ihoAVKpUCV26dMHx48fzdJ2kpKQslrhWrVph586dGZapsLOz0/2flpaG+Ph4VKpUCS4uLvjrr78wdOjQfN/j999/Dx8fHwwcOFC3zdraGlOmTMHAgQNx9uxZdO/ePd/nZRimlMOWtbJJZssa1z3DWAxmU9batm0LqVSKkydPwsrKCu3atcv1GIlEglOnThVD6SyIatVIQbIUqlUr0GGNGzfGkSNHkJqaimvXruHo0aP46KOP0KdPH1y9ehU1atTAo0ePIJVKUalSpQzH+vj4wMXFBY8ePTLFHSAoKCjLNldXV8TExACgWK/k5OQs5QBgdFt22Nra6hS7J0+eYOXKlYiIiMignAHksrhs2TJs374dT58+zRAPFxcXl+frGfLo0SNUrlwZUqk0w3ZhGTTVs2QYhmFKAewGyTAWi9mUNa1WC41Go/uu0WhyXRS7LCxunAWFIt+WLEvGxsYGjRs3RuPGjVGlShWMHDkShw4dwoIFC3T7FPXi6DKZzOh2U7cvmUyG9u3b67536tQJ1apVw9ixY/HNN9/otk+ePBnbt2/H22+/jebNm8PZ2RkSiQQDBgzI8I4wDMMUOWxZYxiGsSjMpqxlzuKXU1Y/pnTSqFEjAEB4eDgAimPUaDS4d+9ehtiwFy9eIDY2ttjiHL28vGBra4v79+9n+c3Ytrzi6+uLadOmYdGiRfj999/RrFkzAMDhw4cxfPhwrFmzRrdvSkoKYmNjMxyfHyU2ODgYf//9NzQaTQbr2u3/4h85ZpRhGIbRwZY1hrFYpLnvwjCF4/Tp00atViJGTSTb6Nq1KwBg3bp1GfZbu3YtAErEURwIi9jXX3+NZ8+e6bbfv38fJ06cKNS5J0+eDIVCgeXLl2e4Xubns2HDBqjV6gzb7O3tASCLEmeMrl274vnz5zhw4IBuW3p6OjZs2AAHBwe0adOmEHfBMEyphS1rZROpVJ9ghOudYSwKi0swcvbsWXz33Xe6mJrg4GB069aNhcsSzOTJk6FUKtGrVy9Uq1YNqampuHDhAg4cOIBy5crp1g+rW7cuhg8fji1btiA2NhZt2rTBpUuXsHPnTvTs2dMkyUXyysKFC/Hjjz+iZcuWGD9+PNRqNTZu3IhatWrh6tWrBT6vu7s7Ro4ciU2bNuHWrVuoXr06unfvjt27d8PZ2Rk1atTAb7/9hp9//lm3jICgXr16kMlkWLFiBeLi4iCXy9GuXbssa9UBwFtvvYXPPvsMI0aMwOXLl1GuXDkcPnwY58+fx7p16zgTJMMwDKNHKgWSk81dCoZhjGAxylpqaioGDhyIr7/+GlqtVreAcmxsLNasWYNevXph3759GVK9MyWD1atX49ChQ/j++++xZcsWpKamIigoCBMmTMC8efMyLJa9detWVKhQATt27MDRo0fh4+OD2bNnZ4hpKw4aNmyIEydOYMaMGXj//fcRGBiIxYsX49atWzpXwoIyffp0fPrpp1ixYgV27NiBjz/+GDKZDHv27EFKSgpatmyJn3/+GZ06dcpwnI+PDz799FMsW7YMo0ePhlqtxunTp40qa3Z2djhz5gzee+897Ny5E/Hx8ahatSq2b99eoAXpGYYpI7BlrWzSvj3wxReAlRXXO8NYGBKthWTtmDt3LpYtW4YZM2bgnXfegbe3NwDKzLdmzRqsWrUKc+fOxQcffGDmkuaf+Ph4ODs7Iy4uDk5OTkb3SUlJwcOHD1G+fHnY2toWcwmZvNKzZ0/cuHED9+7dM3dRmDII9xNMkdO7N3D0KP3/5Ang72/e8jDFg1IJVK1KdT5jBrBqlblLxDClmrzoBgKLiVnbu3cvhg8fjpUrV+oUNYCSPaxYsQLDhg3D7t27zVhCpqyRnMkl5N69e/j+++9zXZCaYRimxMKWtbKJXA4MG2buUjAMYwSLcYMMDw9H06ZNs/29adOm2L9/fzGWiCnrVKhQASNGjECFChXw6NEjbN68GTY2Npg1a5a5i8YwDMMwpkMqBQYPBjZsoCWDGIaxGCxGWQsICMCZM2cwbtw4o7+fPXsWAQEBxVwqpizTuXNn7Nu3D8+fP4dcLkfz5s3x4YcfonLlyuYuGsMwTNHA1rSyiUQCVKsG/PwzYBBHzjCM+bEYZW348OFYsGABXFxcMG3aNFSqVAkSiQT37t3DunXrcOjQISxatMjcxWTKENu3bzd3ERiGYRimeJBKgcaNgbQ0c5eEYRgDLEZZmzNnDv79919s2bIFn3/+uW4hX41GA61Wi+HDh2POnDlmLiXDMAzDlGKEZY0tbGUTiQSwsTF3KRiGMcBilDWZTIYdO3Zg+vTp+P777zOss9a1a1fUqVPHzCVkGIZhmFIOK2kMwzAWhcUoa4I6deqwYsYwDMMw5oSVNoZhGIvA4pQ1we3bt3Ho0CGEh4ejWrVqGDFiRK7rEDAMwzAMUwhYSWMYhrEozKqsbdy4EevXr8eFCxfg4eGh2378+HH07dsXqampum3r16/H77//nmE/hmEYhmGKAImEFTeGYRgLwKyLYn/zzTeoWLFiBgUsPT0dY8aMgUwmw/bt2/HPP/9g+fLlePToEZYuXWrG0jIMwzBMKYcVNIZhGIvCrMrazZs30axZswzbTp8+jZcvX2LatGkYPnw4atasiVmzZqFfv374/vvvzVRShmEYhilDsNLGMAxjEZhVWYuKikJgYGCGbadOnYJEIkGvXr0ybG/ZsiXCwsKKs3gMY1Z++OEH1KtXD7a2tpBIJIiNjcWIESNQrly5XI8NDQ2FRCLBjh07irycRUlpuY+8sGPHDkgkEoSGhpq7KExZhpU0hmEYi8Ksypq3tzeeP3+eYduvv/4KhUKBunXrZthuY2MDm7K69odaTYtUmvujVhf4Fi5fvozOnTvDyckJjo6O6NixI65evZplv5CQEEgkkiyfzp0753oNlUqFyZMnw9PTEwEBAViyZEmWfZ48eQIHBwecP3++wPdSHERFRaFfv36ws7PDJ598gt27d8Pe3t7cxSpRKJVKLFy4EGfOnDF3URim5MFKG8MwjEVg1gQjjRo1ws6dOzF58mQ4Ojrixo0buHTpEnr06AErq4xFu337NgICAsxUUjOiVgOPHwMGyVbMho0NEBgIyGT5Ouyvv/5Cq1atEBgYiAULFkCj0WDTpk1o06YNLl26hKpVq2bYPyAgAMuWLcuwzc/PL9frrFq1Crt27cLcuXORkJCAxYsXo2LFihg4cKBun5kzZ+L1119Hy5Yt83UPxc0ff/yBhIQEfPDBB2jfvr1u++effw6NRmPGkhUvwcHBSE5OhrW1db6PVSqVWLRoEQCaBGAYJg+wksYwDGNRmFVZW7BgARo3bozKlSujZs2auHz5MiQSCWbPnp1l36NHj6Jdu3ZmKKWZ0WhIUZPJACszVld6OpVDo8m3svb+++/Dzs4Ov/32G9zd3QEAQ4YMQZUqVTBnzhx89dVXGfZ3dnbGkCFD8l3Eb7/9Fu+88w5mzZoFAHj8+DG++eYbnbJ27tw5HD9+HLdv3873uYubiIgIAICLi0uG7QVRWkoyEokEtra25i5GBpKSktjKyZR+WGljGIaxCMzqBlm7dm388ssvaNiwIZ49e4ZmzZrh+++/R8OGDTPsd+bMGSgUCvTt29dMJbUArKwAa2vzfQqhKP76669o3769TlEDAF9fX7Rp0wbffvstEhMTsxyTnp5udHtOJCcnw9XVVffdzc0NSqUSAKDRaDB16lTMmjUr3xba2NhYTJs2DeXKlYNcLkdAQACGDRuGyMhI3T4REREYPXo0vL29YWtri7p162Lnzp0ZziPir1avXo0tW7agYsWKkMvlaNy4Mf744w/dfiEhIRg+fDgAoHHjxpBIJBgxYgQAGI1ZE7Fszs7OcHFxwfDhwxEbG2v0Xm7fvo0+ffrAzc0Ntra2aNSoEb755psM+4jYqfPnz2P69Onw9PSEvb09evXqhZcvX2Y554kTJ9CmTRs4OjrCyckJjRs3xt69ezPsc/HiRXTu3BnOzs5QKBRo06ZNnlxRjcWsjRgxAg4ODnj69Cl69uwJBwcHeHp6YsaMGVD/56obGhoKT09PAMCiRYt07rQLFy4s0LM4e/YsJkyYAC8vLwQEBODw4cO67Zn57LPPIJFIcP36dQDA33//jREjRqBChQqwtbWFj48PRo0ahaioqFzvn2GKHVbSGIZhLAqzL4rdokULfPfddznuExISgn/++aeYSsSYGpVKBTs7uyzbFQoFUlNTcf369QxZQe/evQt7e3ukpqbC29sbb775JubPn5+rValx48bYsmULQkJCkJiYiH379mHSpEkAgG3btiEyMhIzZ87MV9kTExPRunVr3Lp1C6NGjUKDBg0QGRmJb775Bk+ePIGHhweSk5MREhKC+/fvY9KkSShfvjwOHTqEESNGIDY2FlOnTs1wzr179yIhIQFjx46FRCLBypUr0bt3bzx48ADW1taYO3cuqlatii1btmDx4sUoX748KlasaLR8Wq0WPXr0wLlz5zBu3DhUr14dR48e1Sl7hty4cQMtW7aEv78/3nvvPdjb2+PgwYPo2bMnvvrqqyxJfSZPngxXV1csWLAAoaGhWLduHSZNmoQDBw7o9tmxYwdGjRqFmjVrYvbs2XBxccGVK1fwww8/YNCgQQCAX375BV26dEHDhg2xYMECSKVSbN++He3atcOvv/6KJk2a5KtOAECtVqNTp05o2rQpVq9ejZ9//hlr1qxBxYoVMX78eHh6emLz5s0YP348evXqhd69ewMA6tT5f3v3HR1F2bYB/NoUEkIaPdRI6DUUaVJ90dDEghQBFRARXpWmSBHpICAqHRRRAigvaOiCtCgtNKlKh0BiIIEAgSSQnr2/P/LNuJvdTTYhmx2S63fOnLM79Zl5dmbnnqdMg1wdi/fffx+lS5fGpEmT8PjxY3Tt2hXu7u74+eef0a5dO6N5169fj7p166JevXoAgD179uD69esYOHAgfHx8cP78eSxfvhznz5/H0aNHoePNMWkRf5dERNogZHOxsbECQGJjYy3Ok5iYKBcuXJDExETjCSkpIpcvi4SFidy6Zb8hLCwjHSkpOd7/+vXrS40aNSQtLU0dl5ycLJUrVxYAEhQUpI5/5513ZMqUKbJhwwZZvXq1vPzyywJAevXqle12IiIipG7dugJAAEibNm0kPj5eHj58KKVLl5Z169blOO2TJk0SALJx40aTaXq9XkRE5s+fLwDkxx9/VKelpKRIy5Ytxd3dXeLi4kRE5MaNGwJASpYsKTExMeq8W7ZsEQCybds2ddzKlSsFgPz5559G2+zfv7/4+vqq3zdv3iwA5IsvvlDHpaWlSZs2bQSArFy5Uh3foUMHqV+/viQlJRntw3PPPSfVq1c32fYLL7yg7qOIyKhRo8TR0VEePnwoIiIPHz4UDw8Pad68ucnvVllOr9dL9erVpWPHjkbrSkhIkCpVqsiLL75oclwNKcfMcD/69+8vAGTatGlG8zZq1EiaNGmifr97964AkMmTJ5usN6fHonXr1ka/XxGRPn36SJkyZYzGR0VFiYODg1HaEhISTLb/v//9TwDIgQMHTLZ148YNi8fD4nWCKK/06ycCiLi4iERG2js1REQFkjWxgcKu1SCpcHj//fdx5coVDBo0CBcuXMC5c+fw9ttvIyoqCkBG9UXF999/j8mTJ6N79+546623sGXLFgwePBg///wzjh49muV2KlasiNOnT+P06dM4f/489u3bB3d3d0ydOhU1a9ZE7969cejQITRv3hyVKlXC8OHDkZJNxy0bNmyAv7+/SUkLALVEZMeOHfDx8THqyMTZ2RnDhw/Ho0ePTKrK9e7d26i6Zps2bQAA169fzzIt5uzYsQNOTk7473//q45zdHTEsGHDjOaLiYnB77//jl69eiE+Ph737t3DvXv3cP/+fXTs2BFXr17FrVu3jJZ57733jEp92rRpg/T0dISHhwPIKDGKj4/HuHHjTNqVKcudOXMGV69eRd++fXH//n11u48fP0aHDh1w4MCBXHeYMnToUKPvbdq0seoY5uZYDB48GI6Z2mr27t0b0dHRRr1NBgUFQa/Xo3fv3uo4w1LlpKQk3Lt3Ty1JPnXqlNX7S5SvdDqWrhERaQCDNbK5oUOH4tNPP8XatWtRt25d1K9fH6GhoWpHIO7u7lku//HHHwMA9u7dm+22nJ2d0bBhQ9SpUwcODg64dOkSli5digULFiAmJgZdu3bFq6++il9++QV79uzBzJkzs1xfaGioWp3NkvDwcFSvXh0ODsanU+3atdXphipXrmz0XQncHjx4kO3+mdt2uXLlTI5h5h42r127BhHBxIkTUbp0aaNh8uTJAP7t1MTadIaGhgJAlsfn6tWrAID+/fubbHfFihVITk5GbGxsTncbrq6uaps0w/RZcwxzcyyqVKlish6lDZ5htdD169ejYcOGqFGjhjouJiYGI0aMQNmyZVG0aFGULl1aXV9u9p3IphigERFpit3brFHhMHPmTIwePRrnz5+Hl5cX6tevj08//RQAjG5szVFenB4TE5Pj7Y4aNQpvvvkmGjdujDVr1qBEiRJqb6NjxozBzJkz1e7d80vmEhqFiNhsm0rp1ejRo9GxY0ez81SrVs3oe16kU9nu3Llz0bBhQ7PzZBesm2MpbTlJU06Ohbk2ly4uLnj11VexadMmLF26FHfu3EFISAg+//xzo/l69eqFw4cP45NPPkHDhg3h7u4OvV6PTp06FarXMNBTgsEaEZGmMFijfFO8eHG0bt1a/b53715UrFgRtWrVynI5pWpb5pKU7Pz66684fPiwWroTGRmJcuXKqdPLly9vUt0ts6pVq6q9+lni6+uLv/76C3q93qh0TXlFgK+vb47SnRO+vr4IDg7Go0ePjIKey5cvG83n5+cHIKPk0fC9bU9C6fTk3LlzJsFN5nk8PT3zbLvWstRxR14ei969e2PVqlUIDg7GxYsXISJGVSAfPHiA4OBgTJ06FZMmTVLHK79JIs1hsEZEpCmsBkl2sX79evz5558YOXKkGuDExcUhOTnZaD4RwYwZMwDAYimIOSkpKfjoo4/w2WefoUyZMgCAsmXL4tq1a0hLSwMAXLx4ET4+Plmu5/XXX8fZs2exadMmk2lKCVOXLl1w+/Zto+pwaWlpWLRoEdzd3U16C8xLXbp0QVpaGpYtW6aOS09Px6JFi4zmK1OmDNq3b49vv/1WbStoyFyX/NkJCAiAh4cHZs2ahaSkJKNpyrFp0qQJqlatii+//NLsqxhys11rubm5AYDJawzy8li88MILKFGiBNavX4/169ejWbNmRlUmlRLAzKWR8+fPt3obRPlKCdYYtBERaQJL1sjmDhw4gGnTpiEgIAAlS5bE0aNHsXLlSnTq1MmoW/tTp06hT58+6NOnD6pVq4bExERs2rQJISEheO+999C4cWOrt7lgwQIAMFp/ly5d8MEHH6Bv37547rnnMH36dLz77rtZrueTTz5BUFAQevbsiXfeeQdNmjRBTEwMtm7dim+++Qb+/v5477338O2332LAgAE4efIknnnmGQQFBSEkJATz58+Hh4dHDo+Y9bp164ZWrVph3LhxCAsLQ506dbBx40azbaGWLFmC1q1bo379+hg8eDD8/Pxw584dHDlyBDdv3sTZs2dztG1PT0/MmzcP7777Lpo2bYq+ffuiePHiOHv2LBISErBq1So4ODhgxYoV6Ny5M+rWrYuBAweiQoUKuHXrFv744w94enpi27ZteXU4jBQtWhR16tTB+vXrUaNGDZQoUQL16tVDvXr18uxYODs7o3v37li3bh0eP36ML7/80mi6p6cn2rZtiy+++AKpqamoUKECdu/ejRs3bthil4mIiKiAYbD2tPj/0qCncfsVKlSAo6Mj5s6di/j4eFSpUgUzZszARx99BCeDl237+vqiTZs22LRpE27fvg0HBwfUrl0b33zzDd577z2rt3fnzh1Mnz4dP/30E4oUKaKOL1OmDDZs2IBRo0Zhz549ePnll9UOJSxxd3fHwYMHMXnyZGzatAmrVq1CmTJl0KFDB/Xl2kWLFsW+ffswbtw4rFq1CnFxcahZsyZWrlypvszaVhwcHLB161aMHDkSP/74I3Q6HV5++WV89dVXaNSokdG8derUwYkTJzB16lQEBgbi/v37KFOmDBo1amRURS8nBg0ahDJlymD27NmYPn06nJ2dUatWLYwaNUqdp3379jhy5AimT5+OxYsX49GjR/Dx8UHz5s0xZMiQJ9r/7KxYsQLDhg3DqFGjkJKSgsmTJ6NevXp5eix69+6NFStWQKfToVevXibT165di2HDhmHJkiUQEQQEBOC3335D+fLl82o3ifIOS9aIiDRFJ7bs1YAAZFTv8/LyQmxsLDw9Pc3Ok5SUhBs3bqBKlSrG3aCnpwMREUA2XczniyJFgEqVgCfo3IGIcs/idYIorwwcCAQGAm5uQGgokE1VcSIiyjlrYgMFS9a0ztExI0DSQq9xDg4M1IiICjKWrBERaQqDtaeBoyODJCIiyl8M2IiI7I69QRIREVEGlqwREWkKgzUiIiIiIiINYrBGREREGViyRkSkKQzWiIiIiIiINIjBmsbwTQpEZAmvD2RzLFkjItIUBmsa4ezsDABISEiwc0qISKuU64NyvSAiIqKCjV33a4SjoyO8vb0RHR0NAHBzc4OOTzaJCBklagkJCYiOjoa3tzcc+SoPshWWrBERaQqDNQ3x8fEBADVgIyIy5O3trV4niGyiZ0/g9GnAw8PeKSEiIjBY0xSdTody5cqhTJkySE1NtXdyiEhDnJ2dWaJGtvfii0CjRsDjxwB/b0REdsdgTYMcHR15U0ZERPZRqlRGyRrbRhIR2R2DNSIiIjLm4mLvFBAREdgbJBERERERkSYxWCMiIiIiItIgBmtEREREREQaxGCNiIiIiIhIg9jBSD4QEQBAXFycnVNCRERERET2pMQESoyQFQZr+SA+Ph4AUKlSJTunhIiIiIiItCA+Ph5eXl5ZzqMTa0I6eiJ6vR6RkZHw8PCATqd74vXFxcWhUqVKiIiIgKenZx6kkPIS80e7mDfaxvzRNuaPdjFvtI35o232yB8RQXx8PMqXLw8Hh6xbpbFkLR84ODigYsWKeb5eT09PnvQaxvzRLuaNtjF/tI35o13MG21j/mhbfudPdiVqCnYwQkREREREpEEM1oiIiIiIiDSIwdpTyMXFBZMnT4aLi4u9k0JmMH+0i3mjbcwfbWP+aBfzRtuYP9qm9fxhByNEREREREQaxJI1IiIiIiIiDWKwRkREREREpEEM1oiIiIiIiDSIwRoREREREZEGMVgjIiIiIiLSIAZrREREREREGsRgjYiIiIiISIMYrBEREREREWkQgzUiIiIiIiINYrBGRERERESkQQzWiIiIiIiINIjBGhERERERkQYxWCMiIiIiItIgBmtEREREREQaxGCNiIiIiIhIgxisERERERERaRCDNSIiIiIiIg1isEZERERERKRBDNaIiIiIiIg0iMEaERERERGRBjFYIyIiIiIi0iAGa0RERERERBrEYI2IiIiIiEiDGKwRERERERFpkJO9E1AY6PV6REZGwsPDAzqdzt7JISIiIiIiOxERxMfHo3z58nBwyLrsjMFaPoiMjESlSpXsnQwiIiIiItKIiIgIVKxYMct5Cnyw9ujRI8ydOxfHjh3D8ePH8eDBA6xcuRIDBgywavmHDx9izJgx2LRpExISEtCsWTN89dVXaNy4sdVp8PDwAJCRIZ6enrnZDSIiIiIiKgDi4uJQqVIlNUbISoEP1u7du4dp06ahcuXK8Pf3x759+6xeVq/Xo2vXrjh79iw++eQTlCpVCkuXLkX79u1x8uRJVK9e3ar1KFUfPT09GawREREREZFVzaMKfLBWrlw5REVFwcfHBydOnEDTpk2tXjYoKAiHDx/GL7/8gh49egAAevXqhRo1amDy5MlYu3atrZJNRERERESFXIHvDdLFxQU+Pj65WjYoKAhly5ZF9+7d1XGlS5dGr169sGXLFiQnJ+dVMomIiIiIiIwU+GDtSZw+fRqNGzc26aWlWbNmSEhIwJUrV8wul5ycjLi4OKOBiIiIiIgoJxisZSEqKgrlypUzGa+Mi4yMNLvcrFmz4OXlpQ7sCZKIiIi0bN68eahVq5a9k0FEmTBYy0JiYiJcXFxMxru6uqrTzRk/fjxiY2PVISIiwqbpJCIiInoSiYmJiImJsXcyiCgTBmtZKFq0qNl2aUlJSep0c1xcXNSeH7XWA2Rqaiq8vb1NOkeJjIzEqVOn7JQqIiIisicRsXcSiMiMAt8b5JNQepLMTBlXvnz5/E7SE3N0dERsbKxJqeAnn3yCy5cv48SJE3ZKGREREdmTNd2IE1H+YslaFho2bIhTp05Br9cbjT927Bjc3NxQo0YNO6Us9xwcHODg4IC0tDSj8S+++CJOnjzJzlCIiIgKIZasEWkTg7X/FxUVhUuXLiE1NVUd16NHD9y5cwcbN25Ux927dw+//PILunXrZrY929PAycnJaD8BqI2Kw8LC7JAiIiIisicRYckakQYVimqQixcvxsOHD9XeG7dt24abN28CAIYNGwYvLy+MHz8eq1atwo0bN/DMM88AyAjWWrRogYEDB+LChQsoVaoUli5divT0dEydOtVeu/PEnJ2dTUrWlH0OCwtDgwYN7JAqIiIisicGa0TaUyiCtS+//BLh4eHq940bN6qlZW+++Sa8vLzMLufo6IgdO3bgk08+wcKFC5GYmIimTZsiMDAQNWvWzJe024KTk5NJsFa2bFnMmjXrqd4vIiIiyh1WgyTSpkIRrFlTtS8wMBCBgYEm44sXL44VK1ZgxYoVeZ8wO3F2djapBqnT6TBu3Dg7pYiIiIjsjSVrRNrDNmuFkLmSNSIiIiq8WLJGpE0M1gqh27dvY9KkSQgNDbV3UoiIiEgjWLJGpD0M1gqx69ev2zsJREREpAEsWSPSJgZrhRifoBEREZGC9wVE2sNgrRDL3MkImafT6TBnzhx7J4OIiChPPXr0CHfv3gXAkjUirWKwVohlDtauXLmCzp074/79+3ZKkfYof16rVq2yc0qIiIienIjg119/xdKlS9GoUSOUKVNGncaSNSLtKRRd95N5KSkpRt89PDywf/9+rFixAmPHjrVTqrQlOTnZ3kkgIiLKM1u2bMFrr71mMp4la0TaxGCtEMtcslauXDnUrl2bvUQaSEpKAsCnjURE9HRKT0+Ho6MjgIyHtOYCtddeew0nTpzgfx2RBrEaZCFmrs2ar68vvvvuO0ybNi3Pt/fXX3/h6NGjeb5eW1KCNSKtmj17Nm7cuGHvZBBRDoWHh9ukNCs0NNSoOcP777+PN998EyKC6Ohoo3lfffVVAEBwcDBu3ryZ52kpqG7duoWpU6fin3/+sXdSqBBgsFaImQvWBgwYAAB4/Phxnm/P398fLVu2NBp34MAB/PXXX0Zpys9XCgQFBeH7779HUFCQ2emJiYk23X58fDzi4+Ntug2t+PjjjzF8+HB7J0NTNm7ciGbNmuV6+ZSUFIwfPx6dO3fOw1QRFU7x8fHYtGkTAODu3bsICQnJ820kJiZiz549iI6OxjPPPINFixaZnW/WrFm57tjK398f33//PaZMmYJq1aqhTp06+Omnn9C5c2fs378fAHDixAkUKVIEJUuWxIABA5CUlAQHBwejkrVFixap9wT0r/T0dPz222+YMmUKfH1982Sd7PCNsiRkc7GxsQJAYmNj7Z0UERFp2LChAJAvvvhCAgICpEGDBuq09PR0KVKkiCxcuDDPtwtAAEhkZKSkp6eLiEjdunUFgNSuXVsaNGgg7777rtSuXVudbmtKmgDI0KFDZeDAgUbTL1y4IACkTp06IiISGRkpAwYMkOTkZKvWf/fuXYmMjLQ4vUiRIuLs7Cyff/657Nu3T/R6vVXrTU9Pt3iM9uzZI+vXr7dqPeYsXrxY9uzZYzL+7NmzVqfPnICAAHn99ddztIxer5f79+/nepvWePTokRw4cCDXy6ekpMi9e/dytWzFihUFgMTHx+dq+ejoaPX327t3b0lMTLQ4b2JionzxxRfy8OHDXG0rOw8fPpS0tDSbrPtJhIaGSkJCgtXzJyQkyN9//200Li4uLss8TkpKyvLYm3PkyBHZtm1bjpZ5GoWFhRn9LoKDg+XQoUNWLfsk1xtz7t+/L5cuXbI4ff369QJAzp07J61atRIAOU5DfHy83Llzx+L0jz/+WABI/fr1BYC0aNFCRDL21fAeoX///vLss8/maNuKihUrioODg3ptiImJUT+/9NJLAkBu374tJUuWlM8//1xEREqWLClOTk5SuXJluXXrljRo0EBdZu3atbJgwQLp2bOnREREWJUGvV4ver1ekpKS5MKFC/LZZ5/l+FieP39eLl++nOP9t7Wvv/7a6N4hL/Tt21fefvtto3ExMTHy1Vdf5fl5YMnNmzdlzpw5Nv/PpQw5iQ0YrOUDrQVrIiJFixY1utgoF+Dbt28LAKlQoYL07NnzibczYcIEWbZsmSQkJBhtz9/fXx4/fizNmjUzGv/hhx9KmTJlJDQ09Im3bQ3DbSvDn3/+qd5EzZ071yhYGzp0qACQY8eOWXWDXq1aNQEgN2/etGr7ISEhFtd19+5duXXrloiIzJ8/X1xcXOTcuXMiIvLhhx/KypUrRUTE09NTAEhqaqo8ePBAPv30UwEg8+fPt7juqKgo+eeff4zSpHjw4IGcPHlSAMiPP/5ocR3p6ely5coVefDggaxevVoNClJTU2XChAlSo0YNk2A4swEDBkj58uXltddek9WrV6tpCQ8Pt7iMXq+XGjVqyPbt243GT5s2TV599VX1+6NHj+TevXty4MABadWqlZw8eVJERObNm6fmaW6MGzdOPb+VmxNr+fn5qft49+5ddfzmzZvl8ePHsnXr1iwDyStXrhj9fhYtWmQyT3h4uGzevFnWrFmjznft2jWr0hceHq7+5jLT6/Xyww8/qPsNQLy9vaVPnz5WrduSJUuWyIwZM+Srr76yKshKTU21+OBi3bp1AkBee+01q7ffuHFjASCnTp0SPz8/mTFjhppPhq5fvy7PPPOMREdHi6enp3Ts2FFOnz4ter1ePv74Yxk9erRcv35dAgMDRUQkJCTE6MFNbm707t+/LytWrJBbt27J9evXZcWKFaLX6yUlJSVH67HG7t275bvvvhMRUfPhzp07Rr+ds2fPSrdu3WTHjh2ydu1ak3UkJiYKAPnss89k9erVsm3bNnn++eelR48ecuTIEUlNTZXk5GSL+Tdv3jypVKmSHDx4UPr06SN6vV4OHTqk3ryOGjVK5syZIyIix48flxo1asipU6cs7pNyPc6cxsjISJk9e7YkJSWJg4ODLFiwQLy9vQWAHDlyxORmGYDMmjVLRDKC7vHjx8vatWtlypQp6vUXgGzYsEFdRgle3n77bZPr/q1bt+S9994TAOp1SbnGK3m7ePFiiYyMtOrGvX79+uqDUOV8nzlzppQoUUKSk5Plxo0bIiJSpUoVGT9+vIiIeHt7S5EiRcTX11fef/99s/+NOfnN/v333+Lo6CjOzs7qcpb+By3Jy2Aor8TGxsoLL7yQJ8FacHCwVKtWTW7cuCHFihWT6dOni0jGA6Zvv/1WvT+6fv26PHz4UAYNGiRxcXG52taWLVvkypUrZqeFh4eLTqeT0aNHq9c+xddffy1fffVVrrapOH78uOzfv/+J1pFXtm/fLo8ePbJ3MkSEwZrmaDFYy3zx1el0kpKSInq9Xu7evSsDBw6UevXqiYjItWvXcv00/vnnn7d4wZ85c6Zs3rxZXFxc1HE///xzjm52n1RWf0hKgAJA6tatKyIi7du3FwDqH2tISIjMnTtXKlasaLTekJAQ2bx5s7q8t7e3HDx4UPR6vTx48MDi9pVgKCYmRl566SX53//+J7t375b4+Hj1JiA8PFyd38PDQzZs2KB+nz59utEf43PPPWe0/ilTppg9DnXq1BEAcvXq1SyPSZkyZcTBwUGqV68u169fl549e0rt2rVlxYoV6jwVKlRQP+/YsUOCg4PV788//7ysW7dOjh8/LiIin332mVSoUEE6d+4sDx8+tLjdVatWyb59++Tq1aty9epVEfn3CfWUKVOMjt+BAwckICBAHfftt99KWlqadOvWzWS9R44ckS+//FLNU5GMG+IbN24Y3RTp9XqZNGmSepPz4MEDGTVqlNy6dUt8fX0FgMyZM8do3Y8ePZLw8HAZPny4GlSLZJSGBQcHi4hI7dq1szzehulMT09Xb/iUtP35558m83bp0kV+//13dXtNmzY1madRo0YSHh4uL7zwgvj4+MiRI0dk79696jKnT5+Wu3fvqr+xiIgI9YZ65syZMmvWLPn9998FyCghuHHjhtmbl/Pnz6vrDQkJkW3btsnIkSMlNTVVRDIeQERFRcnzzz8vN2/elOXLlxutJy4uTo4ePSorV66UZ599Vs6cOSNbt241Op5TpkyRTp06qetU8mfGjBlGT8AVx48ft3hDP3bsWHX+4sWLmxy32bNni0hGKaLh79xwMCyRUIbOnTsLAGnXrp26LXM3evfv35dBgwaZ3ExcvXpVdu7cKTt37jS6phhuY86cOVKlShX5+uuvjZbdvXu3nDlzxuz+KjZu3GgS6Ge+plSvXl0ASMmSJdV5vLy8jNIQGBhoFNybOz7du3dXS5SHDRsmOp1OevToIZs3b5YFCxZIu3bt5OrVq0a/BeWmde3atep2lHUAkPT0dLO/P0NpaWlmp1euXFkdf+XKFSlXrpzZdI8ePVouXrwoqampAkCqVaumniNZDd999516XR02bJgMHz7caLphUKUM0dHRsn//fgEgf//9t1HJGAA5evRolvnZrl076du3r/r/e/ToUVm6dKk4OjoaXdf8/f3lgw8+EBERDw8PKVq0qPj6+kp6eroUK1ZMypYta/Z4DB48WCpXrmwxcLh69aq4u7ubPR5Z0ev1smzZMomNjZXJkyery6xevVq2bNmS5bLZiYiIkD179siyZcuynXf9+vUybNgwAaBe8xXt2rUTR0dHcXNzU4+ZtSVf586dk1WrVgmQ8QAp87FR/hcyj583b560adNGgIySUUNJSUmycOHCbGs1ABBPT0+z05RrufIQv2XLlvLpp5+qD+Gyy7esZD7vUlNT1eO1fft28ff3N5r/0KFD4u3tLY8fP871Ns05efKkHD58WADIkCFD8nTducVgTWO0Hqw5ODiYVHubPXu2eHl5yV9//SUApG/fvtK7d2+LT9kzCw8Pl2PHjslHH31ktK2hQ4dKnz591O9K4KLceBveMNpSenq6nD592iht33zzjdFTwPnz5xtNf/HFF7P8U1YkJydbnOeNN94QAGrJXXZ/9OaGH374IVfLWbroGl6QbTFYuqk1F0RYGgx/MwDkq6++MjtfixYt1KfnhoO5QM3c8Mknn8jMmTPF0dHRqLRiz549Zue3dGOXeejVq5ekp6dLr1691HFvvvlmjo7juHHjpHLlyuof6jfffCM7duwQANKkSROTP/+XX35Zzp07JzVr1rR6G8WKFZPXX3/d4nRLwfyxY8eMvvft29fo+9mzZ42+BwYGSosWLbJNj1IqnHlwcHBQ8+a7774TAGoAp9fr5cMPPxQAsn//fvW38+mnn8qBAwfUdYwfP15SU1MlLS1N0tPTJSUlRX2ynNXg5uYmL7/8co7yThlKlSolv/32m9G5v2PHDunTp48cOXJEBg8eLACkffv2MmDAADl//ryULVtWnbdkyZJWbWf+/PmyatUq0el0AkD++9//Gp3vys1STEyM0fVKuSG+d++eOu6tt94yWX9ycrJMnjzZKGD08PAQADJq1CgR+fd/z9ygpMtwUKrnZzUoD2Ey/77+97//GX1fuXKlHDp0SD3WTZo0kREjRqjTlZK0zDU79uzZY3RO16pVS31Apwy//vqrOm3kyJHZprljx45GpW2Zf9OZa7ko6VOO3+rVq40CSgDSpk0bEcl4WBMTE2NyTX/11Velc+fOcuvWLTXNP/30kwAwehDQunVreeutt0RExM3NTYoVKybPPPOM+h+p1+uNHsSZG7777jsZN26ciGSUCMXGxqr/5+YGEZFPPvlE9u3bJ2FhYfLw4UP1mGT+T8487Ny5U9auXavWQlBqFuzcuVPdp9TUVLlz54789ttvsmHDBvHy8jL5vZ05c0b0er0kJCTI7t27ja71M2bMMJrX19dXRowYIbt27ZKHDx+KTqeThQsXSkJCgkRERKil6deuXTMJXu/du6dWcTcMWswNfn5+EhMTI3Fxcdn+piIiIqRt27Zy9OhRNX+UUtx169bJoEGD5NChQ1K3bl15+PBhtkHXli1bst2mYc2V9PR0OXv2rNl1GTpy5IjROooVKyZt27aVOnXqyK5du9TxFy9elGrVqsmQIUPUcZlrV0VGRsru3btlz5498ujRo2ybDuj1epkyZYp06dJFfcCiDJ06dco27fmBwZrGaD1YGzt2rMn0wMBAAf6t3244fPTRRzJ06NAsn+RMnz5dypYtK48fP1b/JIB/6/9v3LhRnnvuOfWplfIHqFTFs7WpU6eqaZo/f766XXM3JkDGU/YmTZpkeTELCAiQXbt2Se/evbO98HXv3l1E/s2H8ePHW9x2Xg+ZpaWlyYQJE0zmW7NmjWzfvt3kptrJycnsejPf+Fga2rVrZ/R948aNJut85pln1ONer149o9LXrIbRo0cbVS18//335cKFC2bzbt68eRb3Bci4qenfv7/FQK18+fJWH3NnZ2cZOHCgxelbt27NdX6WLVtWvbH6+eef1RIQIKPUq0qVKjb/TS1cuDDL6ZMmTTL6rjy1zm5QqpiaG+7evSu7du2SH3/8UQBIlSpVJDk52aikIigoSMLCwtTvr7zyisl6KlSoIG3btpXKlStLqVKlLAaIWQ3bt2+XqlWrms2bzA+sgIxzwLBE2NaDUprj5uamjlPOCcO8cXd3l7S0NLl69ar06NFDAMgHH3xgsr5atWqZjDt37px4eXmp1QOVkqEnHczVzsjuWmw4LF26VCpVqpSrbffu3dvoOp15sFR6VKRIEQFgdC5aGjp27Gj0e9m8ebN6bba0jJeXl4SEhAgAmTx5ssk1fcOGDbJ27VpJT0+XO3fuSGpqqvofa/jAddy4cWqbNRcXF/H09FSDNYVer5fo6Gg5evRolrUfSpQooX5u2bKlxfkyB7+Gg2FAnZPB8BpnGBhnNRhev8eMGSP37983ekiReahdu7YcPnxYevfubVKNfNu2bQJk1Dz57LPPRETUBwuNGjUSEVFLdSwNSgBq6f/GcOjSpYv6WTl/lX4GMs/7xx9/GOWbSEY764iICJPmKdYMo0aNUpuHKFV2z58/L//5z3+kZ8+ecuXKFbXNplJjJzdDcHCwHDhwQG0LXLp0aZN5oqOjLTYdUa5fgOlD1Y4dO5pdJr8xWNMYLQdrmYugFUpbD6WRtbmhVKlSFhvVjx8/XqpUqaJ+j4+Pz7YdWn5Vf9Tr9UYXd8PSvOTkZPnjjz9M9jUtLc2qIMxw+PDDD42qJRoOysVe+T5x4kQREZMqMj4+Pupnw2qZ5r4rDdaHDBlidIMzdOhQad26tdEFzpzVq1fLxIkT5fnnn5euXbuaHDNle3v37pX79+/LnTt3JD4+Xl1vr169JDo6Wrp27SqXL1+W119/Xb1p8fHxkY4dO8o///wjKSkpRunW6/Vy48YNoxub7777TmrXri1hYWHqH4M1g+E6lKfPIhkB6fXr143m/fLLLyUqKkoaNmwo/v7+JuvKHFRmHjZt2iQeHh6yZ88e9Xhv3bpVQkJC5NatW3L16lXp1q2b0W/NXGmScp4o3w1LcEeMGCF79+41qc5qOOzevdskLzOXPE6aNEkeP35stO8AzP4BAhk3gHq9Xi3B6NSpk8Xt63Q6iwFhgwYNpEuXLhIQEGB0I+To6Gjxhvv69esSGhoqt2/fVm+GDQMbw8A2ICDAqNRUeSpdrFgxASBLliwxOrYAxMXFJcubd71eL0WLFpXZs2fL/fv3Lc5XoUIFOXTokJw/f15EMp42h4WFyc2bN+Xw4cOyZs0auXv3riQmJpq9QVVK0cwNNWrUsDht2bJlRt9//vlnGTNmTJYltWPGjDE73tnZWX2q3rlzZ5POI1q3bi1vvvmmXL161agk3PDmR3kYt337dgEgK1asEBFRayYoQYIyZC5JcnR0FABG1RqVYdGiRbJy5cosz8O8GCw9FFBKrXK6vnr16gmQcY2wNE9ERIT6P6D8T2zdutXo+Fuzra1bt6oPTg1LTTO7fPmyjBw50qhtrCEnJyfx9vY2+t82p3bt2jJy5Ei1Wl52Q3Ylc9YMGzZssPoBT14M5h48uru7S5cuXaRDhw4mxyTzvJlL0TKf60pVSMNBKR1UmlgYDnq9Xu1PwNKgtG3OPN7Pz0+6du1qtC7lXPvll1/U8U5OTnLmzBlZs2aNREZGyp07d6Rhw4ZGD3gyD506dTL5X1UGw+rgly9flmvXruUqL7p06SIzZ87Mdr4//vhDQkNDJTIyUkaNGpXlg9iAgIAsf+P5hcGaxmgxWFOCMaUtVmbKn4xyExscHGxStaFx48YW1z9ixAiL67Y35QZMCYSioqKMppu7+IhkVC0xHKdUr8pcwrJ37171Bi4tLU127dpl1Lbh+vXr6raUcZMmTRIR4yqJJ06cUDuF2LVrl4j82/lB6dKljUoMgIw/xdDQUNHr9Wr+AhnV5d599131e1admOTGiRMn1Au/tYKDg2XEiBGydOlSdZzyBHfGjBlGHQ4Y3jC/9tpr8u2336rflTZfStU9w2pZ5hpTBwUFyeeffy7AvwHyG2+8If/5z3/kjz/+kGHDhsmSJUtkwYIFWf4xNG/eXERETafypNNc2yDD9MfExIher5dBgwbJqVOnZMaMGWpvZ3FxcbJmzRrR6/VqsGJIOf8mTJgg586dM/ptmmMYxJw+fVpEMqql7N69W0JDQwXIuIkXyWhHd+jQIVm8eLEAUNs9LV26VADI22+/bdJGKvMwZcoUmTp1quj1erX6Vd26dSU8PFxtf6DMW7RoUVmyZInZ9RjebBru4/Tp06Vp06ZG1esaNGggzZs3l6+//lqWL18uixYtEp1Opz7Znzp1qoj8W3JfrVo1WbVqlYhkdKqjBAKG54dIRi+1SvvO2NhY+f3339WnuMp8rq6uFo+9Ocq1dMiQIVK7dm05efKkVKtWTU6cOCFvvPGGxMXFye+//y4pKSlGDzSCgoLUBylAxoOMI0eOSKtWrWT16tVG2zB3PI8dO2ZUojhnzhwpVaqUVK1aVa5cuWK2xEXx119/GbXZMTxGsbGxkpSUJMnJyfLTTz/JqVOnBPi3KmVUVJT6IMywJC7z9XLevHnSvn17eemll+Tx48dGT+MXLlwocXFxMnfuXImLizNqU6gMn376qSxZskRu3rwpwL8lcYZBgrL9S5cuyc6dO6VatWri5+cn48ePV6/VyrzKzakh5aFT5raZQMZDS8Pv/fv3l/DwcDVvMt/svvXWW+r5qFDaDGXu+fDs2bNqrQ6l5Or9999Xr09169aVdu3aqW1w7t27Jw4ODkalc9bS6XRSsmTJbIO1tm3bSr9+/SQ6Olq+/PJLmTBhQpZVmiMjI82Ov337drY34ZGRkbJx40YRyfgvNSwFVqoiGwZCrq6uMn36dJkyZYrcv3/f6GGpYcnWb7/9JmPHjrX4wOTLL78UV1dX9bthkwhzJZmZl4+IiDC73tatW8uQIUPkn3/+UTvfqVOnjuzfv18eP34ser1ePDw8ZMKECeq1xrDDJsNOtwyH3r17y82bN02aAJirkaL0cG1uMCcoKEgcHR2fqJRM0b9/f6NeSr/55pscPQTPKgDLyWAu4LYHBmsao8VgTWmoXrVqVbPTlaekSkmF8odt+IOfO3euJCUlyY0bN9QG9EppxeDBg6Vp06b5uEfWu3jxogAZ7ROUBr2GkpKS1LYhjo6OarUGpbrKxx9/LEFBQZKWliZpaWkSFBQkAKRHjx7qzaE5SrUIczejho2egYx68orMAYBht/2nT59Wn9ItWLDAaL67d+/KqlWrJDU1Va2Cd/jwYesPlEYof1rTpk1TxyldbMfExMjOnTvVqiNK+zhLHako6tatKyNGjBCRjOpaSjCsUALCzB2AKKVTP/zwg9H8SrAWFhZmdns7d+6UN954Ixd7/y+9Xm9UTz+rP1gRUUsGlTZEmW3YsMGkNDs1NVWmTZumbkf5Y587d65RD3GZe0MbOnSoUZfoShuBLl26GK1fmX/WrFlqBzzz58+XnTt3ysSJE9VzLbt9nDt3rnh5eUnv3r2Nqm1duHBBFixYID169JA2bdpY1fA/ISFBfUji4eGhtmGzRNk3c9XHsxIXFye3b9+WcePGWbzuGpo5c6ZRD6W3bt2SKlWqZFlDYc6cOWrbMcNjZ/jAwLBbbsPOiazpUTKr35zykMvcaz9ERL744gsBTKtQLlmyRAIDA9UOTq5cuSIbNmyQ2bNnm/3PVJY7ePCgUe+aycnJ0qBBAzlx4oQ67vjx47J48WK5f/++XLhwwap9i4qKMmoDJZLRpblSCpa5/UvmEk3DHmhFMmqVPHjwQPbt2ycALPZEl92rH8qUKSMAjErRRERef/11efHFF0VE1M6nMqc/O8rvv3Tp0uLn55flvK+//rrZkom4uDg1ON++fbtUrlxZbVuq1+vl/PnzZm/gDUt3atSoYdT21pzTp0/L3r17JS0tTZKTk43yI/OxNZwmIvLPP/+YtHVSHmR0795dihUrJrVq1ZLIyEhJSUmRZ599Vv1NGP4+MstcVXfjxo1G35VzMvN/dFhYmFGHY0o+KKXT8fHxRh0nKQ8kMg8pKSlG532vXr3k8uXLai2hwMBAWb9+vYwfP1797zQ3ZEWpXq60QzMXOPXt21d++eUX+c9//qOOO3LkiMm6DI+lXq83qulgqXp4hQoVJDo6Wr3XBIxLBq0ZfHx8ZOjQoWrVVHtjsKYxWgzWlBvgypUrm52+d+9eAf5tO6Q0nFV+9MePH5ekpCT1D9hw8PX1lb59+xr1fKYlSicDFy9etDjPr7/+alIy07ZtWwFg8qevBL7KE3tLHj16ZNJ1sbe3t7Rv396o/d/vv/9u9btsRER+++03AWByo2soMjJShg8frsn3YGUnMTFRTp48mWU1WaUkR2nzkFXQLJIRyHz44YdZzvP222/Lc889Z9RI2hKlumB+vp8mMjIyy3f4hYWFPdH79hTKH6qIqKUImav5mHu1ws6dO02Oh+Fx1Ov1sn379iwDquyO+/z58832xtapUye1Xag1UlNTZebMmWobjOwkJCTk+l2QkyZNMuk9Ni8pHRB5enrK8uXL1fFKNWlDhlW+rXHs2DG1N9bMlGpO5h6AiYhaaqvcACvDt99+a+WeZVBKTXP6XrvsnD59OtuATnHnzh1ZvXq1+Pn5qe27larFtvrf69Chg9l8Gj16tBr8Kw8ic/reSCWoKVu2bLbBWnR0dK57h753754kJCSYXLcy/wZz8psUEenXr5/F+U+ePJnl6xyUh7DmOjdTHlAlJSXJP//8Y/G4tm/f3qjN3qBBgwSA2hZcqYWjvArDEqVXUyVYM2f9+vUSGxsr6enpMmHCBPH19ZXr16+rAY8SuItkVH0FMqoIKpYuXWo20Bo+fHiWaVOq9iYmJsqFCxdMqohnllUeKtMMr6EnTpyQ559/XhISEiQ+Pl62b9+udh4FQH2VlFINXLmfVs45IKNwYcCAAWobQsC4nXKFChVk0qRJUqFChSz3Nb8wWNMYLQZrSi+PPj4+ZqcrAc327dtlwoQJ6s1Q5hPQ8MmsYaPXatWqmTxV1wqlJCynN9ZKPfbMLzzV6/WyYcOGXN28FS1aNMv3n1nj8ePH8tJLL+X4HTYFkVJ917AULre6deumtt2rXLlylgHg/fv3s/0jLggWLFggRYsWFZGMrrC///77bB98GPrzzz+N3j2VncDAQPnmm28sTr97965cuXLFJFhr3bq1yQtmtWLmzJlSpkwZm60/LCxMnJycTLocj4qKMnmXoNI+Ly+CR6WnUMMbQ0PffPONAKbtNr///vscbef27dtW/97yk16vl7feeivb1yTk1oMHD8zWjNi1a5d8+umnkpycrPbKau1DB0VSUpIAGW0RrSn1zWuZ7ysOHz6co/depqam5vr9Y0r1ZHMl1klJSVYdy3bt2kmfPn3k0qVL8uDBA7VXS6WKsVKrJrsHuspDMGvPiVmzZkmJEiVEJCPQe/jwodF9SHJysuzfv98ouB4xYoTUrFlT7fVy06ZN6ns9s7J582aTh/vKe1XNvQ8TyOgIx5ycBOPKg9j+/fuLiKi9eCqUV05lFh8fr9Z+OnjwoDRs2FC8vLxkz5496rsF7S0nsYETqFDy8PAAAKSkpJid7uLiAgCoUKECZsyYoY4/c+aM0XzVqlUDAJQrVw4dOnTAjh07AADXrl1Dw4YN8zjVeeOFF17A0aNH4e3tnaPllGNVokQJo/E6nQ7du3fPVVqSk5Ph6uqaq2UVbm5u2LZt2xOto6BwdnbOs3UNHz5c/RweHp7lvCVKlMC7776bZ9vWquHDh6vHpWLFimjTpg1eeeUV9XqRnWeffRbPPvus1dvr379/ltNLlSqFUqVKmYxfs2YNHB0drd5OfipSpAiSk5Nttn5fX1+kpqaajPfx8YGPj4/ROJ1Oh9u3byM2NvaJt6vX6wEADg4OZqc7OWXcboiI2fHWKlu2LMqWLZuLFNqWTqfD6tWrbbZ+b29vtGzZ0mR8QEAAAgICMH36dEyaNAkAUKxYsRytOz09HQDsds6MHTvW6F7E3H5mxcnJSb2nyalu3brh7NmzqFKlisk0FxcXNG7cONt1iAgcHBxQs2ZNABn3RQcOHFC/v/rqqyhbtqzV9wk6nc6q+Tw8PPDo0SMAGeedl5eX0fQiRYqgbdu2RuNefPFF1K1bF4MHD8aECROs2g4AvPLKK3jllVeMxlWvXt3i/GFhYXBzczM77dKlS+pvLjvlypXDggUL0K9fPwAZx6Zo0aLqdEv/+e7u7urn1q1bIzg4GHFxcXjmmWfwwgsvWLVtLWGwVkh5enoCgMnJrVBuvjLfVPj7+xt9r1evHurXr49Ro0ahf//+qFevHv773//i+vXrJn/KWuHl5YXmzZvneLm1a9di7dq1Ob65sEREcOjQIbN/EmR/T+MFPb9Vr14dmzdvtncyTDzzzDP2ToJFLi4uFh+S2YOnp6f6f/AklGDN0o2mpUAgr66nhd3Dhw/Vz5Zuki0xDLStDRTy0uzZs/N9m4pp06Zh4sSJT7TfImK0vLu7O9q0aaOOd3R0tCqQz+k9k7u7O1JSUpCSkoIiRYpYtUzXrl1ztI3c8vX1tThNCWKtodPpjB6c5laJEiVMHrQ/TXiVLKS8vLzg4eGB+fPnm52unPjZ3VQ4ODjgr7/+Ur8HBATg0KFD8PPzw6BBg/IsvVpQu3ZtTJ8+Pc/Wp9PpcvwEkaxjjxsOImvYumTNXpQbTUsla2XKlAEAlC5d2mg8g7W8YVg6+rSVrNmTTqezOtCxJHOwZrhud3d3tfTLmvUoy1kjICAAf/zxh8VzjgoOXiULKUdHR8TFxVmcbqlkzRrlypVDYmJirtNG9KQYrJFWubi4QK/XIz09vUDdHGdXDbJz587Yvn07Hjx4gF9//VUdz2AtbxiWrOU2WLNXydrTTqkGaU779u3VBxXWsjYPypUrh3LlyuVo3fR0YjhOZllbskakJc899xyqVKmCvn372jspRGYp19aCVrqWXbCm0+nQpUsXk/EFKWC1p9jYWLRr1w6///57jkuKDIM1yjlLJWsAsHXrVrz55ptWr4fIHD7SIrNcXFzg4uJidSNQIi0oXrw4rl+/bu9kEFmk1FpISUnJcdsiLcuuzZriSTsYIfNiY2Ph7++P559/PsfLGgZrDBhyLqtgLafrAVgzhEzxKklmlS5dGklJSfZOBhFRgVKvXj3MnDnzidvJaE12bdYsYbCWN3bv3q0GzDll2GYtLS0tL5NVKOj1+jwNsBisUWa8ShIREeWTmjVr4tNPP7V3MvJcdtUgFSxZs42cvorGENusPZm8LlkjyowVlImIiOiJWFsNMjMGa/ZnWLJ2+fJlTJkyxb4JesqwGiTZ2lMRrKWkpODx48f2TgYRERGZwZK1p1fmDkb27t1rz+Q8dRiska1pKlhbt24dRo0aZTRu6tSpcHd3h7e3N1577TWr31dBRERE+cPaNmsM1rQn83vWGCzkTF4Fa0SWaCpY++qrr4xK0A4fPoypU6eiY8eOGDVqFHbu3ImZM2faMYVERESUmbUla5mx6377y1yyxsAjZ1iyRramqUdaoaGh6N+/v/p97dq18PHxwaZNm+Dk5AS9Xo8NGzZg1qxZdkwlERERGWKbtadX5kCbwULOZPVS7JyuB+DxJ1OaKllLTk6Gq6ur+n337t3o3LmzejGvU6cObt68aa/kERERkRm56bp/+fLl8PPzs1WSyErFihVD586dUbx4cQB8OXZOsRok2ZqmzsgqVaqoDVtPnDiBa9euoVOnTur0O3fuwN3d3V7JIyIiIjNy08HIyy+/DE9PT5umi7JXpUoV7NixAzVq1ADAkp2cYjVIsjVN1T8YMmQIRowYgQsXLuDmzZuoWLEiXnrpJXV6SEgI6tata8cUEhERUWa5abPG9mraxGAhZ/LqpdgM1sgSTQVrw4YNg6urK3bs2IEmTZpg7NixKFq0KAAgJiYGt2/fxtChQ+2cSiIiIjJkbZs1FxcX9TOr22kLg4XcyetqkDz+lJmmgjUAGDx4MAYPHmwyvkSJEjhx4oQdUkRERERZsbbNWs+ePbF48WIcPnyYJWsaxWAhZ/K6GiRRZnysRURERE/E2mqQTk5O+Oyzz1CrVi32BKkxLFnLHbZZI1uz65XyP//5T46X0el0CA4OtkFqiIiIKDdy0nV/586d0blzZ1sniXKJwULOsBok2Zpdg7XcNMpkMTEREZG25Pal2KQdLNnJnbx+zxpRZnYN1vbt22fPzRMREVEeyM171kibGKzlDKtBkq3xqkpERERPhCVrTz8GC7nDapBka5pt3RsfH4/Y2Fj1D8BQ5cqV7ZAiIiIiMicnbdZI25iHOcPeIMnWNBesLVu2DF9//TWuX79ucZ709PR8TBERERFlhdUgn34sWcsdvhSbbE1TV9VvvvkGH3zwAapVq4YZM2ZARDBy5EiMGzcOPj4+8Pf3x/fff2/vZBIREZEBVoMsOBgs5AyrQZKtaeqqumjRInTs2BG//fYb3nvvPQBA165dMXPmTFy4cAHx8fG4f/++nVNJREREhhisPf1YOpo7rAZJtqapMzI0NBTdunUDADg7OwMAUlJSAABeXl549913sXTpUrulj4iIiEyxzVrBwTzMGfYGSbamqWDNy8sLaWlpAABPT0+4ubkhIiJCne7h4YHbt2/bK3lERERkBktlnn4MFnInr96zpuDxp8w0dVWtV68ezp49q35v0aIFli1bhlu3biEiIgLffvstatSoYccUEhERUWasBllwMFjIGVaDJFvTVG+Qb775Jr755hskJyfDxcUFU6dOxQsvvKB21e/s7IwNGzbYOZVERERkiMHa048la7nDapBka5oK1gYOHIiBAweq31u1aoXz589j27ZtcHR0REBAAEvWiIiINIZt1goO5mHOsDdIsjVNBWvm+Pn5YcSIEfZOBhEREVnANmtPP5bs5A6rQZKt8apKRERET4TVIAsOBms5w2qQZGuaKllzcHCw6keanp6eD6khIiIia7Aa5NOPwULu6PV6VoMkm9JUsDZp0iSTH2l6ejrCwsKwefNm1KxZEy+99JKdUkdERETmsBpkwcFgIWdYDZJsTVPB2pQpUyxOi4qKQosWLdjBCBERkcawZO3px5K13Mmr96zx+JMlT80jsHLlymHo0KGYPn26vZNCREREBpSqYLzRfHoxWMgd9gZJtvbUBGsAUKxYMdy4ccPeySAiIiIDed1uh+yH+ZgzrAZJtvbUBGvnzp3DwoULWQ2SiIhIY6pWrYqePXvaOxn0BNjuMHfYGyTZmqbOyCpVqsDPz89kKFGiBPz9/XHnzh18/fXXOV5vcnIyxo4di/Lly6No0aJo3rw59uzZk+1yU6ZMUat1GA6urq652T0iIqIC6cUXX8S6devsnQzKAwwWcobVIMnWNNXBSLt27Ux+pDqdDsWLF0fVqlXxxhtvoESJEjle74ABAxAUFISRI0eievXqCAwMRJcuXfDHH3+gdevW2S6/bNkyuLu7q98dHR1znAYiIiIirWLJTu6wGiTZmqaCtcDAwDxf5/Hjx7Fu3TrMnTsXo0ePBgC8/fbbqFevHsaMGYPDhw9nu44ePXqgVKlSeZ42IiIiIi1hsJYzrAZJtqapapC2EBQUBEdHR7z33nvqOFdXVwwaNAhHjhxBREREtusQEcTFxfGpBxERERVIDBZyhy/FJluza8natGnTcryMTqfDxIkTrZ7/9OnTqFGjBjw9PY3GN2vWDABw5swZVKpUKct1+Pn54dGjRyhWrBheffVVfPXVVyhbtqzF+ZOTk5GcnKx+j4uLszq9RERERPbCYCFn8vo9a0SZ2TVYM/cSbOUikflHq9Pp1KLmnARrUVFRKFeunMl4ZVxkZKTFZYsXL44PP/wQLVu2hIuLCw4ePIglS5bg+PHjOHHihEkAqJg1axamTp1qdRqJiIiI7Ikla7nDapBka3YN1vR6vdH3W7duoWvXrqhXrx5GjhyJmjVrAgAuXbqE+fPn48KFC9i+fXuOtpGYmAgXFxeT8UqPjomJiRaXHTFihNH3119/Hc2aNUO/fv2wdOlSjBs3zuxy48ePx0cffaR+j4uLy7b0joiIiMjeGCzkDIM1sjVNtVn74IMPUL16dfz444949tln4eHhAQ8PDzRt2hQ//fQTqlatig8++CBH6yxatKhRlURFUlKSOj0n+vbtCx8fH+zdu9fiPC4uLvD09DQaiIiIiLSKwULu5HXX/USZaSpY+/333/Gf//zH4vQOHTogODg4R+ssV64coqKiTMYr48qXL5+zRAKoVKkSYmJicrwcERERkZYx8MgZlqyRrWkqWHN1dcWRI0csTj98+HCOX0jdsGFDXLlyxaSTj2PHjqnTc0JEEBYWhtKlS+doOSIiIiKtYrCQOwzWyNY0Faz169cPP/30E4YPH46rV69Cr9dDr9fj6tWrGDZsGNauXYt+/frlaJ09evRAeno6li9fro5LTk7GypUr0bx5c7Ut2T///INLly4ZLXv37l2T9S1btgx3795Fp06dcrGHRERERNrFYCFn8roaJI8/Zaapl2LPmTMH9+7dw+LFi7FkyRK1K1S9Xg8RQZ8+fTBnzpwcrbN58+bo2bMnxo8fj+joaFSrVg2rVq1CWFgYvv/+e3W+t99+G/v37zfqhdLX1xe9e/dG/fr14erqikOHDmHdunVo2LAhhgwZkjc7TURERGRnLNnJnbwuWSPKTFPBWpEiRbBmzRp88skn2LFjB8LDwwFkBE2dO3eGv79/rta7evVqTJw4EWvWrMGDBw/QoEED/Prrr2jbtm2Wy/Xr1w+HDx/Ghg0bkJSUBF9fX4wZMwYTJkyAm5tbrtJCREREpFUM1nJGr9fn6XvWePwpM00Fa4oGDRqgQYMGebY+V1dXzJ07F3PnzrU4z759+0zGfffdd3mWBiIiIiKtUoKFvAg8ChNWgyRb4xlJRERERAAYLOQUq0GSrdm1ZM3BwQEODg5ISEhAkSJF4ODgkO0PXqfTIS0tLZ9SSERERFTwsRpe7rA3SLI1uwZrkyZNgk6ng5OTk9F3IiIiIsp/vA/LGVaDJFuza7A2ZcqULL8TERERke2xZCf3WA2SbIlt1oiIiIgIAIO1nMjLAJfBMlmiqWAtODjYpMfGH374AZUrV0bZsmUxatQopKen2yl1RERERAUTg4Wcs8Ux4/GnzDQVrE2ZMgVnz55Vv//9998YMmQISpcujfbt22PhwoX48ssv7ZhCIiIiooKLwYL1bFGyRpSZpt6zdvHiRbz++uvq9zVr1sDT0xMHDx6Em5sbhg4ditWrV2Ps2LF2TCURERFRwcKStZxzcHBAeno6q0GSTWmqZO3x48fw9PRUv+/cuROdOnWCm5sbAKBp06YIDw+3V/KIiIiICjQGC9bT6XRWvXYqp+skMqSpYK1SpUr4888/AQDXrl3DuXPnEBAQoE6PiYmBi4uLvZJHREREVCCxZMe+WA2SLNFUNch+/fph2rRpuHXrFs6fP4/ixYvjlVdeUaefPHkSNWrUsGMKiYiIiAouBmv2wWCZLNFUsDZhwgSkpKRgx44dqFy5MgIDA+Ht7Q0go1Rt3759GDFihH0TSURERFTAMFjQBh5/ykxTwZqTkxNmzpyJmTNnmkwrUaIEbt++bYdUERERERUODg6aaiFTaLAaJFmi2TMyKioKZ8+exePHj+2dFCIiIqICjSVr9sXjT5ZoLljbsmULatWqhYoVK6Jx48Y4duwYAODevXto1KgRNm3aZOcUEhERERVMDBbsi8efMtNUsLZt2zZ0794dpUqVwuTJk42KhEuVKoUKFSogMDDQfgkkIiIiKoBYsmNfrAZJlmgqWJs2bRratm2LQ4cO4YMPPjCZ3rJlS5w+fdoOKSMiIiIq+Bis2QeDZbJEU8HauXPn0KtXL4vTy5Yti+jo6HxMEREREVHBx2BBG3j8KTNNBWtubm5Zdihy/fp1lCxZMh9TRERERFR4MFiwD1aDJEs0Faw9//zzWLVqFdLS0kym3b59G9999x0CAgLskDIiIiKigosla/bF40+WaCpYmzlzJm7evImmTZvi22+/hU6nw65du/DZZ5+hfv360Ov1mDx5sr2TSURERFQgMViwLx5/ykxTwVrNmjVx6NAhlCxZEhMnToSIYO7cufj8889Rv359hISEwNfX197JJCIiIipQWLJjX6wGSZY42TsBmdWtWxd79+7FgwcPcO3aNej1evj5+cHLywuBgYF4+eWXceXKFXsnk4iIiKjAYbBmHwyWyRJNBGspKSnYunUrQkNDUbx4cbz00ksoX748mjZtioSEBCxevBjz58/H7du3UbVqVXsnl4iIiKhAERH4+vri3XfftXdSCjUGa5SZ3YO1yMhItG/fHqGhoepTBVdXV2zbtg1FihRB3759cevWLTRr1gyLFi1C9+7d7ZxiIiIiooKnXr168PHxsXcyCiVWgyRL7B6sTZgwATdu3MCYMWPQpk0b3LhxA9OmTcN7772He/fuoW7duvjxxx/Rrl07eyeViIiIqEBisGBfrAZJltg9WNuzZw8GDhyIWbNmqeN8fHzQs2dPdO3aFVu2bIGDg6b6QSEiIiIqcBgo2A+DNbLE7lHQnTt30KJFC6Nxyvd33nmHgRoRERGRjbFkjUib7B4Jpaenw9XV1Wic8t3Ly8seSSIiIiIqdFiqYz8sWSNL7F4NEgDCwsJw6tQp9XtsbCwA4OrVq/D29jaZv3HjxvmVNCIiIqICT0QYKNgRgzWyRBPB2sSJEzFx4kST8e+//77Rd+VCkp6enl9JIyIiIioUGCjYH/OAMrN7sLZy5Up7J4GIiIioUGObNfvi8SdL7B6s9e/f395JICIiIir0WKpjP6wGSZbYvYMRIiIiIrIvluxoA4M1yozBGhERERExULAjBstkCYM1IiIiokKOwYJ9sRokWcJgjYiIiIgYKGgA84AyY7BGREREVMixZM2+ePzJEgZrRERERMRSHTtiNUiyhMEaERERUSHHkh1tYLBGmTFYIyIiIiIGCnbEYJksYbBGREREVMgxWLAvVoMkSxisERERERVyIsJAQQOYB5QZgzUiIiIiYqBgRyzZJEsYrBEREREVcgwW7IvVIMkSBmtERERExEBBA5gHlBmDNSIiIqJCjiVr9sXjT5YwWCMiIiIilurYEatBkiUM1oiIiIgKOZbsaAODNcqMwRoRERERMVCwIwbLZAmDNSIiIqJCjsGCffn4+KBXr15wc3Ozd1JIY5zsnQAiIiIisj+WrNlPo0aNsH79ensngzSIJWtEREREhRxL1oi0icEaEREREbFkjUiDGKwRERERFXIsWSPSJgZrRERERMSSNSINYrBGREREVMixZI1ImxisERERERFL1og0iMEaERERUSHHkjUibWKwRkREREQsWSPSoEIRrCUnJ2Ps2LEoX748ihYtiubNm2PPnj1WLXvr1i306tUL3t7e8PT0xCuvvILr16/bOMVERERE+ee5555Dw4YN7Z0MIspEJ4Wg3LtPnz4ICgrCyJEjUb16dQQGBuLPP//EH3/8gdatW1tc7tGjR2jcuDFiY2Px8ccfw9nZGfPmzYOI4MyZMyhZsqRV24+Li4OXlxdiY2Ph6emZV7tFRERERERPmZzEBgU+WDt+/DiaN2+OuXPnYvTo0QCApKQk1KtXD2XKlMHhw4ctLvvFF19g7NixOH78OJo2bQoAuHTpEurVq4cxY8bg888/tyoNDNaIiIiIiAjIWWxQ4KtBBgUFwdHREe+99546ztXVFYMGDcKRI0cQERGR5bJNmzZVAzUAqFWrFjp06ICff/7ZpukmIiIiIqLCrcAHa6dPn0aNGjVMotZmzZoBAM6cOWN2Ob1ej7/++gvPPvusybRmzZohNDQU8fHxZpdNTk5GXFyc0UBERERERJQTBT5Yi4qKQrly5UzGK+MiIyPNLhcTE4Pk5ORcLTtr1ix4eXmpQ6VKlXKbfCIiIiIiKqQKfLCWmJgIFxcXk/Gurq7qdEvLAcjVsuPHj0dsbKw6ZFXVkoiIiIiIyBwneyfA1ooWLYrk5GST8UlJSep0S8sByNWyLi4uZoM8IiIiIiIiaxX4krVy5cohKirKZLwyrnz58maXK1GiBFxcXHK1LBERERER0ZMq8MFaw4YNceXKFZNOPo4dO6ZON8fBwQH169fHiRMnTKYdO3YMfn5+8PDwyPP0EhERERERAYWgGmSPHj3w5ZdfYvny5ep71pKTk7Fy5Uo0b95c7fzjn3/+QUJCAmrVqmW07Lhx43DixAm1V8jLly/j999/V9dlDeVVduwVkoiIiIiocFNiAmted13gX4oNAL169cKmTZswatQoVKtWDatWrcLx48cRHByMtm3bAgDat2+P/fv3Gx20+Ph4NGrUCPHx8Rg9ejScnZ3x9ddfIz09HWfOnEHp0qWt2v7NmzfZIyQREREREakiIiJQsWLFLOcpFMFaUlISJk6ciB9//BEPHjxAgwYNMH36dHTs2FGdx1ywBmQEWqNGjcLu3buh1+vRvn17zJs3D9WqVbN6+3q9HpGRkfDw8IBOp3vi/YmLi0OlSpUQERGR7VvPKf8xf7SLeaNtzB9tY/5oF/NG25g/2maP/BERxMfHo3z58nBwyLpVWqEI1gqauLg4eHl5ITY2lie9BjF/tIt5o23MH21j/mgX80bbmD/apvX8KfAdjBARERERET2NGKwRERERERFpEIO1p5CLiwsmT57MF29rFPNHu5g32sb80Tbmj3Yxb7SN+aNtWs8ftlkjIiIiIiLSIJasERERERERaRCDNSIiIiIiIg1isEZERERERKRBDNaIiIiIiIg0iMEaEREREREVOAWhH0UGa0T01CsIF2MiInp6xMbG2jsJlIX169cDAHQ6nZ1T8uQYrGnA6dOn8c8//xid+Lz51IaEhAR7J4GycP36dSQkJCApKcneSSEzzp49i6tXr+LmzZvqOF7btGHLli14//33cf36dQCAXq+3c4rI0P/+9z94eHggJCTE3kmhTDZu3IiAgADMmzcPYWFh9k4OZbJu3TpUrVoVffr0waFDh+ydnDzBYM2OLl68iNatW6NDhw7w9/dHs2bNsGHDBqSlpUGn0/Gmxo4uX76MJk2a4N1337V3UsiMv/76C127dkW3bt1QpUoVtG/fHiEhITxnNOKvv/7Ciy++iJdeeglNmjSBv78/Fi5cqF7byL727NmD1157DWvWrMGvv/4KAHBw4O2AFpw+fRrNmzfHO++8g65du8LT09PeSaL/FxkZia5du+Ltt99GkSJF4ObmBjc3N3sni/6fcu70798fHh4ecHV1RXJysr2TlSd4dbaT6Oho9OvXDyKCr776Cl9//TVKlCiBd999FzNmzLB38gotEcGGDRvw8ssv4/Tp01i3bh32799v72TR/0tPT8eiRYvwwgsv4PHjx+jRowd69OiBqKgovPvuuzhw4IC9k1iopaam4vPPP0e7du2QmpqKsWPHYvny5WjQoAEmTpyIbdu22TuJhZryMKNkyZIoUaIE0tPTsXbtWpw9exYAS9fsKTExEe+88w6aNGmCokWLYv369Vi4cCHq169v76TR/1u+fDlu3LiB5cuXY9myZRgzZgzKlClj72QVenFxcejfvz+aNGkCNzc3/PLLL/j8888hIjhz5gyAjHuHp5qQXaxbt06cnJwkKChIHXfz5k3p3bu36HQ62bt3rx1TV3iFhoZKvXr1pGTJkjJjxgypU6eOtGjRQlJTU+2dNBKRnTt3ip+fn7zzzjty6dIldXxISIjodDoZO3Ys88qOtm/fLo0bN5aRI0fKlStXJC0tTURErl69KjqdTr744gvR6/V2TiUFBQVJQECAfPPNN6LT6eTTTz9V84r5k//S0tJk5syZotPpZPDgwXL37l2L1zHmj338888/UrZsWRk+fLjJeEPMn/z1+PFjqV69uvj5+cmyZcskPDxcRESuX78uxYsXl+7du0t6erqdU/nknOwdLBZW4eHhKFasGF577TUAGU+kK1SogDFjxuDGjRsYOXIkgoOD+dQmnzk5OeHll19Gr1694O/vj+LFi+PDDz/EqlWrMGjQIHsnr9C7cOECXFxcMHv2bJQuXRoAkJKSgueeew7NmzfHqVOn4OTkBBFhdTs78PLyQr9+/fDWW2+p+QMA586dQ+nSpeHr66tW8Wb+5D/luFeqVAnHjh3Drl27EBQUhJUrV+L555/HCy+8YO8kFkqOjo7o2LEjduzYgYMHD6JUqVIAgK1bt2Ljxo0oW7YsatWqhX79+qFIkSJ2Tm3hFBYWhvj4eHz44YcAgDVr1mD27NkAgBo1aqBXr17o06cPr2v5SK/Xw83NDatWrYKnpydq1KgBZ2dnAECVKlVQrVo1xMTEIDU1FUWKFHmq84bVIG1MqVYimdrSFClSBHq9Xq22pbQXaNSoET7++GNcvXoV33//vdllKW+Yy5vKlStj0qRJ8Pf3BwC88MILePHFFzFlyhTcv3/fLuksrAzzR8mjUaNGYfPmzShdurQ6vUiRIkhPT4erqysSExORlJT0VF+Unxbmzp9WrVrho48+MgrUDh06hIkTJyIpKQkXL17EuXPn1M6UWO3ONiz97yjnRUREhJpHc+fOxe3bt/Hjjz/iwYMHbC+dD8zlT5MmTfDWW2/h8uXLGD16NDp27IhXX30VISEhWLZsGQYNGoQ+ffrg/PnzRuugvGXp3HFzc0NKSgrOnz+PlStXYsCAAahTpw6aNm2Kw4cPo1+/fggMDLRDigsXw/xR7ptbtmyJunXrqoGaiECv16NZs2Y4ffo0EhMTn/rrGoM1G1HabqxcuRLAv3+Syo+lXr16SElJwf79+yEicHR0hF6vh06nQ7t27fDKK69g3rx5SElJ4Y1nHrOUNwoXFxf1c40aNTBo0CDcv38fX3zxRb6ms7Aylz+GeVSjRg0A/z7gUC7asbGxqFChAlxdXZ/qi7LWZXf+AP/+oY4bNw5t27ZF6dKl8dprryEiIgJt2rTBf//7XwDs1CKvZZc3ynlRuXJl3LlzB1FRUWjYsCHeeecdrFu3Djt37gSQ0X6K8l529wWdO3fG66+/jq+//hppaWn47bffEBwcjEuXLmHatGnYvHkzpk6dCoDnTl6z5rrm7e2NDRs2YMGCBZgwYQJWrlyJwMBA7N27FwEBARg9ejQuXbqU30kvFKzJH4VOp4ODgwNKlCiBuLg4HDx4MNtlNC8/61wWFgcOHJC6deuKTqeTgIAAuXDhgoiY1mVu3LixNGrUSP7++2+T6T/99JM4OTnJsmXLzC5LuWNt3hiOi46OlnfeeUdcXV3l3LlzFuenJ5eT/DEUEREhxYoVk1mzZomIqO1vKG9Zmz/K902bNsn69evl3r176rjx48eLg4ODzJ07V0SkQLQn0IKcnDs///yz1KhRQ+7cuSMiInFxceLm5ibPP/+8DBw4UN566y2JjIzM1/QXdNbmz08//SQDBgyQkJAQk2n9+vUTLy8v2bp1q9llKXeszZtWrVqJg4ODlCpVSg4fPmw0bffu3VKiRAkZMWKEiPC6lpdyel+gHPuDBw+KTqeTn3/+Ocv5nwYM1vLYkSNHpFatWvLMM89Iz549RafTyZw5c4waCys3klu2bBGdTiczZsyQxMREo2mXL1+WihUrynvvvceTPo9YkzeWBAcHS4UKFeS1117Lh5QWTk+SPwcOHBCdTie7du3Kh5QWTjnJn6z+FK9evSrVqlUTf39/SUpKsmWSCw1r80bJl4MHD4qbm5tERESo0/r06SOOjo7i7OwskydPlkePHuXrPhRk1uSPkjexsbESHR1ttLwy39GjR0Wn08mUKVOe6htPLcnJPdvOnTtFp9OJTqeTixcviohIcnKyiGQ81O3UqZNUqlSJ17U89CT3BefOnZPixYvLsGHDRITBGhm4cOGCuLi4yC+//CIiIm3atJHq1atLSEiI2fm7dOki5cuXl23btomIcYlA3bp15e233xaRp/tHphU5zRuRf4/7o0ePZOLEiaLT6SQ4OFhERPbv3y9btmwxmo9yLzf5o1i6dKk4OTlJfHy8iGScR6GhoXLixAkRYf7khSfJHxHjJ80tW7aUFi1a8KYmj2TOm7Zt22aZN+vWrZOaNWvKw4cP5Y8//pDWrVuLo6OjeHp6SrVq1eTgwYMiwvMmr+T23FGOv3Lu3L17V7y9vWXMmDG2TXAhktO86devn+h0OhkyZIiIiFHQ0KNHD6lTp47ExsbaPuGFxJP870RHR4uvr6906NBB4uLibJ1Um2KwloeUQMvwqZjyxH/48OHqCWx40xIeHi7u7u7SokULOXXqlDr+6NGj4unpKVOnTs2n1Bds1uaNuZsTJb8uXbokjRs3lvr168vUqVOlUqVKUrJkSbUqEeXek+SPiEi3bt3kueeeE5GMKpE//vijNGrUSBo3biz379+3ceoLvrw4fxS7du0SZ2dnGTlypA1TXHjkJG+U/AkODpYiRYrISy+9JI6OjtKqVSs5cOCA/Pzzz+qNqFJiQE8mL8+dpUuXik6nk++++86GKS48cnPPFhERIZ6eniY1Oc6fPy9Vq1aVN998kw858khenDvdu3eXunXryqNHj57qfGGwlkvr1q2TIUOGyOzZs+XAgQPqeMMfg/Jj6d+/v3h7e8vmzZuN1qH8EAMDA6Vy5cpSpUoVWbhwoaxYsUK6desmlSpVkr/++isf9qZgyYu8MSc8PFwGDBigVoN45ZVXjKoRkXXyMn/0er3Ex8dLuXLl5I033pC9e/fKyy+/LDqdTjp16iQ3b9607c4UQLY6fyIjI2Xbtm3Srl07qVOnjtpWl6yXV3kTEhIiDRo0kNq1a8vixYslIiJC/T9q1aqVDB48mMFaLtjq3Ll9+7Zs2rRJGjRoIO3atZN79+7lfeILuLy8Z1u3bp2UK1dOSpQoIYMHD5bPP/9cOnfuLMWLF2dV/Fyyxbmj1+tlxowZotPp5PLlyybre5owWMuh27dvS8eOHaVYsWLSuHFjKV68uLi4uMjkyZPlwYMHIiImLxe9efOmuLu7S/fu3dWb+/T0dKMfzb59+6RVq1bi5eUlJUuWlAYNGsihQ4fyd+eecnmZN5kdPHhQOnXqJA4ODtKoUSOrq37Rv2yVP9euXRM3Nzdp3LixuLu7S82aNdWqqmQ9W+XPvn37ZPDgwdKjRw/x8PAQf39/+fPPP/NvxwqAvMobpcpWSkqKHDhwQP7++281KFOWU9pPk/Vsee4MHTpU+vTpI+7u7tK4cWM5c+ZM/u1YAWCre7aQkBDp2LGjeHt7S5kyZaRRo0ZGQQZZx5b3bSIi8+bNE51OJ0FBQbbfGRtisJZDq1atkhIlSshPP/0kkZGRcv/+fRkwYIB4eHjI+++/bzK/8uOaOXOmODg4yPLly41OeMPPiYmJcufOHd7I5FJe542hvXv3SpEiRWTx4sU23YeCzFb58/vvv4tOp5MyZcowf56ArfJn27ZtUq1aNWnfvr388MMPNt+PgsgWefO0PmHWIludO0FBQeLu7i7Nmzdn1cdcsuU9W3Jysjx48EDOnj1r+x0poGx17ijBW1RUlAQGBtp2J/IBg7UcateunbRo0cJo3OPHj6V///6i0+lk+/btImIa5aekpEjVqlWlefPmcuXKFRERCQ0NNaqLy14fn4wt80aE3cE/qbzOH8O2gt9++62kpKTYeA8KNlvmT2hoKK9vTyAv8+batWsm1zZ6MrY8d86ePcv/nifAezZts2X+FKQHUgzWrJSeni5JSUnSsWNHadWqlTpeqVZy8uRJadKkifj5+Zn8QDJ31T927FhZuXKlNG7cWIYPHy6PHz/Ovx0pgJg32mbL/Hnae3jSAlvmD7t/fzK2zJuEhIT825ECiueOdvG+QNuYPznDYM2MixcvyogRI2TYsGEyYcIENWoXEXn11VelZs2aauN4w2h/+fLlotPpZN68eSJiWhKTmpoqTZs2FUdHR9HpdFKuXDnZuXOn7XeoAGHeaBvzR9uYP9rFvNE25o92MW+0jfnz5BisGUhOTpbRo0dL0aJF5dlnn5Xq1auLTqcTPz8/9R0PQUFBotPp5IcfflB/VMoPKCwsTDp06CBVqlQxabR96tQpmTBhgri7u4uHh4fMnz/fDnv49GLeaBvzR9uYP9rFvNE25o92MW+0jfmTdxis/b/4+Hj59NNPxc/PT+bMmSOXL1+W9PR02bt3r5QvX17atGkjCQkJkpaWJv7+/tK2bVsJCwszWc+UKVPE29tbrWcrkvHj+vDDD0Wn00n//v3VF/eSdZg32sb80Tbmj3Yxb7SN+aNdzBttY/7kLQZr/+/GjRtSpUoVGTJkiDx8+NBo2pAhQ6R06dJy4sQJERFZs2aN6HQ6+frrr9W6sUrUf/r0aXFwcJBNmzaJyL/1b48fPy4XLlzIp70pWJg32sb80Tbmj3Yxb7SN+aNdzBttY/7kLQZr/0+v18vy5cuNxim9y/3888/i5OQkFy9eFBGRhw8fSvfu3cXHx8fkpXzHjx8XnU4nq1atyp+EFwLMG21j/mgb80e7mDfaxvzRLuaNtjF/8haDNQNKxJ65EePcuXPF0dFRLl26pI6LiIiQsmXLSt26ddUGjbdu3ZIPP/xQfH195fbt2/mX8EKAeaNtzB9tY/5oF/NG25g/2sW80TbmT95hsJYFpbHjiBEjxMfHR30qoPzwdu3aJY0bNxadTicNGzaUli1birOzs0ydOlXS0tIK1DsetIZ5o23MH21j/mgX80bbmD/axbzRNuZP7ulEREBZevbZZ/HMM88gKCgI6enpcHR0VKfdu3cP33//PUJDQxEXF4cRI0agZcuWdkxt4cK80Tbmj7Yxf7SLeaNtzB/tYt5oG/MnF+wdLWpddHS0FC1aVObOnauOS09Pl5iYGDumikSYN1rH/NE25o92MW+0jfmjXcwbbWP+5I6DvYNFrTt37hySkpLQtGlTAMDt27exdu1adOzYEXfv3rVz6go35o22MX+0jfmjXcwbbWP+aBfzRtuYP7nDYM0C+f/aoX/++Se8vLxQvnx57Nu3D++//z7eeecdiAgcHBzU+Sj/MG+0jfmjbcwf7WLeaBvzR7uYN9rG/HkyTvZOgFbpdDoAwLFjx1CyZEnMnTsX69atg4+PD7Zv344XX3zRziksvJg32sb80Tbmj3Yxb7SN+aNdzBttY/48ofyrcfn0SUxMlIYNG4pOpxNPT0+ZN2+evZNE/495o23MH21j/mgX80bbmD/axbzRNuZP7rE3yGyMHTsWOp0OU6dOhYuLi72TQwaYN9rG/NE25o92MW+0jfmjXcwbbWP+5A6DtWzo9Xo4OLBpnxYxb7SN+aNtzB/tYt5oG/NHu5g32sb8yR0Ga0RERERERBrE8JaIiIiIiEiDGKwRERERERFpEIM1IiIiIiIiDWKwRkREREREpEEM1oiIiIiIiDSIwRoREREREZEGMVgjIiIiIiLSIAZrREREREREGsRgjYiIiIiISIMYrBEREREREWkQgzUiIiIiIiIN+j9F/vZDxzyJrwAAAABJRU5ErkJggg==", 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", 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    " ] @@ -94366,7 +49142,7 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "rdtools_313-nb", "language": "python", "name": "python3" }, @@ -94380,7 +49156,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.7" + "version": "3.13.12" } }, "nbformat": 4, diff --git a/docs/notebook_requirements.txt b/docs/notebook_requirements.txt deleted file mode 100644 index b44d257d4..000000000 --- a/docs/notebook_requirements.txt +++ /dev/null @@ -1,57 +0,0 @@ -appnope==0.1.4 -argon2-cffi==23.1.0 -argon2-cffi-bindings==21.2.0 -backcall==0.2.0 -beautifulsoup4==4.12.3 -bleach==6.1.0 -cffi==1.17.0 -colorama==0.4.6 -decorator==5.1.1 -defusedxml==0.7.1 -entrypoints==0.4 -html5lib==1.1 -ipykernel==6.29.5 -ipython==8.26.0 -ipython-genutils==0.2.0 -ipywidgets==8.1.3 -jedi==0.19.1 -Jinja2==3.1.6 -jsonschema==4.23.0 -jupyter==1.0.0 -jupyter-client==8.6.2 -jupyter-console==6.6.3 -jupyter-core==5.7.2 -jupyterlab-pygments==0.3.0 -lxml==5.3.0 -MarkupSafe==2.1.5 -mistune==3.0.2 -nbclient==0.10.0 -nbconvert==7.17.0 -nbformat==5.10.4 -nest-asyncio==1.6.0 -notebook==7.2.2 -numexpr==2.10.2 -pandocfilters==1.5.1 -parso==0.8.4 -pexpect==4.9.0 -pickleshare==0.7.5 -prometheus-client==0.20.0 -prompt-toolkit==3.0.47 -ptyprocess==0.7.0 -pycparser==2.22 -Pygments==2.18.0 -pyzmq==26.1.1 -qtconsole==5.5.2 -Send2Trash==1.8.3 -simplegeneric==0.8.1 -soupsieve==2.6 -tabulate==0.9.0 -terminado==0.18.1 -testpath==0.6.0 -tinycss2==1.2.1 -tornado==6.5.1 -traitlets==5.14.3 -wcwidth==0.2.13 -webencodings==0.5.1 -widgetsnbextension==4.0.11 - diff --git a/docs/sphinx/source/changelog.rst b/docs/sphinx/source/changelog.rst index b6ecffd9f..c440554ce 100644 --- a/docs/sphinx/source/changelog.rst +++ b/docs/sphinx/source/changelog.rst @@ -1,5 +1,6 @@ RdTools Change Log ================== +.. include:: changelog/v3.2.1.rst .. include:: changelog/v3.2.0.rst .. include:: changelog/v3.1.1.rst .. include:: changelog/v3.1.0.rst diff --git a/docs/sphinx/source/changelog/v2.0.0.rst b/docs/sphinx/source/changelog/v2.0.0.rst index a9b981456..e383f5757 100644 --- a/docs/sphinx/source/changelog/v2.0.0.rst +++ b/docs/sphinx/source/changelog/v2.0.0.rst @@ -11,12 +11,12 @@ API Changes right-labeled energy with :py:func:`~rdtools.normalization.energy_from_power` before being used with these normalization functions (:pull:`105`, :pull:`108`). * Remove ``low_power_cutoff`` parameter in :py:func:`~rdtools.filtering.clip_filter` (:issue:`84`). -* Many kwargs have changed name (but not input order) to bring nomenclature into +* Many kwargs have changed name (but not input order) to bring nomenclature into closer alignment with the `DuraMAT pv-terms project `_: (:pull:`185`) * :py:func:`~rdtools.aggregation.aggregation_insol` first kwarg is now ``energy_normalized``. - * :py:func:`~rdtools.degradation.degradation_year_on_year`, - :py:func:`~rdtools.degradation.degradation_ols` and + * :py:func:`~rdtools.degradation.degradation_year_on_year`, + :py:func:`~rdtools.degradation.degradation_ols` and :py:func:`~rdtools.degradation.degradation_classical_decomposition` first kwarg is now ``energy_normalized``. * :py:func:`~rdtools.filtering.normalized_filter` input kwargs are now ``energy_normalized``, ``energy_normalized_low`` and ``energy_normalized_high``. @@ -97,7 +97,7 @@ Example Updates variable names (:pull:`139`). * Add soiling section to the original example notebook. * Add a new example notebook that analyzes data from a PV system located at - NREL's South Table Mountain campus (PVDAQ system #4) (:pull:`171`). + NLR's South Table Mountain campus (PVDAQ system #4) (:pull:`171`). * Explicitly register pandas datetime converters which were `deprecated `_. * Add new ``system_availability_example.ipynb`` notebook (:pull:`131`) diff --git a/docs/sphinx/source/changelog/v3.2.1.rst b/docs/sphinx/source/changelog/v3.2.1.rst new file mode 100644 index 000000000..8220629d4 --- /dev/null +++ b/docs/sphinx/source/changelog/v3.2.1.rst @@ -0,0 +1,59 @@ +******************** +v 3.2.1 (2026-04-XX) +******************** + +Maintenance +----------- +* Migrated project configuration from ``setup.py``/``setup.cfg`` to + ``pyproject.toml`` using ``setuptools`` as the build backend. + (:pull:`488`) +* Replaced ``versioneer`` with ``setuptools-scm`` for automatic version + management from git tags. (:pull:`488`) +* Removed legacy build files: ``setup.py``, ``setup.cfg``, ``versioneer.py``, + ``MANIFEST.in``, and ``rdtools/_version.py``. (:pull:`488`) +* Updated ``rdtools/__init__.py`` to use ``importlib.metadata`` for version + retrieval instead of versioneer. (:pull:`488`) +* Updated GitHub URLs and references from ``NREL/rdtools`` to + ``NatLabRockies/rdtools`` and email addresses from ``@nrel.gov`` to + ``@nlr.gov``. (:pull:`492`) +* Adopted `pixi `_ for reproducible environment management. + Replaced ``requirements.txt``, ``requirements-min.txt``, and + ``docs/notebook_requirements.txt`` with pixi environments and a lockfile. + (:pull:`492`) +* Rewrote CI workflows (``pytest.yaml``, ``nbval.yaml``) to use pixi via + ``prefix-dev/setup-pixi`` and removed the ``requirements.yaml`` workflow. + (:pull:`492`) +* Bumped minimum ``arch`` version from 5.0 to 5.6. (:pull:`492`) +* Added Python 3.14 to the test matrix and package classifiers. + (:pull:`492`) +* Simplified pixi environments: ``core`` (bare), ``default`` (notebooks), + ``dev`` (notebooks + test, alias for ``dev-py313``), ``dev-py310`` through + ``dev-py314`` (full dev per Python version), and ``dev-min`` (minimum + dependency versions). All shared environments pin Python 3.13. + (:pull:`492`) +* Added composable pip extras: ``[notebooks]``, ``[test]``, ``[dev]``, + ``[doc]``, and ``[all]``. (:pull:`492`) +* Updated documentation (README, Sphinx index, developer notes, and example + notebook setup cells) for pixi and pip extras. (:pull:`492`) + +Bug Fixes +--------- +* Fixed broken link to TrendAnalysis example in Sphinx index page. + (:pull:`492`) +* Fixed README CI status badges using a deprecated GitHub Actions badge URL + format. (:pull:`497`) + +Requirements +------------ +* Replaced the unmaintained ``filterpy`` dependency with its maintained fork + ``bayesian-filters``, which provides the same API and fixes + ``SyntaxWarning`` on Python 3.13+. (:pull:`494`) +* Added ``llvm-openmp`` (the conda-forge name for libomp) as a platform-specific + conda dependency for macOS (osx-64 and osx-arm64) to fix XGBoost installation + issues. Users no longer need to install libomp via Homebrew. (:pull:`493`) +* Bumped minimum ``xgboost`` version from 1.6.0 to 1.7.0 to fix + ``pkg_resources`` import error in environments without ``setuptools``. + (:pull:`493`) +* Bumped minimum ``pvlib`` version from 0.12.0 to 0.13.1 to include the + ``detect_clearsky()`` bug fix (pvlib GH2550). (:pull:`493`) + diff --git a/docs/sphinx/source/conf.py b/docs/sphinx/source/conf.py index c46717ae7..4bfd1da3d 100644 --- a/docs/sphinx/source/conf.py +++ b/docs/sphinx/source/conf.py @@ -62,8 +62,8 @@ # List of external link aliases. Allows use of :pull:`123` to autolink that PR extlinks = { - "issue": ("https://github.com/NREL/rdtools/issues/%s", "GH #%s"), - "pull": ("https://github.com/NREL/rdtools/pull/%s", "GH #%s"), + "issue": ("https://github.com/NatLabRockies/rdtools/issues/%s", "GH #%s"), + "pull": ("https://github.com/NatLabRockies/rdtools/pull/%s", "GH #%s"), "ghuser": ("https://github.com/%s", "@%s"), } @@ -195,7 +195,7 @@ def make_github_url(pagename): # either a branch name or a git tag will work for the URL branch = version_map.get(rtd_version, rtd_version) - URL_BASE = "https://github.com/nrel/rdtools/blob/{}/".format(branch) + URL_BASE = "https://github.com/NatLabRockies/rdtools/blob/{}/".format(branch) # is it an API autogen page? if pagename.startswith("generated/"): diff --git a/docs/sphinx/source/developer_notes.rst b/docs/sphinx/source/developer_notes.rst index d33272f24..6c53b331f 100644 --- a/docs/sphinx/source/developer_notes.rst +++ b/docs/sphinx/source/developer_notes.rst @@ -16,17 +16,118 @@ you'll need to clone the RdTools source repository from Github with e.g. :: - git clone https://github.com/NREL/rdtools.git + git clone https://github.com/NatLabRockies/rdtools.git + git clone https://github.com/NatLabRockies/rdtools.git from the command line, or using a GUI git client like Github Desktop. This -will clone the entire git repository onto your computer. +will clone the entire git repository onto your computer. Installing RdTools dependencies ------------------------------- -The packages necessary to run RdTools itself can be installed with ``pip``. -You can install the dependencies along with RdTools itself from -`PyPI `_: +RdTools uses `pixi `_ for reproducible environment management. +Pixi creates isolated environments from the lockfile (``pixi.lock``), ensuring +every contributor gets the exact same package versions. + +To install pixi, follow the instructions at https://pixi.sh. + +Once pixi is installed, navigate to the repository root and run: + +:: + + pixi install + +This creates the default environment with RdTools and its core dependencies. +Pixi environments are stored locally in ``.pixi/`` (gitignored) and do not +interfere with other Python environments on your system. + +To run a command inside a pixi environment, use ``pixi run``: + +:: + + pixi run python -c "import rdtools; print(rdtools.__version__)" + +.. _pixi-environments: + +Available pixi environments +~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +RdTools defines several pixi environments in ``pyproject.toml``: + +- **core** — bare RdTools with core dependencies only (Python 3.13) +- **default** — RdTools + notebook extras for regular users (Python 3.13) +- **dev** — notebooks + test extras combined (Python 3.13); recommended for day-to-day development (alias for **dev-py313**) +- **dev-py310** through **dev-py314** — full dev environment pinned to a specific Python version +- **dev-min** — test-only environment with minimum supported dependency versions (Python 3.10) + +For most contributors, the **dev** environment is the best starting point +because it includes everything needed to run the test suite, launch Jupyter +notebooks, and check code style: + +:: + + pixi install -e dev + pixi run -e dev test # run the test suite + pixi run -e dev lab # launch Jupyter Lab + +To test against a specific Python version: + +:: + + pixi run -e dev-py310 test + +.. _updating-pixi-environments: + +Updating pixi environments +~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +When ``pyproject.toml`` changes (e.g. a dependency is added, removed, or its +version constraint is updated), the pixi lockfile must be regenerated: + +1. **Re-solve dependencies** — run ``pixi update`` from the repository root. + This re-solves all environments against the current ``pyproject.toml`` + constraints and writes a new ``pixi.lock``: + + :: + + pixi update + +2. **Verify environments install correctly** — run ``pixi install`` to + re-create environments from the updated lockfile: + + :: + + pixi install + +3. **Run tests** to make sure nothing is broken: + + :: + + pixi run -e dev test + +4. **Commit both files** — always commit ``pyproject.toml`` and ``pixi.lock`` + together so that CI and other contributors stay in sync: + + :: + + git add pyproject.toml pixi.lock + git commit -m "Update dependencies" + +.. note:: + If you only want to update a single package, you can target it: + ``pixi update numpy``. To update packages only within a specific + environment, use ``pixi update -e dev numpy``. + +.. note:: + Contributors who pull changes that include an updated ``pixi.lock`` + just need to run ``pixi install`` to get the new environment. + +Installing without pixi +~~~~~~~~~~~~~~~~~~~~~~~~ + +If you prefer not to use pixi, you can still install RdTools and its +dependencies with pip. The packages necessary to run RdTools itself can be +installed from `PyPI `_: :: @@ -66,26 +167,35 @@ Installing optional dependencies RdTools has extra dependencies for running its test suite and building its documentation. These packages aren't necessary for running RdTools itself and -are only needed if you want to contribute source code to RdTools. +are only needed if you want to contribute source code to RdTools. .. note:: These will install RdTools along with other packages necessary to build its documentation and run its test suite. We recommend doing this in a virtual environment to keep package installations between projects separate! -Optional dependencies can be installed with the special -`syntax `_: +With pixi (recommended): + +:: + + pixi install -e dev # all development dependencies (recommended) + pixi install -e dev-py310 # dev environment with Python 3.10 + pixi install -e dev-min # minimum supported dependency versions + +With pip: :: - pip install rdtools[test] # test suite dependencies + pip install rdtools[dev] # notebooks + test dependencies + pip install rdtools[test] # test suite dependencies only pip install rdtools[doc] # documentation dependencies Or, if your local repository has an updated dependencies list: :: - pip install .[test] # test suite dependencies + pip install .[dev] # notebooks + test dependencies + pip install .[test] # test suite dependencies only pip install .[doc] # documentation dependencies @@ -96,26 +206,43 @@ RdTools uses `pytest `_ to run its test suite. If you haven't already, install the testing dependencies (:ref:`installing-optional-dependencies`). -To run the entire test suite, navigate to the git repo folder and run +With pixi +~~~~~~~~~ + +Run the full test suite in the dev environment: :: - pytest + pixi run -e dev test -For convenience, pytest lets you run tests for a single module if you don't -want to wait around for the entire suite to finish: +Run a single test module: :: - pytest rdtools/test/soiling_test.py + pixi run -e dev pytest rdtools/test/soiling_test.py -And even a single test function: +Run a single test function: :: + pixi run -e dev pytest rdtools/test/soiling_test.py::test_soiling_srr + +Without pixi +~~~~~~~~~~~~~ + +If you installed RdTools and its test dependencies with pip, you can invoke +pytest directly: + +:: + + pytest rdtools/test/ + pytest rdtools/test/soiling_test.py pytest rdtools/test/soiling_test.py::test_soiling_srr -You can also evaluate code coverage when running the test suite using the +Measuring code coverage +~~~~~~~~~~~~~~~~~~~~~~~ + +You can evaluate code coverage when running the test suite using the `coverage `_ package: :: @@ -125,11 +252,19 @@ You can also evaluate code coverage when running the test suite using the The first line runs the test suite and keeps track of exactly what lines of code were run during test execution. The second line then prints out a -summary report showing how much much of each source file was -executed in the test suite. If a percentage is below 100, that means a -function isn't tested or a branch inside a function isn't tested. To get -specific details, you can run ``coverage html`` to generate a detailed HTML -report at ``htmlcov/index.html`` to view in a browser. +summary report showing how much of each source file was executed in the +test suite. If a percentage is below 100, that means a function isn't tested +or a branch inside a function isn't tested. To get specific details, you can +run ``coverage html`` to generate a detailed HTML report at +``htmlcov/index.html`` to view in a browser. + +Note that the pixi ``test`` task already includes ``--cov`` flags, so coverage +data is collected automatically when running ``pixi run -e dev test``. + +RdTools also uses `Codecov `_ to +track coverage over time. Coverage reports are uploaded automatically by CI +after each test run. Pull requests will show a Codecov status check indicating +whether the change increases or decreases overall coverage. Running the notebooks as tests @@ -142,15 +277,41 @@ and compare outputs for you: :: - pytest --nbval docs/system_availability_example.ipynb + pixi run -e dev pytest --nbval docs/system_availability_example.ipynb + +A helpful option is ``--sanitize-with docs/nbval_sanitization_rules.cfg`` to +ignore nuisance differences like the username shown in warning messages: + +:: + + pixi run -e dev pytest --nbval --sanitize-with docs/nbval_sanitization_rules.cfg docs/system_availability_example.ipynb + +Or to run all notebooks at once using the pixi task: + +:: + + pixi run -e dev nbval + + +Re-running and saving notebook outputs +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -Some helpful options are ``--nbdime`` to display a visual before/after diff -and ``--sanitize-with docs/nbval_sanitization_rules.cfg`` to ignore nuisance -differences like the username shown in warning messages: +If notebook outputs need to be refreshed (e.g. after a code change that +affects plots or printed results), you can re-execute all notebooks in place +using ``jupyter nbconvert``: :: - pytest --nbval --nbdime --sanitize-with docs/nbval_sanitization_rules.cfg docs/system_availability_example.ipynb + pixi run -e dev jupyter nbconvert --to notebook --execute --inplace docs/*.ipynb + +Or a single notebook: + +:: + + pixi run -e dev jupyter nbconvert --to notebook --execute --inplace docs/TrendAnalysis_example.ipynb + +This overwrites each notebook file with freshly executed outputs. Review the +diffs before committing to make sure the changes look correct. Checking for code style @@ -163,13 +324,13 @@ folder and run :: - flake8 + pixi run -e dev flake8 Or, for a more detailed report: :: - flake8 --count --statistics --show-source + pixi run -e dev flake8 --count --statistics --show-source Building documentation locally @@ -214,7 +375,7 @@ docs should result in output like this: dumping search index in English (code: en) ... done dumping object inventory... done build succeeded. - + The HTML pages are in build\html. If you get an error like ``Pandoc wasn't found``, you can install it with conda: @@ -230,7 +391,7 @@ Contributing ------------ Community participation is welcome! New contributions should be based on the -``development`` branch as the ``master`` branch is used only for releases. +``development`` branch as the ``master`` branch is used only for releases. RdTools follows the `PEP 8 `_ style guide. We recommend setting up your text editor to automatically highlight style @@ -238,7 +399,7 @@ violations because it's easy to miss some issues (trailing whitespace, etc) othe Additionally, our documentation is built in part from docstrings in the source code. These docstrings must be in `NumpyDoc format `_ -to be rendered correctly in the documentation. +to be rendered correctly in the documentation. Finally, all code should be tested. Some older tests in RdTools use the unittest -module, but new tests should all use pytest. \ No newline at end of file +module, but new tests should all use pytest. \ No newline at end of file diff --git a/docs/sphinx/source/index.rst b/docs/sphinx/source/index.rst index cf6d0f0cc..61aa7d977 100644 --- a/docs/sphinx/source/index.rst +++ b/docs/sphinx/source/index.rst @@ -53,7 +53,8 @@ The preferred method for degradation rate estimation is the year-on-year (YOY) approach (Jordan 2018), available in :py:func:`.degradation.degradation_year_on_year`. The YOY calculation yields a distribution of degradation rates, the central tendency of which is the most representative of the true -degradation. We note that the workflow described above and implemented in +degradation. We note that the workflow described above and implemented in +degradation. We note that the workflow described above and implemented in :py:class:`.analysis_chains.TrendAnalysis` provides an estimate of degradation rate, not performance loss rate (PLR). PLR includes losses that are explicitly filtered out by the primary workflow (Deceglie 2023). @@ -102,14 +103,14 @@ The combined estimation of degradation and soiling (CODS) method (Skomedal 2020) in RdTools. CODS self-consistently extracts degradation, soiling, and seasonality of the daily-aggregated normalized performance signal. It is particularly useful when soiling trends are biasing degradation results. It's use is shown in both the TrendAnalysis -example notebook as well as the funtional API example notebook for degradation and soiling. +example notebook as well as the funtional API example notebook for degradation and soiling. TrendAnalysis ^^^^^^^^^^^^^ -An object-oriented API for complete soiling and degradation analysis including +An object-oriented API for complete soiling and degradation analysis including the normalize, filter, aggregate, analyze steps is available in :py:class:`.analysis_chains.TrendAnalysis`. See the -`TrendAnalysis example `_ for details. +`TrendAnalysis example `_ for details. Availability ------------ @@ -147,23 +148,22 @@ Alternatively it can be installed manually using the command line: On some systems, installation with ``pip`` can fail due to problems installing requirements. If this occurs, the requirements specified in -``setup.py`` may need to be separately installed (for example by using +``pyproject.toml`` may need to be separately installed (for example by using ``conda``) before installing ``rdtools``. For more detailed instructions, see the :ref:`developer_notes` page. -RdTools currently is tested on Python 3.9+. +RdTools currently is tested on Python 3.10+. Usage and examples ------------------ Full workflow examples are found in the notebooks in :ref:`examples`. -The examples are designed to work with python 3.12. For a consistent -experience, we recommend installing the packages and versions documented -in ``docs/notebook_requirements.txt``. This can be achieved in your -environment by first installing RdTools as described above, then running -``pip install -r docs/notebook_requirements.txt`` from the base -directory. +The examples are designed to work with python 3.13. For a consistent +experience, we recommend using `pixi `_ to set up the +notebook environment. From the base directory, run ``pixi run lab`` +to launch JupyterLab with all required packages. Alternatively, install +manually with ``pip install rdtools[notebooks]``. Documentation ------------- @@ -187,7 +187,7 @@ and the specific DOI coresponding to that version from `Zenodo =2.17,<3.0.a0 + - libgomp >=7.5.0 + constrains: + - openmp_impl <0.0a0 + license: BSD-3-Clause + license_family: BSD + purls: [] + size: 28948 + timestamp: 1770939786096 +- pypi: https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl + name: anyio + version: 4.12.1 + sha256: d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c + requires_dist: + - exceptiongroup>=1.0.2 ; python_full_version < '3.11' + - idna>=2.8 + - typing-extensions>=4.5 ; python_full_version < '3.13' + - trio>=0.32.0 ; python_full_version >= '3.10' and extra == 'trio' + - trio>=0.31.0 ; python_full_version < '3.10' and extra == 'trio' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/81/29/5ecc3a15d5a33e31b26c11426c45c501e439cb865d0bff96315d86443b78/appnope-0.1.4-py2.py3-none-any.whl + 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license_family: BSD + purls: [] + size: 433413 + timestamp: 1764777166076 +- conda: https://conda.anaconda.org/conda-forge/win-64/zstd-1.5.7-h534d264_6.conda + sha256: 368d8628424966fd8f9c8018326a9c779e06913dd39e646cf331226acc90e5b2 + md5: 053b84beec00b71ea8ff7a4f84b55207 + depends: + - vc >=14.3,<15 + - vc14_runtime >=14.44.35208 + - ucrt >=10.0.20348.0 + - libzlib >=1.3.1,<2.0a0 + license: BSD-3-Clause + license_family: BSD + purls: [] + size: 388453 + timestamp: 1764777142545 diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 000000000..f4c264f2a --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,194 @@ +[build-system] +requires = ["setuptools>=64", "setuptools-scm>=8"] +build-backend = "setuptools.build_meta" + +[project] +name = "rdtools" +dynamic = ["version"] +description = "Functions for reproducible timeseries analysis of photovoltaic systems." +readme = "README.md" +license = {text = "MIT"} +requires-python = ">=3.10" +authors = [ + {name = "Rdtools Python Developers", email = "RdTools@nlr.gov"}, +] +maintainers = [ + {email = "RdTools@nlr.gov"}, +] +keywords = [ + "photovoltaic", + "solar", + "analytics", + "analysis", + "performance", + "degradation", + "PV", +] +classifiers = [ + "Development Status :: 5 - Production/Stable", + "License :: OSI Approved :: MIT License", + "Operating System :: OS Independent", + "Intended Audience :: Science/Research", + "Programming Language :: Python", + "Programming Language :: Python :: 3", + "Programming Language :: Python :: 3.10", + "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", + "Programming Language :: Python :: 3.13", + "Programming Language :: Python :: 3.14", + "Topic :: Scientific/Engineering", +] +dependencies = [ + "matplotlib >= 3.5.3", + "numpy >= 1.22.4", + "pandas >= 1.4.4", + "statsmodels >= 0.13.5", + "scipy >= 1.8.1", + "h5py >= 3.7.0", + "plotly >= 4.0.0", + "xgboost >= 1.7.0", + "pvlib >= 0.13.1", + "scikit-learn >= 1.1.3, != 1.6.0", + "arch >= 5.6", + "bayesian-filters >= 1.4.5", +] + +[project.optional-dependencies] +doc = [ + "sphinx==7.4.7", + "nbsphinx==0.9.5", + "nbsphinx-link==1.3.1", + "sphinx_rtd_theme==3.0.1", + "ipython", + "sphinx-gallery==0.18.0", +] +test = [ + "pytest >= 3.10.1", + "pytest-cov", + "coverage", + "flake8", + "nbval >= 0.10.0", + "pytest-mock", +] +notebooks = [ + "jupyter", + "ipywidgets", + "numexpr >= 2.10.2", + "tabulate >= 0.9.0", + "lxml", +] +dev = [ + "rdtools[notebooks,test]", +] +all = [ + "rdtools[dev,doc]", +] + +[project.urls] +Homepage = "https://github.com/NatLabRockies/rdtools" +"Bug Tracker" = "https://github.com/NatLabRockies/rdtools/issues" +Documentation = "https://rdtools.readthedocs.io/" +"Source Code" = "https://github.com/NatLabRockies/rdtools" + +[tool.setuptools_scm] + +[tool.setuptools.packages.find] +include = ["rdtools*"] + +[tool.setuptools.package-data] +rdtools = ["data/*", "models/*"] + +[tool.pytest.ini_options] +addopts = "--verbose" +filterwarnings = [ + "ignore:The .* module is currently experimental:UserWarning:rdtools", +] + +# --- Pixi configuration --- + +[tool.pixi.workspace] +channels = ["conda-forge"] +platforms = ["win-64", "linux-64", "osx-64", "osx-arm64"] + +[tool.pixi.pypi-dependencies] +rdtools = { path = ".", editable = true } + +[tool.pixi.dependencies] +python = ">=3.10" + +# macOS requires llvm-openmp for XGBoost +[tool.pixi.target.osx-64.dependencies] +llvm-openmp = "*" + +[tool.pixi.target.osx-arm64.dependencies] +llvm-openmp = "*" + +# --- Python version features --- + +[tool.pixi.feature.py310.dependencies] +python = "~=3.10.0" + +[tool.pixi.feature.py311.dependencies] +python = "~=3.11.0" + +[tool.pixi.feature.py312.dependencies] +python = "~=3.12.0" + +[tool.pixi.feature.py313.dependencies] +python = "~=3.13.0" + +[tool.pixi.feature.py314.dependencies] +python = "~=3.14.0" + +# --- Extra features --- + +[tool.pixi.feature.notebooks.pypi-dependencies] +rdtools = { path = ".", editable = true, extras = ["notebooks"] } + +[tool.pixi.feature.test.pypi-dependencies] +rdtools = { path = ".", editable = true, extras = ["test"] } + +[tool.pixi.feature.dev.pypi-dependencies] +rdtools = { path = ".", editable = true, extras = ["dev"] } + +# Minimum version pins (matching lower bounds in [project.dependencies]) +[tool.pixi.feature.min.pypi-dependencies] +matplotlib = "==3.5.3" +numpy = "==1.22.4" +pandas = "==1.4.4" +statsmodels = "==0.13.5" +scipy = "==1.8.1" +h5py = "==3.7.0" +plotly = "==4.0.0" +xgboost = "==1.7.0.post0" +pvlib = "==0.13.1" +scikit-learn = "==1.1.3" +arch = "==5.6.0" +bayesian-filters = "==1.4.5" + +# --- Environments --- + +[tool.pixi.environments] +core = { features = ["py313"], solve-group = "default" } +default = { features = ["notebooks", "py313"], solve-group = "default" } +dev = { features = ["notebooks", "dev", "py313"], solve-group = "default" } +dev-py310 = { features = ["notebooks", "dev", "py310"] } +dev-py311 = { features = ["notebooks", "dev", "py311"] } +dev-py312 = { features = ["notebooks", "dev", "py312"] } +dev-py313 = { features = ["notebooks", "dev", "py313"], solve-group = "default" } +dev-py314 = { features = ["notebooks", "dev", "py314"] } +dev-min = { features = ["test", "min", "py310"] } + +# --- Tasks --- + +[tool.pixi.tasks] + +[tool.pixi.feature.notebooks.tasks] +lab = "jupyter lab docs/" + +[tool.pixi.feature.test.tasks] +test = "pytest --cov=rdtools --cov-report=xml rdtools/test/" + +[tool.pixi.feature.dev.tasks] +test = "pytest --cov=rdtools --cov-report=xml rdtools/test/" +nbval = "pytest --nbval --nbval-sanitize-with docs/nbval_sanitization_rules.cfg docs/" diff --git a/rdtools/__init__.py b/rdtools/__init__.py index 2cd286b00..cdf1d2e6c 100644 --- a/rdtools/__init__.py +++ b/rdtools/__init__.py @@ -40,5 +40,9 @@ from rdtools.utilities import robust_median from rdtools.utilities import robust_mean -from . import _version -__version__ = _version.get_versions()['version'] +from importlib.metadata import version, PackageNotFoundError + +try: + __version__ = version("rdtools") +except PackageNotFoundError: + __version__ = "0+unknown" diff --git a/rdtools/_version.py b/rdtools/_version.py deleted file mode 100644 index 2656d62e8..000000000 --- a/rdtools/_version.py +++ /dev/null @@ -1,683 +0,0 @@ - -# This file helps to compute a version number in source trees obtained from -# git-archive tarball (such as those provided by githubs download-from-tag -# feature). Distribution tarballs (built by setup.py sdist) and build -# directories (produced by setup.py build) will contain a much shorter file -# that just contains the computed version number. - -# This file is released into the public domain. -# Generated by versioneer-0.29 -# https://github.com/python-versioneer/python-versioneer - -"""Git implementation of _version.py.""" - -import errno -import os -import re -import subprocess -import sys -from typing import Any, Callable, Dict, List, Optional, Tuple -import functools - - -def get_keywords() -> Dict[str, str]: - """Get the keywords needed to look up the version information.""" - # these strings will be replaced by git during git-archive. - # setup.py/versioneer.py will grep for the variable names, so they must - # each be defined on a line of their own. _version.py will just call - # get_keywords(). - git_refnames = "$Format:%d$" - git_full = "$Format:%H$" - git_date = "$Format:%ci$" - keywords = {"refnames": git_refnames, "full": git_full, "date": git_date} - return keywords - - -class VersioneerConfig: - """Container for Versioneer configuration parameters.""" - - VCS: str - style: str - tag_prefix: str - parentdir_prefix: str - versionfile_source: str - verbose: bool - - -def get_config() -> VersioneerConfig: - """Create, populate and return the VersioneerConfig() object.""" - # these strings are filled in when 'setup.py versioneer' creates - # _version.py - cfg = VersioneerConfig() - cfg.VCS = "git" - cfg.style = "pep440" - cfg.tag_prefix = "" - cfg.parentdir_prefix = "rdtools-" - cfg.versionfile_source = "rdtools/_version.py" - cfg.verbose = False - return cfg - - -class NotThisMethod(Exception): - """Exception raised if a method is not valid for the current scenario.""" - - -LONG_VERSION_PY: Dict[str, str] = {} -HANDLERS: Dict[str, Dict[str, Callable]] = {} - - -def register_vcs_handler(vcs: str, method: str) -> Callable: # decorator - """Create decorator to mark a method as the handler of a VCS.""" - def decorate(f: Callable) -> Callable: - """Store f in HANDLERS[vcs][method].""" - if vcs not in HANDLERS: - HANDLERS[vcs] = {} - HANDLERS[vcs][method] = f - return f - return decorate - - -def run_command( - commands: List[str], - args: List[str], - cwd: Optional[str] = None, - verbose: bool = False, - hide_stderr: bool = False, - env: Optional[Dict[str, str]] = None, -) -> Tuple[Optional[str], Optional[int]]: - """Call the given command(s).""" - assert isinstance(commands, list) - process = None - - popen_kwargs: Dict[str, Any] = {} - if sys.platform == "win32": - # This hides the console window if pythonw.exe is used - startupinfo = subprocess.STARTUPINFO() - startupinfo.dwFlags |= subprocess.STARTF_USESHOWWINDOW - popen_kwargs["startupinfo"] = startupinfo - - for command in commands: - try: - dispcmd = str([command] + args) - # remember shell=False, so use git.cmd on windows, not just git - process = subprocess.Popen([command] + args, cwd=cwd, env=env, - stdout=subprocess.PIPE, - stderr=(subprocess.PIPE if hide_stderr - else None), **popen_kwargs) - break - except OSError as e: - if e.errno == errno.ENOENT: - continue - if verbose: - print("unable to run %s" % dispcmd) - print(e) - return None, None - else: - if verbose: - print("unable to find command, tried %s" % (commands,)) - return None, None - stdout = process.communicate()[0].strip().decode() - if process.returncode != 0: - if verbose: - print("unable to run %s (error)" % dispcmd) - print("stdout was %s" % stdout) - return None, process.returncode - return stdout, process.returncode - - -def versions_from_parentdir( - parentdir_prefix: str, - root: str, - verbose: bool, -) -> Dict[str, Any]: - """Try to determine the version from the parent directory name. - - Source tarballs conventionally unpack into a directory that includes both - the project name and a version string. We will also support searching up - two directory levels for an appropriately named parent directory - """ - rootdirs = [] - - for _ in range(3): - dirname = os.path.basename(root) - if dirname.startswith(parentdir_prefix): - return {"version": dirname[len(parentdir_prefix):], - "full-revisionid": None, - "dirty": False, "error": None, "date": None} - rootdirs.append(root) - root = os.path.dirname(root) # up a level - - if verbose: - print("Tried directories %s but none started with prefix %s" % - (str(rootdirs), parentdir_prefix)) - raise NotThisMethod("rootdir doesn't start with parentdir_prefix") - - -@register_vcs_handler("git", "get_keywords") -def git_get_keywords(versionfile_abs: str) -> Dict[str, str]: - """Extract version information from the given file.""" - # the code embedded in _version.py can just fetch the value of these - # keywords. When used from setup.py, we don't want to import _version.py, - # so we do it with a regexp instead. This function is not used from - # _version.py. - keywords: Dict[str, str] = {} - try: - with open(versionfile_abs, "r") as fobj: - for line in fobj: - if line.strip().startswith("git_refnames ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["refnames"] = mo.group(1) - if line.strip().startswith("git_full ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["full"] = mo.group(1) - if line.strip().startswith("git_date ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["date"] = mo.group(1) - except OSError: - pass - return keywords - - -@register_vcs_handler("git", "keywords") -def git_versions_from_keywords( - keywords: Dict[str, str], - tag_prefix: str, - verbose: bool, -) -> Dict[str, Any]: - """Get version information from git keywords.""" - if "refnames" not in keywords: - raise NotThisMethod("Short version file found") - date = keywords.get("date") - if date is not None: - # Use only the last line. Previous lines may contain GPG signature - # information. - date = date.splitlines()[-1] - - # git-2.2.0 added "%cI", which expands to an ISO-8601 -compliant - # datestamp. However we prefer "%ci" (which expands to an "ISO-8601 - # -like" string, which we must then edit to make compliant), because - # it's been around since git-1.5.3, and it's too difficult to - # discover which version we're using, or to work around using an - # older one. - date = date.strip().replace(" ", "T", 1).replace(" ", "", 1) - refnames = keywords["refnames"].strip() - if refnames.startswith("$Format"): - if verbose: - print("keywords are unexpanded, not using") - raise NotThisMethod("unexpanded keywords, not a git-archive tarball") - refs = {r.strip() for r in refnames.strip("()").split(",")} - # starting in git-1.8.3, tags are listed as "tag: foo-1.0" instead of - # just "foo-1.0". If we see a "tag: " prefix, prefer those. - TAG = "tag: " - tags = {r[len(TAG):] for r in refs if r.startswith(TAG)} - if not tags: - # Either we're using git < 1.8.3, or there really are no tags. We use - # a heuristic: assume all version tags have a digit. The old git %d - # expansion behaves like git log --decorate=short and strips out the - # refs/heads/ and refs/tags/ prefixes that would let us distinguish - # between branches and tags. By ignoring refnames without digits, we - # filter out many common branch names like "release" and - # "stabilization", as well as "HEAD" and "master". - tags = {r for r in refs if re.search(r'\d', r)} - if verbose: - print("discarding '%s', no digits" % ",".join(refs - tags)) - if verbose: - print("likely tags: %s" % ",".join(sorted(tags))) - for ref in sorted(tags): - # sorting will prefer e.g. "2.0" over "2.0rc1" - if ref.startswith(tag_prefix): - r = ref[len(tag_prefix):] - # Filter out refs that exactly match prefix or that don't start - # with a number once the prefix is stripped (mostly a concern - # when prefix is '') - if not re.match(r'\d', r): - continue - if verbose: - print("picking %s" % r) - return {"version": r, - "full-revisionid": keywords["full"].strip(), - "dirty": False, "error": None, - "date": date} - # no suitable tags, so version is "0+unknown", but full hex is still there - if verbose: - print("no suitable tags, using unknown + full revision id") - return {"version": "0+unknown", - "full-revisionid": keywords["full"].strip(), - "dirty": False, "error": "no suitable tags", "date": None} - - -@register_vcs_handler("git", "pieces_from_vcs") -def git_pieces_from_vcs( - tag_prefix: str, - root: str, - verbose: bool, - runner: Callable = run_command -) -> Dict[str, Any]: - """Get version from 'git describe' in the root of the source tree. - - This only gets called if the git-archive 'subst' keywords were *not* - expanded, and _version.py hasn't already been rewritten with a short - version string, meaning we're inside a checked out source tree. - """ - GITS = ["git"] - if sys.platform == "win32": - GITS = ["git.cmd", "git.exe"] - - # GIT_DIR can interfere with correct operation of Versioneer. - # It may be intended to be passed to the Versioneer-versioned project, - # but that should not change where we get our version from. - env = os.environ.copy() - env.pop("GIT_DIR", None) - runner = functools.partial(runner, env=env) - - _, rc = runner(GITS, ["rev-parse", "--git-dir"], cwd=root, - hide_stderr=not verbose) - if rc != 0: - if verbose: - print("Directory %s not under git control" % root) - raise NotThisMethod("'git rev-parse --git-dir' returned error") - - # if there is a tag matching tag_prefix, this yields TAG-NUM-gHEX[-dirty] - # if there isn't one, this yields HEX[-dirty] (no NUM) - describe_out, rc = runner(GITS, [ - "describe", "--tags", "--dirty", "--always", "--long", - "--match", f"{tag_prefix}[[:digit:]]*" - ], cwd=root) - # --long was added in git-1.5.5 - if describe_out is None: - raise NotThisMethod("'git describe' failed") - describe_out = describe_out.strip() - full_out, rc = runner(GITS, ["rev-parse", "HEAD"], cwd=root) - if full_out is None: - raise NotThisMethod("'git rev-parse' failed") - full_out = full_out.strip() - - pieces: Dict[str, Any] = {} - pieces["long"] = full_out - pieces["short"] = full_out[:7] # maybe improved later - pieces["error"] = None - - branch_name, rc = runner(GITS, ["rev-parse", "--abbrev-ref", "HEAD"], - cwd=root) - # --abbrev-ref was added in git-1.6.3 - if rc != 0 or branch_name is None: - raise NotThisMethod("'git rev-parse --abbrev-ref' returned error") - branch_name = branch_name.strip() - - if branch_name == "HEAD": - # If we aren't exactly on a branch, pick a branch which represents - # the current commit. If all else fails, we are on a branchless - # commit. - branches, rc = runner(GITS, ["branch", "--contains"], cwd=root) - # --contains was added in git-1.5.4 - if rc != 0 or branches is None: - raise NotThisMethod("'git branch --contains' returned error") - branches = branches.split("\n") - - # Remove the first line if we're running detached - if "(" in branches[0]: - branches.pop(0) - - # Strip off the leading "* " from the list of branches. - branches = [branch[2:] for branch in branches] - if "master" in branches: - branch_name = "master" - elif not branches: - branch_name = None - else: - # Pick the first branch that is returned. Good or bad. - branch_name = branches[0] - - pieces["branch"] = branch_name - - # parse describe_out. It will be like TAG-NUM-gHEX[-dirty] or HEX[-dirty] - # TAG might have hyphens. - git_describe = describe_out - - # look for -dirty suffix - dirty = git_describe.endswith("-dirty") - pieces["dirty"] = dirty - if dirty: - git_describe = git_describe[:git_describe.rindex("-dirty")] - - # now we have TAG-NUM-gHEX or HEX - - if "-" in git_describe: - # TAG-NUM-gHEX - mo = re.search(r'^(.+)-(\d+)-g([0-9a-f]+)$', git_describe) - if not mo: - # unparsable. Maybe git-describe is misbehaving? - pieces["error"] = ("unable to parse git-describe output: '%s'" - % describe_out) - return pieces - - # tag - full_tag = mo.group(1) - if not full_tag.startswith(tag_prefix): - if verbose: - fmt = "tag '%s' doesn't start with prefix '%s'" - print(fmt % (full_tag, tag_prefix)) - pieces["error"] = ("tag '%s' doesn't start with prefix '%s'" - % (full_tag, tag_prefix)) - return pieces - pieces["closest-tag"] = full_tag[len(tag_prefix):] - - # distance: number of commits since tag - pieces["distance"] = int(mo.group(2)) - - # commit: short hex revision ID - pieces["short"] = mo.group(3) - - else: - # HEX: no tags - pieces["closest-tag"] = None - out, rc = runner(GITS, ["rev-list", "HEAD", "--left-right"], cwd=root) - pieces["distance"] = len(out.split()) # total number of commits - - # commit date: see ISO-8601 comment in git_versions_from_keywords() - date = runner(GITS, ["show", "-s", "--format=%ci", "HEAD"], cwd=root)[0].strip() - # Use only the last line. Previous lines may contain GPG signature - # information. - date = date.splitlines()[-1] - pieces["date"] = date.strip().replace(" ", "T", 1).replace(" ", "", 1) - - return pieces - - -def plus_or_dot(pieces: Dict[str, Any]) -> str: - """Return a + if we don't already have one, else return a .""" - if "+" in pieces.get("closest-tag", ""): - return "." - return "+" - - -def render_pep440(pieces: Dict[str, Any]) -> str: - """Build up version string, with post-release "local version identifier". - - Our goal: TAG[+DISTANCE.gHEX[.dirty]] . Note that if you - get a tagged build and then dirty it, you'll get TAG+0.gHEX.dirty - - Exceptions: - 1: no tags. git_describe was just HEX. 0+untagged.DISTANCE.gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += plus_or_dot(pieces) - rendered += "%d.g%s" % (pieces["distance"], pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0+untagged.%d.g%s" % (pieces["distance"], - pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def render_pep440_branch(pieces: Dict[str, Any]) -> str: - """TAG[[.dev0]+DISTANCE.gHEX[.dirty]] . - - The ".dev0" means not master branch. Note that .dev0 sorts backwards - (a feature branch will appear "older" than the master branch). - - Exceptions: - 1: no tags. 0[.dev0]+untagged.DISTANCE.gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "%d.g%s" % (pieces["distance"], pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0" - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += "+untagged.%d.g%s" % (pieces["distance"], - pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def pep440_split_post(ver: str) -> Tuple[str, Optional[int]]: - """Split pep440 version string at the post-release segment. - - Returns the release segments before the post-release and the - post-release version number (or -1 if no post-release segment is present). - """ - vc = str.split(ver, ".post") - return vc[0], int(vc[1] or 0) if len(vc) == 2 else None - - -def render_pep440_pre(pieces: Dict[str, Any]) -> str: - """TAG[.postN.devDISTANCE] -- No -dirty. - - Exceptions: - 1: no tags. 0.post0.devDISTANCE - """ - if pieces["closest-tag"]: - if pieces["distance"]: - # update the post release segment - tag_version, post_version = pep440_split_post(pieces["closest-tag"]) - rendered = tag_version - if post_version is not None: - rendered += ".post%d.dev%d" % (post_version + 1, pieces["distance"]) - else: - rendered += ".post0.dev%d" % (pieces["distance"]) - else: - # no commits, use the tag as the version - rendered = pieces["closest-tag"] - else: - # exception #1 - rendered = "0.post0.dev%d" % pieces["distance"] - return rendered - - -def render_pep440_post(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]+gHEX] . - - The ".dev0" means dirty. Note that .dev0 sorts backwards - (a dirty tree will appear "older" than the corresponding clean one), - but you shouldn't be releasing software with -dirty anyways. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "g%s" % pieces["short"] - else: - # exception #1 - rendered = "0.post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - rendered += "+g%s" % pieces["short"] - return rendered - - -def render_pep440_post_branch(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]+gHEX[.dirty]] . - - The ".dev0" means not master branch. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0]+gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%d" % pieces["distance"] - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "g%s" % pieces["short"] - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0.post%d" % pieces["distance"] - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += "+g%s" % pieces["short"] - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def render_pep440_old(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]] . - - The ".dev0" means dirty. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - else: - # exception #1 - rendered = "0.post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - return rendered - - -def render_git_describe(pieces: Dict[str, Any]) -> str: - """TAG[-DISTANCE-gHEX][-dirty]. - - Like 'git describe --tags --dirty --always'. - - Exceptions: - 1: no tags. HEX[-dirty] (note: no 'g' prefix) - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"]: - rendered += "-%d-g%s" % (pieces["distance"], pieces["short"]) - else: - # exception #1 - rendered = pieces["short"] - if pieces["dirty"]: - rendered += "-dirty" - return rendered - - -def render_git_describe_long(pieces: Dict[str, Any]) -> str: - """TAG-DISTANCE-gHEX[-dirty]. - - Like 'git describe --tags --dirty --always -long'. - The distance/hash is unconditional. - - Exceptions: - 1: no tags. HEX[-dirty] (note: no 'g' prefix) - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - rendered += "-%d-g%s" % (pieces["distance"], pieces["short"]) - else: - # exception #1 - rendered = pieces["short"] - if pieces["dirty"]: - rendered += "-dirty" - return rendered - - -def render(pieces: Dict[str, Any], style: str) -> Dict[str, Any]: - """Render the given version pieces into the requested style.""" - if pieces["error"]: - return {"version": "unknown", - "full-revisionid": pieces.get("long"), - "dirty": None, - "error": pieces["error"], - "date": None} - - if not style or style == "default": - style = "pep440" # the default - - if style == "pep440": - rendered = render_pep440(pieces) - elif style == "pep440-branch": - rendered = render_pep440_branch(pieces) - elif style == "pep440-pre": - rendered = render_pep440_pre(pieces) - elif style == "pep440-post": - rendered = render_pep440_post(pieces) - elif style == "pep440-post-branch": - rendered = render_pep440_post_branch(pieces) - elif style == "pep440-old": - rendered = render_pep440_old(pieces) - elif style == "git-describe": - rendered = render_git_describe(pieces) - elif style == "git-describe-long": - rendered = render_git_describe_long(pieces) - else: - raise ValueError("unknown style '%s'" % style) - - return {"version": rendered, "full-revisionid": pieces["long"], - "dirty": pieces["dirty"], "error": None, - "date": pieces.get("date")} - - -def get_versions() -> Dict[str, Any]: - """Get version information or return default if unable to do so.""" - # I am in _version.py, which lives at ROOT/VERSIONFILE_SOURCE. If we have - # __file__, we can work backwards from there to the root. Some - # py2exe/bbfreeze/non-CPython implementations don't do __file__, in which - # case we can only use expanded keywords. - - cfg = get_config() - verbose = cfg.verbose - - try: - return git_versions_from_keywords(get_keywords(), cfg.tag_prefix, - verbose) - except NotThisMethod: - pass - - try: - root = os.path.realpath(__file__) - # versionfile_source is the relative path from the top of the source - # tree (where the .git directory might live) to this file. Invert - # this to find the root from __file__. - for _ in cfg.versionfile_source.split('/'): - root = os.path.dirname(root) - except NameError: - return {"version": "0+unknown", "full-revisionid": None, - "dirty": None, - "error": "unable to find root of source tree", - "date": None} - - try: - pieces = git_pieces_from_vcs(cfg.tag_prefix, root, verbose) - return render(pieces, cfg.style) - except NotThisMethod: - pass - - try: - if cfg.parentdir_prefix: - return versions_from_parentdir(cfg.parentdir_prefix, root, verbose) - except NotThisMethod: - pass - - return {"version": "0+unknown", "full-revisionid": None, - "dirty": None, - "error": "unable to compute version", "date": None} diff --git a/rdtools/soiling.py b/rdtools/soiling.py index ef7b2b052..9a49ed9ab 100644 --- a/rdtools/soiling.py +++ b/rdtools/soiling.py @@ -13,8 +13,8 @@ import pandas as pd import numpy as np from scipy.stats.mstats import theilslopes -from filterpy.kalman import KalmanFilter -from filterpy.common import Q_discrete_white_noise +from bayesian_filters.kalman import KalmanFilter +from bayesian_filters.common import Q_discrete_white_noise import itertools import bisect import time @@ -123,7 +123,7 @@ def _calc_daily_df(self, day_scale=13, clean_threshold='infer', warnings.warn('An even value of day_scale was passed. An odd value is ' 'recommended, otherwise, consecutive days may be erroneously ' 'flagged as cleaning events. ' - 'See https://github.com/NREL/rdtools/issues/189', + 'See https://github.com/NatLabRockies/rdtools/issues/189', stacklevel=2) df = self.pm.to_frame() @@ -383,7 +383,7 @@ def _calc_monte(self, monte, method='half_norm_clean'): 'validity criteria such as increasing "max_relative_slope_error" ' 'and/or "max_negative_step" and/or decreasing "min_interval_length".' ' Alternatively, consider using method="perfect_clean". For more' - ' info see https://github.com/NREL/rdtools/issues/272', + ' info see https://github.com/NatLabRockies/rdtools/issues/272', stacklevel=2 ) monte_losses = [] diff --git a/rdtools/test/filtering_test.py b/rdtools/test/filtering_test.py index 586b32165..8a993571a 100644 --- a/rdtools/test/filtering_test.py +++ b/rdtools/test/filtering_test.py @@ -509,7 +509,7 @@ def test_hour_angle_filter(): series = pd.Series([1, 2, 3, 4, 5], index=index) # Define latitude and longitude - lat, lon = 39.7413, -105.1684 # NREL, Golden, CO + lat, lon = 39.7413, -105.1684 # NLR, Golden, CO # Call the function with the test data result = hour_angle_filter(series, lat, lon) diff --git a/rdtools/test/soiling_test.py b/rdtools/test/soiling_test.py index a1a678378..464f6a183 100644 --- a/rdtools/test/soiling_test.py +++ b/rdtools/test/soiling_test.py @@ -212,7 +212,7 @@ def test_soiling_srr_max_negative_slope_error(soiling_normalized_daily, soiling_ def test_soiling_srr_with_nan_interval(soiling_normalized_daily, soiling_insolation): ''' Previous versions had a bug which would have raised an error when an entire interval - was NaN. See https://github.com/NREL/rdtools/issues/129 + was NaN. See https://github.com/NatLabRockies/rdtools/issues/129 ''' reps = 10 normalized_corrupt = soiling_normalized_daily.copy() diff --git a/requirements-min.txt b/requirements-min.txt deleted file mode 100644 index 2362cd30e..000000000 --- a/requirements-min.txt +++ /dev/null @@ -1,12 +0,0 @@ -matplotlib==3.5.3 -numpy==1.22.4 -pandas==1.4.4 -statsmodels==0.13.5 -scipy==1.8.1 -h5py==3.7.0 -plotly==4.0.0 -xgboost==1.7.0.post0 -pvlib==0.13.1 -scikit-learn==1.1.3 -arch==5.6 -filterpy==1.4.5 diff --git a/requirements.txt b/requirements.txt deleted file mode 100644 index f1a4f7f92..000000000 --- a/requirements.txt +++ /dev/null @@ -1,35 +0,0 @@ -cached-property==1.5.2 -certifi==2024.7.4 -chardet==5.2.0 -cycler==0.12.1 -fonttools==4.58.4 -h5py==3.12.0 -idna==3.8 -joblib==1.5.2 -kiwisolver==1.4.6 -matplotlib==3.9.4 -numpy==2.1.1 -packaging==26.0 -pandas==2.2.3 -patsy==1.0.0 -Pillow==12.1.1 -plotly==6.1.1 -pvlib==0.14.0 -pyparsing==3.2.0 -python-dateutil==2.9.0 -pytz==2025.2 -arch==7.0.0 -filterpy==1.4.5 -requests==2.32.4 -retrying==1.3.4 -scikit-learn==1.7.2 -scipy==1.14.1 -setuptools-scm==9.2.2 -six==1.17.0 -statsmodels==0.14.6 -threadpoolctl==3.6.0 -tomli==2.0.2 -typing_extensions==4.15.0 -urllib3==2.6.3 -xgboost==3.1.3 - diff --git a/setup.cfg b/setup.cfg deleted file mode 100644 index 36500c527..000000000 --- a/setup.cfg +++ /dev/null @@ -1,28 +0,0 @@ -# See the docstring in versioneer.py for instructions. Note that you must -# re-run 'versioneer.py setup' after changing this section, and commit the -# resulting files. - -[versioneer] -VCS = git -style = pep440 -versionfile_source = rdtools/_version.py -versionfile_build = rdtools/_version.py -tag_prefix = '' -parentdir_prefix = rdtools- - -[metadata] -description-file = README.md - - -[bdist_wheel] -universal = 1 - -[aliases] -test = pytest - -[tool:pytest] -addopts = --verbose -# suppress warnings. syntax is "action:message:category:module:lineno" -# https://docs.python.org/3/library/warnings.html#the-warnings-filter -filterwarnings = - ignore:The .* module is currently experimental:UserWarning:rdtools diff --git a/setup.py b/setup.py deleted file mode 100755 index eecd211ca..000000000 --- a/setup.py +++ /dev/null @@ -1,133 +0,0 @@ -#!/usr/bin/env python - -try: - from setuptools import setup -except ImportError: - raise RuntimeError('setuptools is required') - - -import versioneer - - -DESCRIPTION = 'Functions for reproducible timeseries analysis of photovoltaic systems.' - -LONG_DESCRIPTION = """ -RdTools is an open-source library to support reproducible technical analysis of -PV time series data. The library aims to provide best practice analysis -routines along with the building blocks for users to tailor their own analyses. - -Source code: https://github.com/NREL/rdtools -""" - -DISTNAME = 'rdtools' -LICENSE = 'MIT' -AUTHOR = 'Rdtools Python Developers' -AUTHOR_EMAIL = 'RdTools@nrel.gov' -MAINTAINER_EMAIL = 'RdTools@nrel.gov' - -URL = 'https://github.com/NREL/rdtools' - -SETUP_REQUIRES = [ - 'pytest-runner', -] - -TESTS_REQUIRE = [ - "pytest >= 3.10.1", - "pytest-cov", - "coverage", - "flake8", - "nbval>=0.10.0", - "pytest-mock", -] - -INSTALL_REQUIRES = [ - "matplotlib >= 3.5.3", - "numpy >= 1.22.4", - "pandas >= 1.4.4", - "statsmodels >= 0.13.5", - "scipy >= 1.8.1", - "h5py >= 3.7.0", - "plotly>=4.0.0", - "xgboost >= 1.7.0.post0", - "pvlib >= 0.13.1", - "scikit-learn >= 1.1.3, != 1.6.0", - "arch >= 5.6", - "filterpy >= 1.4.2", -] - -EXTRAS_REQUIRE = { - "doc": [ - "sphinx==7.4.7", - "nbsphinx==0.9.5", - "nbsphinx-link==1.3.1", - "sphinx_rtd_theme==3.0.1", - "ipython", - # sphinx-gallery used indirectly for nbsphinx thumbnail galleries; see: - # https://nbsphinx.readthedocs.io/en/0.6.0/subdir/gallery.html#Creating-Thumbnail-Galleries - "sphinx-gallery==0.18.0", - ], - "test": TESTS_REQUIRE, -} -EXTRAS_REQUIRE['all'] = sorted(set(sum(EXTRAS_REQUIRE.values(), []))) - - -CLASSIFIERS = [ - "Development Status :: 5 - Production/Stable", - "License :: OSI Approved :: MIT License", - "Operating System :: OS Independent", - "Intended Audience :: Science/Research", - "Programming Language :: Python", - "Programming Language :: Python :: 3", - "Programming Language :: Python :: 3.10", - "Programming Language :: Python :: 3.11", - "Programming Language :: Python :: 3.12", - "Programming Language :: Python :: 3.13", - "Topic :: Scientific/Engineering", -] - -KEYWORDS = [ - 'photovoltaic', - 'solar', - 'analytics', - 'analysis', - 'performance', - 'degradation', - 'PV' -] - -PROJECT_URLS = { - "Bug Tracker": "https://github.com/NREL/rdtools/issues", - "Documentation": "https://rdtools.readthedocs.io/", - "Source Code": "https://github.com/NREL/rdtools", -} - -setuptools_kwargs = { - 'zip_safe': False, - 'scripts': [], - 'include_package_data': True -} - -# set up packages to be installed and extensions to be compiled -PACKAGES = ['rdtools'] - - -setup(name=DISTNAME, - version=versioneer.get_version(), - cmdclass=versioneer.get_cmdclass(), - packages=PACKAGES, - keywords=KEYWORDS, - setup_requires=SETUP_REQUIRES, - tests_require=TESTS_REQUIRE, - install_requires=INSTALL_REQUIRES, - extras_require=EXTRAS_REQUIRE, - description=DESCRIPTION, - long_description=LONG_DESCRIPTION, - author=AUTHOR, - author_email=AUTHOR_EMAIL, - maintainer_email=MAINTAINER_EMAIL, - license=LICENSE, - url=URL, - project_urls=PROJECT_URLS, - classifiers=CLASSIFIERS, - python_requires='>=3.10', - **setuptools_kwargs) diff --git a/versioneer.py b/versioneer.py deleted file mode 100644 index 1e3753e63..000000000 --- a/versioneer.py +++ /dev/null @@ -1,2277 +0,0 @@ - -# Version: 0.29 - -"""The Versioneer - like a rocketeer, but for versions. - -The Versioneer -============== - -* like a rocketeer, but for versions! -* https://github.com/python-versioneer/python-versioneer -* Brian Warner -* License: Public Domain (Unlicense) -* Compatible with: Python 3.7, 3.8, 3.9, 3.10, 3.11 and pypy3 -* [![Latest Version][pypi-image]][pypi-url] -* [![Build Status][travis-image]][travis-url] - -This is a tool for managing a recorded version number in setuptools-based -python projects. The goal is to remove the tedious and error-prone "update -the embedded version string" step from your release process. Making a new -release should be as easy as recording a new tag in your version-control -system, and maybe making new tarballs. - - -## Quick Install - -Versioneer provides two installation modes. The "classic" vendored mode installs -a copy of versioneer into your repository. The experimental build-time dependency mode -is intended to allow you to skip this step and simplify the process of upgrading. - -### Vendored mode - -* `pip install versioneer` to somewhere in your $PATH - * A [conda-forge recipe](https://github.com/conda-forge/versioneer-feedstock) is - available, so you can also use `conda install -c conda-forge versioneer` -* add a `[tool.versioneer]` section to your `pyproject.toml` or a - `[versioneer]` section to your `setup.cfg` (see [Install](INSTALL.md)) - * Note that you will need to add `tomli; python_version < "3.11"` to your - build-time dependencies if you use `pyproject.toml` -* run `versioneer install --vendor` in your source tree, commit the results -* verify version information with `python setup.py version` - -### Build-time dependency mode - -* `pip install versioneer` to somewhere in your $PATH - * A [conda-forge recipe](https://github.com/conda-forge/versioneer-feedstock) is - available, so you can also use `conda install -c conda-forge versioneer` -* add a `[tool.versioneer]` section to your `pyproject.toml` or a - `[versioneer]` section to your `setup.cfg` (see [Install](INSTALL.md)) -* add `versioneer` (with `[toml]` extra, if configuring in `pyproject.toml`) - to the `requires` key of the `build-system` table in `pyproject.toml`: - ```toml - [build-system] - requires = ["setuptools", "versioneer[toml]"] - build-backend = "setuptools.build_meta" - ``` -* run `versioneer install --no-vendor` in your source tree, commit the results -* verify version information with `python setup.py version` - -## Version Identifiers - -Source trees come from a variety of places: - -* a version-control system checkout (mostly used by developers) -* a nightly tarball, produced by build automation -* a snapshot tarball, produced by a web-based VCS browser, like github's - "tarball from tag" feature -* a release tarball, produced by "setup.py sdist", distributed through PyPI - -Within each source tree, the version identifier (either a string or a number, -this tool is format-agnostic) can come from a variety of places: - -* ask the VCS tool itself, e.g. "git describe" (for checkouts), which knows - about recent "tags" and an absolute revision-id -* the name of the directory into which the tarball was unpacked -* an expanded VCS keyword ($Id$, etc) -* a `_version.py` created by some earlier build step - -For released software, the version identifier is closely related to a VCS -tag. Some projects use tag names that include more than just the version -string (e.g. "myproject-1.2" instead of just "1.2"), in which case the tool -needs to strip the tag prefix to extract the version identifier. For -unreleased software (between tags), the version identifier should provide -enough information to help developers recreate the same tree, while also -giving them an idea of roughly how old the tree is (after version 1.2, before -version 1.3). Many VCS systems can report a description that captures this, -for example `git describe --tags --dirty --always` reports things like -"0.7-1-g574ab98-dirty" to indicate that the checkout is one revision past the -0.7 tag, has a unique revision id of "574ab98", and is "dirty" (it has -uncommitted changes). - -The version identifier is used for multiple purposes: - -* to allow the module to self-identify its version: `myproject.__version__` -* to choose a name and prefix for a 'setup.py sdist' tarball - -## Theory of Operation - -Versioneer works by adding a special `_version.py` file into your source -tree, where your `__init__.py` can import it. This `_version.py` knows how to -dynamically ask the VCS tool for version information at import time. - -`_version.py` also contains `$Revision$` markers, and the installation -process marks `_version.py` to have this marker rewritten with a tag name -during the `git archive` command. As a result, generated tarballs will -contain enough information to get the proper version. - -To allow `setup.py` to compute a version too, a `versioneer.py` is added to -the top level of your source tree, next to `setup.py` and the `setup.cfg` -that configures it. This overrides several distutils/setuptools commands to -compute the version when invoked, and changes `setup.py build` and `setup.py -sdist` to replace `_version.py` with a small static file that contains just -the generated version data. - -## Installation - -See [INSTALL.md](./INSTALL.md) for detailed installation instructions. - -## Version-String Flavors - -Code which uses Versioneer can learn about its version string at runtime by -importing `_version` from your main `__init__.py` file and running the -`get_versions()` function. From the "outside" (e.g. in `setup.py`), you can -import the top-level `versioneer.py` and run `get_versions()`. - -Both functions return a dictionary with different flavors of version -information: - -* `['version']`: A condensed version string, rendered using the selected - style. This is the most commonly used value for the project's version - string. The default "pep440" style yields strings like `0.11`, - `0.11+2.g1076c97`, or `0.11+2.g1076c97.dirty`. See the "Styles" section - below for alternative styles. - -* `['full-revisionid']`: detailed revision identifier. For Git, this is the - full SHA1 commit id, e.g. "1076c978a8d3cfc70f408fe5974aa6c092c949ac". - -* `['date']`: Date and time of the latest `HEAD` commit. For Git, it is the - commit date in ISO 8601 format. This will be None if the date is not - available. - -* `['dirty']`: a boolean, True if the tree has uncommitted changes. Note that - this is only accurate if run in a VCS checkout, otherwise it is likely to - be False or None - -* `['error']`: if the version string could not be computed, this will be set - to a string describing the problem, otherwise it will be None. It may be - useful to throw an exception in setup.py if this is set, to avoid e.g. - creating tarballs with a version string of "unknown". - -Some variants are more useful than others. Including `full-revisionid` in a -bug report should allow developers to reconstruct the exact code being tested -(or indicate the presence of local changes that should be shared with the -developers). `version` is suitable for display in an "about" box or a CLI -`--version` output: it can be easily compared against release notes and lists -of bugs fixed in various releases. - -The installer adds the following text to your `__init__.py` to place a basic -version in `YOURPROJECT.__version__`: - - from ._version import get_versions - __version__ = get_versions()['version'] - del get_versions - -## Styles - -The setup.cfg `style=` configuration controls how the VCS information is -rendered into a version string. - -The default style, "pep440", produces a PEP440-compliant string, equal to the -un-prefixed tag name for actual releases, and containing an additional "local -version" section with more detail for in-between builds. For Git, this is -TAG[+DISTANCE.gHEX[.dirty]] , using information from `git describe --tags ---dirty --always`. For example "0.11+2.g1076c97.dirty" indicates that the -tree is like the "1076c97" commit but has uncommitted changes (".dirty"), and -that this commit is two revisions ("+2") beyond the "0.11" tag. For released -software (exactly equal to a known tag), the identifier will only contain the -stripped tag, e.g. "0.11". - -Other styles are available. See [details.md](details.md) in the Versioneer -source tree for descriptions. - -## Debugging - -Versioneer tries to avoid fatal errors: if something goes wrong, it will tend -to return a version of "0+unknown". To investigate the problem, run `setup.py -version`, which will run the version-lookup code in a verbose mode, and will -display the full contents of `get_versions()` (including the `error` string, -which may help identify what went wrong). - -## Known Limitations - -Some situations are known to cause problems for Versioneer. This details the -most significant ones. More can be found on Github -[issues page](https://github.com/python-versioneer/python-versioneer/issues). - -### Subprojects - -Versioneer has limited support for source trees in which `setup.py` is not in -the root directory (e.g. `setup.py` and `.git/` are *not* siblings). The are -two common reasons why `setup.py` might not be in the root: - -* Source trees which contain multiple subprojects, such as - [Buildbot](https://github.com/buildbot/buildbot), which contains both - "master" and "slave" subprojects, each with their own `setup.py`, - `setup.cfg`, and `tox.ini`. Projects like these produce multiple PyPI - distributions (and upload multiple independently-installable tarballs). -* Source trees whose main purpose is to contain a C library, but which also - provide bindings to Python (and perhaps other languages) in subdirectories. - -Versioneer will look for `.git` in parent directories, and most operations -should get the right version string. However `pip` and `setuptools` have bugs -and implementation details which frequently cause `pip install .` from a -subproject directory to fail to find a correct version string (so it usually -defaults to `0+unknown`). - -`pip install --editable .` should work correctly. `setup.py install` might -work too. - -Pip-8.1.1 is known to have this problem, but hopefully it will get fixed in -some later version. - -[Bug #38](https://github.com/python-versioneer/python-versioneer/issues/38) is tracking -this issue. The discussion in -[PR #61](https://github.com/python-versioneer/python-versioneer/pull/61) describes the -issue from the Versioneer side in more detail. -[pip PR#3176](https://github.com/pypa/pip/pull/3176) and -[pip PR#3615](https://github.com/pypa/pip/pull/3615) contain work to improve -pip to let Versioneer work correctly. - -Versioneer-0.16 and earlier only looked for a `.git` directory next to the -`setup.cfg`, so subprojects were completely unsupported with those releases. - -### Editable installs with setuptools <= 18.5 - -`setup.py develop` and `pip install --editable .` allow you to install a -project into a virtualenv once, then continue editing the source code (and -test) without re-installing after every change. - -"Entry-point scripts" (`setup(entry_points={"console_scripts": ..})`) are a -convenient way to specify executable scripts that should be installed along -with the python package. - -These both work as expected when using modern setuptools. When using -setuptools-18.5 or earlier, however, certain operations will cause -`pkg_resources.DistributionNotFound` errors when running the entrypoint -script, which must be resolved by re-installing the package. This happens -when the install happens with one version, then the egg_info data is -regenerated while a different version is checked out. Many setup.py commands -cause egg_info to be rebuilt (including `sdist`, `wheel`, and installing into -a different virtualenv), so this can be surprising. - -[Bug #83](https://github.com/python-versioneer/python-versioneer/issues/83) describes -this one, but upgrading to a newer version of setuptools should probably -resolve it. - - -## Updating Versioneer - -To upgrade your project to a new release of Versioneer, do the following: - -* install the new Versioneer (`pip install -U versioneer` or equivalent) -* edit `setup.cfg` and `pyproject.toml`, if necessary, - to include any new configuration settings indicated by the release notes. - See [UPGRADING](./UPGRADING.md) for details. -* re-run `versioneer install --[no-]vendor` in your source tree, to replace - `SRC/_version.py` -* commit any changed files - -## Future Directions - -This tool is designed to make it easily extended to other version-control -systems: all VCS-specific components are in separate directories like -src/git/ . The top-level `versioneer.py` script is assembled from these -components by running make-versioneer.py . In the future, make-versioneer.py -will take a VCS name as an argument, and will construct a version of -`versioneer.py` that is specific to the given VCS. It might also take the -configuration arguments that are currently provided manually during -installation by editing setup.py . Alternatively, it might go the other -direction and include code from all supported VCS systems, reducing the -number of intermediate scripts. - -## Similar projects - -* [setuptools_scm](https://github.com/pypa/setuptools_scm/) - a non-vendored build-time - dependency -* [minver](https://github.com/jbweston/miniver) - a lightweight reimplementation of - versioneer -* [versioningit](https://github.com/jwodder/versioningit) - a PEP 518-based setuptools - plugin - -## License - -To make Versioneer easier to embed, all its code is dedicated to the public -domain. The `_version.py` that it creates is also in the public domain. -Specifically, both are released under the "Unlicense", as described in -https://unlicense.org/. - -[pypi-image]: https://img.shields.io/pypi/v/versioneer.svg -[pypi-url]: https://pypi.python.org/pypi/versioneer/ -[travis-image]: -https://img.shields.io/travis/com/python-versioneer/python-versioneer.svg -[travis-url]: https://travis-ci.com/github/python-versioneer/python-versioneer - -""" -# pylint:disable=invalid-name,import-outside-toplevel,missing-function-docstring -# pylint:disable=missing-class-docstring,too-many-branches,too-many-statements -# pylint:disable=raise-missing-from,too-many-lines,too-many-locals,import-error -# pylint:disable=too-few-public-methods,redefined-outer-name,consider-using-with -# pylint:disable=attribute-defined-outside-init,too-many-arguments - -import configparser -import errno -import json -import os -import re -import subprocess -import sys -from pathlib import Path -from typing import Any, Callable, cast, Dict, List, Optional, Tuple, Union -from typing import NoReturn -import functools - -have_tomllib = True -if sys.version_info >= (3, 11): - import tomllib -else: - try: - import tomli as tomllib - except ImportError: - have_tomllib = False - - -class VersioneerConfig: - """Container for Versioneer configuration parameters.""" - - VCS: str - style: str - tag_prefix: str - versionfile_source: str - versionfile_build: Optional[str] - parentdir_prefix: Optional[str] - verbose: Optional[bool] - - -def get_root() -> str: - """Get the project root directory. - - We require that all commands are run from the project root, i.e. the - directory that contains setup.py, setup.cfg, and versioneer.py . - """ - root = os.path.realpath(os.path.abspath(os.getcwd())) - setup_py = os.path.join(root, "setup.py") - pyproject_toml = os.path.join(root, "pyproject.toml") - versioneer_py = os.path.join(root, "versioneer.py") - if not ( - os.path.exists(setup_py) - or os.path.exists(pyproject_toml) - or os.path.exists(versioneer_py) - ): - # allow 'python path/to/setup.py COMMAND' - root = os.path.dirname(os.path.realpath(os.path.abspath(sys.argv[0]))) - setup_py = os.path.join(root, "setup.py") - pyproject_toml = os.path.join(root, "pyproject.toml") - versioneer_py = os.path.join(root, "versioneer.py") - if not ( - os.path.exists(setup_py) - or os.path.exists(pyproject_toml) - or os.path.exists(versioneer_py) - ): - err = ("Versioneer was unable to run the project root directory. " - "Versioneer requires setup.py to be executed from " - "its immediate directory (like 'python setup.py COMMAND'), " - "or in a way that lets it use sys.argv[0] to find the root " - "(like 'python path/to/setup.py COMMAND').") - raise VersioneerBadRootError(err) - try: - # Certain runtime workflows (setup.py install/develop in a setuptools - # tree) execute all dependencies in a single python process, so - # "versioneer" may be imported multiple times, and python's shared - # module-import table will cache the first one. So we can't use - # os.path.dirname(__file__), as that will find whichever - # versioneer.py was first imported, even in later projects. - my_path = os.path.realpath(os.path.abspath(__file__)) - me_dir = os.path.normcase(os.path.splitext(my_path)[0]) - vsr_dir = os.path.normcase(os.path.splitext(versioneer_py)[0]) - if me_dir != vsr_dir and "VERSIONEER_PEP518" not in globals(): - print("Warning: build in %s is using versioneer.py from %s" - % (os.path.dirname(my_path), versioneer_py)) - except NameError: - pass - return root - - -def get_config_from_root(root: str) -> VersioneerConfig: - """Read the project setup.cfg file to determine Versioneer config.""" - # This might raise OSError (if setup.cfg is missing), or - # configparser.NoSectionError (if it lacks a [versioneer] section), or - # configparser.NoOptionError (if it lacks "VCS="). See the docstring at - # the top of versioneer.py for instructions on writing your setup.cfg . - root_pth = Path(root) - pyproject_toml = root_pth / "pyproject.toml" - setup_cfg = root_pth / "setup.cfg" - section: Union[Dict[str, Any], configparser.SectionProxy, None] = None - if pyproject_toml.exists() and have_tomllib: - try: - with open(pyproject_toml, 'rb') as fobj: - pp = tomllib.load(fobj) - section = pp['tool']['versioneer'] - except (tomllib.TOMLDecodeError, KeyError) as e: - print(f"Failed to load config from {pyproject_toml}: {e}") - print("Try to load it from setup.cfg") - if not section: - parser = configparser.ConfigParser() - with open(setup_cfg) as cfg_file: - parser.read_file(cfg_file) - parser.get("versioneer", "VCS") # raise error if missing - - section = parser["versioneer"] - - # `cast`` really shouldn't be used, but its simplest for the - # common VersioneerConfig users at the moment. We verify against - # `None` values elsewhere where it matters - - cfg = VersioneerConfig() - cfg.VCS = section['VCS'] - cfg.style = section.get("style", "") - cfg.versionfile_source = cast(str, section.get("versionfile_source")) - cfg.versionfile_build = section.get("versionfile_build") - cfg.tag_prefix = cast(str, section.get("tag_prefix")) - if cfg.tag_prefix in ("''", '""', None): - cfg.tag_prefix = "" - cfg.parentdir_prefix = section.get("parentdir_prefix") - if isinstance(section, configparser.SectionProxy): - # Make sure configparser translates to bool - cfg.verbose = section.getboolean("verbose") - else: - cfg.verbose = section.get("verbose") - - return cfg - - -class NotThisMethod(Exception): - """Exception raised if a method is not valid for the current scenario.""" - - -# these dictionaries contain VCS-specific tools -LONG_VERSION_PY: Dict[str, str] = {} -HANDLERS: Dict[str, Dict[str, Callable]] = {} - - -def register_vcs_handler(vcs: str, method: str) -> Callable: # decorator - """Create decorator to mark a method as the handler of a VCS.""" - def decorate(f: Callable) -> Callable: - """Store f in HANDLERS[vcs][method].""" - HANDLERS.setdefault(vcs, {})[method] = f - return f - return decorate - - -def run_command( - commands: List[str], - args: List[str], - cwd: Optional[str] = None, - verbose: bool = False, - hide_stderr: bool = False, - env: Optional[Dict[str, str]] = None, -) -> Tuple[Optional[str], Optional[int]]: - """Call the given command(s).""" - assert isinstance(commands, list) - process = None - - popen_kwargs: Dict[str, Any] = {} - if sys.platform == "win32": - # This hides the console window if pythonw.exe is used - startupinfo = subprocess.STARTUPINFO() - startupinfo.dwFlags |= subprocess.STARTF_USESHOWWINDOW - popen_kwargs["startupinfo"] = startupinfo - - for command in commands: - try: - dispcmd = str([command] + args) - # remember shell=False, so use git.cmd on windows, not just git - process = subprocess.Popen([command] + args, cwd=cwd, env=env, - stdout=subprocess.PIPE, - stderr=(subprocess.PIPE if hide_stderr - else None), **popen_kwargs) - break - except OSError as e: - if e.errno == errno.ENOENT: - continue - if verbose: - print("unable to run %s" % dispcmd) - print(e) - return None, None - else: - if verbose: - print("unable to find command, tried %s" % (commands,)) - return None, None - stdout = process.communicate()[0].strip().decode() - if process.returncode != 0: - if verbose: - print("unable to run %s (error)" % dispcmd) - print("stdout was %s" % stdout) - return None, process.returncode - return stdout, process.returncode - - -LONG_VERSION_PY['git'] = r''' -# This file helps to compute a version number in source trees obtained from -# git-archive tarball (such as those provided by githubs download-from-tag -# feature). Distribution tarballs (built by setup.py sdist) and build -# directories (produced by setup.py build) will contain a much shorter file -# that just contains the computed version number. - -# This file is released into the public domain. -# Generated by versioneer-0.29 -# https://github.com/python-versioneer/python-versioneer - -"""Git implementation of _version.py.""" - -import errno -import os -import re -import subprocess -import sys -from typing import Any, Callable, Dict, List, Optional, Tuple -import functools - - -def get_keywords() -> Dict[str, str]: - """Get the keywords needed to look up the version information.""" - # these strings will be replaced by git during git-archive. - # setup.py/versioneer.py will grep for the variable names, so they must - # each be defined on a line of their own. _version.py will just call - # get_keywords(). - git_refnames = "%(DOLLAR)sFormat:%%d%(DOLLAR)s" - git_full = "%(DOLLAR)sFormat:%%H%(DOLLAR)s" - git_date = "%(DOLLAR)sFormat:%%ci%(DOLLAR)s" - keywords = {"refnames": git_refnames, "full": git_full, "date": git_date} - return keywords - - -class VersioneerConfig: - """Container for Versioneer configuration parameters.""" - - VCS: str - style: str - tag_prefix: str - parentdir_prefix: str - versionfile_source: str - verbose: bool - - -def get_config() -> VersioneerConfig: - """Create, populate and return the VersioneerConfig() object.""" - # these strings are filled in when 'setup.py versioneer' creates - # _version.py - cfg = VersioneerConfig() - cfg.VCS = "git" - cfg.style = "%(STYLE)s" - cfg.tag_prefix = "%(TAG_PREFIX)s" - cfg.parentdir_prefix = "%(PARENTDIR_PREFIX)s" - cfg.versionfile_source = "%(VERSIONFILE_SOURCE)s" - cfg.verbose = False - return cfg - - -class NotThisMethod(Exception): - """Exception raised if a method is not valid for the current scenario.""" - - -LONG_VERSION_PY: Dict[str, str] = {} -HANDLERS: Dict[str, Dict[str, Callable]] = {} - - -def register_vcs_handler(vcs: str, method: str) -> Callable: # decorator - """Create decorator to mark a method as the handler of a VCS.""" - def decorate(f: Callable) -> Callable: - """Store f in HANDLERS[vcs][method].""" - if vcs not in HANDLERS: - HANDLERS[vcs] = {} - HANDLERS[vcs][method] = f - return f - return decorate - - -def run_command( - commands: List[str], - args: List[str], - cwd: Optional[str] = None, - verbose: bool = False, - hide_stderr: bool = False, - env: Optional[Dict[str, str]] = None, -) -> Tuple[Optional[str], Optional[int]]: - """Call the given command(s).""" - assert isinstance(commands, list) - process = None - - popen_kwargs: Dict[str, Any] = {} - if sys.platform == "win32": - # This hides the console window if pythonw.exe is used - startupinfo = subprocess.STARTUPINFO() - startupinfo.dwFlags |= subprocess.STARTF_USESHOWWINDOW - popen_kwargs["startupinfo"] = startupinfo - - for command in commands: - try: - dispcmd = str([command] + args) - # remember shell=False, so use git.cmd on windows, not just git - process = subprocess.Popen([command] + args, cwd=cwd, env=env, - stdout=subprocess.PIPE, - stderr=(subprocess.PIPE if hide_stderr - else None), **popen_kwargs) - break - except OSError as e: - if e.errno == errno.ENOENT: - continue - if verbose: - print("unable to run %%s" %% dispcmd) - print(e) - return None, None - else: - if verbose: - print("unable to find command, tried %%s" %% (commands,)) - return None, None - stdout = process.communicate()[0].strip().decode() - if process.returncode != 0: - if verbose: - print("unable to run %%s (error)" %% dispcmd) - print("stdout was %%s" %% stdout) - return None, process.returncode - return stdout, process.returncode - - -def versions_from_parentdir( - parentdir_prefix: str, - root: str, - verbose: bool, -) -> Dict[str, Any]: - """Try to determine the version from the parent directory name. - - Source tarballs conventionally unpack into a directory that includes both - the project name and a version string. We will also support searching up - two directory levels for an appropriately named parent directory - """ - rootdirs = [] - - for _ in range(3): - dirname = os.path.basename(root) - if dirname.startswith(parentdir_prefix): - return {"version": dirname[len(parentdir_prefix):], - "full-revisionid": None, - "dirty": False, "error": None, "date": None} - rootdirs.append(root) - root = os.path.dirname(root) # up a level - - if verbose: - print("Tried directories %%s but none started with prefix %%s" %% - (str(rootdirs), parentdir_prefix)) - raise NotThisMethod("rootdir doesn't start with parentdir_prefix") - - -@register_vcs_handler("git", "get_keywords") -def git_get_keywords(versionfile_abs: str) -> Dict[str, str]: - """Extract version information from the given file.""" - # the code embedded in _version.py can just fetch the value of these - # keywords. When used from setup.py, we don't want to import _version.py, - # so we do it with a regexp instead. This function is not used from - # _version.py. - keywords: Dict[str, str] = {} - try: - with open(versionfile_abs, "r") as fobj: - for line in fobj: - if line.strip().startswith("git_refnames ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["refnames"] = mo.group(1) - if line.strip().startswith("git_full ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["full"] = mo.group(1) - if line.strip().startswith("git_date ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["date"] = mo.group(1) - except OSError: - pass - return keywords - - -@register_vcs_handler("git", "keywords") -def git_versions_from_keywords( - keywords: Dict[str, str], - tag_prefix: str, - verbose: bool, -) -> Dict[str, Any]: - """Get version information from git keywords.""" - if "refnames" not in keywords: - raise NotThisMethod("Short version file found") - date = keywords.get("date") - if date is not None: - # Use only the last line. Previous lines may contain GPG signature - # information. - date = date.splitlines()[-1] - - # git-2.2.0 added "%%cI", which expands to an ISO-8601 -compliant - # datestamp. However we prefer "%%ci" (which expands to an "ISO-8601 - # -like" string, which we must then edit to make compliant), because - # it's been around since git-1.5.3, and it's too difficult to - # discover which version we're using, or to work around using an - # older one. - date = date.strip().replace(" ", "T", 1).replace(" ", "", 1) - refnames = keywords["refnames"].strip() - if refnames.startswith("$Format"): - if verbose: - print("keywords are unexpanded, not using") - raise NotThisMethod("unexpanded keywords, not a git-archive tarball") - refs = {r.strip() for r in refnames.strip("()").split(",")} - # starting in git-1.8.3, tags are listed as "tag: foo-1.0" instead of - # just "foo-1.0". If we see a "tag: " prefix, prefer those. - TAG = "tag: " - tags = {r[len(TAG):] for r in refs if r.startswith(TAG)} - if not tags: - # Either we're using git < 1.8.3, or there really are no tags. We use - # a heuristic: assume all version tags have a digit. The old git %%d - # expansion behaves like git log --decorate=short and strips out the - # refs/heads/ and refs/tags/ prefixes that would let us distinguish - # between branches and tags. By ignoring refnames without digits, we - # filter out many common branch names like "release" and - # "stabilization", as well as "HEAD" and "master". - tags = {r for r in refs if re.search(r'\d', r)} - if verbose: - print("discarding '%%s', no digits" %% ",".join(refs - tags)) - if verbose: - print("likely tags: %%s" %% ",".join(sorted(tags))) - for ref in sorted(tags): - # sorting will prefer e.g. "2.0" over "2.0rc1" - if ref.startswith(tag_prefix): - r = ref[len(tag_prefix):] - # Filter out refs that exactly match prefix or that don't start - # with a number once the prefix is stripped (mostly a concern - # when prefix is '') - if not re.match(r'\d', r): - continue - if verbose: - print("picking %%s" %% r) - return {"version": r, - "full-revisionid": keywords["full"].strip(), - "dirty": False, "error": None, - "date": date} - # no suitable tags, so version is "0+unknown", but full hex is still there - if verbose: - print("no suitable tags, using unknown + full revision id") - return {"version": "0+unknown", - "full-revisionid": keywords["full"].strip(), - "dirty": False, "error": "no suitable tags", "date": None} - - -@register_vcs_handler("git", "pieces_from_vcs") -def git_pieces_from_vcs( - tag_prefix: str, - root: str, - verbose: bool, - runner: Callable = run_command -) -> Dict[str, Any]: - """Get version from 'git describe' in the root of the source tree. - - This only gets called if the git-archive 'subst' keywords were *not* - expanded, and _version.py hasn't already been rewritten with a short - version string, meaning we're inside a checked out source tree. - """ - GITS = ["git"] - if sys.platform == "win32": - GITS = ["git.cmd", "git.exe"] - - # GIT_DIR can interfere with correct operation of Versioneer. - # It may be intended to be passed to the Versioneer-versioned project, - # but that should not change where we get our version from. - env = os.environ.copy() - env.pop("GIT_DIR", None) - runner = functools.partial(runner, env=env) - - _, rc = runner(GITS, ["rev-parse", "--git-dir"], cwd=root, - hide_stderr=not verbose) - if rc != 0: - if verbose: - print("Directory %%s not under git control" %% root) - raise NotThisMethod("'git rev-parse --git-dir' returned error") - - # if there is a tag matching tag_prefix, this yields TAG-NUM-gHEX[-dirty] - # if there isn't one, this yields HEX[-dirty] (no NUM) - describe_out, rc = runner(GITS, [ - "describe", "--tags", "--dirty", "--always", "--long", - "--match", f"{tag_prefix}[[:digit:]]*" - ], cwd=root) - # --long was added in git-1.5.5 - if describe_out is None: - raise NotThisMethod("'git describe' failed") - describe_out = describe_out.strip() - full_out, rc = runner(GITS, ["rev-parse", "HEAD"], cwd=root) - if full_out is None: - raise NotThisMethod("'git rev-parse' failed") - full_out = full_out.strip() - - pieces: Dict[str, Any] = {} - pieces["long"] = full_out - pieces["short"] = full_out[:7] # maybe improved later - pieces["error"] = None - - branch_name, rc = runner(GITS, ["rev-parse", "--abbrev-ref", "HEAD"], - cwd=root) - # --abbrev-ref was added in git-1.6.3 - if rc != 0 or branch_name is None: - raise NotThisMethod("'git rev-parse --abbrev-ref' returned error") - branch_name = branch_name.strip() - - if branch_name == "HEAD": - # If we aren't exactly on a branch, pick a branch which represents - # the current commit. If all else fails, we are on a branchless - # commit. - branches, rc = runner(GITS, ["branch", "--contains"], cwd=root) - # --contains was added in git-1.5.4 - if rc != 0 or branches is None: - raise NotThisMethod("'git branch --contains' returned error") - branches = branches.split("\n") - - # Remove the first line if we're running detached - if "(" in branches[0]: - branches.pop(0) - - # Strip off the leading "* " from the list of branches. - branches = [branch[2:] for branch in branches] - if "master" in branches: - branch_name = "master" - elif not branches: - branch_name = None - else: - # Pick the first branch that is returned. Good or bad. - branch_name = branches[0] - - pieces["branch"] = branch_name - - # parse describe_out. It will be like TAG-NUM-gHEX[-dirty] or HEX[-dirty] - # TAG might have hyphens. - git_describe = describe_out - - # look for -dirty suffix - dirty = git_describe.endswith("-dirty") - pieces["dirty"] = dirty - if dirty: - git_describe = git_describe[:git_describe.rindex("-dirty")] - - # now we have TAG-NUM-gHEX or HEX - - if "-" in git_describe: - # TAG-NUM-gHEX - mo = re.search(r'^(.+)-(\d+)-g([0-9a-f]+)$', git_describe) - if not mo: - # unparsable. Maybe git-describe is misbehaving? - pieces["error"] = ("unable to parse git-describe output: '%%s'" - %% describe_out) - return pieces - - # tag - full_tag = mo.group(1) - if not full_tag.startswith(tag_prefix): - if verbose: - fmt = "tag '%%s' doesn't start with prefix '%%s'" - print(fmt %% (full_tag, tag_prefix)) - pieces["error"] = ("tag '%%s' doesn't start with prefix '%%s'" - %% (full_tag, tag_prefix)) - return pieces - pieces["closest-tag"] = full_tag[len(tag_prefix):] - - # distance: number of commits since tag - pieces["distance"] = int(mo.group(2)) - - # commit: short hex revision ID - pieces["short"] = mo.group(3) - - else: - # HEX: no tags - pieces["closest-tag"] = None - out, rc = runner(GITS, ["rev-list", "HEAD", "--left-right"], cwd=root) - pieces["distance"] = len(out.split()) # total number of commits - - # commit date: see ISO-8601 comment in git_versions_from_keywords() - date = runner(GITS, ["show", "-s", "--format=%%ci", "HEAD"], cwd=root)[0].strip() - # Use only the last line. Previous lines may contain GPG signature - # information. - date = date.splitlines()[-1] - pieces["date"] = date.strip().replace(" ", "T", 1).replace(" ", "", 1) - - return pieces - - -def plus_or_dot(pieces: Dict[str, Any]) -> str: - """Return a + if we don't already have one, else return a .""" - if "+" in pieces.get("closest-tag", ""): - return "." - return "+" - - -def render_pep440(pieces: Dict[str, Any]) -> str: - """Build up version string, with post-release "local version identifier". - - Our goal: TAG[+DISTANCE.gHEX[.dirty]] . Note that if you - get a tagged build and then dirty it, you'll get TAG+0.gHEX.dirty - - Exceptions: - 1: no tags. git_describe was just HEX. 0+untagged.DISTANCE.gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += plus_or_dot(pieces) - rendered += "%%d.g%%s" %% (pieces["distance"], pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0+untagged.%%d.g%%s" %% (pieces["distance"], - pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def render_pep440_branch(pieces: Dict[str, Any]) -> str: - """TAG[[.dev0]+DISTANCE.gHEX[.dirty]] . - - The ".dev0" means not master branch. Note that .dev0 sorts backwards - (a feature branch will appear "older" than the master branch). - - Exceptions: - 1: no tags. 0[.dev0]+untagged.DISTANCE.gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "%%d.g%%s" %% (pieces["distance"], pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0" - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += "+untagged.%%d.g%%s" %% (pieces["distance"], - pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def pep440_split_post(ver: str) -> Tuple[str, Optional[int]]: - """Split pep440 version string at the post-release segment. - - Returns the release segments before the post-release and the - post-release version number (or -1 if no post-release segment is present). - """ - vc = str.split(ver, ".post") - return vc[0], int(vc[1] or 0) if len(vc) == 2 else None - - -def render_pep440_pre(pieces: Dict[str, Any]) -> str: - """TAG[.postN.devDISTANCE] -- No -dirty. - - Exceptions: - 1: no tags. 0.post0.devDISTANCE - """ - if pieces["closest-tag"]: - if pieces["distance"]: - # update the post release segment - tag_version, post_version = pep440_split_post(pieces["closest-tag"]) - rendered = tag_version - if post_version is not None: - rendered += ".post%%d.dev%%d" %% (post_version + 1, pieces["distance"]) - else: - rendered += ".post0.dev%%d" %% (pieces["distance"]) - else: - # no commits, use the tag as the version - rendered = pieces["closest-tag"] - else: - # exception #1 - rendered = "0.post0.dev%%d" %% pieces["distance"] - return rendered - - -def render_pep440_post(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]+gHEX] . - - The ".dev0" means dirty. Note that .dev0 sorts backwards - (a dirty tree will appear "older" than the corresponding clean one), - but you shouldn't be releasing software with -dirty anyways. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%%d" %% pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "g%%s" %% pieces["short"] - else: - # exception #1 - rendered = "0.post%%d" %% pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - rendered += "+g%%s" %% pieces["short"] - return rendered - - -def render_pep440_post_branch(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]+gHEX[.dirty]] . - - The ".dev0" means not master branch. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0]+gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%%d" %% pieces["distance"] - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "g%%s" %% pieces["short"] - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0.post%%d" %% pieces["distance"] - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += "+g%%s" %% pieces["short"] - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def render_pep440_old(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]] . - - The ".dev0" means dirty. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%%d" %% pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - else: - # exception #1 - rendered = "0.post%%d" %% pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - return rendered - - -def render_git_describe(pieces: Dict[str, Any]) -> str: - """TAG[-DISTANCE-gHEX][-dirty]. - - Like 'git describe --tags --dirty --always'. - - Exceptions: - 1: no tags. HEX[-dirty] (note: no 'g' prefix) - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"]: - rendered += "-%%d-g%%s" %% (pieces["distance"], pieces["short"]) - else: - # exception #1 - rendered = pieces["short"] - if pieces["dirty"]: - rendered += "-dirty" - return rendered - - -def render_git_describe_long(pieces: Dict[str, Any]) -> str: - """TAG-DISTANCE-gHEX[-dirty]. - - Like 'git describe --tags --dirty --always -long'. - The distance/hash is unconditional. - - Exceptions: - 1: no tags. HEX[-dirty] (note: no 'g' prefix) - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - rendered += "-%%d-g%%s" %% (pieces["distance"], pieces["short"]) - else: - # exception #1 - rendered = pieces["short"] - if pieces["dirty"]: - rendered += "-dirty" - return rendered - - -def render(pieces: Dict[str, Any], style: str) -> Dict[str, Any]: - """Render the given version pieces into the requested style.""" - if pieces["error"]: - return {"version": "unknown", - "full-revisionid": pieces.get("long"), - "dirty": None, - "error": pieces["error"], - "date": None} - - if not style or style == "default": - style = "pep440" # the default - - if style == "pep440": - rendered = render_pep440(pieces) - elif style == "pep440-branch": - rendered = render_pep440_branch(pieces) - elif style == "pep440-pre": - rendered = render_pep440_pre(pieces) - elif style == "pep440-post": - rendered = render_pep440_post(pieces) - elif style == "pep440-post-branch": - rendered = render_pep440_post_branch(pieces) - elif style == "pep440-old": - rendered = render_pep440_old(pieces) - elif style == "git-describe": - rendered = render_git_describe(pieces) - elif style == "git-describe-long": - rendered = render_git_describe_long(pieces) - else: - raise ValueError("unknown style '%%s'" %% style) - - return {"version": rendered, "full-revisionid": pieces["long"], - "dirty": pieces["dirty"], "error": None, - "date": pieces.get("date")} - - -def get_versions() -> Dict[str, Any]: - """Get version information or return default if unable to do so.""" - # I am in _version.py, which lives at ROOT/VERSIONFILE_SOURCE. If we have - # __file__, we can work backwards from there to the root. Some - # py2exe/bbfreeze/non-CPython implementations don't do __file__, in which - # case we can only use expanded keywords. - - cfg = get_config() - verbose = cfg.verbose - - try: - return git_versions_from_keywords(get_keywords(), cfg.tag_prefix, - verbose) - except NotThisMethod: - pass - - try: - root = os.path.realpath(__file__) - # versionfile_source is the relative path from the top of the source - # tree (where the .git directory might live) to this file. Invert - # this to find the root from __file__. - for _ in cfg.versionfile_source.split('/'): - root = os.path.dirname(root) - except NameError: - return {"version": "0+unknown", "full-revisionid": None, - "dirty": None, - "error": "unable to find root of source tree", - "date": None} - - try: - pieces = git_pieces_from_vcs(cfg.tag_prefix, root, verbose) - return render(pieces, cfg.style) - except NotThisMethod: - pass - - try: - if cfg.parentdir_prefix: - return versions_from_parentdir(cfg.parentdir_prefix, root, verbose) - except NotThisMethod: - pass - - return {"version": "0+unknown", "full-revisionid": None, - "dirty": None, - "error": "unable to compute version", "date": None} -''' - - -@register_vcs_handler("git", "get_keywords") -def git_get_keywords(versionfile_abs: str) -> Dict[str, str]: - """Extract version information from the given file.""" - # the code embedded in _version.py can just fetch the value of these - # keywords. When used from setup.py, we don't want to import _version.py, - # so we do it with a regexp instead. This function is not used from - # _version.py. - keywords: Dict[str, str] = {} - try: - with open(versionfile_abs, "r") as fobj: - for line in fobj: - if line.strip().startswith("git_refnames ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["refnames"] = mo.group(1) - if line.strip().startswith("git_full ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["full"] = mo.group(1) - if line.strip().startswith("git_date ="): - mo = re.search(r'=\s*"(.*)"', line) - if mo: - keywords["date"] = mo.group(1) - except OSError: - pass - return keywords - - -@register_vcs_handler("git", "keywords") -def git_versions_from_keywords( - keywords: Dict[str, str], - tag_prefix: str, - verbose: bool, -) -> Dict[str, Any]: - """Get version information from git keywords.""" - if "refnames" not in keywords: - raise NotThisMethod("Short version file found") - date = keywords.get("date") - if date is not None: - # Use only the last line. Previous lines may contain GPG signature - # information. - date = date.splitlines()[-1] - - # git-2.2.0 added "%cI", which expands to an ISO-8601 -compliant - # datestamp. However we prefer "%ci" (which expands to an "ISO-8601 - # -like" string, which we must then edit to make compliant), because - # it's been around since git-1.5.3, and it's too difficult to - # discover which version we're using, or to work around using an - # older one. - date = date.strip().replace(" ", "T", 1).replace(" ", "", 1) - refnames = keywords["refnames"].strip() - if refnames.startswith("$Format"): - if verbose: - print("keywords are unexpanded, not using") - raise NotThisMethod("unexpanded keywords, not a git-archive tarball") - refs = {r.strip() for r in refnames.strip("()").split(",")} - # starting in git-1.8.3, tags are listed as "tag: foo-1.0" instead of - # just "foo-1.0". If we see a "tag: " prefix, prefer those. - TAG = "tag: " - tags = {r[len(TAG):] for r in refs if r.startswith(TAG)} - if not tags: - # Either we're using git < 1.8.3, or there really are no tags. We use - # a heuristic: assume all version tags have a digit. The old git %d - # expansion behaves like git log --decorate=short and strips out the - # refs/heads/ and refs/tags/ prefixes that would let us distinguish - # between branches and tags. By ignoring refnames without digits, we - # filter out many common branch names like "release" and - # "stabilization", as well as "HEAD" and "master". - tags = {r for r in refs if re.search(r'\d', r)} - if verbose: - print("discarding '%s', no digits" % ",".join(refs - tags)) - if verbose: - print("likely tags: %s" % ",".join(sorted(tags))) - for ref in sorted(tags): - # sorting will prefer e.g. "2.0" over "2.0rc1" - if ref.startswith(tag_prefix): - r = ref[len(tag_prefix):] - # Filter out refs that exactly match prefix or that don't start - # with a number once the prefix is stripped (mostly a concern - # when prefix is '') - if not re.match(r'\d', r): - continue - if verbose: - print("picking %s" % r) - return {"version": r, - "full-revisionid": keywords["full"].strip(), - "dirty": False, "error": None, - "date": date} - # no suitable tags, so version is "0+unknown", but full hex is still there - if verbose: - print("no suitable tags, using unknown + full revision id") - return {"version": "0+unknown", - "full-revisionid": keywords["full"].strip(), - "dirty": False, "error": "no suitable tags", "date": None} - - -@register_vcs_handler("git", "pieces_from_vcs") -def git_pieces_from_vcs( - tag_prefix: str, - root: str, - verbose: bool, - runner: Callable = run_command -) -> Dict[str, Any]: - """Get version from 'git describe' in the root of the source tree. - - This only gets called if the git-archive 'subst' keywords were *not* - expanded, and _version.py hasn't already been rewritten with a short - version string, meaning we're inside a checked out source tree. - """ - GITS = ["git"] - if sys.platform == "win32": - GITS = ["git.cmd", "git.exe"] - - # GIT_DIR can interfere with correct operation of Versioneer. - # It may be intended to be passed to the Versioneer-versioned project, - # but that should not change where we get our version from. - env = os.environ.copy() - env.pop("GIT_DIR", None) - runner = functools.partial(runner, env=env) - - _, rc = runner(GITS, ["rev-parse", "--git-dir"], cwd=root, - hide_stderr=not verbose) - if rc != 0: - if verbose: - print("Directory %s not under git control" % root) - raise NotThisMethod("'git rev-parse --git-dir' returned error") - - # if there is a tag matching tag_prefix, this yields TAG-NUM-gHEX[-dirty] - # if there isn't one, this yields HEX[-dirty] (no NUM) - describe_out, rc = runner(GITS, [ - "describe", "--tags", "--dirty", "--always", "--long", - "--match", f"{tag_prefix}[[:digit:]]*" - ], cwd=root) - # --long was added in git-1.5.5 - if describe_out is None: - raise NotThisMethod("'git describe' failed") - describe_out = describe_out.strip() - full_out, rc = runner(GITS, ["rev-parse", "HEAD"], cwd=root) - if full_out is None: - raise NotThisMethod("'git rev-parse' failed") - full_out = full_out.strip() - - pieces: Dict[str, Any] = {} - pieces["long"] = full_out - pieces["short"] = full_out[:7] # maybe improved later - pieces["error"] = None - - branch_name, rc = runner(GITS, ["rev-parse", "--abbrev-ref", "HEAD"], - cwd=root) - # --abbrev-ref was added in git-1.6.3 - if rc != 0 or branch_name is None: - raise NotThisMethod("'git rev-parse --abbrev-ref' returned error") - branch_name = branch_name.strip() - - if branch_name == "HEAD": - # If we aren't exactly on a branch, pick a branch which represents - # the current commit. If all else fails, we are on a branchless - # commit. - branches, rc = runner(GITS, ["branch", "--contains"], cwd=root) - # --contains was added in git-1.5.4 - if rc != 0 or branches is None: - raise NotThisMethod("'git branch --contains' returned error") - branches = branches.split("\n") - - # Remove the first line if we're running detached - if "(" in branches[0]: - branches.pop(0) - - # Strip off the leading "* " from the list of branches. - branches = [branch[2:] for branch in branches] - if "master" in branches: - branch_name = "master" - elif not branches: - branch_name = None - else: - # Pick the first branch that is returned. Good or bad. - branch_name = branches[0] - - pieces["branch"] = branch_name - - # parse describe_out. It will be like TAG-NUM-gHEX[-dirty] or HEX[-dirty] - # TAG might have hyphens. - git_describe = describe_out - - # look for -dirty suffix - dirty = git_describe.endswith("-dirty") - pieces["dirty"] = dirty - if dirty: - git_describe = git_describe[:git_describe.rindex("-dirty")] - - # now we have TAG-NUM-gHEX or HEX - - if "-" in git_describe: - # TAG-NUM-gHEX - mo = re.search(r'^(.+)-(\d+)-g([0-9a-f]+)$', git_describe) - if not mo: - # unparsable. Maybe git-describe is misbehaving? - pieces["error"] = ("unable to parse git-describe output: '%s'" - % describe_out) - return pieces - - # tag - full_tag = mo.group(1) - if not full_tag.startswith(tag_prefix): - if verbose: - fmt = "tag '%s' doesn't start with prefix '%s'" - print(fmt % (full_tag, tag_prefix)) - pieces["error"] = ("tag '%s' doesn't start with prefix '%s'" - % (full_tag, tag_prefix)) - return pieces - pieces["closest-tag"] = full_tag[len(tag_prefix):] - - # distance: number of commits since tag - pieces["distance"] = int(mo.group(2)) - - # commit: short hex revision ID - pieces["short"] = mo.group(3) - - else: - # HEX: no tags - pieces["closest-tag"] = None - out, rc = runner(GITS, ["rev-list", "HEAD", "--left-right"], cwd=root) - pieces["distance"] = len(out.split()) # total number of commits - - # commit date: see ISO-8601 comment in git_versions_from_keywords() - date = runner(GITS, ["show", "-s", "--format=%ci", "HEAD"], cwd=root)[0].strip() - # Use only the last line. Previous lines may contain GPG signature - # information. - date = date.splitlines()[-1] - pieces["date"] = date.strip().replace(" ", "T", 1).replace(" ", "", 1) - - return pieces - - -def do_vcs_install(versionfile_source: str, ipy: Optional[str]) -> None: - """Git-specific installation logic for Versioneer. - - For Git, this means creating/changing .gitattributes to mark _version.py - for export-subst keyword substitution. - """ - GITS = ["git"] - if sys.platform == "win32": - GITS = ["git.cmd", "git.exe"] - files = [versionfile_source] - if ipy: - files.append(ipy) - if "VERSIONEER_PEP518" not in globals(): - try: - my_path = __file__ - if my_path.endswith((".pyc", ".pyo")): - my_path = os.path.splitext(my_path)[0] + ".py" - versioneer_file = os.path.relpath(my_path) - except NameError: - versioneer_file = "versioneer.py" - files.append(versioneer_file) - present = False - try: - with open(".gitattributes", "r") as fobj: - for line in fobj: - if line.strip().startswith(versionfile_source): - if "export-subst" in line.strip().split()[1:]: - present = True - break - except OSError: - pass - if not present: - with open(".gitattributes", "a+") as fobj: - fobj.write(f"{versionfile_source} export-subst\n") - files.append(".gitattributes") - run_command(GITS, ["add", "--"] + files) - - -def versions_from_parentdir( - parentdir_prefix: str, - root: str, - verbose: bool, -) -> Dict[str, Any]: - """Try to determine the version from the parent directory name. - - Source tarballs conventionally unpack into a directory that includes both - the project name and a version string. We will also support searching up - two directory levels for an appropriately named parent directory - """ - rootdirs = [] - - for _ in range(3): - dirname = os.path.basename(root) - if dirname.startswith(parentdir_prefix): - return {"version": dirname[len(parentdir_prefix):], - "full-revisionid": None, - "dirty": False, "error": None, "date": None} - rootdirs.append(root) - root = os.path.dirname(root) # up a level - - if verbose: - print("Tried directories %s but none started with prefix %s" % - (str(rootdirs), parentdir_prefix)) - raise NotThisMethod("rootdir doesn't start with parentdir_prefix") - - -SHORT_VERSION_PY = """ -# This file was generated by 'versioneer.py' (0.29) from -# revision-control system data, or from the parent directory name of an -# unpacked source archive. Distribution tarballs contain a pre-generated copy -# of this file. - -import json - -version_json = ''' -%s -''' # END VERSION_JSON - - -def get_versions(): - return json.loads(version_json) -""" - - -def versions_from_file(filename: str) -> Dict[str, Any]: - """Try to determine the version from _version.py if present.""" - try: - with open(filename) as f: - contents = f.read() - except OSError: - raise NotThisMethod("unable to read _version.py") - mo = re.search(r"version_json = '''\n(.*)''' # END VERSION_JSON", - contents, re.M | re.S) - if not mo: - mo = re.search(r"version_json = '''\r\n(.*)''' # END VERSION_JSON", - contents, re.M | re.S) - if not mo: - raise NotThisMethod("no version_json in _version.py") - return json.loads(mo.group(1)) - - -def write_to_version_file(filename: str, versions: Dict[str, Any]) -> None: - """Write the given version number to the given _version.py file.""" - contents = json.dumps(versions, sort_keys=True, - indent=1, separators=(",", ": ")) - with open(filename, "w") as f: - f.write(SHORT_VERSION_PY % contents) - - print("set %s to '%s'" % (filename, versions["version"])) - - -def plus_or_dot(pieces: Dict[str, Any]) -> str: - """Return a + if we don't already have one, else return a .""" - if "+" in pieces.get("closest-tag", ""): - return "." - return "+" - - -def render_pep440(pieces: Dict[str, Any]) -> str: - """Build up version string, with post-release "local version identifier". - - Our goal: TAG[+DISTANCE.gHEX[.dirty]] . Note that if you - get a tagged build and then dirty it, you'll get TAG+0.gHEX.dirty - - Exceptions: - 1: no tags. git_describe was just HEX. 0+untagged.DISTANCE.gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += plus_or_dot(pieces) - rendered += "%d.g%s" % (pieces["distance"], pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0+untagged.%d.g%s" % (pieces["distance"], - pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def render_pep440_branch(pieces: Dict[str, Any]) -> str: - """TAG[[.dev0]+DISTANCE.gHEX[.dirty]] . - - The ".dev0" means not master branch. Note that .dev0 sorts backwards - (a feature branch will appear "older" than the master branch). - - Exceptions: - 1: no tags. 0[.dev0]+untagged.DISTANCE.gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "%d.g%s" % (pieces["distance"], pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0" - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += "+untagged.%d.g%s" % (pieces["distance"], - pieces["short"]) - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def pep440_split_post(ver: str) -> Tuple[str, Optional[int]]: - """Split pep440 version string at the post-release segment. - - Returns the release segments before the post-release and the - post-release version number (or -1 if no post-release segment is present). - """ - vc = str.split(ver, ".post") - return vc[0], int(vc[1] or 0) if len(vc) == 2 else None - - -def render_pep440_pre(pieces: Dict[str, Any]) -> str: - """TAG[.postN.devDISTANCE] -- No -dirty. - - Exceptions: - 1: no tags. 0.post0.devDISTANCE - """ - if pieces["closest-tag"]: - if pieces["distance"]: - # update the post release segment - tag_version, post_version = pep440_split_post(pieces["closest-tag"]) - rendered = tag_version - if post_version is not None: - rendered += ".post%d.dev%d" % (post_version + 1, pieces["distance"]) - else: - rendered += ".post0.dev%d" % (pieces["distance"]) - else: - # no commits, use the tag as the version - rendered = pieces["closest-tag"] - else: - # exception #1 - rendered = "0.post0.dev%d" % pieces["distance"] - return rendered - - -def render_pep440_post(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]+gHEX] . - - The ".dev0" means dirty. Note that .dev0 sorts backwards - (a dirty tree will appear "older" than the corresponding clean one), - but you shouldn't be releasing software with -dirty anyways. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "g%s" % pieces["short"] - else: - # exception #1 - rendered = "0.post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - rendered += "+g%s" % pieces["short"] - return rendered - - -def render_pep440_post_branch(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]+gHEX[.dirty]] . - - The ".dev0" means not master branch. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0]+gHEX[.dirty] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%d" % pieces["distance"] - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += plus_or_dot(pieces) - rendered += "g%s" % pieces["short"] - if pieces["dirty"]: - rendered += ".dirty" - else: - # exception #1 - rendered = "0.post%d" % pieces["distance"] - if pieces["branch"] != "master": - rendered += ".dev0" - rendered += "+g%s" % pieces["short"] - if pieces["dirty"]: - rendered += ".dirty" - return rendered - - -def render_pep440_old(pieces: Dict[str, Any]) -> str: - """TAG[.postDISTANCE[.dev0]] . - - The ".dev0" means dirty. - - Exceptions: - 1: no tags. 0.postDISTANCE[.dev0] - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"] or pieces["dirty"]: - rendered += ".post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - else: - # exception #1 - rendered = "0.post%d" % pieces["distance"] - if pieces["dirty"]: - rendered += ".dev0" - return rendered - - -def render_git_describe(pieces: Dict[str, Any]) -> str: - """TAG[-DISTANCE-gHEX][-dirty]. - - Like 'git describe --tags --dirty --always'. - - Exceptions: - 1: no tags. HEX[-dirty] (note: no 'g' prefix) - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - if pieces["distance"]: - rendered += "-%d-g%s" % (pieces["distance"], pieces["short"]) - else: - # exception #1 - rendered = pieces["short"] - if pieces["dirty"]: - rendered += "-dirty" - return rendered - - -def render_git_describe_long(pieces: Dict[str, Any]) -> str: - """TAG-DISTANCE-gHEX[-dirty]. - - Like 'git describe --tags --dirty --always -long'. - The distance/hash is unconditional. - - Exceptions: - 1: no tags. HEX[-dirty] (note: no 'g' prefix) - """ - if pieces["closest-tag"]: - rendered = pieces["closest-tag"] - rendered += "-%d-g%s" % (pieces["distance"], pieces["short"]) - else: - # exception #1 - rendered = pieces["short"] - if pieces["dirty"]: - rendered += "-dirty" - return rendered - - -def render(pieces: Dict[str, Any], style: str) -> Dict[str, Any]: - """Render the given version pieces into the requested style.""" - if pieces["error"]: - return {"version": "unknown", - "full-revisionid": pieces.get("long"), - "dirty": None, - "error": pieces["error"], - "date": None} - - if not style or style == "default": - style = "pep440" # the default - - if style == "pep440": - rendered = render_pep440(pieces) - elif style == "pep440-branch": - rendered = render_pep440_branch(pieces) - elif style == "pep440-pre": - rendered = render_pep440_pre(pieces) - elif style == "pep440-post": - rendered = render_pep440_post(pieces) - elif style == "pep440-post-branch": - rendered = render_pep440_post_branch(pieces) - elif style == "pep440-old": - rendered = render_pep440_old(pieces) - elif style == "git-describe": - rendered = render_git_describe(pieces) - elif style == "git-describe-long": - rendered = render_git_describe_long(pieces) - else: - raise ValueError("unknown style '%s'" % style) - - return {"version": rendered, "full-revisionid": pieces["long"], - "dirty": pieces["dirty"], "error": None, - "date": pieces.get("date")} - - -class VersioneerBadRootError(Exception): - """The project root directory is unknown or missing key files.""" - - -def get_versions(verbose: bool = False) -> Dict[str, Any]: - """Get the project version from whatever source is available. - - Returns dict with two keys: 'version' and 'full'. - """ - if "versioneer" in sys.modules: - # see the discussion in cmdclass.py:get_cmdclass() - del sys.modules["versioneer"] - - root = get_root() - cfg = get_config_from_root(root) - - assert cfg.VCS is not None, "please set [versioneer]VCS= in setup.cfg" - handlers = HANDLERS.get(cfg.VCS) - assert handlers, "unrecognized VCS '%s'" % cfg.VCS - verbose = verbose or bool(cfg.verbose) # `bool()` used to avoid `None` - assert cfg.versionfile_source is not None, \ - "please set versioneer.versionfile_source" - assert cfg.tag_prefix is not None, "please set versioneer.tag_prefix" - - versionfile_abs = os.path.join(root, cfg.versionfile_source) - - # extract version from first of: _version.py, VCS command (e.g. 'git - # describe'), parentdir. This is meant to work for developers using a - # source checkout, for users of a tarball created by 'setup.py sdist', - # and for users of a tarball/zipball created by 'git archive' or github's - # download-from-tag feature or the equivalent in other VCSes. - - get_keywords_f = handlers.get("get_keywords") - from_keywords_f = handlers.get("keywords") - if get_keywords_f and from_keywords_f: - try: - keywords = get_keywords_f(versionfile_abs) - ver = from_keywords_f(keywords, cfg.tag_prefix, verbose) - if verbose: - print("got version from expanded keyword %s" % ver) - return ver - except NotThisMethod: - pass - - try: - ver = versions_from_file(versionfile_abs) - if verbose: - print("got version from file %s %s" % (versionfile_abs, ver)) - return ver - except NotThisMethod: - pass - - from_vcs_f = handlers.get("pieces_from_vcs") - if from_vcs_f: - try: - pieces = from_vcs_f(cfg.tag_prefix, root, verbose) - ver = render(pieces, cfg.style) - if verbose: - print("got version from VCS %s" % ver) - return ver - except NotThisMethod: - pass - - try: - if cfg.parentdir_prefix: - ver = versions_from_parentdir(cfg.parentdir_prefix, root, verbose) - if verbose: - print("got version from parentdir %s" % ver) - return ver - except NotThisMethod: - pass - - if verbose: - print("unable to compute version") - - return {"version": "0+unknown", "full-revisionid": None, - "dirty": None, "error": "unable to compute version", - "date": None} - - -def get_version() -> str: - """Get the short version string for this project.""" - return get_versions()["version"] - - -def get_cmdclass(cmdclass: Optional[Dict[str, Any]] = None): - """Get the custom setuptools subclasses used by Versioneer. - - If the package uses a different cmdclass (e.g. one from numpy), it - should be provide as an argument. - """ - if "versioneer" in sys.modules: - del sys.modules["versioneer"] - # this fixes the "python setup.py develop" case (also 'install' and - # 'easy_install .'), in which subdependencies of the main project are - # built (using setup.py bdist_egg) in the same python process. Assume - # a main project A and a dependency B, which use different versions - # of Versioneer. A's setup.py imports A's Versioneer, leaving it in - # sys.modules by the time B's setup.py is executed, causing B to run - # with the wrong versioneer. Setuptools wraps the sub-dep builds in a - # sandbox that restores sys.modules to it's pre-build state, so the - # parent is protected against the child's "import versioneer". By - # removing ourselves from sys.modules here, before the child build - # happens, we protect the child from the parent's versioneer too. - # Also see https://github.com/python-versioneer/python-versioneer/issues/52 - - cmds = {} if cmdclass is None else cmdclass.copy() - - # we add "version" to setuptools - from setuptools import Command - - class cmd_version(Command): - description = "report generated version string" - user_options: List[Tuple[str, str, str]] = [] - boolean_options: List[str] = [] - - def initialize_options(self) -> None: - pass - - def finalize_options(self) -> None: - pass - - def run(self) -> None: - vers = get_versions(verbose=True) - print("Version: %s" % vers["version"]) - print(" full-revisionid: %s" % vers.get("full-revisionid")) - print(" dirty: %s" % vers.get("dirty")) - print(" date: %s" % vers.get("date")) - if vers["error"]: - print(" error: %s" % vers["error"]) - cmds["version"] = cmd_version - - # we override "build_py" in setuptools - # - # most invocation pathways end up running build_py: - # distutils/build -> build_py - # distutils/install -> distutils/build ->.. - # setuptools/bdist_wheel -> distutils/install ->.. - # setuptools/bdist_egg -> distutils/install_lib -> build_py - # setuptools/install -> bdist_egg ->.. - # setuptools/develop -> ? - # pip install: - # copies source tree to a tempdir before running egg_info/etc - # if .git isn't copied too, 'git describe' will fail - # then does setup.py bdist_wheel, or sometimes setup.py install - # setup.py egg_info -> ? - - # pip install -e . and setuptool/editable_wheel will invoke build_py - # but the build_py command is not expected to copy any files. - - # we override different "build_py" commands for both environments - if 'build_py' in cmds: - _build_py: Any = cmds['build_py'] - else: - from setuptools.command.build_py import build_py as _build_py - - class cmd_build_py(_build_py): - def run(self) -> None: - root = get_root() - cfg = get_config_from_root(root) - versions = get_versions() - _build_py.run(self) - if getattr(self, "editable_mode", False): - # During editable installs `.py` and data files are - # not copied to build_lib - return - # now locate _version.py in the new build/ directory and replace - # it with an updated value - if cfg.versionfile_build: - target_versionfile = os.path.join(self.build_lib, - cfg.versionfile_build) - print("UPDATING %s" % target_versionfile) - write_to_version_file(target_versionfile, versions) - cmds["build_py"] = cmd_build_py - - if 'build_ext' in cmds: - _build_ext: Any = cmds['build_ext'] - else: - from setuptools.command.build_ext import build_ext as _build_ext - - class cmd_build_ext(_build_ext): - def run(self) -> None: - root = get_root() - cfg = get_config_from_root(root) - versions = get_versions() - _build_ext.run(self) - if self.inplace: - # build_ext --inplace will only build extensions in - # build/lib<..> dir with no _version.py to write to. - # As in place builds will already have a _version.py - # in the module dir, we do not need to write one. - return - # now locate _version.py in the new build/ directory and replace - # it with an updated value - if not cfg.versionfile_build: - return - target_versionfile = os.path.join(self.build_lib, - cfg.versionfile_build) - if not os.path.exists(target_versionfile): - print(f"Warning: {target_versionfile} does not exist, skipping " - "version update. This can happen if you are running build_ext " - "without first running build_py.") - return - print("UPDATING %s" % target_versionfile) - write_to_version_file(target_versionfile, versions) - cmds["build_ext"] = cmd_build_ext - - if "cx_Freeze" in sys.modules: # cx_freeze enabled? - from cx_Freeze.dist import build_exe as _build_exe # type: ignore - # nczeczulin reports that py2exe won't like the pep440-style string - # as FILEVERSION, but it can be used for PRODUCTVERSION, e.g. - # setup(console=[{ - # "version": versioneer.get_version().split("+", 1)[0], # FILEVERSION - # "product_version": versioneer.get_version(), - # ... - - class cmd_build_exe(_build_exe): - def run(self) -> None: - root = get_root() - cfg = get_config_from_root(root) - versions = get_versions() - target_versionfile = cfg.versionfile_source - print("UPDATING %s" % target_versionfile) - write_to_version_file(target_versionfile, versions) - - _build_exe.run(self) - os.unlink(target_versionfile) - with open(cfg.versionfile_source, "w") as f: - LONG = LONG_VERSION_PY[cfg.VCS] - f.write(LONG % - {"DOLLAR": "$", - "STYLE": cfg.style, - "TAG_PREFIX": cfg.tag_prefix, - "PARENTDIR_PREFIX": cfg.parentdir_prefix, - "VERSIONFILE_SOURCE": cfg.versionfile_source, - }) - cmds["build_exe"] = cmd_build_exe - del cmds["build_py"] - - if 'py2exe' in sys.modules: # py2exe enabled? - try: - from py2exe.setuptools_buildexe import py2exe as _py2exe # type: ignore - except ImportError: - from py2exe.distutils_buildexe import py2exe as _py2exe # type: ignore - - class cmd_py2exe(_py2exe): - def run(self) -> None: - root = get_root() - cfg = get_config_from_root(root) - versions = get_versions() - target_versionfile = cfg.versionfile_source - print("UPDATING %s" % target_versionfile) - write_to_version_file(target_versionfile, versions) - - _py2exe.run(self) - os.unlink(target_versionfile) - with open(cfg.versionfile_source, "w") as f: - LONG = LONG_VERSION_PY[cfg.VCS] - f.write(LONG % - {"DOLLAR": "$", - "STYLE": cfg.style, - "TAG_PREFIX": cfg.tag_prefix, - "PARENTDIR_PREFIX": cfg.parentdir_prefix, - "VERSIONFILE_SOURCE": cfg.versionfile_source, - }) - cmds["py2exe"] = cmd_py2exe - - # sdist farms its file list building out to egg_info - if 'egg_info' in cmds: - _egg_info: Any = cmds['egg_info'] - else: - from setuptools.command.egg_info import egg_info as _egg_info - - class cmd_egg_info(_egg_info): - def find_sources(self) -> None: - # egg_info.find_sources builds the manifest list and writes it - # in one shot - super().find_sources() - - # Modify the filelist and normalize it - root = get_root() - cfg = get_config_from_root(root) - self.filelist.append('versioneer.py') - if cfg.versionfile_source: - # There are rare cases where versionfile_source might not be - # included by default, so we must be explicit - self.filelist.append(cfg.versionfile_source) - self.filelist.sort() - self.filelist.remove_duplicates() - - # The write method is hidden in the manifest_maker instance that - # generated the filelist and was thrown away - # We will instead replicate their final normalization (to unicode, - # and POSIX-style paths) - from setuptools import unicode_utils - normalized = [unicode_utils.filesys_decode(f).replace(os.sep, '/') - for f in self.filelist.files] - - manifest_filename = os.path.join(self.egg_info, 'SOURCES.txt') - with open(manifest_filename, 'w') as fobj: - fobj.write('\n'.join(normalized)) - - cmds['egg_info'] = cmd_egg_info - - # we override different "sdist" commands for both environments - if 'sdist' in cmds: - _sdist: Any = cmds['sdist'] - else: - from setuptools.command.sdist import sdist as _sdist - - class cmd_sdist(_sdist): - def run(self) -> None: - versions = get_versions() - self._versioneer_generated_versions = versions - # unless we update this, the command will keep using the old - # version - self.distribution.metadata.version = versions["version"] - return _sdist.run(self) - - def make_release_tree(self, base_dir: str, files: List[str]) -> None: - root = get_root() - cfg = get_config_from_root(root) - _sdist.make_release_tree(self, base_dir, files) - # now locate _version.py in the new base_dir directory - # (remembering that it may be a hardlink) and replace it with an - # updated value - target_versionfile = os.path.join(base_dir, cfg.versionfile_source) - print("UPDATING %s" % target_versionfile) - write_to_version_file(target_versionfile, - self._versioneer_generated_versions) - cmds["sdist"] = cmd_sdist - - return cmds - - -CONFIG_ERROR = """ -setup.cfg is missing the necessary Versioneer configuration. You need -a section like: - - [versioneer] - VCS = git - style = pep440 - versionfile_source = src/myproject/_version.py - versionfile_build = myproject/_version.py - tag_prefix = - parentdir_prefix = myproject- - -You will also need to edit your setup.py to use the results: - - import versioneer - setup(version=versioneer.get_version(), - cmdclass=versioneer.get_cmdclass(), ...) - -Please read the docstring in ./versioneer.py for configuration instructions, -edit setup.cfg, and re-run the installer or 'python versioneer.py setup'. -""" - -SAMPLE_CONFIG = """ -# See the docstring in versioneer.py for instructions. Note that you must -# re-run 'versioneer.py setup' after changing this section, and commit the -# resulting files. - -[versioneer] -#VCS = git -#style = pep440 -#versionfile_source = -#versionfile_build = -#tag_prefix = -#parentdir_prefix = - -""" - -OLD_SNIPPET = """ -from ._version import get_versions -__version__ = get_versions()['version'] -del get_versions -""" - -INIT_PY_SNIPPET = """ -from . import {0} -__version__ = {0}.get_versions()['version'] -""" - - -def do_setup() -> int: - """Do main VCS-independent setup function for installing Versioneer.""" - root = get_root() - try: - cfg = get_config_from_root(root) - except (OSError, configparser.NoSectionError, - configparser.NoOptionError) as e: - if isinstance(e, (OSError, configparser.NoSectionError)): - print("Adding sample versioneer config to setup.cfg", - file=sys.stderr) - with open(os.path.join(root, "setup.cfg"), "a") as f: - f.write(SAMPLE_CONFIG) - print(CONFIG_ERROR, file=sys.stderr) - return 1 - - print(" creating %s" % cfg.versionfile_source) - with open(cfg.versionfile_source, "w") as f: - LONG = LONG_VERSION_PY[cfg.VCS] - f.write(LONG % {"DOLLAR": "$", - "STYLE": cfg.style, - "TAG_PREFIX": cfg.tag_prefix, - "PARENTDIR_PREFIX": cfg.parentdir_prefix, - "VERSIONFILE_SOURCE": cfg.versionfile_source, - }) - - ipy = os.path.join(os.path.dirname(cfg.versionfile_source), - "__init__.py") - maybe_ipy: Optional[str] = ipy - if os.path.exists(ipy): - try: - with open(ipy, "r") as f: - old = f.read() - except OSError: - old = "" - module = os.path.splitext(os.path.basename(cfg.versionfile_source))[0] - snippet = INIT_PY_SNIPPET.format(module) - if OLD_SNIPPET in old: - print(" replacing boilerplate in %s" % ipy) - with open(ipy, "w") as f: - f.write(old.replace(OLD_SNIPPET, snippet)) - elif snippet not in old: - print(" appending to %s" % ipy) - with open(ipy, "a") as f: - f.write(snippet) - else: - print(" %s unmodified" % ipy) - else: - print(" %s doesn't exist, ok" % ipy) - maybe_ipy = None - - # Make VCS-specific changes. For git, this means creating/changing - # .gitattributes to mark _version.py for export-subst keyword - # substitution. - do_vcs_install(cfg.versionfile_source, maybe_ipy) - return 0 - - -def scan_setup_py() -> int: - """Validate the contents of setup.py against Versioneer's expectations.""" - found = set() - setters = False - errors = 0 - with open("setup.py", "r") as f: - for line in f.readlines(): - if "import versioneer" in line: - found.add("import") - if "versioneer.get_cmdclass()" in line: - found.add("cmdclass") - if "versioneer.get_version()" in line: - found.add("get_version") - if "versioneer.VCS" in line: - setters = True - if "versioneer.versionfile_source" in line: - setters = True - if len(found) != 3: - print("") - print("Your setup.py appears to be missing some important items") - print("(but I might be wrong). Please make sure it has something") - print("roughly like the following:") - print("") - print(" import versioneer") - print(" setup( version=versioneer.get_version(),") - print(" cmdclass=versioneer.get_cmdclass(), ...)") - print("") - errors += 1 - if setters: - print("You should remove lines like 'versioneer.VCS = ' and") - print("'versioneer.versionfile_source = ' . This configuration") - print("now lives in setup.cfg, and should be removed from setup.py") - print("") - errors += 1 - return errors - - -def setup_command() -> NoReturn: - """Set up Versioneer and exit with appropriate error code.""" - errors = do_setup() - errors += scan_setup_py() - sys.exit(1 if errors else 0) - - -if __name__ == "__main__": - cmd = sys.argv[1] - if cmd == "setup": - setup_command()