From 9cdce3dcd42da93c29d8a365df0fed07a04443a8 Mon Sep 17 00:00:00 2001 From: dominiquef Date: Tue, 29 Jul 2025 15:52:28 -0700 Subject: [PATCH 1/9] Move files. 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.../regularization/sparse.ipynb} | 128 ++---------------- .../inversion/images/regularization_alpha.png | Bin 44829 -> 0 bytes docs/tutorials/airborne_tem.ipynb | 2 +- docs/tutorials/dc_resistivity.ipynb | 2 +- docs/tutorials/gravity.ipynb | 2 +- docs/tutorials/magnetic.ipynb | 2 +- docs/tutorials/tipper.ipynb | 2 +- 60 files changed, 198 insertions(+), 161 deletions(-) rename docs/{inversion/fundamentals.ipynb => fundamentals/background.ipynb} (88%) rename docs/{inversion => fundamentals}/data_misfit.ipynb (95%) rename docs/{inversion => fundamentals}/depth_of_investigation.ipynb (100%) rename docs/{inversion => fundamentals}/images/apply_mask.png (100%) rename docs/{inversion => fundamentals}/images/beta_optimal.png (100%) rename docs/{inversion => fundamentals}/images/beta_too_high.png (100%) rename docs/{inversion => fundamentals}/images/beta_too_low.png (100%) rename docs/{inversion => fundamentals}/images/cell_size_estimate.png (100%) rename docs/{inversion => 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rename docs/{inversion => fundamentals/regularization}/images/smoothness_norm_setup.png (100%) rename docs/{inversion => fundamentals/regularization}/images/sparse_models.png (100%) create mode 100644 docs/fundamentals/regularization/regularization.ipynb rename docs/{inversion/regularization.ipynb => fundamentals/regularization/sparse.ipynb} (54%) delete mode 100644 docs/inversion/images/regularization_alpha.png diff --git a/docs/_toc.yml b/docs/_toc.yml index 7a2c0d1b..638336e8 100644 --- a/docs/_toc.yml +++ b/docs/_toc.yml @@ -4,15 +4,17 @@ format: jb-book root: intro chapters: -- file: inversion/index +- file: fundamentals/index sections: - - file: inversion/fundamentals - - file: inversion/data_misfit - - file: inversion/regularization - - file: inversion/mesh_design - - file: inversion/joint_inversion - - file: inversion/depth_of_investigation - - file: inversion/optimization + - file: fundamentals/background + - file: fundamentals/data_misfit + - file: fundamentals/regularization/regularization + sections: + - file: fundamentals/regularization/sparse + - file: fundamentals/mesh_design + - file: fundamentals/joint_inversion + - file: fundamentals/depth_of_investigation + - file: fundamentals/optimization - file: tutorials/introduction sections: - file: tutorials/background @@ -22,13 +24,13 @@ chapters: - file: tutorials/tipper - file: tutorials/airborne_tem - file: tutorials/joint_inversion -- file: case_studies/index - sections: - - file: case_studies/Forrestania/forrestania - sections: - - file: case_studies/Forrestania/open_code - sections: - - file: case_studies/Forrestania/python_code/gravity - - file: case_studies/Forrestania/python_code/magnetics - - file: case_studies/Forrestania/python_code/joint_grav_mag +#- file: case_studies/index +# sections: +# - file: case_studies/Forrestania/forrestania +# sections: +# - file: case_studies/Forrestania/open_code +# sections: +# - file: case_studies/Forrestania/python_code/gravity +# - file: case_studies/Forrestania/python_code/magnetics +# - file: case_studies/Forrestania/python_code/joint_grav_mag - file: THIRD_PARTY_SOFTWARE diff --git a/docs/inversion/fundamentals.ipynb b/docs/fundamentals/background.ipynb similarity index 88% rename from docs/inversion/fundamentals.ipynb rename to docs/fundamentals/background.ipynb index c8e1e6f5..969dadc7 100644 --- a/docs/inversion/fundamentals.ipynb +++ b/docs/fundamentals/background.ipynb @@ -83,19 +83,7 @@ "metadata": { "lines_to_next_cell": 2 }, - "outputs": [ - { - "ename": "ModuleNotFoundError", - "evalue": "No module named 'numpy'", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[1;32mIn[1], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mnumpy\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mnp\u001b[39;00m\n\u001b[0;32m 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mnumpy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mlinalg\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m LinAlgError\n", - "\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'numpy'" - ] - } - ], + "outputs": [], "source": [ "import numpy as np\n", "from numpy.linalg import LinAlgError" @@ -103,7 +91,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "f4503466", "metadata": {}, "outputs": [], @@ -122,10 +110,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "d94c5ea7", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([1.])" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "np.dot(F, [0.5, 0.25])" ] @@ -175,7 +174,7 @@ "where the data weights $\\mathbf{W}_d$ are diagonal matrices with estimated data uncertainties. More details can be found in the [data misfit](data_misfit.ipynb) module.\n", "\n", "\n", - "- $\\phi_m$ is a [regularization](regularization.ipynb) function measuring how well we **fit geological assumptions**\n", + "- $\\phi_m$ is a [regularization](regularization) function measuring how well we **fit geological assumptions**\n", "\n", "$$\n", "\\phi_m =\\sum_{i=1}^{N}\\left(w_i f(m_i - {m}_i^{ref})\\right)^2\n", @@ -188,7 +187,7 @@ "\\phi_m = (\\mathbf{m} - \\mathbf{m}^{ref})^T \\mathbf{R}^T \\mathbf{R}(\\mathbf{m} - \\mathbf{m}^{ref})\n", "$$\n", "\n", - "where the operator $\\mathbf{R}$ describe all functions used to guide the solution to a reference model $\\mathbf{m}_{ref}$. More details can be found in the [regularization](regularization.ipynb) module. A solution for the minimum of the objective function can be computed by taking its partial derivatives with respect to the model and setting it to zero\n", + "where the operator $\\mathbf{R}$ describe all functions used to guide the solution to a reference model $\\mathbf{m}_{ref}$. More details can be found in the [regularization](regularization) module. A solution for the minimum of the objective function can be computed by taking its partial derivatives with respect to the model and setting it to zero\n", "\n", "$$\n", "\\frac{\\delta \\phi(m)}{\\delta m} = \\frac{\\delta \\phi_d}{\\delta m} + \\beta \\frac{\\delta \\phi_m}{\\delta m} = 0\n", @@ -285,7 +284,7 @@ "id": "11b58143", "metadata": {}, "source": [ - "We have found a solution to this under-determined problem: $m = [0.2,\\; 0.4]$. This result is known as the `least-norm` solution, which differs from the true answer $m = [0.5, \\;0.25]$. Other \"better\" solutions could be found if more information is provided to the inverse problem to push the model towards expected values. This will be the topic of the [Regularization Section](regularization.ipynb)" + "We have found a solution to this under-determined problem: $m = [0.2,\\; 0.4]$. This result is known as the `least-norm` solution, which differs from the true answer $m = [0.5, \\;0.25]$. Other \"better\" solutions could be found if more information is provided to the inverse problem to push the model towards expected values. This will be the topic of the [Regularization Section](regularization)" ] }, { diff --git a/docs/inversion/data_misfit.ipynb b/docs/fundamentals/data_misfit.ipynb similarity index 95% rename from docs/inversion/data_misfit.ipynb rename to docs/fundamentals/data_misfit.ipynb index d20ef329..1c24293b 100644 --- a/docs/inversion/data_misfit.ipynb +++ b/docs/fundamentals/data_misfit.ipynb @@ -5,6 +5,8 @@ "id": "43572ed1", "metadata": {}, "source": [ + "(data-misfit)=\n", + "\n", "# Data Fitting\n", "\n", "The data misfit function ($\\phi_d$) measures the quality of a model $\\mathbf{m}$ at **fitting the observed data**. It generally takes the form\n", @@ -13,19 +15,18 @@ "\\phi_d =\\sum_{i=1}^{N}\\left(\\frac{d_i^{pred} - {d}_i^{obs}}{w_i}\\right)^2 \\;.\n", "$$\n", "\n", - "It measures the sum of **weighted residual** between observed ($\\mathbf{d}^{obs}$) and predicted ($\\mathbf{d}^{pred}$) data. In matrix form, this least-square measure can be written as\n", + "It measures the sum of **weighted residual** between observed ($\\mathbf{d}^{obs}$) and predicted ($\\mathbf{d}^{pred}$) data. In matrix form, this least-squares measure can be written as\n", "\n", "$$\n", "\\phi_d =(F(\\mathbf{m}) - \\mathbf{d}^{obs})^T \\mathbf{W}_d^T \\mathbf{W}_d (F(\\mathbf{m}) - \\mathbf{d}^{obs})\\;,\n", "$$\n", "\n", - "where $F(\\mathbf{m})$ is a forward simulation of data (gravity, magnetic, EM, etc.) due to a model $m$. The $\\mathbf{W}_d$ is a diagonal matrix holding the data weights ($\\frac{1}{\\mathbf{w}}$), also referred to as **data uncertainties**. The larger the weights, the less importance a given datum has on the solution. There are many sources of **noise** that can yield large data residuals:\n", - "\n", + "where $F(\\mathbf{m})$ is a forward simulation of data (gravity, magnetic, EM, etc.) due to a model $m$. The $\\mathbf{W}_d$ is a diagonal matrix holding the data weights ($\\frac{1}{\\mathbf{w}}$), also referred to as **data uncertainties**. The larger the weights, the less important a datum is to drive the solution. There are many sources of **noise** that can yield large data residuals:\n", "\n", " - Experimental noise from $\\mathbf{d}^{obs}$, generally introduced during acquisition (positioning, instrumental noise)\n", " - Numerical noise introduced by $F(\\mathbf{m})$ from our inability to perfectly simulate the physics (discretization, interpolation, etc.)\n", "\n", - "In all cases, we may never expect the data residual to completely vanish, but we may allow it to be within an *acceptable* level of fitness for modelling purposes." + "In all cases, we may never expect the data residual to vanish completely, but we may allow it to be within an *acceptable* level of fitness for modelling purposes." ] }, { diff --git a/docs/inversion/depth_of_investigation.ipynb b/docs/fundamentals/depth_of_investigation.ipynb similarity index 100% rename from docs/inversion/depth_of_investigation.ipynb rename to docs/fundamentals/depth_of_investigation.ipynb diff --git a/docs/inversion/images/apply_mask.png 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rename to docs/fundamentals/images/setup.png diff --git a/docs/inversion/images/setup_plot.png b/docs/fundamentals/images/setup_plot.png similarity index 100% rename from docs/inversion/images/setup_plot.png rename to docs/fundamentals/images/setup_plot.png diff --git a/docs/inversion/images/small_floor.png b/docs/fundamentals/images/small_floor.png similarity index 100% rename from docs/inversion/images/small_floor.png rename to docs/fundamentals/images/small_floor.png diff --git a/docs/inversion/images/small_floor_plot.png b/docs/fundamentals/images/small_floor_plot.png similarity index 100% rename from docs/inversion/images/small_floor_plot.png rename to docs/fundamentals/images/small_floor_plot.png diff --git a/docs/inversion/images/tradeoff_setup.png b/docs/fundamentals/images/tradeoff_setup.png similarity index 100% rename from docs/inversion/images/tradeoff_setup.png rename to docs/fundamentals/images/tradeoff_setup.png diff --git a/docs/inversion/images/uijson.png b/docs/fundamentals/images/uijson.png similarity index 100% rename from docs/inversion/images/uijson.png rename to docs/fundamentals/images/uijson.png diff --git a/docs/inversion/index.ipynb b/docs/fundamentals/index.ipynb similarity index 82% rename from docs/inversion/index.ipynb rename to docs/fundamentals/index.ipynb index 235e55f9..506dafab 100644 --- a/docs/inversion/index.ipynb +++ b/docs/fundamentals/index.ipynb @@ -10,11 +10,11 @@ "This module documents the use of [SimPEG](https://simpeg.xyz/) for geophysical data inversion with user-interface (UIjson) made available through the [Mira Geoscience-geoapps](https://mirageoscience-geoapps.readthedocs-hosted.com/) project. While the code itself has its own documentation, there is a need to demonstrate the effect of parameters controlling the inversion. This document is meant to be a reference guide with practical examples to help practitioners with their inversion work.\n", "\n", "\n", - "- [Background](fundamentals.ipynb): An overview of the inversion framework.\n", + "- [Background](background.ipynb): An overview of the inversion framework.\n", "\n", "- [Data Fit](data_misfit.ipynb): Assigning uncertainties and global target (data misfit).\n", "\n", - "- [Constraints](regularization.ipynb): Adding modeling constraints (regularization).\n", + "- [Regularization (Constraints)](regularization): Adding modeling constraints (regularization).\n", "\n", "- [Mesh Design](mesh_design.ipynb): Designing an inversion mesh.\n", "\n", @@ -24,6 +24,14 @@ "\n", "![inversion_ui](./images/inversion_ui.png)" ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2308931b-c540-4082-8b20-b4d011e127af", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { diff --git a/docs/inversion/joint_inversion.ipynb 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" + ] + }, + { + "cell_type": "markdown", + "id": "17654719-df2b-4903-8217-5487f098b204", + "metadata": {}, + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.17" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/inversion/regularization.ipynb b/docs/fundamentals/regularization/sparse.ipynb similarity index 54% rename from docs/inversion/regularization.ipynb rename to docs/fundamentals/regularization/sparse.ipynb index a40f8315..19e98cf6 100644 --- a/docs/inversion/regularization.ipynb +++ b/docs/fundamentals/regularization/sparse.ipynb @@ -1,113 +1,5 @@ { "cells": [ - { - "cell_type": "markdown", - "id": "3a9fd274", - "metadata": {}, - "source": [ - "(regularization)=\n", - "\n", - "# Constraints (Regularization)\n", - "\n", - "This section focuses on the regularization functions, or constraints, that can be used to inject \"geological knowledge\" into the inversion process. More specifically, this section covers the weighted least-squares regularization functions:\n", - "\n", - "- [Conventional L2-norm](l2-norm)\n", - "\n", - "- [General Lp-norms](lp-norm)\n", - "\n", - "While often referred to as an \"unconstrained inversion\", one could argue that the conventional model norm regularizations do still incorporate some degree of geological information, at least in the form of physical property distribution. Exactly what kind of a priori information is available dictates the complexity of the constraints. For more advanced petrophysical and/or geometric constraints, see the [Joint Inversion](./joint_inversion.ipynb) section." - ] - }, - { - "cell_type": "markdown", - "id": "3e78e630", - "metadata": {}, - "source": [ - "(l2-norm)=\n", - "\n", - "## L2-norm regularization\n", - "\n", - "The conventional L2-norm regularization function imposes constraints based on the least-square measure with respect to the inversion model value\n", - "\n", - "$$\n", - "\\phi(m) = \\| f(\\mathbf{m}) \\|_2^2 \\;,\n", - "$$\n", - "\n", - "where $f(\\mathbf{m})$ is any linear function of the model $\\mathbf{m}$. The following sections introduce the conventional model \"smallness\" and \"smoothness\" functions.\n", - "\n", - "\n", - "### Model smallness\n", - "\n", - "In the seminal work of {cite:t}`TikhonovArsenin77`, the function $f(\\mathbf{m})$ simply measures the deviation between the inversion model from a reference\n", - "\n", - "$$\n", - "f_s(\\mathbf{m}) = \\mathbf{m} - \\mathbf{m}_{ref} \\;,\n", - "$$\n", - "\n", - "where $\\mathbf{m}_{ref}$ is a reference model. This function tries to keep the model \"small\", as large deviations from the reference value are penalized more heavily. The reference model can vary in complexity, from a constant background value to a full 3D geological representation of the physical property. This constitutes our first constraint.\n", - "\n", - "![ref_model](./images/reference_model.png)\n", - "\n", - "\n", - "(smooth-ref)=\n", - "\n", - "### Model smoothness\n", - "\n", - "A second set of terms can be added to the regularization function to apply constraints on the model gradients, or roughness of the solution. Following the notation used in {cite:t}`LiOldenburg1998` and others before,\n", - "\n", - "$$\n", - "f_x(\\mathbf{m}) = \\mathbf{G}_x (\\mathbf{m} - \\mathbf{m}_{ref}) \\;,\n", - "$$\n", - "\n", - "where $\\mathbf{G}_x$ is a finite difference operator that measures the gradient of the model $\\mathbf{m}$ along one of the Cartesian directions (`x` for Easting). This function keeps the model \"smooth\", as large gradients (sharp contrasts) are penalized strongly. Two additional terms are needed to measure the model gradients along the Northing ($f_y$) and vertical ($f_z$) direction.\n", - "\n", - "\n", - "### Scaling\n", - "\n", - "For 3D inverse problems, the full regularization function contains 4 terms: one for the reference model and three terms for the smoothness measures along the three Cartesian axes:\n", - "\n", - "$$\n", - "\\phi_m = \\sum_{i = s,x,y,z} \\alpha_i \\| \\mathbf{W}_i f_i(\\mathbf{m}) \\|_2^2\n", - "$$\n", - "\n", - "Note that we have added scaling parameters $\\alpha_i$ to each function. The role of those multipliers is two-fold:\n", - "\n", - "- User-defined weights to emphasize the contribution of a particular function\n", - "\n", - "- Dimensionality scaling to level the functions with each other.\n", - "\n", - "Dimensionality scales arise from the difference operators:\n", - "\n", - "$$\n", - "\\phi_x(m) = \\sum_{i=1}^{N_{fx}} \\left(\\frac{\\Delta m_i}{h_{xi}}\\right)^2\n", - "$$\n", - "\n", - "such that $\\Delta m_i$ is the difference in model values between two cells separated by a distance $h_{xi}$ along the x-axis. When adding together the [reference](#Model smallness) and [model smoothnedd](#Model smoothness) terms in the regularization, it is obvious that the scale factor of $h^{-2}$ would favor $\\phi_m$ to have a larger impact on the solution. The standard practice is to weight down the influence of the reference model accordingly.\n", - "\n", - "\n", - "**Note**\n", - "\n", - "For all SimPEG inversions, dimensionality scaling of $h^2$ is applied directly for the gradient terms by the program, allowing the default state to be all 1s for simplicity.\n", - "\n", - "\n", - "![reg_alphas](./images/regularization_alpha.png)\n", - "\n", - "\n", - "\n", - "### Model weights (future option)\n", - "\n", - "\n", - "Any of the regularization functions mentioned above can be further augmented with weights associated with each model cell such that\n", - "\n", - "$$\n", - "\\phi_i = \\| \\mathbf{W}_i f_i(\\mathbf{m}) \\|_2^2\n", - "$$\n", - "\n", - "where $\\mathbf{W}_i$ contains positive values that change the relative strength of the regularization function in specific volumes of the 3D space. This is typically done for advanced constraints to reflect variable degrees of confidence in the reference geological model (e.g. high near the surface, low at depth). This option is currently not available but it is planned to be included in geoapps v0.12.0.\n", - "\n", - "

" - ] - }, { "cell_type": "markdown", "id": "d1c00010", @@ -118,17 +10,25 @@ "## Sparse regularization\n", "\n", "\n", - "It is possible to generalize the conventional least-squares approach such that we can recover different solutions with variable degrees of sparsity {cite:t}`fournier_2019`. The goal is to explore the model space by changing our assumption about the character of the solution, in terms of volume of the anomalies and sharpness of contrasts between domains. We can do this by changing the \"ruler\" by which we evaluate the model function $f(\\mathbf{m})$.\n", + "It is possible to generalize the conventional least-squares approach such that we can recover different solutions with variable degrees of sparsity. The goal is to explore the model space by changing our assumption about the character of the solution, in terms of the volume of the anomalies and the sharpness of their edges. We can do this by changing the \"ruler\" by which we evaluate the model function $f(\\mathbf{m})$.\n", "\n", "\n", "### Approximated $L_p$-norm\n", "\n", - "Since the general $L_p$ norm is not linear with respect to the model, an approximation is used where\n", + "The general $L_p$ norm measure \n", "\n", "$$\n", "\\phi(m) = \\| f(\\mathbf{m}) \\|_p\n", "$$\n", "\n", + "can also be expressed as\n", + "\n", + "$$\n", + "\\phi(m) = \\sum_{j}^M {|f(m)_i |}^p\n", + "$$\n", + "\n", + "For $p<=1$, the function is non-linear with respect to the model. It is possible to approximate the function in a linearized form as \n", + "\n", "$$\n", "\\sum_{j}^M {|f(m)_i |}^p \\approx \\sum_{i} {\\frac{ {f(m)_i}^2}{\\left( {{f(m)_i}}^{2} + \\epsilon^2 \\right)^{1-p/2 }}}\n", "$$\n", @@ -152,7 +52,7 @@ "\\mathbf{R}_i = {\\frac{1}{\\left( {{f(m)^{(k-1)}_i}}^{2} + \\epsilon^2 \\right)^{1-p/2 }}}\\,.\n", "$$\n", "\n", - "Here the superscript $(k)$ denotes the inversion iteration number. This is also known as an iterative re-weighted least-squares (IRLS) method. For more details on the implementation refer to {cite:t}`fournier_2019`.\n", + "Here, the superscript $(k)$ denotes the iteration step of the inversion. This is also known as an iterative re-weighted least-squares (IRLS) method. For more details on the implementation, refer to {cite:t}`fournier_2019`.\n", "\n", "The next two sub-sections apply this methodology to the [model smallness](reference-model) and [model smoothness](model-smoothness) regularizers.\n", "\n", @@ -178,7 +78,7 @@ "$$\n", "\n", "\n", - "That is, we ask the inversion to recover anomalies that have small volumes but large physical property contrasts. This is desirable if we know the geological bodies to be discrete and compact (e.g. kimberlite pip, dyke, etc.). The example below demonstrates the outcome of an inversion for different combinations of norms applied to the model\n", + "That is, we ask the inversion to recover anomalies that have small volumes but large physical property contrasts. This is desirable if we know the geological bodies to be discrete and compact (e.g. kimberlite pipe, dyke, etc.). The example below demonstrates the outcome of an inversion for different combinations of norms applied to the model\n", "\n", "```{figure} ./images/sparse_models.png\n", "---\n", @@ -188,14 +88,14 @@ "\n", "The [figure above](sparse_model) shows vertical sections through the true and recovered models (from left to right) with L2, L1 and L0-norm on the model values.\n", "\n", - "Note that as $p \\rightarrow 0$ the volume of the anomaly shrinks to a few non-zero elements while the physical property contrasts increase. They generally agree on the center position of the anomaly but differ greatly on the extent and shape.\n", + "Note that as $p \\rightarrow 0$ the volume of the anomaly shrinks to a few non-zero elements while the physical property contrasts increase. They generally agree on the center position of the anomaly but differ significantly in their extent and shape.\n", "\n", "![smallness_setup](./images/smallness_norm_setup.png)\n", "\n", "No smoothness constraints were used ($\\alpha_{x,y,z} = 0$), only a penalty on the reference model ($m_{ref} = 0$).\n", "\n", "\n", - "All those models fit the data to the target [data misfit](data_misfit) and are therefore valid solutions to the inversion.\n", + "All those models fit the data to the target [data misfit](data-misfit) and are therefore valid solutions to the inversion.\n", "\n", "

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Fix links --- docs/_toc.yml | 1 + .../regularization/regularization.ipynb | 64 +++++++---- .../regularization/rotated_gradients.ipynb | 45 ++++++++ docs/fundamentals/regularization/sparse.ipynb | 108 +++++++++--------- docs/tutorials/airborne_tem.ipynb | 8 +- docs/tutorials/dc_resistivity.ipynb | 10 +- docs/tutorials/joint_inversion.ipynb | 12 ++ docs/tutorials/magnetic.ipynb | 10 +- docs/tutorials/tipper.ipynb | 22 ++-- 9 files changed, 181 insertions(+), 99 deletions(-) create mode 100644 docs/fundamentals/regularization/rotated_gradients.ipynb diff --git a/docs/_toc.yml b/docs/_toc.yml index 638336e8..036676fa 100644 --- a/docs/_toc.yml +++ b/docs/_toc.yml @@ -11,6 +11,7 @@ chapters: - file: fundamentals/regularization/regularization sections: - file: fundamentals/regularization/sparse + - file: fundamentals/regularization/rotated_gradients - file: fundamentals/mesh_design - file: fundamentals/joint_inversion - file: fundamentals/depth_of_investigation diff --git a/docs/fundamentals/regularization/regularization.ipynb b/docs/fundamentals/regularization/regularization.ipynb index 4e56945b..c0d90bae 100644 --- a/docs/fundamentals/regularization/regularization.ipynb +++ b/docs/fundamentals/regularization/regularization.ipynb @@ -9,11 +9,10 @@ "\n", "# Regularization (Constraints)\n", "\n", - "This section focuses on the regularization functions, or constraints, that can be used to inject \"geological knowledge\" into the inversion process. More specifically, this section covers the weighted least-squares regularization functions.\n", + "This section focuses on the regularization functions, or model constraints, that can inject \"geological knowledge\" into the inversion process. More specifically, this section covers the weighted least-squares regularization functions. Readers are invited to visit the following sections for more advanced options\n", "\n", - "While often referred to as an \"unconstrained inversion\", one could argue that the conventional model norm regularizations do still incorporate some degree of geological information, at least in the form of physical property distribution. The type of a priori information available dictates the complexity of the constraints. The next sections cover more advanced features\n", - "\n", - "- [Sparse Lp-norms](lp-norm)" + "- [Sparse Lp-norms](lp-norm)\n", + "- [Rotate Gradients](rotated-gradients)" ] }, { @@ -25,22 +24,22 @@ "\n", "## Least-squares regularization\n", "\n", - "The conventional L2-norm regularization function imposes constraints based on the least-squares measures, either of the model and/or its spatial gradients. We can express these various constraints as\n", + "The conventional L2-norm regularization function imposes constraints based on least-squares measures, either of the model and/or its spatial gradients. We can express these various constraints as\n", "\n", "$$\n", - "\\phi(m) = \\| \\mathbf{W} f(\\mathbf{m}) \\|_2^2 \\;,\n", + "\\phi(m) = \\| f(\\mathbf{m}) \\|_2^2 \\;,\n", "$$\n", "\n", - "where $f(\\mathbf{m})$ is any linear function of the model $\\mathbf{m}$. The generic matrix $\\mathbf{W}$ contains weights that can be used to tune the influence of the function spatially. See the section on [Weights](weights) for more details on the matter.\n", + "where $f(\\mathbf{m})$ is any linear function of the model $\\mathbf{m}$. While often referred to as an *unconstrained inversion*, one could argue that the conventional least-squares regularization does still incorporate first-degree information about the geological background, at least in the form of physical property distribution.\n", "\n", "(small-ref)=\n", "\n", "### Model smallness (reference)\n", "\n", - "In the seminal work of {cite:t}`TikhonovArsenin77`, the function $f(\\mathbf{m})$ simply measures the deviation between the inversion model from a reference\n", + "In the seminal work of {cite:t}`TikhonovArsenin77`, the function $f(\\mathbf{m})$ simply measures the deviation between the inversion model from a reference value\n", "\n", "$$\n", - "f_s(\\mathbf{m}) = \\mathbf{m} - \\mathbf{m}_{ref} \\;,\n", + "\\phi_s = \\| \\mathbf{m} - \\mathbf{m}_{ref} \\|\n", "$$\n", "\n", "where $\\mathbf{m}_{ref}$ is a reference model. This function tries to keep the model \"small\", in terms of deviation from the reference values. The reference model can vary in complexity, from a constant background value to a full 3D geological representation of the physical property. \n", @@ -55,42 +54,61 @@ "A second set of terms can be added to the regularization function to apply constraints on the model gradients, or the roughness, of the solution. Following the notation used in {cite:t}`LiOldenburg1998`,\n", "\n", "$$\n", - "f_x(\\mathbf{m}) = \\mathbf{G}_x (\\mathbf{m} - \\mathbf{m}_{ref}) \\;,\n", + "\\phi_i(\\mathbf{m}) = \\| \\mathbf{G}_i (\\mathbf{m} - \\mathbf{m}_{ref}) \\|\\;,\n", + "$$\n", + "\n", + "where $\\mathbf{G}_i$ is a finite difference operator that measures the gradient of the model $\\mathbf{m}$ along one of the Cartesian directions. For 3D inversions, three functions are needed to measure the model gradients along the Easting ($f_x$), Northing ($f_y$) and vertical ($f_z$) directions. These functions enforce the model to remain smooth, as large gradients (sharp contrasts) are penalized strongly. \n", + "\n", + "For 3D inverse problems, the full regularization function contains 4 terms: one for the reference model and three terms for the smoothness measures along the three Cartesian axes:\n", + "\n", + "$$\n", + "\\phi_m = \\sum_{i = s,x,y,z} \\| \\mathbf{W}_i f_i(\\mathbf{m}) \\|_2^2\n", "$$\n", "\n", - "where $\\mathbf{G}_x$ is a finite difference operator that measures the gradient of the model $\\mathbf{m}$ along one of the Cartesian directions (`x` for Easting). These functions enforce the model to remain smooth, as large gradients (sharp contrasts) are penalized strongly. Two additional terms are needed to measure the model gradients along the Northing ($f_y$) and vertical ($f_z$) direction.\n", + "Weighting matrices $\\mathbf{W}_i$ are added to each function to scale the constraints among each other. \n", "\n", "(weights)=\n", "\n", - "### Scaling\n", + "### Weights\n", "\n", - "For 3D inverse problems, the full regularization function contains 4 terms: one for the reference model and three terms for the smoothness measures along the three Cartesian axes:\n", + "The weighting matrices $\\mathbf{W}_i$ are made up of default and user-defined weights\n", "\n", "$$\n", - "\\phi_m = \\sum_{i = s,x,y,z} \\| \\mathbf{W}_i f_i(\\mathbf{m}) \\|_2^2\n", + "\\mathbf{W}_i = \\mathbf{W}_h * \\mathbf{W}_j * \\mathbf{W}_u\n", "$$\n", "\n", - "Note that we have added scaling parameters $\\alpha_i$ to each function. The role of those multipliers is two-fold:\n", + "#### User-defined weights ($\\mathbf{W}_u$)\n", "\n", - "- User-defined weights to emphasize the contribution of a particular function. This is typically done for advanced constraints to reflect variable degrees of confidence in the reference geological model (e.g. high near the surface, low at depth). \n", + "User-defined weights can be tuned to emphasize the contribution of a particular function. This can be done globally, as a constant, or locally on a cell-by-cell basis. Weights may reflect variable degrees of confidence in the reference geological model (e.g. high near the surface, low at depth), or to accentuate specific trends in the model.\n", "\n", - "- Default scaling to level the functions with each other.\n", + "![reg_alphas](./images/regularization_alpha.png)\n", + "\n", + "\n", + "#### Sensitivity-based weights ($\\mathbf{W}_j$)\n", "\n", - "Dimensionality scales arise from the difference operators:\n", + "Sensitivity-based weights are computed as the sum-squares the rows of the sensitivities\n", "\n", "$$\n", - "\\phi_x(m) = \\sum_{i=1}^{N_{fx}} \\left(\\frac{\\Delta m_i}{h_{xi}}\\right)^2\n", + "\\mathbf{W}_j = [\\sum_{i=1}^{N} \\mathbf{J}_{ij}^2 + \\epsilon ]^{1/4} \\;,\n", "$$\n", "\n", - "such that $\\Delta m_i$ is the difference in model values between two cells separated by a distance $h_{xi}$ along the x-axis. When adding together the [reference](small-ref) and [model smoothness](smooth-ref) terms in the regularization, it is obvious that the scale factor of $h^{-2}$ would favor $\\phi_m$ to have a larger impact on the solution. The standard practice is to weigh down the influence of the reference model accordingly.\n", + "where $\\mathbf{J}$ are the sensitivities (Jacobian) of the forward problem. The weighting attempts to compensate for the strong influence of the misfit function near the receiver locations, which would favour a model with high complexity near the surface. A small constant $\\epsilon$ is added to threshold the weights in regions of extremely low sensitivity.\n", "\n", "\n", - "**Note**\n", + "#### Dimensionality scaling ($\\mathbf{W}_h$)\n", "\n", - "For all SimPEG inversions, dimensionality scaling of $h^2$ is applied directly for the gradient terms by the program, allowing the default state to be all 1s for simplicity.\n", + "Dimensionality scaling is applied to the gradient terms $\\phi_{i=(x,y,z)}$ as constants to account for length scales in the *smoothness* terms\n", "\n", + "$$\n", + "\\mathbf{W}_{hi} = h_i \n", + "$$\n", "\n", - "![reg_alphas](./images/regularization_alpha.png)\n", + "where $h$ is defined by the smallest cell dimension in each dimension $i=x,y,z$. This default scaling brings the *smallness* and *smoothness* terms to be dimensionally equivalent, which would otherwise be\n", + "\n", + "$$\n", + "dim\\; \\phi_s = M^2, \\; \n", + "dim\\; \\phi_x = \\frac{M^2}{H^2}\n", + "$$\n", "\n", "\n", "

" diff --git a/docs/fundamentals/regularization/rotated_gradients.ipynb b/docs/fundamentals/regularization/rotated_gradients.ipynb new file mode 100644 index 00000000..f7574b08 --- /dev/null +++ b/docs/fundamentals/regularization/rotated_gradients.ipynb @@ -0,0 +1,45 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "d1c00010", + "metadata": {}, + "source": [ + "(rotated-gradients)=\n", + "\n", + "# Rotated Gradients\n", + "\n", + "This section provides details about the rotation of gradient penalties to enforce trends in the model." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "35b60ef2-b3c4-4074-b7ce-4e8835a5c3f4", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.17" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/fundamentals/regularization/sparse.ipynb b/docs/fundamentals/regularization/sparse.ipynb index 19e98cf6..013e9cc1 100644 --- a/docs/fundamentals/regularization/sparse.ipynb +++ b/docs/fundamentals/regularization/sparse.ipynb @@ -7,59 +7,10 @@ "source": [ "(lp-norm)=\n", "\n", - "## Sparse regularization\n", + "# Sparse regularization\n", "\n", "\n", - "It is possible to generalize the conventional least-squares approach such that we can recover different solutions with variable degrees of sparsity. The goal is to explore the model space by changing our assumption about the character of the solution, in terms of the volume of the anomalies and the sharpness of their edges. We can do this by changing the \"ruler\" by which we evaluate the model function $f(\\mathbf{m})$.\n", - "\n", - "\n", - "### Approximated $L_p$-norm\n", - "\n", - "The general $L_p$ norm measure \n", - "\n", - "$$\n", - "\\phi(m) = \\| f(\\mathbf{m}) \\|_p\n", - "$$\n", - "\n", - "can also be expressed as\n", - "\n", - "$$\n", - "\\phi(m) = \\sum_{j}^M {|f(m)_i |}^p\n", - "$$\n", - "\n", - "For $p<=1$, the function is non-linear with respect to the model. It is possible to approximate the function in a linearized form as \n", - "\n", - "$$\n", - "\\sum_{j}^M {|f(m)_i |}^p \\approx \\sum_{i} {\\frac{ {f(m)_i}^2}{\\left( {{f(m)_i}}^{2} + \\epsilon^2 \\right)^{1-p/2 }}}\n", - "$$\n", - "\n", - "where $p$ is any constant between $[0,\\;2]$. This is a decent approximation of the $l_p$-norm for any of the functions presented in the [L2-norm](l2-norm) section.\n", - "\n", - "![lp_norm](./images/lp_norm.png)\n", - "\n", - "Note that choosing a different $l_p$-norm greatly changes how we measure the function $f(m)$. Rather than simply increasing exponentially with the size of $f(m)$, small norms increase the penalty on low $f(m)$ values.\n", - "As $p\\rightarrow 0$, we attempt to recover as few non-zero elements, which in turn favour sparse solutions.\n", - "\n", - "Since it is a non-linear function with respect to $\\mathbf{m}$, we must first linearize it as\n", - "\n", - "$$\n", - "\\| f(\\mathbf{m})_i \\|_p \\approx \\| \\mathbf{R}_i f(\\mathbf{m})_i\\|\n", - "$$\n", - "\n", - "where\n", - "\n", - "$$\n", - "\\mathbf{R}_i = {\\frac{1}{\\left( {{f(m)^{(k-1)}_i}}^{2} + \\epsilon^2 \\right)^{1-p/2 }}}\\,.\n", - "$$\n", - "\n", - "Here, the superscript $(k)$ denotes the iteration step of the inversion. This is also known as an iterative re-weighted least-squares (IRLS) method. For more details on the implementation, refer to {cite:t}`fournier_2019`.\n", - "\n", - "The next two sub-sections apply this methodology to the [model smallness](reference-model) and [model smoothness](model-smoothness) regularizers.\n", - "\n", - "![reg_lp](./images/regularization_lp.png)\n", - "\n", - "\n", - "

" + "It is possible to generalize the conventional least-squares approach such that we can recover different solutions with variable degrees of sparsity. By sparsity, we mean fewer model cells (or gradients) away from the reference, but with larger values. The goal is to explore the model space by changing our assumption about the character of the solution, in terms of the volume of the anomalies and the sharpness of their edges. We can do this by changing the \"ruler\" by which we evaluate the model function $f(\\mathbf{m})$." ] }, { @@ -69,7 +20,7 @@ "source": [ "(reference-model)=\n", "\n", - "### Smallness norm model\n", + "## Smallness norm model\n", "\n", "The first option is to impose sparsity assumptions on the model values.\n", "\n", @@ -107,11 +58,11 @@ "source": [ "(model-smoothness)=\n", "\n", - "### Smoothness norm model\n", + "## Smoothness norm model\n", "\n", "Next, we explore the effect of applying sparse norms on the model gradients. We have two options.\n", "\n", - "#### Gradient type: Total\n", + "### Gradient type: Total\n", "\n", "The favoured approach is to measure the total gradient of the model\n", "\n", @@ -139,7 +90,7 @@ "\n", "No reference model was used ($\\alpha_s = 0$) with uniform norm values on all three Cartesian components.\n", "\n", - "All those models also fit the data to the target [data misfit](data_misfit) and are therefore valid solutions to the inversion. Note that as $p \\rightarrow 0$ the edges of the anomaly become tighter while variability inside the body diminishes. They generally agree on the center position of the anomaly but differ greatly on the extent and shape.\n", + "All those models also fit the data to the target [data misfit](data-misfit) and are therefore valid solutions to the inversion. Note that as $p \\rightarrow 0$ the edges of the anomaly become tighter while variability inside the body diminishes. They generally agree on the center position of the anomaly but differ greatly on the extent and shape.\n", "\n", "\n", "\n", @@ -190,6 +141,53 @@ "To be continued..." ] }, + { + "cell_type": "markdown", + "id": "e8b6527c-842e-4b8f-8619-bb96ff3deffc", + "metadata": {}, + "source": [ + "### Background: Approximated $L_p$-norm\n", + "\n", + "The standard $L_p$ norm measure is generally written as\n", + "\n", + "$$\n", + "\\phi(m) = \\| f(\\mathbf{m}) \\|_p ] \\;,\n", + "$$\n", + "\n", + "which can also be expressed as\n", + "\n", + "$$\n", + "\\phi(m) = \\sum_{j}^M {|f(m)_i |}^p \\;.\n", + "$$\n", + "\n", + "For $p<=1$, the function is non-linear with respect to the model. It is possible to approximate the function in a linearized form as \n", + "\n", + "$$\n", + "\\sum_{j}^M {|f(m)_i |}^p \\approx \\sum_{i} {\\frac{ {f(m)_i}^2}{\\left( {{f(m)_i}}^{2} + \\epsilon^2 \\right)^{1-p/2 }}}\n", + "$$\n", + "\n", + "where $p$ is any constant between $[0,\\;2]$. This is a decent approximation of the $l_p$-norm for any of the functions presented in the [L2-norm](l2-norm) section.\n", + "\n", + "![lp_norm](./images/lp_norm.png)\n", + "\n", + "Note that choosing a different $l_p$-norm greatly changes how we measure the function $f(m)$. Rather than simply increasing exponentially with the size of $f(m)$, small norms increase the penalty on low $f(m)$ values.\n", + "As $p\\rightarrow 0$, we attempt to recover as few non-zero elements, which in turn favour sparse solutions.\n", + "\n", + "Since it is a non-linear function with respect to $\\mathbf{m}$, we must first linearize it as\n", + "\n", + "$$\n", + "\\| f(\\mathbf{m})_i \\|_p \\approx \\| \\mathbf{R}_i \\mathbf{W}_i f(\\mathbf{m})_i\\|\n", + "$$\n", + "\n", + "where\n", + "\n", + "$$\n", + "\\mathbf{R}_i = {\\frac{1}{\\left( {{f(m)^{(k-1)}_i}}^{2} + \\epsilon^2 \\right)^{1-p/2 }}}\\,.\n", + "$$\n", + "\n", + "Here, the superscript $(k)$ denotes the iteration step of the inversion. This is also known as an iterative re-weighted least-squares (IRLS) method. For more details on the implementation, refer to {cite:t}`fournier_2019`." + ] + }, { "cell_type": "markdown", "id": "2bf887ab", diff --git a/docs/tutorials/airborne_tem.ipynb b/docs/tutorials/airborne_tem.ipynb index 75191c57..d9ce0bcf 100644 --- a/docs/tutorials/airborne_tem.ipynb +++ b/docs/tutorials/airborne_tem.ipynb @@ -125,9 +125,9 @@ "\n", "### Refinements\n", "\n", - "- For the first refinement, we insert 4 cells for the first three octree levels along the flight path. The refinement is done radially around the segments of the flight path curve to assure good numerical accuracy near the receiver locations. This is especially important for EM methods with low frequencies.\n", + "- For the first refinement, we insert 4 cells for the first three octree levels along the flight path. The refinement is done radially around the segments of the flight path curve to ensure good numerical accuracy near the receiver locations. This is especially important for EM methods with low frequencies.\n", "\n", - "- We use a second refinement along topography to get a coarse but continuous air-ground interface outside the area or interest.\n", + "- We use a second refinement along topography to get a coarse but continuous air-ground interface outside the area of interest.\n", "\n", "- Lastly, we refine a \"horizon\" to get a core region at depth with increasing cell size directly below the survey. This is our volume of interest most strongly influenced by the data.\n", "\n", @@ -136,10 +136,10 @@ "scale: 50%\n", "name: atem_refinement\n", "---\n", - "Refinement strategy used for the atem modeling.\n", + "Refinement strategy used for the atem modelling.\n", "```\n", "\n", - "See [Mesh creation](mesh_design) section for general details on the parameters." + "See [Mesh creation](mesh-design) section for general details on the parameters." ] }, { diff --git a/docs/tutorials/dc_resistivity.ipynb b/docs/tutorials/dc_resistivity.ipynb index 27a45d29..5b5eb3e3 100644 --- a/docs/tutorials/dc_resistivity.ipynb +++ b/docs/tutorials/dc_resistivity.ipynb @@ -84,11 +84,11 @@ "\n", "### Refinements\n", "\n", - "- The first refinement adds more cells around each pole location, radially outward. This assures good numerical accuracy, espatially on the outer boundary of the survey area.\n", + "- The first refinement adds more cells around each pole location, radially outward. This assures good numerical accuracy, especially on the outer boundary of the survey area.\n", "\n", - "- A second refinement is used along topography to get a coarse but continuous air-ground interface outside the area or interest.\n", + "- A second refinement is used along topography to get a coarse but continuous air-ground interface outside the area of interest.\n", "\n", - "- The third refinement \"horizon\" is used to get a core region at depth with increasing cell size directly below the survey. This is our volume of interest most strongly influence by the data. We use a maximum distance of 100 m to limit the refinement away from the survey lines. In the case of remote electrodes, this parameter prevents from discretization finely everywhere in between.\n", + "- The third refinement, \"horizon\", is used to get a core region at depth with increasing cell size directly below the survey. This is our volume of interest most strongly influenced by the data. We use a maximum distance of 100 m to limit the refinement away from the survey lines. In the case of remote electrodes, this parameter prevents discretization from applying everywhere in between.\n", "\n", "\n", "```{figure} ./images/dc/dc_refinement.png\n", @@ -96,10 +96,10 @@ "scale: 50%\n", "name: dc_refinement\n", "---\n", - "Refinement strategy used for the direct-current modeling.\n", + "Refinement strategy used for the direct-current modelling.\n", "```\n", "\n", - "See [Mesh creation](mesh_design) section for general details on the parameters.\n" + "See [Mesh creation](mesh-design) section for general details on the parameters.\n" ] }, { diff --git a/docs/tutorials/joint_inversion.ipynb b/docs/tutorials/joint_inversion.ipynb index 9b807f46..21a7fb18 100644 --- a/docs/tutorials/joint_inversion.ipynb +++ b/docs/tutorials/joint_inversion.ipynb @@ -16,6 +16,18 @@ "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.17" } }, "nbformat": 4, diff --git a/docs/tutorials/magnetic.ipynb b/docs/tutorials/magnetic.ipynb index 37811327..fefb112d 100644 --- a/docs/tutorials/magnetic.ipynb +++ b/docs/tutorials/magnetic.ipynb @@ -82,21 +82,21 @@ "\n", "### Refinements\n", "\n", - "- For the first refinement, we insert two cells around our survey lines. The refinement is done radially around the segments of the curve to assure that the air-ground interface near the receivers are modeled with the finest cell size.\n", + "- For the first refinement, we insert two cells around our survey lines. The refinement is done radially around the segments of the curve to ensure that the air-ground interface near the receivers is modelled with the finest cell size.\n", "\n", - "- A second refinement is used along topography to get a coarse but continuous air-ground interface outside the area or interest.\n", + "- A second refinement is used along topography to get a coarse but continuous air-ground interface outside the area of interest.\n", "\n", - "- The third refinement \"horizon\" is used to get a core region at depth with increasing cell size directly below the survey. This is our volume of interest most strongly influence by the data.\n", + "- The third refinement, \"horizon\", is used to get a core region at depth with increasing cell size directly below the survey. This is our volume of interest most strongly influenced by the data.\n", "\n", "```{figure} ./images/magnetics/mesh_refinement.png\n", "---\n", "scale: 50%\n", "name: mag_refinement\n", "---\n", - "Refinement strategy used for the magnetic modeling.\n", + "Refinement strategy used for the magnetic modelling.\n", "```\n", "\n", - "See [Mesh creation](mesh_design) section for general details on the parameters.\n" + "See [Mesh creation](mesh-design) section for general details on the parameters.\n" ] }, { diff --git a/docs/tutorials/tipper.ipynb b/docs/tutorials/tipper.ipynb index 123c15d6..7528827d 100644 --- a/docs/tutorials/tipper.ipynb +++ b/docs/tutorials/tipper.ipynb @@ -88,9 +88,9 @@ "\n", "### Refinements\n", "\n", - "- For the first refinement, we insert 4 cells for the first three octree levels along the flight path. The refinement is done radially around the segments of the flight path curve to assure good numerical accuracy near the receiver locations. This is especially important for EM methods with low frequencies.\n", + "- For the first refinement, we insert 4 cells for the first three octree levels along the flight path. The refinement is done radially around the segments of the flight path curve to ensure good numerical accuracy near the receiver locations. This is especially important for EM methods with low frequencies.\n", "\n", - "- We use a second refinement along topography to get a coarse but continuous air-ground interface outside the area or interest.\n", + "- We use a second refinement along topography to get a coarse but continuous air-ground interface outside the area of interest.\n", "\n", "- Lastly, we refine a \"horizon\" to get a core region at depth with increasing cell size directly below the survey. This is our volume of interest most strongly influenced by the data.\n", "\n", @@ -99,10 +99,10 @@ "scale: 50%\n", "name: tipper_refinement\n", "---\n", - "Refinement strategy used for the tipper modeling.\n", + "Refinement strategy used for the tipper modelling.\n", "```\n", "\n", - "See [Mesh creation](mesh_design) section for general details on the parameters." + "See [Mesh creation](mesh-design) section for general details on the parameters." ] }, { @@ -114,7 +114,7 @@ "\n", "**Runtime: ~2.0 h**\n", "\n", - "Tipper data involves 2 receiver configuration (x and y), with two components (real and imaginary) and measured over 6 frequencies. Balancing all this data can be challenging and time consuming. Here we adopt a variable floor strategy based on the 10th percentile of each data layer.\n", + "Tipper data involves 2 receiver configurations (x and y), with two components (real and imaginary) and measured over 6 frequencies. Balancing all this data can be challenging and time-consuming. Here, we adopt a variable floor strategy based on the 10th percentile of each data layer.\n", "\n", "```{figure} ./images/tipper/tipper_uncerts.png\n", "---\n", @@ -125,7 +125,7 @@ "\n", "This approach is a good starting point, but experimentation is generally required.\n", "\n", - "After running the inversion we recover the following solution:\n", + "After running the inversion, we recover the following solution:\n", "\n", "\n", "```{figure} ./images/tipper/tipper_unconstrained.png\n", @@ -134,11 +134,19 @@ "---\n", "(Left) Horizontal section at 120 m elevation after reaching target misfit (iteration 5).\n", "\n", - "(Right)(top) 2D profiles of observed versus predicted data for all 4 channels and 6 frequencies and (bottom) vertical section through the conductivity model below the same line.\n", + "(Right)(top) 2D profiles of observed versus predicted data for all 4 channels and 6 frequencies, and (bottom) vertical section through the conductivity model below the same line.\n", "```\n", "\n", "Despite our simplistic floor uncertainties, the inversion managed to converge fairly quickly to a reasonable model that fits our data well. We have recovered a clear conductor at depth that overlaps with the ore body. However, the inversion could not resolve the thin conductive overburden layer, as expected by the low frequency range of the tipper system." ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6db10672-d6a6-4cf9-bb21-03ae881dff7b", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { From a88bf8435e8f01d926c601961abdcda088d4b084 Mon Sep 17 00:00:00 2001 From: dominiquef Date: Fri, 1 Aug 2025 14:10:53 -0700 Subject: [PATCH 3/9] More content --- .../images/create_orientation.png | Bin 0 -> 76645 bytes .../images/flin_flon_no_rotation.png | Bin 0 -> 200769 bytes .../images/flin_flon_rotated.png | Bin 0 -> 189767 bytes .../images/gradient_direction.png | Bin 0 -> 77178 bytes .../regularization/images/set_orientation.png | Bin 0 -> 30393 bytes .../images/smallness_norm_setup.png | Bin 61204 -> 32391 bytes .../images/smoothness_norm_setup.png | Bin 57958 -> 32060 bytes .../regularization/regularization.ipynb | 48 ++++------ 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b/docs/fundamentals/regularization/regularization.ipynb index c0d90bae..064a60b7 100644 --- a/docs/fundamentals/regularization/regularization.ipynb +++ b/docs/fundamentals/regularization/regularization.ipynb @@ -24,13 +24,16 @@ "\n", "## Least-squares regularization\n", "\n", - "The conventional L2-norm regularization function imposes constraints based on least-squares measures, either of the model and/or its spatial gradients. We can express these various constraints as\n", + "The conventional L2-norm regularization function imposes constraints based on least-squares measures, either of the model and/or its spatial gradients. \n", + "\n", + "For 3D inverse problems, the full regularization function contains 4 terms: one for the reference model and three terms for the smoothness measures along the three Cartesian axes. We can express these various constraints as\n", "\n", "$$\n", - "\\phi(m) = \\| f(\\mathbf{m}) \\|_2^2 \\;,\n", + "\\phi_m = \\sum_{i = s,x,y,z} \\| \\mathbf{W}_i f_i(\\mathbf{m}) \\|_2^2\n", "$$\n", "\n", - "where $f(\\mathbf{m})$ is any linear function of the model $\\mathbf{m}$. While often referred to as an *unconstrained inversion*, one could argue that the conventional least-squares regularization does still incorporate first-degree information about the geological background, at least in the form of physical property distribution.\n", + "Weighting matrices $\\mathbf{W}_i$ are added to each function to scale the constraints among each other. \n", + "While often referred to as an *unconstrained inversion*, one could argue that the conventional least-squares regularization does still incorporate first-degree information about the geological background, at least in the form of physical property distribution. The following sections provide details on each element of the regularization.\n", "\n", "(small-ref)=\n", "\n", @@ -39,7 +42,7 @@ "In the seminal work of {cite:t}`TikhonovArsenin77`, the function $f(\\mathbf{m})$ simply measures the deviation between the inversion model from a reference value\n", "\n", "$$\n", - "\\phi_s = \\| \\mathbf{m} - \\mathbf{m}_{ref} \\|\n", + "\\mathbf{f}_s = \\mathbf{m} - \\mathbf{m}_{ref}\n", "$$\n", "\n", "where $\\mathbf{m}_{ref}$ is a reference model. This function tries to keep the model \"small\", in terms of deviation from the reference values. The reference model can vary in complexity, from a constant background value to a full 3D geological representation of the physical property. \n", @@ -54,71 +57,58 @@ "A second set of terms can be added to the regularization function to apply constraints on the model gradients, or the roughness, of the solution. Following the notation used in {cite:t}`LiOldenburg1998`,\n", "\n", "$$\n", - "\\phi_i(\\mathbf{m}) = \\| \\mathbf{G}_i (\\mathbf{m} - \\mathbf{m}_{ref}) \\|\\;,\n", - "$$\n", - "\n", - "where $\\mathbf{G}_i$ is a finite difference operator that measures the gradient of the model $\\mathbf{m}$ along one of the Cartesian directions. For 3D inversions, three functions are needed to measure the model gradients along the Easting ($f_x$), Northing ($f_y$) and vertical ($f_z$) directions. These functions enforce the model to remain smooth, as large gradients (sharp contrasts) are penalized strongly. \n", - "\n", - "For 3D inverse problems, the full regularization function contains 4 terms: one for the reference model and three terms for the smoothness measures along the three Cartesian axes:\n", - "\n", - "$$\n", - "\\phi_m = \\sum_{i = s,x,y,z} \\| \\mathbf{W}_i f_i(\\mathbf{m}) \\|_2^2\n", + "\\mathbf{f}_i = \\mathbf{G}_i (\\mathbf{m} - \\mathbf{m}_{ref}),\n", "$$\n", "\n", - "Weighting matrices $\\mathbf{W}_i$ are added to each function to scale the constraints among each other. \n", + "where $\\mathbf{G}_i$ is a finite difference operator that measures the gradient of the model $\\mathbf{m}$ along one of the Cartesian directions. \n", + "Three functions are needed to calculate the model gradients along the Easting ($f_x$), Northing ($f_y$) and vertical ($f_z$) directions. These functions enforce the model to remain smooth, as large gradients (sharp contrasts) are penalized strongly. \n", "\n", "(weights)=\n", "\n", "### Weights\n", "\n", - "The weighting matrices $\\mathbf{W}_i$ are made up of default and user-defined weights\n", + "The diagonal weighting matrices $\\mathbf{W}_i$ are made up of default and user-defined weights\n", "\n", "$$\n", - "\\mathbf{W}_i = \\mathbf{W}_h * \\mathbf{W}_j * \\mathbf{W}_u\n", + "\\mathbf{W}_i = diag(\\mathbf{w}_h * \\mathbf{w}_s * \\mathbf{w}_u)\n", "$$\n", "\n", - "#### User-defined weights ($\\mathbf{W}_u$)\n", + "#### User-defined weights ($\\mathbf{w}_u$)\n", "\n", "User-defined weights can be tuned to emphasize the contribution of a particular function. This can be done globally, as a constant, or locally on a cell-by-cell basis. Weights may reflect variable degrees of confidence in the reference geological model (e.g. high near the surface, low at depth), or to accentuate specific trends in the model.\n", "\n", "![reg_alphas](./images/regularization_alpha.png)\n", "\n", "\n", - "#### Sensitivity-based weights ($\\mathbf{W}_j$)\n", + "#### Sensitivity-based weights ($\\mathbf{w}_s$)\n", "\n", "Sensitivity-based weights are computed as the sum-squares the rows of the sensitivities\n", "\n", "$$\n", - "\\mathbf{W}_j = [\\sum_{i=1}^{N} \\mathbf{J}_{ij}^2 + \\epsilon ]^{1/4} \\;,\n", + "\\mathbf{w}_s = [\\sum_{i=1}^{N} \\mathbf{J}_{ij}^2 + \\epsilon ]^{1/4} \\;,\n", "$$\n", "\n", "where $\\mathbf{J}$ are the sensitivities (Jacobian) of the forward problem. The weighting attempts to compensate for the strong influence of the misfit function near the receiver locations, which would favour a model with high complexity near the surface. A small constant $\\epsilon$ is added to threshold the weights in regions of extremely low sensitivity.\n", "\n", "\n", - "#### Dimensionality scaling ($\\mathbf{W}_h$)\n", + "#### Dimensionality scaling ($\\mathbf{w}_h$)\n", "\n", "Dimensionality scaling is applied to the gradient terms $\\phi_{i=(x,y,z)}$ as constants to account for length scales in the *smoothness* terms\n", "\n", "$$\n", - "\\mathbf{W}_{hi} = h_i \n", + "\\mathbf{w}_{hi} = h_i \n", "$$\n", "\n", "where $h$ is defined by the smallest cell dimension in each dimension $i=x,y,z$. This default scaling brings the *smallness* and *smoothness* terms to be dimensionally equivalent, which would otherwise be\n", "\n", "$$\n", - "dim\\; \\phi_s = M^2, \\; \n", - "dim\\; \\phi_x = \\frac{M^2}{H^2}\n", + "dim\\; \\phi_s = [m]^2, \\; \n", + "dim\\; \\phi_x = \\frac{[m]^2}{[h]^2}\n", "$$\n", "\n", "\n", "

" ] - }, - { - "cell_type": "markdown", - "id": "17654719-df2b-4903-8217-5487f098b204", - "metadata": {}, - "source": [] } ], "metadata": { diff --git a/docs/fundamentals/regularization/rotated_gradients.ipynb b/docs/fundamentals/regularization/rotated_gradients.ipynb index f7574b08..e2d5ff9a 100644 --- a/docs/fundamentals/regularization/rotated_gradients.ipynb +++ b/docs/fundamentals/regularization/rotated_gradients.ipynb @@ -9,16 +9,57 @@ "\n", "# Rotated Gradients\n", "\n", - "This section provides details about the rotation of gradient penalties to enforce trends in the model." + "This section provides details about the rotation of gradient penalties to enforce trends in the model. This option is useful for counteracting modelling bias due to survey design (wide line separation) and reinforcing known geological trends. " ] }, { - "cell_type": "code", - "execution_count": null, - "id": "35b60ef2-b3c4-4074-b7ce-4e8835a5c3f4", + "cell_type": "markdown", + "id": "8405d820-2336-466f-9946-f0f55340b5dd", + "metadata": {}, + "source": [ + "## Background\n", + "\n", + "As covered in the [Regularization](smooth-ref) section, penalties on the model gradients (smoothness) are by default applied along each of the Cartesian axes:\n", + "\n", + "$$\n", + "\\mathbf{f}_i = \\mathbf{G}_i (\\mathbf{m} - \\mathbf{m}_{ref}),\n", + "$$\n", + "\n", + "where $\\mathbf{G}_i$ is a finite difference operator that measures the gradient of the model $\\mathbf{m}$ along one of the Cartesian directions. As proposed by {cite:t}`LiOldenburg2000`, orientation information can be incorporated in the inversion by rotating the gradient operators along different directions such that \n", + "\n", + "$$\n", + "\\mathbf{\\hat f}_i = \\mathbf{\\hat G}_i (\\mathbf{m} - \\mathbf{m}_{ref}),\n", + "$$\n", + "\n", + "where $\\mathbf{\\hat G}_i$ is the rotated gradient along one of the $u$, $v$ and $w$-axis. \n", + "\n", + "![grad](./images/gradient_direction.png)\n", + "\n", + "\n", + "In the case of rotated gradients, we want to treat each component independently such that trends can be reinforced along specific directions.\n", + "$$\n", + "\\phi(m) = \\| \\mathbf{G}_x \\mathbf{m} \\|_p + \\| \\mathbf{G}_y \\mathbf{m} \\|_p + \\| \\mathbf{G}_z \\mathbf{m} \\|_p \\;.\n", + "$$\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "1ec1e9e0-2f64-41ec-875f-56da5e5ed2ee", "metadata": {}, - "outputs": [], - "source": [] + "source": [ + "## Example\n", + "\n", + "We re-use the [magnetic inversion tutorial]()\n", + "\n", + "Direction information can be supplied as either `Dip & Dip direction`, `Dip & Strike` or as `3D Vector` data group. \n", + "\n", + "![set_ori](./images/create_orientation.png)\n", + "\n", + "Setting the group through the UI and lowering the norms along the oriented plane.\n", + "\n", + "![set_ori](./images/set_orientation.png)" + ] } ], "metadata": { diff --git a/docs/fundamentals/regularization/sparse.ipynb b/docs/fundamentals/regularization/sparse.ipynb index 013e9cc1..14a9da85 100644 --- a/docs/fundamentals/regularization/sparse.ipynb +++ b/docs/fundamentals/regularization/sparse.ipynb @@ -60,11 +60,7 @@ "\n", "## Smoothness norm model\n", "\n", - "Next, we explore the effect of applying sparse norms on the model gradients. We have two options.\n", - "\n", - "### Gradient type: Total\n", - "\n", - "The favoured approach is to measure the total gradient of the model\n", + "Next, we explore the effect of applying sparse norms on the model gradients. \n", "\n", "$$\n", "\\phi(m) = \\| |\\nabla \\mathbf{m}| \\|_p\n", @@ -90,43 +86,7 @@ "\n", "No reference model was used ($\\alpha_s = 0$) with uniform norm values on all three Cartesian components.\n", "\n", - "All those models also fit the data to the target [data misfit](data-misfit) and are therefore valid solutions to the inversion. Note that as $p \\rightarrow 0$ the edges of the anomaly become tighter while variability inside the body diminishes. They generally agree on the center position of the anomaly but differ greatly on the extent and shape.\n", - "\n", - "\n", - "\n", - "**Note**\n", - "\n", - "In the literature, the majority of studies on sparse norms use the L1-norm on the model gradients, also called `Total Variation` inversion. While the implementation may differ slightly, the general $l_p$-norm methodology presented above covers this specific case. We can re-write\n", - "\n", - "$$\n", - "\\sum_{i} {|f(m)_i |}^p \\approx \\sum_{i} {\\frac{ (\\mathbf{G}_x \\mathbf{m})_i^2 + (\\mathbf{G}_y \\mathbf{m})_i^2 + (\\mathbf{G}_z \\mathbf{m})_i^2}{\\left( (\\mathbf{G}_x \\mathbf{m})_i^2 + (\\mathbf{G}_y \\mathbf{m})_i^2 + (\\mathbf{G}_z \\mathbf{m})_i^2 + \\epsilon^2 \\right)^{1-p/2 }}} \\;.\n", - "$$\n", - "\n", - "Then for $p=1$\n", - "\n", - "$$\n", - "\\phi(m) \\approx \\sum_{i} \\sqrt{(\\mathbf{G}_x \\mathbf{m})_i^2 + (\\mathbf{G}_y \\mathbf{m})_i^2 + (\\mathbf{G}_z \\mathbf{m})_i^2} \\;,\n", - "$$\n", - "\n", - "we recover the total-variation (TV) function. \n", - "Lastly, for $p=2$\n", - "\n", - "$$\n", - "\\phi(m) = \\sum_{i} (\\mathbf{G}_x \\mathbf{m})_i^2 + (\\mathbf{G}_y \\mathbf{m})_i^2 + (\\mathbf{G}_z \\mathbf{m})_i^2 \\;,\n", - "$$\n", - "\n", - "we recover the smooth regularization.\n", - "\n", - "\n", - "#### Gradient type: Components\n", - "\n", - "Alternatively, we can treat each gradient term independently, such that\n", - "\n", - "$$\n", - "\\phi(m) = \\| \\mathbf{G}_x \\mathbf{m} \\|_p + \\| \\mathbf{G}_y \\mathbf{m} \\|_p + \\| \\mathbf{G}_z \\mathbf{m} \\|_p \\;.\n", - "$$\n", - "\n", - "This formulation tends to recover box-like anomalies with edges aligned with the Cartesian axes. This is generally not desirable unless the gradients can be rotated in 3D.\n" + "All those models also fit the data to the target [data misfit](data-misfit) and are therefore valid solutions to the inversion. Note that as $p \\rightarrow 0$ the edges of the anomaly become tighter while variability inside the body diminishes. They generally agree on the center position of the anomaly but differ greatly on the extent and shape.\n" ] }, { @@ -146,7 +106,7 @@ "id": "e8b6527c-842e-4b8f-8619-bb96ff3deffc", "metadata": {}, "source": [ - "### Background: Approximated $L_p$-norm\n", + "## Background: Approximated $L_p$-norm\n", "\n", "The standard $L_p$ norm measure is generally written as\n", "\n", @@ -173,7 +133,7 @@ "Note that choosing a different $l_p$-norm greatly changes how we measure the function $f(m)$. Rather than simply increasing exponentially with the size of $f(m)$, small norms increase the penalty on low $f(m)$ values.\n", "As $p\\rightarrow 0$, we attempt to recover as few non-zero elements, which in turn favour sparse solutions.\n", "\n", - "Since it is a non-linear function with respect to $\\mathbf{m}$, we must first linearize it as\n", + "Since it is a non-linear function with respect to $\\mathbf{m}$, we can linearize it as\n", "\n", "$$\n", "\\| f(\\mathbf{m})_i \\|_p \\approx \\| \\mathbf{R}_i \\mathbf{W}_i f(\\mathbf{m})_i\\|\n", @@ -185,16 +145,39 @@ "\\mathbf{R}_i = {\\frac{1}{\\left( {{f(m)^{(k-1)}_i}}^{2} + \\epsilon^2 \\right)^{1-p/2 }}}\\,.\n", "$$\n", "\n", - "Here, the superscript $(k)$ denotes the iteration step of the inversion. This is also known as an iterative re-weighted least-squares (IRLS) method. For more details on the implementation, refer to {cite:t}`fournier_2019`." + "Here, the superscript $(k)$ denotes the iteration step of the inversion. This is also known as an iterative re-weighted least-squares (IRLS) method. For more details on the implementation, refer to {cite:t}`fournier_2019`.\n", + "\n", + "### Note on `Total Variation`\n", + "\n", + "In the literature and other inversion software, sparsity constraints are imposed as an L1-norm on the model gradients, also called `Total Variation` inversion. While the implementation may differ slightly, the general $l_p$-norm methodology presented above encompasses this specific case. We can write\n", + "\n", + "$$\n", + "\\sum_{i} {|f(m)_i |}^p \\approx \\sum_{i} {\\frac{ (\\mathbf{G}_x \\mathbf{m})_i^2 + (\\mathbf{G}_y \\mathbf{m})_i^2 + (\\mathbf{G}_z \\mathbf{m})_i^2}{\\left( (\\mathbf{G}_x \\mathbf{m})_i^2 + (\\mathbf{G}_y \\mathbf{m})_i^2 + (\\mathbf{G}_z \\mathbf{m})_i^2 + \\epsilon^2 \\right)^{1-p/2 }}} \\;.\n", + "$$\n", + "\n", + "Then for $p=1$\n", + "\n", + "$$\n", + "\\phi(m) \\approx \\sum_{i} \\sqrt{(\\mathbf{G}_x \\mathbf{m})_i^2 + (\\mathbf{G}_y \\mathbf{m})_i^2 + (\\mathbf{G}_z \\mathbf{m})_i^2} \\;,\n", + "$$\n", + "\n", + "which recovers the total-variation (TV) function. \n", + "Lastly, for $p=2$\n", + "\n", + "$$\n", + "\\phi(m) = \\sum_{i} (\\mathbf{G}_x \\mathbf{m})_i^2 + (\\mathbf{G}_y \\mathbf{m})_i^2 + (\\mathbf{G}_z \\mathbf{m})_i^2 \\;,\n", + "$$\n", + "\n", + "which recovers the smooth regularization. The Total Variation (L1) and Smooth (L2) inversion strategies are therefore specific cases of the more general Lp-norm regularization function for $p \\in [0, 2]$." ] }, { - "cell_type": "markdown", - "id": "2bf887ab", + "cell_type": "code", + "execution_count": null, + "id": "38eb4170-29e8-47e7-8c7f-972c52d8e8ab", "metadata": {}, - "source": [ - "

\n" - ] + "outputs": [], + "source": [] } ], "metadata": { diff --git a/docs/references.bib b/docs/references.bib index 11dfaadd..65f378e5 100644 --- a/docs/references.bib +++ b/docs/references.bib @@ -50,6 +50,15 @@ @Book{TikhonovArsenin77 address = {Washington, D.C.}, } +@Article{LiOldenburg2000, + author = {Y. Li. and D. W. Oldenburg}, + title = {Incorporating geological dip information into geophysical inversions}, + journal = {Geophysics}, + year = {2000}, + volume = {65}, + pages = {148-157}, +} + @Article{LiOldenburg1998, author = {Y. Li. and D. W. Oldenburg}, title = {3-D inversion of gravity data}, diff --git a/docs/tutorials/magnetic.ipynb b/docs/tutorials/magnetic.ipynb index fefb112d..98ef31d3 100644 --- a/docs/tutorials/magnetic.ipynb +++ b/docs/tutorials/magnetic.ipynb @@ -7,10 +7,11 @@ "source": [ "

\n", "\n", - "# Magnetic Inversion\n", + "(magnetic-tutorial)=\n", "\n", - "This section focuses on the inversion of magnetic data using a scalar (susceptibility) and a magnetization (vector) approach generated from the Flin Flon magnetic model. We also cover some strategies on how to remove regional signal and the use of compact norms.\n", + "# Magnetic Inversion\n", "\n", + "This section focuses on the inversion of magnetic scalar (susceptibility) and vector (magnetization) approaches with data generated from the Flin Flon magnetic model. We also cover some strategies on regional signal removal and the use of compact norms.\n", "\n", "\n", "```{figure} ./images/magnetics/mag_model.png\n", From 8b58f6fa95b389811abffaee565f5684804fcf61 Mon Sep 17 00:00:00 2001 From: dominiquef Date: Thu, 7 Aug 2025 08:45:51 -0700 Subject: [PATCH 4/9] Add figure, start reformating text --- .../regularization/images/rotated_demo.png | Bin 0 -> 153182 bytes .../regularization/rotated_gradients.ipynb | 49 ++++++++++++------ 2 files changed, 33 insertions(+), 16 deletions(-) create mode 100644 docs/fundamentals/regularization/images/rotated_demo.png diff --git a/docs/fundamentals/regularization/images/rotated_demo.png b/docs/fundamentals/regularization/images/rotated_demo.png new file mode 100644 index 0000000000000000000000000000000000000000..d7bfc6d34f0d268a8076d491930d3c595302011e GIT binary patch literal 153182 zcma%i1z1#F+b#%-k`f|4(jqO=G14V1-QC@-A|NdxIe>(KfP{4S&?Vj7-8szJ!~1>j 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This option is useful for counteracting modelling bias due to survey design (wide line separation) and reinforcing known geological trends. " + "This section provides details about the rotation of gradient penalties to enforce trends in the model. This option is useful for counteracting modelling bias due to survey design (wide line separation) or reinforcing known geological trends, as depicted in the image below. \n", + "\n", + "```{figure} ./images/rotated_demo.png\n", + "---\n", + "scale: 30%\n", + "---\n", + "(Top) Horizontal and (bottom) verticel sections through (left) a simple dipping dyke model under smooth topography. (Center) Model recovered with the conventional smooth norm inversion. (Right) Compact model obtained with the rotation of the objective function at $45\\circ$ dip and $90\\circ$ azimuth. \n", + "```" ] }, { @@ -19,7 +26,7 @@ "source": [ "## Background\n", "\n", - "As covered in the [Regularization](smooth-ref) section, penalties on the model gradients (smoothness) are by default applied along each of the Cartesian axes:\n", + "As covered in the [Regularization](smooth-ref) section, penalties on the model gradients (smoothness) are defined as:\n", "\n", "$$\n", "\\mathbf{f}_i = \\mathbf{G}_i (\\mathbf{m} - \\mathbf{m}_{ref}),\n", @@ -31,15 +38,8 @@ "\\mathbf{\\hat f}_i = \\mathbf{\\hat G}_i (\\mathbf{m} - \\mathbf{m}_{ref}),\n", "$$\n", "\n", - "where $\\mathbf{\\hat G}_i$ is the rotated gradient along one of the $u$, $v$ and $w$-axis. \n", - "\n", - "![grad](./images/gradient_direction.png)\n", - "\n", + "where $\\mathbf{\\hat G}_i$ is the rotated gradient along one of the $u$, $v$ and $w$-axis. `Simpeg-drivers` uses a combination of forward and backward gradient operators to achieve better symmetry in 3D. The gradient operators are constructed based on the partial volumes intercepted by ghost cells rotated about the center of each cell. The partial volumes include diagonal neighbours. \n", "\n", - "In the case of rotated gradients, we want to treat each component independently such that trends can be reinforced along specific directions.\n", - "$$\n", - "\\phi(m) = \\| \\mathbf{G}_x \\mathbf{m} \\|_p + \\| \\mathbf{G}_y \\mathbf{m} \\|_p + \\| \\mathbf{G}_z \\mathbf{m} \\|_p \\;.\n", - "$$\n", "\n" ] }, @@ -48,18 +48,35 @@ "id": "1ec1e9e0-2f64-41ec-875f-56da5e5ed2ee", "metadata": {}, "source": [ - "## Example\n", - "\n", - "We re-use the [magnetic inversion tutorial]()\n", + "## Inputs\n", "\n", "Direction information can be supplied as either `Dip & Dip direction`, `Dip & Strike` or as `3D Vector` data group. \n", "\n", - "![set_ori](./images/create_orientation.png)\n", "\n", - "Setting the group through the UI and lowering the norms along the oriented plane.\n", + "```{figure} ./images/set_orientation.png\n", + "---\n", + "scale: 30%\n", + "---\n", + " \n", + "```\n", + "\n", + "The `dip` angle is a positive angle (degree) downward from the horizontal. The `strike` and `dip direction` are clockwise angles from North. The `3D vector` defines the unit normal of a plane and is perpendicular to both the `Dip & Dip direction` and `Strike & Dip` vectors.\n", "\n", - "![set_ori](./images/set_orientation.png)" + "```{figure} ./images/gradient_direction.png\n", + "---\n", + "scale: 30%\n", + "---\n", + "Illustration for the three supported orientation data: (a) `Dip & Dip direction`, (b)`Dip & Strike` and (c) `3D Vector`. \n", + "```\n" ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fa4ead38-6e6d-4591-a276-d2a8d4cf3005", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { From 1ca14b154d19827db064002af4dc9f345b69f6bb Mon Sep 17 00:00:00 2001 From: dominiquef Date: Thu, 7 Aug 2025 11:54:43 -0700 Subject: [PATCH 5/9] Add figures for partial volumes and plane rotation --- .../regularization/images/partial_volumes.png | Bin 0 -> 29239 bytes .../regularization/images/plane_rotation.png | Bin 0 -> 55878 bytes .../regularization/rotated_gradients.ipynb | 17 ++++++++++++++--- 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z40FIY+Q`sQPj`K4wd4mfeJp2elDn=munO+yGv1fw1@h literal 0 HcmV?d00001 diff --git a/docs/fundamentals/regularization/rotated_gradients.ipynb b/docs/fundamentals/regularization/rotated_gradients.ipynb index 97ed1fca..2fb7002a 100644 --- a/docs/fundamentals/regularization/rotated_gradients.ipynb +++ b/docs/fundamentals/regularization/rotated_gradients.ipynb @@ -9,13 +9,13 @@ "\n", "# Rotated Gradients\n", "\n", - "This section provides details about the rotation of gradient penalties to enforce trends in the model. This option is useful for counteracting modelling bias due to survey design (wide line separation) or reinforcing known geological trends, as depicted in the image below. \n", + "This section provides details about the rotation of gradient penalties to enforce trends in the model. Used in conjunction with weights and sparse norms, the rotation can help reinforce structural trends, as depicted in the image below. \n", "\n", "```{figure} ./images/rotated_demo.png\n", "---\n", "scale: 30%\n", "---\n", - "(Top) Horizontal and (bottom) verticel sections through (left) a simple dipping dyke model under smooth topography. (Center) Model recovered with the conventional smooth norm inversion. (Right) Compact model obtained with the rotation of the objective function at $45\\circ$ dip and $90\\circ$ azimuth. \n", + "(Top) Horizontal and (bottom) vertical sections through (left) a simple dipping dyke model under smooth topography. (Center) Model recovered using the conventional smooth norm inversion. (Right) Compact model obtained with the rotation of the objective function at $45\\circ$ dip towards East. \n", "```" ] }, @@ -40,7 +40,18 @@ "\n", "where $\\mathbf{\\hat G}_i$ is the rotated gradient along one of the $u$, $v$ and $w$-axis. `Simpeg-drivers` uses a combination of forward and backward gradient operators to achieve better symmetry in 3D. The gradient operators are constructed based on the partial volumes intercepted by ghost cells rotated about the center of each cell. The partial volumes include diagonal neighbours. \n", "\n", - "\n" + "```{figure} ./images/plane_rotation.png\n", + "---\n", + "scale: 30%\n", + "---\n", + "```\n", + "\n", + "\n", + "```{figure} ./images/partial_volumes.png\n", + "---\n", + "scale: 30%\n", + "---\n", + "```\n" ] }, { From b0f39b6daa77353793b918ea738b5f8bdfb5bb2f Mon Sep 17 00:00:00 2001 From: dominiquef Date: Thu, 7 Aug 2025 13:51:06 -0700 Subject: [PATCH 6/9] Fix links --- docs/case_studies/Forrestania/forrestania.ipynb | 2 +- docs/case_studies/Forrestania/open_code.ipynb | 2 +- docs/case_studies/Forrestania/python_code/joint_grav_mag.ipynb | 2 +- .../python_code/unconstrained_gravity_inv_training.ipynb | 2 +- .../python_code/unconstrained_magnetics_inv_training.ipynb | 2 +- docs/fundamentals/data_misfit.ipynb | 2 +- docs/tutorials/gravity.ipynb | 2 +- 7 files changed, 7 insertions(+), 7 deletions(-) diff --git a/docs/case_studies/Forrestania/forrestania.ipynb b/docs/case_studies/Forrestania/forrestania.ipynb index 51d35fc0..bc742dde 100644 --- a/docs/case_studies/Forrestania/forrestania.ipynb +++ b/docs/case_studies/Forrestania/forrestania.ipynb @@ -5,7 +5,7 @@ "id": "34c04eea-4ec5-468f-90aa-0f4bea2b44f3", "metadata": {}, "source": [ - "(forrestania)=\n", + "(forrestania-main)=\n", "\n", "# Forrestania: Joint grav/mag\n", "\n", diff --git a/docs/case_studies/Forrestania/open_code.ipynb b/docs/case_studies/Forrestania/open_code.ipynb index e9da22bd..fbfdae81 100644 --- a/docs/case_studies/Forrestania/open_code.ipynb +++ b/docs/case_studies/Forrestania/open_code.ipynb @@ -14,7 +14,7 @@ "---\n", "```\n", "\n", - "This section demonstrates the processing and inversion of the Forrestania datasets using purely open-source packages. For an equivalent and streamlined version, see the parent [Forrestania](forrestania) case study.\n", + "This section demonstrates the processing and inversion of the Forrestania datasets using purely open-source packages. For an equivalent and streamlined version, see the parent [Forrestania](forrestania-main) case study.\n", "\n", "- [Gravity inversion](gravity-code)\n", "- [Magnetics inversion](magnetics-code)\n", diff --git a/docs/case_studies/Forrestania/python_code/joint_grav_mag.ipynb b/docs/case_studies/Forrestania/python_code/joint_grav_mag.ipynb index a7e35534..f931f86c 100644 --- a/docs/case_studies/Forrestania/python_code/joint_grav_mag.ipynb +++ b/docs/case_studies/Forrestania/python_code/joint_grav_mag.ipynb @@ -18,7 +18,7 @@ "\n", "This section demonstrates the joint inversion of gravity and magnetic data.\n", "\n", - "For an equivalent and streamlined version of this tutorial, see the parent [Forrestania](forrestania) case study.\n", + "For an equivalent and streamlined version of this tutorial, see the parent [Forrestania](forrestania-main) case study.\n", "\n", "```{note}\n", "The steps taken in this tutorial are strongly based on the official [SimPEG Tutorials](https://simpeg.xyz/user-tutorials/).\n", diff --git a/docs/case_studies/Forrestania/python_code/unconstrained_gravity_inv_training.ipynb b/docs/case_studies/Forrestania/python_code/unconstrained_gravity_inv_training.ipynb index 2764cf74..4d06c363 100644 --- a/docs/case_studies/Forrestania/python_code/unconstrained_gravity_inv_training.ipynb +++ b/docs/case_studies/Forrestania/python_code/unconstrained_gravity_inv_training.ipynb @@ -12,7 +12,7 @@ "This section demonstrates the processing and inversion of the **Forrestania gravity dataset** using purely open-source packages.\n", "\n", "For an equivalent and streamlined version, see the parent case study here: \n", - "👉 [Forrestania Case Study](https://mirageoscience-simpeg-drivers.readthedocs-hosted.com/en/geopy-2297/case_studies/Forrestania/forrestania.html#forrestania)\n", + "👉 [Forrestania Case Study](forrestania-main)\n", "\n", "> 💡 **Note**: \n", "> The steps taken in this tutorial are strongly based on the official [SimPEG Tutorials](https://simpeg.xyz/user-tutorials/).\n", diff --git a/docs/case_studies/Forrestania/python_code/unconstrained_magnetics_inv_training.ipynb b/docs/case_studies/Forrestania/python_code/unconstrained_magnetics_inv_training.ipynb index fd092be3..ea098b23 100644 --- a/docs/case_studies/Forrestania/python_code/unconstrained_magnetics_inv_training.ipynb +++ b/docs/case_studies/Forrestania/python_code/unconstrained_magnetics_inv_training.ipynb @@ -12,7 +12,7 @@ "This section demonstrates the processing and inversion of the Forrestania airborne **magnetic** dataset using purely open-source packages. \n", "\n", "For an equivalent and streamlined version, see the parent case study here: \n", - "👉 [Forrestania Case Study](https://mirageoscience-simpeg-drivers.readthedocs-hosted.com/en/geopy-2297/case_studies/Forrestania/forrestania.html#forrestania)\n", + "👉 [Forrestania Case Study](forrestania-main)\n", "\n", "> 💡 **Note**: \n", "\n", diff --git a/docs/fundamentals/data_misfit.ipynb b/docs/fundamentals/data_misfit.ipynb index 1c24293b..4c93e6c5 100644 --- a/docs/fundamentals/data_misfit.ipynb +++ b/docs/fundamentals/data_misfit.ipynb @@ -75,7 +75,7 @@ "source": [ "#### Noise floor too high\n", "\n", - "With a high floor, the inversion is dominated by the [regularization](regularization.ipynb) function and the data remains underfitted - there is coherent signal in the observed data that is not accounted for. The model is very smooth and we have a poor recovery of the shape of the susceptible body." + "With a high floor, the inversion is dominated by the [regularization](regularization) function. As the data remains underfitted, a coherent signal remains unaccounted for. The model is very smooth, and we have a poor recovery of the shape of the susceptible body." ] }, { diff --git a/docs/tutorials/gravity.ipynb b/docs/tutorials/gravity.ipynb index 9a762942..016eeb33 100644 --- a/docs/tutorials/gravity.ipynb +++ b/docs/tutorials/gravity.ipynb @@ -87,7 +87,7 @@ "Refinement strategy used for the magnetic modeling.\n", "```\n", "\n", - "See [Mesh creation](mesh_design) section for general details on the parameters.\n" + "See [Mesh creation](mesh-design) section for general details on the parameters.\n" ] }, { From 547061df262f60c25ddd2aec3d693c186433aa73 Mon Sep 17 00:00:00 2001 From: dominiquef Date: Thu, 7 Aug 2025 15:37:33 -0700 Subject: [PATCH 7/9] FInal edits --- .../regularization/images/local_rotation.png | Bin 0 -> 49371 bytes .../regularization/images/set_orientation.png | Bin 30393 -> 81998 bytes .../regularization/regularization.ipynb | 8 ++ .../regularization/rotated_gradients.ipynb | 88 ++++++++++-------- 4 files changed, 57 insertions(+), 39 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a/docs/fundamentals/regularization/regularization.ipynb +++ b/docs/fundamentals/regularization/regularization.ipynb @@ -109,6 +109,14 @@ "\n", "

" ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "84ea9df7-f402-45e7-b92e-4dfdd04202b4", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { diff --git a/docs/fundamentals/regularization/rotated_gradients.ipynb b/docs/fundamentals/regularization/rotated_gradients.ipynb index 2fb7002a..33b269d2 100644 --- a/docs/fundamentals/regularization/rotated_gradients.ipynb +++ b/docs/fundamentals/regularization/rotated_gradients.ipynb @@ -9,13 +9,40 @@ "\n", "# Rotated Gradients\n", "\n", - "This section provides details about the rotation of gradient penalties to enforce trends in the model. Used in conjunction with weights and sparse norms, the rotation can help reinforce structural trends, as depicted in the image below. \n", + "This section provides details about rotating the model gradients used in the [Regularization](#Regularization) function. Applied in conjunction with weights and sparse norms, the rotation can help reinforce structural trends, as depicted in the image below. \n", "\n", "```{figure} ./images/rotated_demo.png\n", "---\n", "scale: 30%\n", "---\n", - "(Top) Horizontal and (bottom) vertical sections through (left) a simple dipping dyke model under smooth topography. (Center) Model recovered using the conventional smooth norm inversion. (Right) Compact model obtained with the rotation of the objective function at $45\\circ$ dip towards East. \n", + "(Top) Horizontal and (bottom) vertical sections through (left) a simple dipping dyke model under smooth topography. (Center) Model recovered using the conventional smooth norm inversion. (Right) Compact model obtained with a dip rotation of $45\\circ$ towards East. \n", + "```\n", + "\n", + "The rotation angles can be applied globally, or on a cell-by-cell basis to reflect local orientations, such as faults and folds. \n", + "\n", + "```{figure} ./images/local_rotation.png\n", + "---\n", + "scale: 30%\n", + "---\n", + "Example of an inversion with local rotations along the expected limbs of a folded layer.\n", + "```\n", + "\n", + "## Input format\n", + "\n", + "Direction information must be supplied as a `Data Group` defined on the inversion mesh. The following group types are accepted: `Dip direction & Dip`, `Strike & Dip` or as `3D vector`. \n", + "\n", + "```{figure} ./images/set_orientation.png\n", + "---\n", + "scale: 30%\n", + "---\n", + "```\n", + "\n", + "The `dip` angles (degrees) are positive downward from the horizontal. The `strike` and `dip direction` angles (degrees) are positive clockwise from North. The `3D vector` vector data defines the unit normals, which are perpendicular to both the `Dip direction & Dip` and `Strike & Dip` directions. As illustrated below, all three formats define a rotated plane in 3D.\n", + "\n", + "```{figure} ./images/gradient_direction.png\n", + "---\n", + "scale: 50%\n", + "--- \n", "```" ] }, @@ -26,68 +53,51 @@ "source": [ "## Background\n", "\n", - "As covered in the [Regularization](smooth-ref) section, penalties on the model gradients (smoothness) are defined as:\n", + "As covered in the [Model Smoothness](smooth-ref) section, penalties on the model gradients are measured by:\n", "\n", "$$\n", "\\mathbf{f}_i = \\mathbf{G}_i (\\mathbf{m} - \\mathbf{m}_{ref}),\n", "$$\n", "\n", - "where $\\mathbf{G}_i$ is a finite difference operator that measures the gradient of the model $\\mathbf{m}$ along one of the Cartesian directions. As proposed by {cite:t}`LiOldenburg2000`, orientation information can be incorporated in the inversion by rotating the gradient operators along different directions such that \n", + "where $\\mathbf{G}_i$ is a finite difference operator that computes the difference in model $\\mathbf{m}$ values between adjacent cells along one of the Cartesian directions: East (X), North (Y) and vertical (Z). As proposed by {cite:t}`LiOldenburg2000`, orientation information can be incorporated in the inversion by rotating the gradient operators along arbitrary directions such that \n", "\n", "$$\n", "\\mathbf{\\hat f}_i = \\mathbf{\\hat G}_i (\\mathbf{m} - \\mathbf{m}_{ref}),\n", "$$\n", "\n", - "where $\\mathbf{\\hat G}_i$ is the rotated gradient along one of the $u$, $v$ and $w$-axis. `Simpeg-drivers` uses a combination of forward and backward gradient operators to achieve better symmetry in 3D. The gradient operators are constructed based on the partial volumes intercepted by ghost cells rotated about the center of each cell. The partial volumes include diagonal neighbours. \n", + "where $\\mathbf{\\hat G}_i$ are rotated gradients along one of the $u$, $v$ and $w$-axis.\n", "\n", "```{figure} ./images/plane_rotation.png\n", "---\n", - "scale: 30%\n", + "name: plane_rotation\n", + "scale: 50%\n", "---\n", + "Rotation of the Cartesian axes along an arbitrary plane.\n", "```\n", "\n", + "- $X \\rightarrow u$ pointing down-dip\n", + "- $Y \\rightarrow v$ pointing along strike\n", + "- $Z \\rightarrow w$ pointing along the normal\n", "\n", - "```{figure} ./images/partial_volumes.png\n", - "---\n", - "scale: 30%\n", - "---\n", - "```\n" - ] - }, - { - "cell_type": "markdown", - "id": "1ec1e9e0-2f64-41ec-875f-56da5e5ed2ee", - "metadata": {}, - "source": [ - "## Inputs\n", - "\n", - "Direction information can be supplied as either `Dip & Dip direction`, `Dip & Strike` or as `3D Vector` data group. \n", + "### Special note\n", "\n", + "`Simpeg-Drivers` uses a combination of both forward and backward gradient operators to achieve better symmetry in 3D. The gradient operators are constructed based on the partial volumes intercepted by ghost cells rotated about the center of each cell. The partial volumes include all diagonal neighbours intercepted by the ghost cells. \n", "\n", - "```{figure} ./images/set_orientation.png\n", + "```{figure} ./images/partial_volumes.png\n", "---\n", - "scale: 30%\n", + "scale: 50%\n", "---\n", - " \n", + "Plan-view depiction of the $u,v$ forward gradient operators, made up of partial volumes from neighbouring cells.\n", "```\n", "\n", - "The `dip` angle is a positive angle (degree) downward from the horizontal. The `strike` and `dip direction` are clockwise angles from North. The `3D vector` defines the unit normal of a plane and is perpendicular to both the `Dip & Dip direction` and `Strike & Dip` vectors.\n", + "The full regularization term is made up of seven terms in total\n", "\n", - "```{figure} ./images/gradient_direction.png\n", - "---\n", - "scale: 30%\n", - "---\n", - "Illustration for the three supported orientation data: (a) `Dip & Dip direction`, (b)`Dip & Strike` and (c) `3D Vector`. \n", - "```\n" + "$$\n", + "\\phi_m = \\| \\mathbf{W}_s (\\mathbf{m} - \\mathbf{m}_{ref}) \\|_2^2 + \\sum_{i = u^F,v^F,w^F} \\| \\mathbf{W}_i \\mathbf{G}_i(\\mathbf{m}) \\|_2^2 + \\sum_{i = u^B,v^B,w^B,} \\| \\mathbf{W}_i \\mathbf{G}_i(\\mathbf{m}) \\|_2^2\n", + "$$\n", + "\n", + "\n" ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "fa4ead38-6e6d-4591-a276-d2a8d4cf3005", - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { From ea0934c8661b5a5757d02f6f818d9a81f2eeb33a Mon Sep 17 00:00:00 2001 From: dominiquef Date: Mon, 11 Aug 2025 10:34:10 -0700 Subject: [PATCH 8/9] Re-lock --- .../py-3.10-linux-64-dev.conda.lock.yml | 83 ++- environments/py-3.10-linux-64.conda.lock.yml | 59 +- .../py-3.10-win-64-dev.conda.lock.yml | 73 +- environments/py-3.10-win-64.conda.lock.yml | 49 +- .../py-3.11-linux-64-dev.conda.lock.yml | 85 ++- environments/py-3.11-linux-64.conda.lock.yml | 61 +- .../py-3.11-win-64-dev.conda.lock.yml | 75 +- environments/py-3.11-win-64.conda.lock.yml | 51 +- .../py-3.12-linux-64-dev.conda.lock.yml | 85 ++- environments/py-3.12-linux-64.conda.lock.yml | 61 +- .../py-3.12-win-64-dev.conda.lock.yml | 75 +- environments/py-3.12-win-64.conda.lock.yml | 51 +- py-3.10.conda-lock.yml | 658 ++++++++--------- py-3.11.conda-lock.yml | 674 +++++++++--------- py-3.12.conda-lock.yml | 674 +++++++++--------- 15 files changed, 1362 insertions(+), 1452 deletions(-) diff --git a/environments/py-3.10-linux-64-dev.conda.lock.yml b/environments/py-3.10-linux-64-dev.conda.lock.yml index fff35ec6..4d6d8496 100644 --- a/environments/py-3.10-linux-64-dev.conda.lock.yml +++ b/environments/py-3.10-linux-64-dev.conda.lock.yml @@ -1,6 +1,6 @@ # Generated by conda-lock. # platform: linux-64 -# input_hash: 7b2bb2835665234d0ef442f0e4a4c9717b61f9a50ae298c50cf9cae2e9369ece +# input_hash: aa70c6c517bbe8472b7de3ce4e8d391ca7e1d86e6bfe0e2a4e53e756c6e8388b channels: - conda-forge @@ -10,9 +10,9 @@ dependencies: - accessible-pygments=0.0.5=pyhd8ed1ab_1 - alabaster=0.7.16=pyhd8ed1ab_0 - annotated-types=0.7.0=pyhd8ed1ab_1 - - anyio=4.9.0=pyh29332c3_0 + - anyio=4.10.0=pyhe01879c_0 - argon2-cffi=25.1.0=pyhd8ed1ab_0 - - argon2-cffi-bindings=21.2.0=py310ha75aee5_5 + - argon2-cffi-bindings=25.1.0=py310h7c4b9e2_0 - arrow=1.3.0=pyhd8ed1ab_1 - asciitree=0.3.3=py_2 - astroid=3.3.11=py310hff52083_0 @@ -29,23 +29,23 @@ dependencies: - brotli-python=1.1.0=py310hf71b8c6_3 - bzip2=1.0.8=h4bc722e_7 - c-ares=1.34.5=hb9d3cd8_0 - - ca-certificates=2025.7.14=hbd8a1cb_0 + - ca-certificates=2025.8.3=hbd8a1cb_0 - cached-property=1.5.2=hd8ed1ab_1 - cached_property=1.5.2=pyha770c72_1 - - certifi=2025.7.14=pyhd8ed1ab_0 + - certifi=2025.8.3=pyhd8ed1ab_0 - cffi=1.17.1=py310h8deb56e_0 - - charset-normalizer=3.4.2=pyhd8ed1ab_0 + - charset-normalizer=3.4.3=pyhd8ed1ab_0 - click=8.2.1=pyh707e725_0 - cloudpickle=3.1.1=pyhd8ed1ab_0 - colorama=0.4.6=pyhd8ed1ab_1 - comm=0.2.3=pyhe01879c_0 - contourpy=1.3.2=py310h3788b33_0 - - coverage=7.10.1=py310h3406613_0 + - coverage=7.10.3=py310h3406613_0 - cycler=0.12.1=pyhd8ed1ab_1 - cytoolz=1.0.1=py310ha75aee5_0 - dask-core=2025.3.0=pyhd8ed1ab_0 - dataclasses=0.8=pyhc8e2a94_3 - - debugpy=1.8.15=py310h25320af_0 + - debugpy=1.8.16=py310h25320af_0 - decorator=5.2.1=pyhd8ed1ab_0 - defusedxml=0.7.1=pyhd8ed1ab_0 - dill=0.4.0=pyhd8ed1ab_0 @@ -60,7 +60,7 @@ dependencies: - freetype=2.13.3=ha770c72_1 - fsspec=2025.7.0=pyhd8ed1ab_0 - geoana=0.7.2=py310ha2bacc8_0 - - greenlet=3.2.3=py310hf71b8c6_0 + - greenlet=3.2.4=py310hea6c23e_0 - h11=0.16.0=pyhd8ed1ab_0 - h2=4.2.0=pyhd8ed1ab_0 - h5py=3.14.0=nompi_py310hea1e86d_100 @@ -69,13 +69,12 @@ dependencies: - httpcore=1.0.9=pyh29332c3_0 - httpx=0.28.1=pyhd8ed1ab_0 - hyperframe=6.1.0=pyhd8ed1ab_0 - - icu=75.1=he02047a_0 - idna=3.10=pyhd8ed1ab_1 - imagesize=1.4.1=pyhd8ed1ab_0 - importlib-metadata=8.7.0=pyhe01879c_1 - importlib_metadata=8.7.0=h40b2b14_1 - iniconfig=2.0.0=pyhd8ed1ab_1 - - ipykernel=6.30.0=pyh82676e8_0 + - ipykernel=6.30.1=pyh82676e8_0 - ipython=8.37.0=pyh8f84b5b_0 - ipython_genutils=0.2.0=pyhd8ed1ab_2 - ipywidgets=7.8.5=pyhd8ed1ab_0 @@ -102,8 +101,8 @@ dependencies: - jupyterlab_server=2.27.3=pyhd8ed1ab_1 - jupyterlab_widgets=1.1.11=pyhd8ed1ab_0 - jupytext=1.17.2=pyh80e38bb_0 - - keyutils=1.6.1=h166bdaf_0 - - kiwisolver=1.4.8=py310h3788b33_1 + - keyutils=1.6.3=hb9d3cd8_0 + - kiwisolver=1.4.9=py310haaf941d_0 - krb5=1.21.3=h659f571_0 - lark=1.2.2=pyhd8ed1ab_1 - latexcodec=2.0.1=pyh9f0ad1d_0 @@ -111,11 +110,11 @@ dependencies: - ld_impl_linux-64=2.44=h1423503_1 - lerc=4.0.0=h0aef613_1 - libaec=1.1.4=h3f801dc_0 - - libblas=3.9.0=32_hfdb39a5_mkl + - libblas=3.9.0=34_hfdb39a5_mkl - libbrotlicommon=1.1.0=hb9d3cd8_3 - libbrotlidec=1.1.0=hb9d3cd8_3 - libbrotlienc=1.1.0=hb9d3cd8_3 - - libcblas=3.9.0=32_h372d94f_mkl + - libcblas=3.9.0=34_h372d94f_mkl - libcurl=8.14.1=h332b0f4_0 - libdeflate=1.24=h86f0d12_0 - libdlf=0.3.0=pyhd8ed1ab_1 @@ -125,14 +124,14 @@ dependencies: - libffi=3.4.6=h2dba641_1 - libfreetype=2.13.3=ha770c72_1 - libfreetype6=2.13.3=h48d6fc4_1 - - libgcc=15.1.0=h767d61c_3 - - libgcc-ng=15.1.0=h69a702a_3 - - libgfortran=15.1.0=h69a702a_3 - - libgfortran5=15.1.0=hcea5267_3 - - libhwloc=2.11.2=default_h3d81e11_1002 - - libiconv=1.18=h4ce23a2_1 + - libgcc=15.1.0=h767d61c_4 + - libgcc-ng=15.1.0=h69a702a_4 + - libgfortran=15.1.0=h69a702a_4 + - libgfortran5=15.1.0=hcea5267_4 + - libhwloc=2.12.1=default_h3d81e11_1000 + - libiconv=1.18=h3b78370_2 - libjpeg-turbo=3.1.0=hb9d3cd8_0 - - liblapack=3.9.0=32_hc41d3b0_mkl + - liblapack=3.9.0=34_hc41d3b0_mkl - liblzma=5.8.1=hb9d3cd8_2 - libnghttp2=1.64.0=h161d5f1_0 - libnsl=2.0.1=hb9d3cd8_1 @@ -140,19 +139,19 @@ dependencies: - libscotch=7.0.6=hea33c07_1 - libsodium=1.0.20=h4ab18f5_0 - libspatialindex=2.0.0=he02047a_0 - - libsqlite=3.50.3=hee844dc_1 + - libsqlite=3.50.4=h0c1763c_0 - libssh2=1.11.1=hcf80075_0 - - libstdcxx=15.1.0=h8f9b012_3 - - libstdcxx-ng=15.1.0=h4852527_3 + - libstdcxx=15.1.0=h8f9b012_4 + - libstdcxx-ng=15.1.0=h4852527_4 - libtiff=4.7.0=hf01ce69_5 - libuuid=2.38.1=h0b41bf4_0 - libwebp-base=1.6.0=hd42ef1d_0 - libxcb=1.17.0=h8a09558_0 - libxcrypt=4.4.36=hd590300_1 - - libxml2=2.13.8=h4bc477f_0 + - libxml2=2.13.8=h2cb61b6_1 - libzlib=1.3.1=hb9d3cd8_2 - linkify-it-py=2.0.3=pyhd8ed1ab_1 - - llvm-openmp=20.1.8=h4922eb0_0 + - llvm-openmp=20.1.8=h4922eb0_1 - locket=1.0.0=pyhd8ed1ab_0 - markdown-it-py=2.2.0=pyhd8ed1ab_0 - markupsafe=3.0.2=py310h89163eb_1 @@ -163,7 +162,7 @@ dependencies: - mdurl=0.1.2=pyhd8ed1ab_1 - metis=5.1.0=hd0bcaf9_1007 - mistune=3.1.3=pyh29332c3_0 - - mkl=2024.2.2=ha770c72_16 + - mkl=2024.2.2=ha770c72_17 - msgpack-python=1.1.1=py310h3788b33_0 - mumps-include=5.7.3=h82cca05_10 - mumps-seq=5.7.3=h06cbf8f_10 @@ -177,12 +176,12 @@ dependencies: - nbformat=5.10.4=pyhd8ed1ab_1 - ncurses=6.5=h2d0b736_3 - nest-asyncio=1.6.0=pyhd8ed1ab_1 - - notebook=7.4.4=pyhd8ed1ab_0 + - notebook=7.4.5=pyhd8ed1ab_0 - notebook-shim=0.2.4=pyhd8ed1ab_1 - numcodecs=0.13.1=py310h5eaa309_0 - numpy=1.26.4=py310hb13e2d6_0 - - openjpeg=2.5.3=h5fbd93e_0 - - openssl=3.5.1=h7b32b05_0 + - openjpeg=2.5.3=h55fea9a_1 + - openssl=3.5.2=h26f9b46_0 - overrides=7.7.0=pyhd8ed1ab_1 - packaging=25.0=pyh29332c3_1 - pandas=2.3.1=py310h0158d43_0 @@ -193,7 +192,7 @@ dependencies: - pexpect=4.9.0=pyhd8ed1ab_1 - pickleshare=0.7.5=pyhd8ed1ab_1004 - pillow=10.3.0=py310hebfe307_1 - - pip=25.1.1=pyh8b19718_0 + - pip=25.2=pyh8b19718_0 - platformdirs=4.3.8=pyhe01879c_0 - pluggy=1.6.0=pyhd8ed1ab_0 - prometheus_client=0.22.1=pyhd8ed1ab_0 @@ -210,7 +209,7 @@ dependencies: - pydata-sphinx-theme=0.15.4=pyhd8ed1ab_0 - pydiso=0.1.2=py310h69a6472_0 - pygments=2.19.2=pyhd8ed1ab_0 - - pylint=3.3.7=pyhe01879c_0 + - pylint=3.3.8=pyhe01879c_0 - pymatsolver=0.3.1=pyh48887ae_201 - pyparsing=3.2.3=pyhe01879c_2 - pysocks=1.7.1=pyha55dd90_7 @@ -225,7 +224,7 @@ dependencies: - python_abi=3.10=8_cp310 - pytz=2025.2=pyhd8ed1ab_0 - pyyaml=6.0.2=py310h89163eb_2 - - pyzmq=27.0.0=py310h71f11fc_0 + - pyzmq=27.0.1=py310h9a5fd63_0 - readline=8.2=h8c095d6_2 - readthedocs-sphinx-ext=2.2.5=pyhd8ed1ab_1 - referencing=0.36.2=pyh29332c3_0 @@ -233,9 +232,9 @@ dependencies: - rfc3339-validator=0.1.4=pyhd8ed1ab_1 - rfc3986-validator=0.1.1=pyh9f0ad1d_0 - rfc3987-syntax=1.1.0=pyhe01879c_1 - - rpds-py=0.26.0=py310hbcd0ec0_0 + - rpds-py=0.27.0=py310hd8f68c5_0 - rtree=1.2.0=py310haf1e407_1 - - scikit-learn=1.5.2=py310h27f47ee_1 + - scikit-learn=1.6.1=py310h27f47ee_0 - scipy=1.14.1=py310hfcf56fc_2 - send2trash=1.8.3=pyh0d859eb_1 - setuptools=80.9.0=pyhff2d567_0 @@ -264,7 +263,7 @@ dependencies: - sqlalchemy=2.0.42=py310h7c4b9e2_0 - stack_data=0.6.3=pyhd8ed1ab_1 - tabulate=0.9.0=pyhd8ed1ab_2 - - tbb=2021.13.0=hceb3a55_1 + - tbb=2021.13.0=hb60516a_2 - tblib=3.1.0=pyhd8ed1ab_0 - terminado=0.18.1=pyh0d859eb_0 - threadpoolctl=3.6.0=pyhecae5ae_0 @@ -274,11 +273,11 @@ dependencies: - tomli=2.2.1=pyhe01879c_2 - tomlkit=0.13.3=pyha770c72_0 - toolz=1.0.0=pyhd8ed1ab_1 - - tornado=6.5.1=py310ha75aee5_0 + - tornado=6.5.2=py310h7c4b9e2_0 - tqdm=4.67.1=pyhd8ed1ab_1 - traitlets=5.14.3=pyhd8ed1ab_1 - trimesh=4.1.8=pyhd8ed1ab_0 - - types-python-dateutil=2.9.0.20250708=pyhd8ed1ab_0 + - types-python-dateutil=2.9.0.20250809=pyhd8ed1ab_0 - typing-extensions=4.14.1=h4440ef1_0 - typing-inspection=0.4.1=pyhd8ed1ab_0 - typing_extensions=4.14.1=pyhe01879c_0 @@ -305,9 +304,9 @@ dependencies: - zstandard=0.23.0=py310ha75aee5_2 - zstd=1.5.7=hb8e6e7a_2 - pip: - - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@020de8616b4767a596a4d0f49bce53c8d0c9da5b - - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@d567cc98901ecfa360ff2e93f8a6334a1bed24bc - - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@01a7068fdab7fba8695ad371c9fd9164760a09df + - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@1dbe97d441d65962a94e071b5c1c27d9facd2050 + - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@570ea996ae7e48ab1b8b971b23c9c73b7f5637b2 + - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@a1cf0ec4aa28705eb7de68cfedb255de6e590433 - octree-creation-app @ git+https://github.com/MiraGeoscience/octree-creation-app.git@02fbd85bf7d54b8f4336f1f0094c1c3e27714e81 - param-sweeps @ git+https://github.com/MiraGeoscience/param-sweeps.git@9ed6091534d638171957a17324e1a1e8f067b434 diff --git a/environments/py-3.10-linux-64.conda.lock.yml b/environments/py-3.10-linux-64.conda.lock.yml index 0839556c..6fa49d78 100644 --- a/environments/py-3.10-linux-64.conda.lock.yml +++ b/environments/py-3.10-linux-64.conda.lock.yml @@ -1,6 +1,6 @@ # Generated by conda-lock. # platform: linux-64 -# input_hash: 7b2bb2835665234d0ef442f0e4a4c9717b61f9a50ae298c50cf9cae2e9369ece +# input_hash: aa70c6c517bbe8472b7de3ce4e8d391ca7e1d86e6bfe0e2a4e53e756c6e8388b channels: - conda-forge @@ -15,10 +15,10 @@ dependencies: - brotli-python=1.1.0=py310hf71b8c6_3 - bzip2=1.0.8=h4bc722e_7 - c-ares=1.34.5=hb9d3cd8_0 - - ca-certificates=2025.7.14=hbd8a1cb_0 + - ca-certificates=2025.8.3=hbd8a1cb_0 - cached-property=1.5.2=hd8ed1ab_1 - cached_property=1.5.2=pyha770c72_1 - - certifi=2025.7.14=pyhd8ed1ab_0 + - certifi=2025.8.3=pyhd8ed1ab_0 - cffi=1.17.1=py310h8deb56e_0 - click=8.2.1=pyh707e725_0 - cloudpickle=3.1.1=pyhd8ed1ab_0 @@ -39,22 +39,21 @@ dependencies: - hdf5=1.14.6=nompi_h6e4c0c1_103 - hpack=4.1.0=pyhd8ed1ab_0 - hyperframe=6.1.0=pyhd8ed1ab_0 - - icu=75.1=he02047a_0 - importlib-metadata=8.7.0=pyhe01879c_1 - jinja2=3.1.6=pyhd8ed1ab_0 - joblib=1.5.1=pyhd8ed1ab_0 - - keyutils=1.6.1=h166bdaf_0 - - kiwisolver=1.4.8=py310h3788b33_1 + - keyutils=1.6.3=hb9d3cd8_0 + - kiwisolver=1.4.9=py310haaf941d_0 - krb5=1.21.3=h659f571_0 - lcms2=2.17=h717163a_0 - ld_impl_linux-64=2.44=h1423503_1 - lerc=4.0.0=h0aef613_1 - libaec=1.1.4=h3f801dc_0 - - libblas=3.9.0=32_hfdb39a5_mkl + - libblas=3.9.0=34_hfdb39a5_mkl - libbrotlicommon=1.1.0=hb9d3cd8_3 - libbrotlidec=1.1.0=hb9d3cd8_3 - libbrotlienc=1.1.0=hb9d3cd8_3 - - libcblas=3.9.0=32_h372d94f_mkl + - libcblas=3.9.0=34_h372d94f_mkl - libcurl=8.14.1=h332b0f4_0 - libdeflate=1.24=h86f0d12_0 - libdlf=0.3.0=pyhd8ed1ab_1 @@ -64,37 +63,37 @@ dependencies: - libffi=3.4.6=h2dba641_1 - libfreetype=2.13.3=ha770c72_1 - libfreetype6=2.13.3=h48d6fc4_1 - - libgcc=15.1.0=h767d61c_3 - - libgcc-ng=15.1.0=h69a702a_3 - - libgfortran=15.1.0=h69a702a_3 - - libgfortran5=15.1.0=hcea5267_3 - - libhwloc=2.11.2=default_h3d81e11_1002 - - libiconv=1.18=h4ce23a2_1 + - libgcc=15.1.0=h767d61c_4 + - libgcc-ng=15.1.0=h69a702a_4 + - libgfortran=15.1.0=h69a702a_4 + - libgfortran5=15.1.0=hcea5267_4 + - libhwloc=2.12.1=default_h3d81e11_1000 + - libiconv=1.18=h3b78370_2 - libjpeg-turbo=3.1.0=hb9d3cd8_0 - - liblapack=3.9.0=32_hc41d3b0_mkl + - liblapack=3.9.0=34_hc41d3b0_mkl - liblzma=5.8.1=hb9d3cd8_2 - libnghttp2=1.64.0=h161d5f1_0 - libnsl=2.0.1=hb9d3cd8_1 - libpng=1.6.50=h421ea60_1 - libscotch=7.0.6=hea33c07_1 - libspatialindex=2.0.0=he02047a_0 - - libsqlite=3.50.3=hee844dc_1 + - libsqlite=3.50.4=h0c1763c_0 - libssh2=1.11.1=hcf80075_0 - - libstdcxx=15.1.0=h8f9b012_3 - - libstdcxx-ng=15.1.0=h4852527_3 + - libstdcxx=15.1.0=h8f9b012_4 + - libstdcxx-ng=15.1.0=h4852527_4 - libtiff=4.7.0=hf01ce69_5 - libuuid=2.38.1=h0b41bf4_0 - libwebp-base=1.6.0=hd42ef1d_0 - libxcb=1.17.0=h8a09558_0 - libxcrypt=4.4.36=hd590300_1 - - libxml2=2.13.8=h4bc477f_0 + - libxml2=2.13.8=h2cb61b6_1 - libzlib=1.3.1=hb9d3cd8_2 - - llvm-openmp=20.1.8=h4922eb0_0 + - llvm-openmp=20.1.8=h4922eb0_1 - locket=1.0.0=pyhd8ed1ab_0 - markupsafe=3.0.2=py310h89163eb_1 - matplotlib-base=3.8.4=py310hef631a5_2 - metis=5.1.0=hd0bcaf9_1007 - - mkl=2024.2.2=ha770c72_16 + - mkl=2024.2.2=ha770c72_17 - msgpack-python=1.1.1=py310h3788b33_0 - mumps-include=5.7.3=h82cca05_10 - mumps-seq=5.7.3=h06cbf8f_10 @@ -102,13 +101,13 @@ dependencies: - ncurses=6.5=h2d0b736_3 - numcodecs=0.13.1=py310h5eaa309_0 - numpy=1.26.4=py310hb13e2d6_0 - - openjpeg=2.5.3=h5fbd93e_0 - - openssl=3.5.1=h7b32b05_0 + - openjpeg=2.5.3=h55fea9a_1 + - openssl=3.5.2=h26f9b46_0 - packaging=25.0=pyh29332c3_1 - pandas=2.3.1=py310h0158d43_0 - partd=1.4.2=pyhd8ed1ab_0 - pillow=10.3.0=py310hebfe307_1 - - pip=25.1.1=pyh8b19718_0 + - pip=25.2=pyh8b19718_0 - psutil=7.0.0=py310ha75aee5_0 - pthread-stubs=0.4=hb9d3cd8_1002 - pycparser=2.22=pyh29332c3_1 @@ -127,17 +126,17 @@ dependencies: - pyyaml=6.0.2=py310h89163eb_2 - readline=8.2=h8c095d6_2 - rtree=1.2.0=py310haf1e407_1 - - scikit-learn=1.5.2=py310h27f47ee_1 + - scikit-learn=1.6.1=py310h27f47ee_0 - scipy=1.14.1=py310hfcf56fc_2 - setuptools=80.9.0=pyhff2d567_0 - six=1.17.0=pyhe01879c_1 - sortedcontainers=2.4.0=pyhd8ed1ab_1 - - tbb=2021.13.0=hceb3a55_1 + - tbb=2021.13.0=hb60516a_2 - tblib=3.1.0=pyhd8ed1ab_0 - threadpoolctl=3.6.0=pyhecae5ae_0 - tk=8.6.13=noxft_hd72426e_102 - toolz=1.0.0=pyhd8ed1ab_1 - - tornado=6.5.1=py310ha75aee5_0 + - tornado=6.5.2=py310h7c4b9e2_0 - tqdm=4.67.1=pyhd8ed1ab_1 - trimesh=4.1.8=pyhd8ed1ab_0 - typing-extensions=4.14.1=h4440ef1_0 @@ -157,9 +156,9 @@ dependencies: - zstandard=0.23.0=py310ha75aee5_2 - zstd=1.5.7=hb8e6e7a_2 - pip: - - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@020de8616b4767a596a4d0f49bce53c8d0c9da5b - - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@d567cc98901ecfa360ff2e93f8a6334a1bed24bc - - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@01a7068fdab7fba8695ad371c9fd9164760a09df + - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@1dbe97d441d65962a94e071b5c1c27d9facd2050 + - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@570ea996ae7e48ab1b8b971b23c9c73b7f5637b2 + - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@a1cf0ec4aa28705eb7de68cfedb255de6e590433 - octree-creation-app @ git+https://github.com/MiraGeoscience/octree-creation-app.git@02fbd85bf7d54b8f4336f1f0094c1c3e27714e81 - param-sweeps @ git+https://github.com/MiraGeoscience/param-sweeps.git@9ed6091534d638171957a17324e1a1e8f067b434 diff --git a/environments/py-3.10-win-64-dev.conda.lock.yml b/environments/py-3.10-win-64-dev.conda.lock.yml index b85ae2c2..23350ad5 100644 --- a/environments/py-3.10-win-64-dev.conda.lock.yml +++ b/environments/py-3.10-win-64-dev.conda.lock.yml @@ -1,6 +1,6 @@ # Generated by conda-lock. # platform: win-64 -# input_hash: 12cc832b6afad224ba7a18f42ebe117e16cedc70424e95b2c7e3894be647d2bf +# input_hash: 5babf042397838038a28ac78c72c28e9b56b16d89d92d69d08e0421c96c8624b channels: - conda-forge @@ -10,9 +10,9 @@ dependencies: - accessible-pygments=0.0.5=pyhd8ed1ab_1 - alabaster=0.7.16=pyhd8ed1ab_0 - annotated-types=0.7.0=pyhd8ed1ab_1 - - anyio=4.9.0=pyh29332c3_0 + - anyio=4.10.0=pyhe01879c_0 - argon2-cffi=25.1.0=pyhd8ed1ab_0 - - argon2-cffi-bindings=21.2.0=py310ha8f682b_5 + - argon2-cffi-bindings=25.1.0=py310h29418f3_0 - arrow=1.3.0=pyhd8ed1ab_1 - asciitree=0.3.3=py_2 - astroid=3.3.11=py310h5588dad_0 @@ -28,24 +28,24 @@ dependencies: - brotli-bin=1.1.0=h2466b09_3 - brotli-python=1.1.0=py310h9e98ed7_3 - bzip2=1.0.8=h2466b09_7 - - ca-certificates=2025.7.14=h4c7d964_0 + - ca-certificates=2025.8.3=h4c7d964_0 - cached-property=1.5.2=hd8ed1ab_1 - cached_property=1.5.2=pyha770c72_1 - - certifi=2025.7.14=pyhd8ed1ab_0 + - certifi=2025.8.3=pyhd8ed1ab_0 - cffi=1.17.1=py310ha8f682b_0 - - charset-normalizer=3.4.2=pyhd8ed1ab_0 + - charset-normalizer=3.4.3=pyhd8ed1ab_0 - click=8.2.1=pyh7428d3b_0 - cloudpickle=3.1.1=pyhd8ed1ab_0 - colorama=0.4.6=pyhd8ed1ab_1 - comm=0.2.3=pyhe01879c_0 - contourpy=1.3.2=py310hc19bc0b_0 - - coverage=7.10.1=py310hdb0e946_0 + - coverage=7.10.3=py310hdb0e946_0 - cpython=3.10.18=py310hd8ed1ab_0 - cycler=0.12.1=pyhd8ed1ab_1 - cytoolz=1.0.1=py310ha8f682b_0 - dask-core=2025.3.0=pyhd8ed1ab_0 - dataclasses=0.8=pyhc8e2a94_3 - - debugpy=1.8.15=py310h699e580_0 + - debugpy=1.8.16=py310h699e580_0 - decorator=5.2.1=pyhd8ed1ab_0 - defusedxml=0.7.1=pyhd8ed1ab_0 - dill=0.4.0=pyhd8ed1ab_0 @@ -60,7 +60,7 @@ dependencies: - freetype=2.13.3=h57928b3_1 - fsspec=2025.7.0=pyhd8ed1ab_0 - geoana=0.7.2=py310h3e8ed56_0 - - greenlet=3.2.3=py310h9e98ed7_0 + - greenlet=3.2.4=py310h73ae2b4_0 - h11=0.16.0=pyhd8ed1ab_0 - h2=4.2.0=pyhd8ed1ab_0 - h5py=3.14.0=nompi_py310h877c39c_100 @@ -74,8 +74,7 @@ dependencies: - importlib-metadata=8.7.0=pyhe01879c_1 - importlib_metadata=8.7.0=h40b2b14_1 - iniconfig=2.0.0=pyhd8ed1ab_1 - - intel-openmp=2024.2.1=h57928b3_1083 - - ipykernel=6.30.0=pyh3521513_0 + - ipykernel=6.30.1=pyh3521513_0 - ipython=8.37.0=pyha7b4d00_0 - ipython_genutils=0.2.0=pyhd8ed1ab_2 - ipywidgets=7.8.5=pyhd8ed1ab_0 @@ -102,18 +101,18 @@ dependencies: - jupyterlab_server=2.27.3=pyhd8ed1ab_1 - jupyterlab_widgets=1.1.11=pyhd8ed1ab_0 - jupytext=1.17.2=pyh80e38bb_0 - - kiwisolver=1.4.8=py310he9f1925_1 + - kiwisolver=1.4.9=py310h1e1005b_0 - krb5=1.21.3=hdf4eb48_0 - lark=1.2.2=pyhd8ed1ab_1 - latexcodec=2.0.1=pyh9f0ad1d_0 - lcms2=2.17=hbcf6048_0 - lerc=4.0.0=h6470a55_1 - libaec=1.1.4=h20038f6_0 - - libblas=3.9.0=32_h641d27c_mkl + - libblas=3.9.0=34_h5709861_mkl - libbrotlicommon=1.1.0=h2466b09_3 - libbrotlidec=1.1.0=h2466b09_3 - libbrotlienc=1.1.0=h2466b09_3 - - libcblas=3.9.0=32_h5e41251_mkl + - libcblas=3.9.0=34_h2a3cdd5_mkl - libcurl=8.14.1=h88aaa65_0 - libdeflate=1.24=h76ddb4d_0 - libdlf=0.3.0=pyhd8ed1ab_1 @@ -121,26 +120,26 @@ dependencies: - libffi=3.4.6=h537db12_1 - libfreetype=2.13.3=h57928b3_1 - libfreetype6=2.13.3=h0b5ce68_1 - - libgcc=15.1.0=h1383e82_3 - - libgomp=15.1.0=h1383e82_3 - - libhwloc=2.11.2=default_h88281d1_1002 - - libiconv=1.18=h135ad9c_1 + - libgcc=15.1.0=h1383e82_4 + - libgomp=15.1.0=h1383e82_4 + - libhwloc=2.12.1=default_h88281d1_1000 + - libiconv=1.18=hc1393d2_2 - libjpeg-turbo=3.1.0=h2466b09_0 - - liblapack=3.9.0=32_h1aa476e_mkl + - liblapack=3.9.0=34_hf9ab0e9_mkl - liblzma=5.8.1=h2466b09_2 - libpng=1.6.50=h7351971_1 - libsodium=1.0.20=hc70643c_0 - libspatialindex=2.0.0=h5a68840_0 - - libsqlite=3.50.3=hf5d6505_1 + - libsqlite=3.50.4=hf5d6505_0 - libssh2=1.11.1=h9aa295b_0 - libtiff=4.7.0=h05922d8_5 - libwebp-base=1.6.0=h4d5522a_0 - libwinpthread=12.0.0.r4.gg4f2fc60ca=h57928b3_9 - libxcb=1.17.0=h0e4246c_0 - - libxml2=2.13.8=h442d1da_0 + - libxml2=2.13.8=h741aa76_1 - libzlib=1.3.1=h2466b09_2 - linkify-it-py=2.0.3=pyhd8ed1ab_1 - - llvm-openmp=20.1.8=hfa2b4ca_0 + - llvm-openmp=20.1.8=hfa2b4ca_1 - locket=1.0.0=pyhd8ed1ab_0 - markdown-it-py=2.2.0=pyhd8ed1ab_0 - markupsafe=3.0.2=py310h38315fa_1 @@ -150,7 +149,7 @@ dependencies: - mdit-py-plugins=0.4.2=pyhd8ed1ab_1 - mdurl=0.1.2=pyhd8ed1ab_1 - mistune=3.1.3=pyh29332c3_0 - - mkl=2024.2.2=h66d3029_15 + - mkl=2024.2.2=h57928b3_16 - msgpack-python=1.1.1=py310hc19bc0b_0 - mumps-seq=5.7.3=hbaa6519_10 - munkres=1.1.4=pyhd8ed1ab_1 @@ -162,12 +161,12 @@ dependencies: - nbconvert-pandoc=7.16.6=hed9df3c_0 - nbformat=5.10.4=pyhd8ed1ab_1 - nest-asyncio=1.6.0=pyhd8ed1ab_1 - - notebook=7.4.4=pyhd8ed1ab_0 + - notebook=7.4.5=pyhd8ed1ab_0 - notebook-shim=0.2.4=pyhd8ed1ab_1 - numcodecs=0.13.1=py310hb4db72f_0 - numpy=1.26.4=py310hf667824_0 - - openjpeg=2.5.3=h4d64b90_0 - - openssl=3.5.1=h725018a_0 + - openjpeg=2.5.3=h24db6dd_1 + - openssl=3.5.2=h725018a_0 - overrides=7.7.0=pyhd8ed1ab_1 - packaging=25.0=pyh29332c3_1 - pandas=2.3.1=py310hed136d8_0 @@ -177,7 +176,7 @@ dependencies: - partd=1.4.2=pyhd8ed1ab_0 - pickleshare=0.7.5=pyhd8ed1ab_1004 - pillow=10.3.0=py310h3e38d90_1 - - pip=25.1.1=pyh8b19718_0 + - pip=25.2=pyh8b19718_0 - platformdirs=4.3.8=pyhe01879c_0 - pluggy=1.6.0=pyhd8ed1ab_0 - prometheus_client=0.22.1=pyhd8ed1ab_0 @@ -193,7 +192,7 @@ dependencies: - pydata-sphinx-theme=0.15.4=pyhd8ed1ab_0 - pydiso=0.1.2=py310h8f92c26_0 - pygments=2.19.2=pyhd8ed1ab_0 - - pylint=3.3.7=pyhe01879c_0 + - pylint=3.3.8=pyhe01879c_0 - pymatsolver=0.3.1=pyh48887ae_201 - pyparsing=3.2.3=pyhe01879c_2 - pysocks=1.7.1=pyh09c184e_7 @@ -210,16 +209,16 @@ dependencies: - pywin32=311=py310h282bd7d_0 - pywinpty=2.0.15=py310h9e98ed7_0 - pyyaml=6.0.2=py310h38315fa_2 - - pyzmq=27.0.0=py310h656833d_0 + - pyzmq=27.0.1=py310h49f0f51_0 - readthedocs-sphinx-ext=2.2.5=pyhd8ed1ab_1 - referencing=0.36.2=pyh29332c3_0 - requests=2.32.4=pyhd8ed1ab_0 - rfc3339-validator=0.1.4=pyhd8ed1ab_1 - rfc3986-validator=0.1.1=pyh9f0ad1d_0 - rfc3987-syntax=1.1.0=pyhe01879c_1 - - rpds-py=0.26.0=py310h034784e_0 + - rpds-py=0.27.0=py310h034784e_0 - rtree=1.2.0=py310h08d5ad2_1 - - scikit-learn=1.5.2=py310hf2a6c47_1 + - scikit-learn=1.6.1=py310hf2a6c47_0 - scipy=1.14.1=py310hbd0dde3_2 - send2trash=1.8.3=pyh5737063_1 - setuptools=80.9.0=pyhff2d567_0 @@ -248,7 +247,7 @@ dependencies: - sqlalchemy=2.0.42=py310h29418f3_0 - stack_data=0.6.3=pyhd8ed1ab_1 - tabulate=0.9.0=pyhd8ed1ab_2 - - tbb=2021.13.0=h62715c5_1 + - tbb=2021.13.0=h18a62a1_2 - tblib=3.1.0=pyhd8ed1ab_0 - terminado=0.18.1=pyh5737063_0 - threadpoolctl=3.6.0=pyhecae5ae_0 @@ -258,11 +257,11 @@ dependencies: - tomli=2.2.1=pyhe01879c_2 - tomlkit=0.13.3=pyha770c72_0 - toolz=1.0.0=pyhd8ed1ab_1 - - tornado=6.5.1=py310ha8f682b_0 + - tornado=6.5.2=py310h29418f3_0 - tqdm=4.67.1=pyhd8ed1ab_1 - traitlets=5.14.3=pyhd8ed1ab_1 - trimesh=4.1.8=pyhd8ed1ab_0 - - types-python-dateutil=2.9.0.20250708=pyhd8ed1ab_0 + - types-python-dateutil=2.9.0.20250809=pyhd8ed1ab_0 - typing-extensions=4.14.1=h4440ef1_0 - typing-inspection=0.4.1=pyhd8ed1ab_0 - typing_extensions=4.14.1=pyhe01879c_0 @@ -295,9 +294,9 @@ dependencies: - zstandard=0.23.0=py310ha8f682b_2 - zstd=1.5.7=hbeecb71_2 - pip: - - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@020de8616b4767a596a4d0f49bce53c8d0c9da5b - - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@d567cc98901ecfa360ff2e93f8a6334a1bed24bc - - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@01a7068fdab7fba8695ad371c9fd9164760a09df + - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@1dbe97d441d65962a94e071b5c1c27d9facd2050 + - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@570ea996ae7e48ab1b8b971b23c9c73b7f5637b2 + - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@a1cf0ec4aa28705eb7de68cfedb255de6e590433 - octree-creation-app @ git+https://github.com/MiraGeoscience/octree-creation-app.git@02fbd85bf7d54b8f4336f1f0094c1c3e27714e81 - param-sweeps @ git+https://github.com/MiraGeoscience/param-sweeps.git@9ed6091534d638171957a17324e1a1e8f067b434 diff --git a/environments/py-3.10-win-64.conda.lock.yml b/environments/py-3.10-win-64.conda.lock.yml index 6285fc19..4b67710b 100644 --- a/environments/py-3.10-win-64.conda.lock.yml +++ b/environments/py-3.10-win-64.conda.lock.yml @@ -1,6 +1,6 @@ # Generated by conda-lock. # platform: win-64 -# input_hash: 12cc832b6afad224ba7a18f42ebe117e16cedc70424e95b2c7e3894be647d2bf +# input_hash: 5babf042397838038a28ac78c72c28e9b56b16d89d92d69d08e0421c96c8624b channels: - conda-forge @@ -14,10 +14,10 @@ dependencies: - brotli-bin=1.1.0=h2466b09_3 - brotli-python=1.1.0=py310h9e98ed7_3 - bzip2=1.0.8=h2466b09_7 - - ca-certificates=2025.7.14=h4c7d964_0 + - ca-certificates=2025.8.3=h4c7d964_0 - cached-property=1.5.2=hd8ed1ab_1 - cached_property=1.5.2=pyha770c72_1 - - certifi=2025.7.14=pyhd8ed1ab_0 + - certifi=2025.8.3=pyhd8ed1ab_0 - cffi=1.17.1=py310ha8f682b_0 - click=8.2.1=pyh7428d3b_0 - cloudpickle=3.1.1=pyhd8ed1ab_0 @@ -39,19 +39,18 @@ dependencies: - hpack=4.1.0=pyhd8ed1ab_0 - hyperframe=6.1.0=pyhd8ed1ab_0 - importlib-metadata=8.7.0=pyhe01879c_1 - - intel-openmp=2024.2.1=h57928b3_1083 - jinja2=3.1.6=pyhd8ed1ab_0 - joblib=1.5.1=pyhd8ed1ab_0 - - kiwisolver=1.4.8=py310he9f1925_1 + - kiwisolver=1.4.9=py310h1e1005b_0 - krb5=1.21.3=hdf4eb48_0 - lcms2=2.17=hbcf6048_0 - lerc=4.0.0=h6470a55_1 - libaec=1.1.4=h20038f6_0 - - libblas=3.9.0=32_h641d27c_mkl + - libblas=3.9.0=34_h5709861_mkl - libbrotlicommon=1.1.0=h2466b09_3 - libbrotlidec=1.1.0=h2466b09_3 - libbrotlienc=1.1.0=h2466b09_3 - - libcblas=3.9.0=32_h5e41251_mkl + - libcblas=3.9.0=34_h2a3cdd5_mkl - libcurl=8.14.1=h88aaa65_0 - libdeflate=1.24=h76ddb4d_0 - libdlf=0.3.0=pyhd8ed1ab_1 @@ -59,40 +58,40 @@ dependencies: - libffi=3.4.6=h537db12_1 - libfreetype=2.13.3=h57928b3_1 - libfreetype6=2.13.3=h0b5ce68_1 - - libgcc=15.1.0=h1383e82_3 - - libgomp=15.1.0=h1383e82_3 - - libhwloc=2.11.2=default_h88281d1_1002 - - libiconv=1.18=h135ad9c_1 + - libgcc=15.1.0=h1383e82_4 + - libgomp=15.1.0=h1383e82_4 + - libhwloc=2.12.1=default_h88281d1_1000 + - libiconv=1.18=hc1393d2_2 - libjpeg-turbo=3.1.0=h2466b09_0 - - liblapack=3.9.0=32_h1aa476e_mkl + - liblapack=3.9.0=34_hf9ab0e9_mkl - liblzma=5.8.1=h2466b09_2 - libpng=1.6.50=h7351971_1 - libspatialindex=2.0.0=h5a68840_0 - - libsqlite=3.50.3=hf5d6505_1 + - libsqlite=3.50.4=hf5d6505_0 - libssh2=1.11.1=h9aa295b_0 - libtiff=4.7.0=h05922d8_5 - libwebp-base=1.6.0=h4d5522a_0 - libwinpthread=12.0.0.r4.gg4f2fc60ca=h57928b3_9 - libxcb=1.17.0=h0e4246c_0 - - libxml2=2.13.8=h442d1da_0 + - libxml2=2.13.8=h741aa76_1 - libzlib=1.3.1=h2466b09_2 - - llvm-openmp=20.1.8=hfa2b4ca_0 + - llvm-openmp=20.1.8=hfa2b4ca_1 - locket=1.0.0=pyhd8ed1ab_0 - markupsafe=3.0.2=py310h38315fa_1 - matplotlib-base=3.8.4=py310hadb10a8_2 - - mkl=2024.2.2=h66d3029_15 + - mkl=2024.2.2=h57928b3_16 - msgpack-python=1.1.1=py310hc19bc0b_0 - mumps-seq=5.7.3=hbaa6519_10 - munkres=1.1.4=pyhd8ed1ab_1 - numcodecs=0.13.1=py310hb4db72f_0 - numpy=1.26.4=py310hf667824_0 - - openjpeg=2.5.3=h4d64b90_0 - - openssl=3.5.1=h725018a_0 + - openjpeg=2.5.3=h24db6dd_1 + - openssl=3.5.2=h725018a_0 - packaging=25.0=pyh29332c3_1 - pandas=2.3.1=py310hed136d8_0 - partd=1.4.2=pyhd8ed1ab_0 - pillow=10.3.0=py310h3e38d90_1 - - pip=25.1.1=pyh8b19718_0 + - pip=25.2=pyh8b19718_0 - psutil=7.0.0=py310ha8f682b_0 - pthread-stubs=0.4=h0e40799_1002 - pycparser=2.22=pyh29332c3_1 @@ -110,17 +109,17 @@ dependencies: - pytz=2025.2=pyhd8ed1ab_0 - pyyaml=6.0.2=py310h38315fa_2 - rtree=1.2.0=py310h08d5ad2_1 - - scikit-learn=1.5.2=py310hf2a6c47_1 + - scikit-learn=1.6.1=py310hf2a6c47_0 - scipy=1.14.1=py310hbd0dde3_2 - setuptools=80.9.0=pyhff2d567_0 - six=1.17.0=pyhe01879c_1 - sortedcontainers=2.4.0=pyhd8ed1ab_1 - - tbb=2021.13.0=h62715c5_1 + - tbb=2021.13.0=h18a62a1_2 - tblib=3.1.0=pyhd8ed1ab_0 - threadpoolctl=3.6.0=pyhecae5ae_0 - tk=8.6.13=h2c6b04d_2 - toolz=1.0.0=pyhd8ed1ab_1 - - tornado=6.5.1=py310ha8f682b_0 + - tornado=6.5.2=py310h29418f3_0 - tqdm=4.67.1=pyhd8ed1ab_1 - trimesh=4.1.8=pyhd8ed1ab_0 - typing-extensions=4.14.1=h4440ef1_0 @@ -145,9 +144,9 @@ dependencies: - zstandard=0.23.0=py310ha8f682b_2 - zstd=1.5.7=hbeecb71_2 - pip: - - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@020de8616b4767a596a4d0f49bce53c8d0c9da5b - - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@d567cc98901ecfa360ff2e93f8a6334a1bed24bc - - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@01a7068fdab7fba8695ad371c9fd9164760a09df + - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@1dbe97d441d65962a94e071b5c1c27d9facd2050 + - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@570ea996ae7e48ab1b8b971b23c9c73b7f5637b2 + - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@a1cf0ec4aa28705eb7de68cfedb255de6e590433 - octree-creation-app @ git+https://github.com/MiraGeoscience/octree-creation-app.git@02fbd85bf7d54b8f4336f1f0094c1c3e27714e81 - param-sweeps @ git+https://github.com/MiraGeoscience/param-sweeps.git@9ed6091534d638171957a17324e1a1e8f067b434 diff --git a/environments/py-3.11-linux-64-dev.conda.lock.yml b/environments/py-3.11-linux-64-dev.conda.lock.yml index e5d33ad9..9788f133 100644 --- a/environments/py-3.11-linux-64-dev.conda.lock.yml +++ b/environments/py-3.11-linux-64-dev.conda.lock.yml @@ -1,6 +1,6 @@ # Generated by conda-lock. # platform: linux-64 -# input_hash: 3bdb725cf9e2e0a18331b01a1fd271c67ce2f7d54cfb3de3bcc9379dc3f52ad6 +# input_hash: 8cce520abc7830e77c6c1ae22f85de23c1a3f189a6830f442297dd1ec77be9d5 channels: - conda-forge @@ -10,9 +10,9 @@ dependencies: - accessible-pygments=0.0.5=pyhd8ed1ab_1 - alabaster=0.7.16=pyhd8ed1ab_0 - annotated-types=0.7.0=pyhd8ed1ab_1 - - anyio=4.9.0=pyh29332c3_0 + - anyio=4.10.0=pyhe01879c_0 - argon2-cffi=25.1.0=pyhd8ed1ab_0 - - argon2-cffi-bindings=21.2.0=py311h9ecbd09_5 + - argon2-cffi-bindings=25.1.0=py311h49ec1c0_0 - arrow=1.3.0=pyhd8ed1ab_1 - asciitree=0.3.3=py_2 - astroid=3.3.11=py311h38be061_0 @@ -29,23 +29,23 @@ dependencies: - brotli-python=1.1.0=py311hfdbb021_3 - bzip2=1.0.8=h4bc722e_7 - c-ares=1.34.5=hb9d3cd8_0 - - ca-certificates=2025.7.14=hbd8a1cb_0 + - ca-certificates=2025.8.3=hbd8a1cb_0 - cached-property=1.5.2=hd8ed1ab_1 - cached_property=1.5.2=pyha770c72_1 - - certifi=2025.7.14=pyhd8ed1ab_0 + - certifi=2025.8.3=pyhd8ed1ab_0 - cffi=1.17.1=py311hf29c0ef_0 - - charset-normalizer=3.4.2=pyhd8ed1ab_0 + - charset-normalizer=3.4.3=pyhd8ed1ab_0 - click=8.2.1=pyh707e725_0 - cloudpickle=3.1.1=pyhd8ed1ab_0 - colorama=0.4.6=pyhd8ed1ab_1 - comm=0.2.3=pyhe01879c_0 - - contourpy=1.3.3=py311hdf67eae_0 - - coverage=7.10.1=py311h3778330_0 + - contourpy=1.3.3=py311hdf67eae_1 + - coverage=7.10.3=py311h3778330_0 - cycler=0.12.1=pyhd8ed1ab_1 - cytoolz=1.0.1=py311h9ecbd09_0 - dask-core=2025.3.0=pyhd8ed1ab_0 - dataclasses=0.8=pyhc8e2a94_3 - - debugpy=1.8.15=py311hc665b79_0 + - debugpy=1.8.16=py311hc665b79_0 - decorator=5.2.1=pyhd8ed1ab_0 - defusedxml=0.7.1=pyhd8ed1ab_0 - deprecated=1.2.18=pyhd8ed1ab_0 @@ -61,7 +61,7 @@ dependencies: - freetype=2.13.3=ha770c72_1 - fsspec=2025.7.0=pyhd8ed1ab_0 - geoana=0.7.2=py311h5b7b71f_0 - - greenlet=3.2.3=py311hfdbb021_0 + - greenlet=3.2.4=py311h1ddb823_0 - h11=0.16.0=pyhd8ed1ab_0 - h2=4.2.0=pyhd8ed1ab_0 - h5py=3.14.0=nompi_py311h7f87ba5_100 @@ -70,13 +70,12 @@ dependencies: - httpcore=1.0.9=pyh29332c3_0 - httpx=0.28.1=pyhd8ed1ab_0 - hyperframe=6.1.0=pyhd8ed1ab_0 - - icu=75.1=he02047a_0 - idna=3.10=pyhd8ed1ab_1 - imagesize=1.4.1=pyhd8ed1ab_0 - importlib-metadata=8.7.0=pyhe01879c_1 - importlib_metadata=8.7.0=h40b2b14_1 - iniconfig=2.0.0=pyhd8ed1ab_1 - - ipykernel=6.30.0=pyh82676e8_0 + - ipykernel=6.30.1=pyh82676e8_0 - ipython=9.4.0=pyhfa0c392_0 - ipython_genutils=0.2.0=pyhd8ed1ab_2 - ipython_pygments_lexers=1.1.1=pyhd8ed1ab_0 @@ -104,8 +103,8 @@ dependencies: - jupyterlab_server=2.27.3=pyhd8ed1ab_1 - jupyterlab_widgets=1.1.11=pyhd8ed1ab_0 - jupytext=1.17.2=pyh80e38bb_0 - - keyutils=1.6.1=h166bdaf_0 - - kiwisolver=1.4.8=py311hd18a35c_1 + - keyutils=1.6.3=hb9d3cd8_0 + - kiwisolver=1.4.9=py311h724c32c_0 - krb5=1.21.3=h659f571_0 - lark=1.2.2=pyhd8ed1ab_1 - latexcodec=2.0.1=pyh9f0ad1d_0 @@ -113,11 +112,11 @@ dependencies: - ld_impl_linux-64=2.44=h1423503_1 - lerc=4.0.0=h0aef613_1 - libaec=1.1.4=h3f801dc_0 - - libblas=3.9.0=32_hfdb39a5_mkl + - libblas=3.9.0=34_hfdb39a5_mkl - libbrotlicommon=1.1.0=hb9d3cd8_3 - libbrotlidec=1.1.0=hb9d3cd8_3 - libbrotlienc=1.1.0=hb9d3cd8_3 - - libcblas=3.9.0=32_h372d94f_mkl + - libcblas=3.9.0=34_h372d94f_mkl - libcurl=8.14.1=h332b0f4_0 - libdeflate=1.24=h86f0d12_0 - libdlf=0.3.0=pyhd8ed1ab_1 @@ -127,14 +126,14 @@ dependencies: - libffi=3.4.6=h2dba641_1 - libfreetype=2.13.3=ha770c72_1 - libfreetype6=2.13.3=h48d6fc4_1 - - libgcc=15.1.0=h767d61c_3 - - libgcc-ng=15.1.0=h69a702a_3 - - libgfortran=15.1.0=h69a702a_3 - - libgfortran5=15.1.0=hcea5267_3 - - libhwloc=2.11.2=default_h3d81e11_1002 - - libiconv=1.18=h4ce23a2_1 + - libgcc=15.1.0=h767d61c_4 + - libgcc-ng=15.1.0=h69a702a_4 + - libgfortran=15.1.0=h69a702a_4 + - libgfortran5=15.1.0=hcea5267_4 + - libhwloc=2.12.1=default_h3d81e11_1000 + - libiconv=1.18=h3b78370_2 - libjpeg-turbo=3.1.0=hb9d3cd8_0 - - liblapack=3.9.0=32_hc41d3b0_mkl + - liblapack=3.9.0=34_hc41d3b0_mkl - liblzma=5.8.1=hb9d3cd8_2 - libnghttp2=1.64.0=h161d5f1_0 - libnsl=2.0.1=hb9d3cd8_1 @@ -142,19 +141,19 @@ dependencies: - libscotch=7.0.6=hea33c07_1 - libsodium=1.0.20=h4ab18f5_0 - libspatialindex=2.0.0=he02047a_0 - - libsqlite=3.50.3=hee844dc_1 + - libsqlite=3.50.4=h0c1763c_0 - libssh2=1.11.1=hcf80075_0 - - libstdcxx=15.1.0=h8f9b012_3 - - libstdcxx-ng=15.1.0=h4852527_3 + - libstdcxx=15.1.0=h8f9b012_4 + - libstdcxx-ng=15.1.0=h4852527_4 - libtiff=4.7.0=hf01ce69_5 - libuuid=2.38.1=h0b41bf4_0 - libwebp-base=1.6.0=hd42ef1d_0 - libxcb=1.17.0=h8a09558_0 - libxcrypt=4.4.36=hd590300_1 - - libxml2=2.13.8=h4bc477f_0 + - libxml2=2.13.8=h2cb61b6_1 - libzlib=1.3.1=hb9d3cd8_2 - linkify-it-py=2.0.3=pyhd8ed1ab_1 - - llvm-openmp=20.1.8=h4922eb0_0 + - llvm-openmp=20.1.8=h4922eb0_1 - locket=1.0.0=pyhd8ed1ab_0 - markdown-it-py=2.2.0=pyhd8ed1ab_0 - markupsafe=3.0.2=py311h2dc5d0c_1 @@ -165,7 +164,7 @@ dependencies: - mdurl=0.1.2=pyhd8ed1ab_1 - metis=5.1.0=hd0bcaf9_1007 - mistune=3.1.3=pyh29332c3_0 - - mkl=2024.2.2=ha770c72_16 + - mkl=2024.2.2=ha770c72_17 - msgpack-python=1.1.1=py311hd18a35c_0 - mumps-include=5.7.3=h82cca05_10 - mumps-seq=5.7.3=h06cbf8f_10 @@ -179,12 +178,12 @@ dependencies: - nbformat=5.10.4=pyhd8ed1ab_1 - ncurses=6.5=h2d0b736_3 - nest-asyncio=1.6.0=pyhd8ed1ab_1 - - notebook=7.4.4=pyhd8ed1ab_0 + - notebook=7.4.5=pyhd8ed1ab_0 - notebook-shim=0.2.4=pyhd8ed1ab_1 - numcodecs=0.15.1=py311h7db5c69_0 - numpy=1.26.4=py311h64a7726_0 - - openjpeg=2.5.3=h5fbd93e_0 - - openssl=3.5.1=h7b32b05_0 + - openjpeg=2.5.3=h55fea9a_1 + - openssl=3.5.2=h26f9b46_0 - overrides=7.7.0=pyhd8ed1ab_1 - packaging=25.0=pyh29332c3_1 - pandas=2.3.1=py311hed34c8f_0 @@ -195,7 +194,7 @@ dependencies: - pexpect=4.9.0=pyhd8ed1ab_1 - pickleshare=0.7.5=pyhd8ed1ab_1004 - pillow=10.3.0=py311h82a398c_1 - - pip=25.1.1=pyh8b19718_0 + - pip=25.2=pyh8b19718_0 - platformdirs=4.3.8=pyhe01879c_0 - pluggy=1.6.0=pyhd8ed1ab_0 - prometheus_client=0.22.1=pyhd8ed1ab_0 @@ -212,7 +211,7 @@ dependencies: - pydata-sphinx-theme=0.15.4=pyhd8ed1ab_0 - pydiso=0.1.2=py311h19ea254_0 - pygments=2.19.2=pyhd8ed1ab_0 - - pylint=3.3.7=pyhe01879c_0 + - pylint=3.3.8=pyhe01879c_0 - pymatsolver=0.3.1=pyh48887ae_201 - pyparsing=3.2.3=pyhe01879c_2 - pysocks=1.7.1=pyha55dd90_7 @@ -227,7 +226,7 @@ dependencies: - python_abi=3.11=8_cp311 - pytz=2025.2=pyhd8ed1ab_0 - pyyaml=6.0.2=py311h2dc5d0c_2 - - pyzmq=27.0.0=py311h7deb3e3_0 + - pyzmq=27.0.1=py311hc251a9f_0 - readline=8.2=h8c095d6_2 - readthedocs-sphinx-ext=2.2.5=pyhd8ed1ab_1 - referencing=0.36.2=pyh29332c3_0 @@ -235,9 +234,9 @@ dependencies: - rfc3339-validator=0.1.4=pyhd8ed1ab_1 - rfc3986-validator=0.1.1=pyh9f0ad1d_0 - rfc3987-syntax=1.1.0=pyhe01879c_1 - - rpds-py=0.26.0=py311hdae7d1d_0 + - rpds-py=0.27.0=py311h902ca64_0 - rtree=1.2.0=py311ha1603b9_1 - - scikit-learn=1.5.2=py311h57cc02b_1 + - scikit-learn=1.6.1=py311h57cc02b_0 - scipy=1.14.1=py311he9a78e4_2 - send2trash=1.8.3=pyh0d859eb_1 - setuptools=80.9.0=pyhff2d567_0 @@ -266,7 +265,7 @@ dependencies: - sqlalchemy=2.0.42=py311h49ec1c0_0 - stack_data=0.6.3=pyhd8ed1ab_1 - tabulate=0.9.0=pyhd8ed1ab_2 - - tbb=2021.13.0=hceb3a55_1 + - tbb=2021.13.0=hb60516a_2 - tblib=3.1.0=pyhd8ed1ab_0 - terminado=0.18.1=pyh0d859eb_0 - threadpoolctl=3.6.0=pyhecae5ae_0 @@ -276,11 +275,11 @@ dependencies: - tomli=2.2.1=pyhe01879c_2 - tomlkit=0.13.3=pyha770c72_0 - toolz=1.0.0=pyhd8ed1ab_1 - - tornado=6.5.1=py311h9ecbd09_0 + - tornado=6.5.2=py311h49ec1c0_0 - tqdm=4.67.1=pyhd8ed1ab_1 - traitlets=5.14.3=pyhd8ed1ab_1 - trimesh=4.1.8=pyhd8ed1ab_0 - - types-python-dateutil=2.9.0.20250708=pyhd8ed1ab_0 + - types-python-dateutil=2.9.0.20250809=pyhd8ed1ab_0 - typing-extensions=4.14.1=h4440ef1_0 - typing-inspection=0.4.1=pyhd8ed1ab_0 - typing_extensions=4.14.1=pyhe01879c_0 @@ -308,9 +307,9 @@ dependencies: - zstandard=0.23.0=py311h9ecbd09_2 - zstd=1.5.7=hb8e6e7a_2 - pip: - - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@020de8616b4767a596a4d0f49bce53c8d0c9da5b - - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@d567cc98901ecfa360ff2e93f8a6334a1bed24bc - - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@01a7068fdab7fba8695ad371c9fd9164760a09df + - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@1dbe97d441d65962a94e071b5c1c27d9facd2050 + - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@570ea996ae7e48ab1b8b971b23c9c73b7f5637b2 + - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@a1cf0ec4aa28705eb7de68cfedb255de6e590433 - octree-creation-app @ git+https://github.com/MiraGeoscience/octree-creation-app.git@02fbd85bf7d54b8f4336f1f0094c1c3e27714e81 - param-sweeps @ git+https://github.com/MiraGeoscience/param-sweeps.git@9ed6091534d638171957a17324e1a1e8f067b434 diff --git a/environments/py-3.11-linux-64.conda.lock.yml b/environments/py-3.11-linux-64.conda.lock.yml index b61a80a5..6888f2bd 100644 --- a/environments/py-3.11-linux-64.conda.lock.yml +++ b/environments/py-3.11-linux-64.conda.lock.yml @@ -1,6 +1,6 @@ # Generated by conda-lock. # platform: linux-64 -# input_hash: 3bdb725cf9e2e0a18331b01a1fd271c67ce2f7d54cfb3de3bcc9379dc3f52ad6 +# input_hash: 8cce520abc7830e77c6c1ae22f85de23c1a3f189a6830f442297dd1ec77be9d5 channels: - conda-forge @@ -15,15 +15,15 @@ dependencies: - brotli-python=1.1.0=py311hfdbb021_3 - bzip2=1.0.8=h4bc722e_7 - c-ares=1.34.5=hb9d3cd8_0 - - ca-certificates=2025.7.14=hbd8a1cb_0 + - ca-certificates=2025.8.3=hbd8a1cb_0 - cached-property=1.5.2=hd8ed1ab_1 - cached_property=1.5.2=pyha770c72_1 - - certifi=2025.7.14=pyhd8ed1ab_0 + - certifi=2025.8.3=pyhd8ed1ab_0 - cffi=1.17.1=py311hf29c0ef_0 - click=8.2.1=pyh707e725_0 - cloudpickle=3.1.1=pyhd8ed1ab_0 - colorama=0.4.6=pyhd8ed1ab_1 - - contourpy=1.3.3=py311hdf67eae_0 + - contourpy=1.3.3=py311hdf67eae_1 - cycler=0.12.1=pyhd8ed1ab_1 - cytoolz=1.0.1=py311h9ecbd09_0 - dask-core=2025.3.0=pyhd8ed1ab_0 @@ -40,22 +40,21 @@ dependencies: - hdf5=1.14.6=nompi_h6e4c0c1_103 - hpack=4.1.0=pyhd8ed1ab_0 - hyperframe=6.1.0=pyhd8ed1ab_0 - - icu=75.1=he02047a_0 - importlib-metadata=8.7.0=pyhe01879c_1 - jinja2=3.1.6=pyhd8ed1ab_0 - joblib=1.5.1=pyhd8ed1ab_0 - - keyutils=1.6.1=h166bdaf_0 - - kiwisolver=1.4.8=py311hd18a35c_1 + - keyutils=1.6.3=hb9d3cd8_0 + - kiwisolver=1.4.9=py311h724c32c_0 - krb5=1.21.3=h659f571_0 - lcms2=2.17=h717163a_0 - ld_impl_linux-64=2.44=h1423503_1 - lerc=4.0.0=h0aef613_1 - libaec=1.1.4=h3f801dc_0 - - libblas=3.9.0=32_hfdb39a5_mkl + - libblas=3.9.0=34_hfdb39a5_mkl - libbrotlicommon=1.1.0=hb9d3cd8_3 - libbrotlidec=1.1.0=hb9d3cd8_3 - libbrotlienc=1.1.0=hb9d3cd8_3 - - libcblas=3.9.0=32_h372d94f_mkl + - libcblas=3.9.0=34_h372d94f_mkl - libcurl=8.14.1=h332b0f4_0 - libdeflate=1.24=h86f0d12_0 - libdlf=0.3.0=pyhd8ed1ab_1 @@ -65,37 +64,37 @@ dependencies: - libffi=3.4.6=h2dba641_1 - libfreetype=2.13.3=ha770c72_1 - libfreetype6=2.13.3=h48d6fc4_1 - - libgcc=15.1.0=h767d61c_3 - - libgcc-ng=15.1.0=h69a702a_3 - - libgfortran=15.1.0=h69a702a_3 - - libgfortran5=15.1.0=hcea5267_3 - - libhwloc=2.11.2=default_h3d81e11_1002 - - libiconv=1.18=h4ce23a2_1 + - libgcc=15.1.0=h767d61c_4 + - libgcc-ng=15.1.0=h69a702a_4 + - libgfortran=15.1.0=h69a702a_4 + - libgfortran5=15.1.0=hcea5267_4 + - libhwloc=2.12.1=default_h3d81e11_1000 + - libiconv=1.18=h3b78370_2 - libjpeg-turbo=3.1.0=hb9d3cd8_0 - - liblapack=3.9.0=32_hc41d3b0_mkl + - liblapack=3.9.0=34_hc41d3b0_mkl - liblzma=5.8.1=hb9d3cd8_2 - libnghttp2=1.64.0=h161d5f1_0 - libnsl=2.0.1=hb9d3cd8_1 - libpng=1.6.50=h421ea60_1 - libscotch=7.0.6=hea33c07_1 - libspatialindex=2.0.0=he02047a_0 - - libsqlite=3.50.3=hee844dc_1 + - libsqlite=3.50.4=h0c1763c_0 - libssh2=1.11.1=hcf80075_0 - - libstdcxx=15.1.0=h8f9b012_3 - - libstdcxx-ng=15.1.0=h4852527_3 + - libstdcxx=15.1.0=h8f9b012_4 + - libstdcxx-ng=15.1.0=h4852527_4 - libtiff=4.7.0=hf01ce69_5 - libuuid=2.38.1=h0b41bf4_0 - libwebp-base=1.6.0=hd42ef1d_0 - libxcb=1.17.0=h8a09558_0 - libxcrypt=4.4.36=hd590300_1 - - libxml2=2.13.8=h4bc477f_0 + - libxml2=2.13.8=h2cb61b6_1 - libzlib=1.3.1=hb9d3cd8_2 - - llvm-openmp=20.1.8=h4922eb0_0 + - llvm-openmp=20.1.8=h4922eb0_1 - locket=1.0.0=pyhd8ed1ab_0 - markupsafe=3.0.2=py311h2dc5d0c_1 - matplotlib-base=3.8.4=py311ha4ca890_2 - metis=5.1.0=hd0bcaf9_1007 - - mkl=2024.2.2=ha770c72_16 + - mkl=2024.2.2=ha770c72_17 - msgpack-python=1.1.1=py311hd18a35c_0 - mumps-include=5.7.3=h82cca05_10 - mumps-seq=5.7.3=h06cbf8f_10 @@ -103,13 +102,13 @@ dependencies: - ncurses=6.5=h2d0b736_3 - numcodecs=0.15.1=py311h7db5c69_0 - numpy=1.26.4=py311h64a7726_0 - - openjpeg=2.5.3=h5fbd93e_0 - - openssl=3.5.1=h7b32b05_0 + - openjpeg=2.5.3=h55fea9a_1 + - openssl=3.5.2=h26f9b46_0 - packaging=25.0=pyh29332c3_1 - pandas=2.3.1=py311hed34c8f_0 - partd=1.4.2=pyhd8ed1ab_0 - pillow=10.3.0=py311h82a398c_1 - - pip=25.1.1=pyh8b19718_0 + - pip=25.2=pyh8b19718_0 - psutil=7.0.0=py311h9ecbd09_0 - pthread-stubs=0.4=hb9d3cd8_1002 - pycparser=2.22=pyh29332c3_1 @@ -128,17 +127,17 @@ dependencies: - pyyaml=6.0.2=py311h2dc5d0c_2 - readline=8.2=h8c095d6_2 - rtree=1.2.0=py311ha1603b9_1 - - scikit-learn=1.5.2=py311h57cc02b_1 + - scikit-learn=1.6.1=py311h57cc02b_0 - scipy=1.14.1=py311he9a78e4_2 - setuptools=80.9.0=pyhff2d567_0 - six=1.17.0=pyhe01879c_1 - sortedcontainers=2.4.0=pyhd8ed1ab_1 - - tbb=2021.13.0=hceb3a55_1 + - tbb=2021.13.0=hb60516a_2 - tblib=3.1.0=pyhd8ed1ab_0 - threadpoolctl=3.6.0=pyhecae5ae_0 - tk=8.6.13=noxft_hd72426e_102 - toolz=1.0.0=pyhd8ed1ab_1 - - tornado=6.5.1=py311h9ecbd09_0 + - tornado=6.5.2=py311h49ec1c0_0 - tqdm=4.67.1=pyhd8ed1ab_1 - trimesh=4.1.8=pyhd8ed1ab_0 - typing-extensions=4.14.1=h4440ef1_0 @@ -159,9 +158,9 @@ dependencies: - zstandard=0.23.0=py311h9ecbd09_2 - zstd=1.5.7=hb8e6e7a_2 - pip: - - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@020de8616b4767a596a4d0f49bce53c8d0c9da5b - - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@d567cc98901ecfa360ff2e93f8a6334a1bed24bc - - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@01a7068fdab7fba8695ad371c9fd9164760a09df + - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@1dbe97d441d65962a94e071b5c1c27d9facd2050 + - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@570ea996ae7e48ab1b8b971b23c9c73b7f5637b2 + - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@a1cf0ec4aa28705eb7de68cfedb255de6e590433 - octree-creation-app @ git+https://github.com/MiraGeoscience/octree-creation-app.git@02fbd85bf7d54b8f4336f1f0094c1c3e27714e81 - param-sweeps @ git+https://github.com/MiraGeoscience/param-sweeps.git@9ed6091534d638171957a17324e1a1e8f067b434 diff --git a/environments/py-3.11-win-64-dev.conda.lock.yml b/environments/py-3.11-win-64-dev.conda.lock.yml index b6594e35..784fe677 100644 --- a/environments/py-3.11-win-64-dev.conda.lock.yml +++ b/environments/py-3.11-win-64-dev.conda.lock.yml @@ -1,6 +1,6 @@ # Generated by conda-lock. # platform: win-64 -# input_hash: 57805dd7243378b72dd91648b00eb790f855375cd6ad3095c5099809073a0210 +# input_hash: 35467c865311a1b10fc72659b58f28578bcf2a4985e82e4f6bc78fe91e1743c8 channels: - conda-forge @@ -10,9 +10,9 @@ dependencies: - accessible-pygments=0.0.5=pyhd8ed1ab_1 - alabaster=0.7.16=pyhd8ed1ab_0 - annotated-types=0.7.0=pyhd8ed1ab_1 - - anyio=4.9.0=pyh29332c3_0 + - anyio=4.10.0=pyhe01879c_0 - argon2-cffi=25.1.0=pyhd8ed1ab_0 - - argon2-cffi-bindings=21.2.0=py311he736701_5 + - argon2-cffi-bindings=25.1.0=py311h3485c13_0 - arrow=1.3.0=pyhd8ed1ab_1 - asciitree=0.3.3=py_2 - astroid=3.3.11=py311h1ea47a8_0 @@ -28,24 +28,24 @@ dependencies: - brotli-bin=1.1.0=h2466b09_3 - brotli-python=1.1.0=py311hda3d55a_3 - bzip2=1.0.8=h2466b09_7 - - ca-certificates=2025.7.14=h4c7d964_0 + - ca-certificates=2025.8.3=h4c7d964_0 - cached-property=1.5.2=hd8ed1ab_1 - cached_property=1.5.2=pyha770c72_1 - - certifi=2025.7.14=pyhd8ed1ab_0 + - certifi=2025.8.3=pyhd8ed1ab_0 - cffi=1.17.1=py311he736701_0 - - charset-normalizer=3.4.2=pyhd8ed1ab_0 + - charset-normalizer=3.4.3=pyhd8ed1ab_0 - click=8.2.1=pyh7428d3b_0 - cloudpickle=3.1.1=pyhd8ed1ab_0 - colorama=0.4.6=pyhd8ed1ab_1 - comm=0.2.3=pyhe01879c_0 - - contourpy=1.3.3=py311h3fd045d_0 - - coverage=7.10.1=py311h3f79411_0 + - contourpy=1.3.3=py311h3fd045d_1 + - coverage=7.10.3=py311h3f79411_0 - cpython=3.11.13=py311hd8ed1ab_0 - cycler=0.12.1=pyhd8ed1ab_1 - cytoolz=1.0.1=py311he736701_0 - dask-core=2025.3.0=pyhd8ed1ab_0 - dataclasses=0.8=pyhc8e2a94_3 - - debugpy=1.8.15=py311h5dfdfe8_0 + - debugpy=1.8.16=py311h5dfdfe8_0 - decorator=5.2.1=pyhd8ed1ab_0 - defusedxml=0.7.1=pyhd8ed1ab_0 - deprecated=1.2.18=pyhd8ed1ab_0 @@ -61,7 +61,7 @@ dependencies: - freetype=2.13.3=h57928b3_1 - fsspec=2025.7.0=pyhd8ed1ab_0 - geoana=0.7.2=py311h9b10771_0 - - greenlet=3.2.3=py311hda3d55a_0 + - greenlet=3.2.4=py311h3e6a449_0 - h11=0.16.0=pyhd8ed1ab_0 - h2=4.2.0=pyhd8ed1ab_0 - h5py=3.14.0=nompi_py311h97e6cc2_100 @@ -75,8 +75,7 @@ dependencies: - importlib-metadata=8.7.0=pyhe01879c_1 - importlib_metadata=8.7.0=h40b2b14_1 - iniconfig=2.0.0=pyhd8ed1ab_1 - - intel-openmp=2024.2.1=h57928b3_1083 - - ipykernel=6.30.0=pyh3521513_0 + - ipykernel=6.30.1=pyh3521513_0 - ipython=9.4.0=pyh6be1c34_0 - ipython_genutils=0.2.0=pyhd8ed1ab_2 - ipython_pygments_lexers=1.1.1=pyhd8ed1ab_0 @@ -104,18 +103,18 @@ dependencies: - jupyterlab_server=2.27.3=pyhd8ed1ab_1 - jupyterlab_widgets=1.1.11=pyhd8ed1ab_0 - jupytext=1.17.2=pyh80e38bb_0 - - kiwisolver=1.4.8=py311h3fd045d_1 + - kiwisolver=1.4.9=py311h275cad7_0 - krb5=1.21.3=hdf4eb48_0 - lark=1.2.2=pyhd8ed1ab_1 - latexcodec=2.0.1=pyh9f0ad1d_0 - lcms2=2.17=hbcf6048_0 - lerc=4.0.0=h6470a55_1 - libaec=1.1.4=h20038f6_0 - - libblas=3.9.0=32_h641d27c_mkl + - libblas=3.9.0=34_h5709861_mkl - libbrotlicommon=1.1.0=h2466b09_3 - libbrotlidec=1.1.0=h2466b09_3 - libbrotlienc=1.1.0=h2466b09_3 - - libcblas=3.9.0=32_h5e41251_mkl + - libcblas=3.9.0=34_h2a3cdd5_mkl - libcurl=8.14.1=h88aaa65_0 - libdeflate=1.24=h76ddb4d_0 - libdlf=0.3.0=pyhd8ed1ab_1 @@ -123,26 +122,26 @@ dependencies: - libffi=3.4.6=h537db12_1 - libfreetype=2.13.3=h57928b3_1 - libfreetype6=2.13.3=h0b5ce68_1 - - libgcc=15.1.0=h1383e82_3 - - libgomp=15.1.0=h1383e82_3 - - libhwloc=2.11.2=default_h88281d1_1002 - - libiconv=1.18=h135ad9c_1 + - libgcc=15.1.0=h1383e82_4 + - libgomp=15.1.0=h1383e82_4 + - libhwloc=2.12.1=default_h88281d1_1000 + - libiconv=1.18=hc1393d2_2 - libjpeg-turbo=3.1.0=h2466b09_0 - - liblapack=3.9.0=32_h1aa476e_mkl + - liblapack=3.9.0=34_hf9ab0e9_mkl - liblzma=5.8.1=h2466b09_2 - libpng=1.6.50=h7351971_1 - libsodium=1.0.20=hc70643c_0 - libspatialindex=2.0.0=h5a68840_0 - - libsqlite=3.50.3=hf5d6505_1 + - libsqlite=3.50.4=hf5d6505_0 - libssh2=1.11.1=h9aa295b_0 - libtiff=4.7.0=h05922d8_5 - libwebp-base=1.6.0=h4d5522a_0 - libwinpthread=12.0.0.r4.gg4f2fc60ca=h57928b3_9 - libxcb=1.17.0=h0e4246c_0 - - libxml2=2.13.8=h442d1da_0 + - libxml2=2.13.8=h741aa76_1 - libzlib=1.3.1=h2466b09_2 - linkify-it-py=2.0.3=pyhd8ed1ab_1 - - llvm-openmp=20.1.8=hfa2b4ca_0 + - llvm-openmp=20.1.8=hfa2b4ca_1 - locket=1.0.0=pyhd8ed1ab_0 - markdown-it-py=2.2.0=pyhd8ed1ab_0 - markupsafe=3.0.2=py311h5082efb_1 @@ -152,7 +151,7 @@ dependencies: - mdit-py-plugins=0.4.2=pyhd8ed1ab_1 - mdurl=0.1.2=pyhd8ed1ab_1 - mistune=3.1.3=pyh29332c3_0 - - mkl=2024.2.2=h66d3029_15 + - mkl=2024.2.2=h57928b3_16 - msgpack-python=1.1.1=py311h3257749_0 - mumps-seq=5.7.3=hbaa6519_10 - munkres=1.1.4=pyhd8ed1ab_1 @@ -164,12 +163,12 @@ dependencies: - nbconvert-pandoc=7.16.6=hed9df3c_0 - nbformat=5.10.4=pyhd8ed1ab_1 - nest-asyncio=1.6.0=pyhd8ed1ab_1 - - notebook=7.4.4=pyhd8ed1ab_0 + - notebook=7.4.5=pyhd8ed1ab_0 - notebook-shim=0.2.4=pyhd8ed1ab_1 - numcodecs=0.15.1=py311hcf9f919_0 - numpy=1.26.4=py311h0b4df5a_0 - - openjpeg=2.5.3=h4d64b90_0 - - openssl=3.5.1=h725018a_0 + - openjpeg=2.5.3=h24db6dd_1 + - openssl=3.5.2=h725018a_0 - overrides=7.7.0=pyhd8ed1ab_1 - packaging=25.0=pyh29332c3_1 - pandas=2.3.1=py311h11fd7f3_0 @@ -179,7 +178,7 @@ dependencies: - partd=1.4.2=pyhd8ed1ab_0 - pickleshare=0.7.5=pyhd8ed1ab_1004 - pillow=10.3.0=py311h5592be9_1 - - pip=25.1.1=pyh8b19718_0 + - pip=25.2=pyh8b19718_0 - platformdirs=4.3.8=pyhe01879c_0 - pluggy=1.6.0=pyhd8ed1ab_0 - prometheus_client=0.22.1=pyhd8ed1ab_0 @@ -195,7 +194,7 @@ dependencies: - pydata-sphinx-theme=0.15.4=pyhd8ed1ab_0 - pydiso=0.1.2=py311h66870c1_0 - pygments=2.19.2=pyhd8ed1ab_0 - - pylint=3.3.7=pyhe01879c_0 + - pylint=3.3.8=pyhe01879c_0 - pymatsolver=0.3.1=pyh48887ae_201 - pyparsing=3.2.3=pyhe01879c_2 - pysocks=1.7.1=pyh09c184e_7 @@ -212,16 +211,16 @@ dependencies: - pywin32=311=py311hefeebc8_0 - pywinpty=2.0.15=py311hda3d55a_0 - pyyaml=6.0.2=py311h5082efb_2 - - pyzmq=27.0.0=py311h484c95c_0 + - pyzmq=27.0.1=py311ha362a94_0 - readthedocs-sphinx-ext=2.2.5=pyhd8ed1ab_1 - referencing=0.36.2=pyh29332c3_0 - requests=2.32.4=pyhd8ed1ab_0 - rfc3339-validator=0.1.4=pyhd8ed1ab_1 - rfc3986-validator=0.1.1=pyh9f0ad1d_0 - rfc3987-syntax=1.1.0=pyhe01879c_1 - - rpds-py=0.26.0=py311hf51aa87_0 + - rpds-py=0.27.0=py311hf51aa87_0 - rtree=1.2.0=py311h44d53c4_1 - - scikit-learn=1.5.2=py311hdcb8d17_1 + - scikit-learn=1.6.1=py311hdcb8d17_0 - scipy=1.14.1=py311hf16d85f_2 - send2trash=1.8.3=pyh5737063_1 - setuptools=80.9.0=pyhff2d567_0 @@ -250,7 +249,7 @@ dependencies: - sqlalchemy=2.0.42=py311h3485c13_0 - stack_data=0.6.3=pyhd8ed1ab_1 - tabulate=0.9.0=pyhd8ed1ab_2 - - tbb=2021.13.0=h62715c5_1 + - tbb=2021.13.0=h18a62a1_2 - tblib=3.1.0=pyhd8ed1ab_0 - terminado=0.18.1=pyh5737063_0 - threadpoolctl=3.6.0=pyhecae5ae_0 @@ -260,11 +259,11 @@ dependencies: - tomli=2.2.1=pyhe01879c_2 - tomlkit=0.13.3=pyha770c72_0 - toolz=1.0.0=pyhd8ed1ab_1 - - tornado=6.5.1=py311he736701_0 + - tornado=6.5.2=py311h3485c13_0 - tqdm=4.67.1=pyhd8ed1ab_1 - traitlets=5.14.3=pyhd8ed1ab_1 - trimesh=4.1.8=pyhd8ed1ab_0 - - types-python-dateutil=2.9.0.20250708=pyhd8ed1ab_0 + - types-python-dateutil=2.9.0.20250809=pyhd8ed1ab_0 - typing-extensions=4.14.1=h4440ef1_0 - typing-inspection=0.4.1=pyhd8ed1ab_0 - typing_extensions=4.14.1=pyhe01879c_0 @@ -298,9 +297,9 @@ dependencies: - zstandard=0.23.0=py311he736701_2 - zstd=1.5.7=hbeecb71_2 - pip: - - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@020de8616b4767a596a4d0f49bce53c8d0c9da5b - - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@d567cc98901ecfa360ff2e93f8a6334a1bed24bc - - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@01a7068fdab7fba8695ad371c9fd9164760a09df + - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@1dbe97d441d65962a94e071b5c1c27d9facd2050 + - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@570ea996ae7e48ab1b8b971b23c9c73b7f5637b2 + - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@a1cf0ec4aa28705eb7de68cfedb255de6e590433 - octree-creation-app @ git+https://github.com/MiraGeoscience/octree-creation-app.git@02fbd85bf7d54b8f4336f1f0094c1c3e27714e81 - param-sweeps @ git+https://github.com/MiraGeoscience/param-sweeps.git@9ed6091534d638171957a17324e1a1e8f067b434 diff --git a/environments/py-3.11-win-64.conda.lock.yml b/environments/py-3.11-win-64.conda.lock.yml index dc76f14c..a958dc78 100644 --- a/environments/py-3.11-win-64.conda.lock.yml +++ b/environments/py-3.11-win-64.conda.lock.yml @@ -1,6 +1,6 @@ # Generated by conda-lock. # platform: win-64 -# input_hash: 57805dd7243378b72dd91648b00eb790f855375cd6ad3095c5099809073a0210 +# input_hash: 35467c865311a1b10fc72659b58f28578bcf2a4985e82e4f6bc78fe91e1743c8 channels: - conda-forge @@ -14,15 +14,15 @@ dependencies: - brotli-bin=1.1.0=h2466b09_3 - brotli-python=1.1.0=py311hda3d55a_3 - bzip2=1.0.8=h2466b09_7 - - ca-certificates=2025.7.14=h4c7d964_0 + - ca-certificates=2025.8.3=h4c7d964_0 - cached-property=1.5.2=hd8ed1ab_1 - cached_property=1.5.2=pyha770c72_1 - - certifi=2025.7.14=pyhd8ed1ab_0 + - certifi=2025.8.3=pyhd8ed1ab_0 - cffi=1.17.1=py311he736701_0 - click=8.2.1=pyh7428d3b_0 - cloudpickle=3.1.1=pyhd8ed1ab_0 - colorama=0.4.6=pyhd8ed1ab_1 - - contourpy=1.3.3=py311h3fd045d_0 + - contourpy=1.3.3=py311h3fd045d_1 - cycler=0.12.1=pyhd8ed1ab_1 - cytoolz=1.0.1=py311he736701_0 - dask-core=2025.3.0=pyhd8ed1ab_0 @@ -40,19 +40,18 @@ dependencies: - hpack=4.1.0=pyhd8ed1ab_0 - hyperframe=6.1.0=pyhd8ed1ab_0 - importlib-metadata=8.7.0=pyhe01879c_1 - - intel-openmp=2024.2.1=h57928b3_1083 - jinja2=3.1.6=pyhd8ed1ab_0 - joblib=1.5.1=pyhd8ed1ab_0 - - kiwisolver=1.4.8=py311h3fd045d_1 + - kiwisolver=1.4.9=py311h275cad7_0 - krb5=1.21.3=hdf4eb48_0 - lcms2=2.17=hbcf6048_0 - lerc=4.0.0=h6470a55_1 - libaec=1.1.4=h20038f6_0 - - libblas=3.9.0=32_h641d27c_mkl + - libblas=3.9.0=34_h5709861_mkl - libbrotlicommon=1.1.0=h2466b09_3 - libbrotlidec=1.1.0=h2466b09_3 - libbrotlienc=1.1.0=h2466b09_3 - - libcblas=3.9.0=32_h5e41251_mkl + - libcblas=3.9.0=34_h2a3cdd5_mkl - libcurl=8.14.1=h88aaa65_0 - libdeflate=1.24=h76ddb4d_0 - libdlf=0.3.0=pyhd8ed1ab_1 @@ -60,40 +59,40 @@ dependencies: - libffi=3.4.6=h537db12_1 - libfreetype=2.13.3=h57928b3_1 - libfreetype6=2.13.3=h0b5ce68_1 - - libgcc=15.1.0=h1383e82_3 - - libgomp=15.1.0=h1383e82_3 - - libhwloc=2.11.2=default_h88281d1_1002 - - libiconv=1.18=h135ad9c_1 + - libgcc=15.1.0=h1383e82_4 + - libgomp=15.1.0=h1383e82_4 + - libhwloc=2.12.1=default_h88281d1_1000 + - libiconv=1.18=hc1393d2_2 - libjpeg-turbo=3.1.0=h2466b09_0 - - liblapack=3.9.0=32_h1aa476e_mkl + - liblapack=3.9.0=34_hf9ab0e9_mkl - liblzma=5.8.1=h2466b09_2 - libpng=1.6.50=h7351971_1 - libspatialindex=2.0.0=h5a68840_0 - - libsqlite=3.50.3=hf5d6505_1 + - libsqlite=3.50.4=hf5d6505_0 - libssh2=1.11.1=h9aa295b_0 - libtiff=4.7.0=h05922d8_5 - libwebp-base=1.6.0=h4d5522a_0 - libwinpthread=12.0.0.r4.gg4f2fc60ca=h57928b3_9 - libxcb=1.17.0=h0e4246c_0 - - libxml2=2.13.8=h442d1da_0 + - libxml2=2.13.8=h741aa76_1 - libzlib=1.3.1=h2466b09_2 - - llvm-openmp=20.1.8=hfa2b4ca_0 + - llvm-openmp=20.1.8=hfa2b4ca_1 - locket=1.0.0=pyhd8ed1ab_0 - markupsafe=3.0.2=py311h5082efb_1 - matplotlib-base=3.8.4=py311h9b31f6e_2 - - mkl=2024.2.2=h66d3029_15 + - mkl=2024.2.2=h57928b3_16 - msgpack-python=1.1.1=py311h3257749_0 - mumps-seq=5.7.3=hbaa6519_10 - munkres=1.1.4=pyhd8ed1ab_1 - numcodecs=0.15.1=py311hcf9f919_0 - numpy=1.26.4=py311h0b4df5a_0 - - openjpeg=2.5.3=h4d64b90_0 - - openssl=3.5.1=h725018a_0 + - openjpeg=2.5.3=h24db6dd_1 + - openssl=3.5.2=h725018a_0 - packaging=25.0=pyh29332c3_1 - pandas=2.3.1=py311h11fd7f3_0 - partd=1.4.2=pyhd8ed1ab_0 - pillow=10.3.0=py311h5592be9_1 - - pip=25.1.1=pyh8b19718_0 + - pip=25.2=pyh8b19718_0 - psutil=7.0.0=py311he736701_0 - pthread-stubs=0.4=h0e40799_1002 - pycparser=2.22=pyh29332c3_1 @@ -111,17 +110,17 @@ dependencies: - pytz=2025.2=pyhd8ed1ab_0 - pyyaml=6.0.2=py311h5082efb_2 - rtree=1.2.0=py311h44d53c4_1 - - scikit-learn=1.5.2=py311hdcb8d17_1 + - scikit-learn=1.6.1=py311hdcb8d17_0 - scipy=1.14.1=py311hf16d85f_2 - setuptools=80.9.0=pyhff2d567_0 - six=1.17.0=pyhe01879c_1 - sortedcontainers=2.4.0=pyhd8ed1ab_1 - - tbb=2021.13.0=h62715c5_1 + - tbb=2021.13.0=h18a62a1_2 - tblib=3.1.0=pyhd8ed1ab_0 - threadpoolctl=3.6.0=pyhecae5ae_0 - tk=8.6.13=h2c6b04d_2 - toolz=1.0.0=pyhd8ed1ab_1 - - tornado=6.5.1=py311he736701_0 + - tornado=6.5.2=py311h3485c13_0 - tqdm=4.67.1=pyhd8ed1ab_1 - trimesh=4.1.8=pyhd8ed1ab_0 - typing-extensions=4.14.1=h4440ef1_0 @@ -147,9 +146,9 @@ dependencies: - zstandard=0.23.0=py311he736701_2 - zstd=1.5.7=hbeecb71_2 - pip: - - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@020de8616b4767a596a4d0f49bce53c8d0c9da5b - - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@d567cc98901ecfa360ff2e93f8a6334a1bed24bc - - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@01a7068fdab7fba8695ad371c9fd9164760a09df + - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@1dbe97d441d65962a94e071b5c1c27d9facd2050 + - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@570ea996ae7e48ab1b8b971b23c9c73b7f5637b2 + - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@a1cf0ec4aa28705eb7de68cfedb255de6e590433 - octree-creation-app @ git+https://github.com/MiraGeoscience/octree-creation-app.git@02fbd85bf7d54b8f4336f1f0094c1c3e27714e81 - param-sweeps @ git+https://github.com/MiraGeoscience/param-sweeps.git@9ed6091534d638171957a17324e1a1e8f067b434 diff --git a/environments/py-3.12-linux-64-dev.conda.lock.yml b/environments/py-3.12-linux-64-dev.conda.lock.yml index b94eeaa2..b883d8f9 100644 --- a/environments/py-3.12-linux-64-dev.conda.lock.yml +++ b/environments/py-3.12-linux-64-dev.conda.lock.yml @@ -1,6 +1,6 @@ # Generated by conda-lock. # platform: linux-64 -# input_hash: 0411d0bb5b468d1fb923a36f5fc20b1e4f1af3a872d37f6492e422e64a4e5142 +# input_hash: 2e48ea762f31ce7d0e20196680dec38b885bd725bb1dc73d18f428e1faa16c06 channels: - conda-forge @@ -10,9 +10,9 @@ dependencies: - accessible-pygments=0.0.5=pyhd8ed1ab_1 - alabaster=0.7.16=pyhd8ed1ab_0 - annotated-types=0.7.0=pyhd8ed1ab_1 - - anyio=4.9.0=pyh29332c3_0 + - anyio=4.10.0=pyhe01879c_0 - argon2-cffi=25.1.0=pyhd8ed1ab_0 - - argon2-cffi-bindings=21.2.0=py312h66e93f0_5 + - argon2-cffi-bindings=25.1.0=py312h4c3975b_0 - arrow=1.3.0=pyhd8ed1ab_1 - asciitree=0.3.3=py_2 - astroid=3.3.11=py312h7900ff3_0 @@ -29,23 +29,23 @@ dependencies: - brotli-python=1.1.0=py312h2ec8cdc_3 - bzip2=1.0.8=h4bc722e_7 - c-ares=1.34.5=hb9d3cd8_0 - - ca-certificates=2025.7.14=hbd8a1cb_0 + - ca-certificates=2025.8.3=hbd8a1cb_0 - cached-property=1.5.2=hd8ed1ab_1 - cached_property=1.5.2=pyha770c72_1 - - certifi=2025.7.14=pyhd8ed1ab_0 + - certifi=2025.8.3=pyhd8ed1ab_0 - cffi=1.17.1=py312h06ac9bb_0 - - charset-normalizer=3.4.2=pyhd8ed1ab_0 + - charset-normalizer=3.4.3=pyhd8ed1ab_0 - click=8.2.1=pyh707e725_0 - cloudpickle=3.1.1=pyhd8ed1ab_0 - colorama=0.4.6=pyhd8ed1ab_1 - comm=0.2.3=pyhe01879c_0 - - contourpy=1.3.3=py312hd9148b4_0 - - coverage=7.10.1=py312h8a5da7c_0 + - contourpy=1.3.3=py312hd9148b4_1 + - coverage=7.10.3=py312h8a5da7c_0 - cycler=0.12.1=pyhd8ed1ab_1 - cytoolz=1.0.1=py312h66e93f0_0 - dask-core=2025.3.0=pyhd8ed1ab_0 - dataclasses=0.8=pyhc8e2a94_3 - - debugpy=1.8.15=py312h8285ef7_0 + - debugpy=1.8.16=py312h8285ef7_0 - decorator=5.2.1=pyhd8ed1ab_0 - defusedxml=0.7.1=pyhd8ed1ab_0 - deprecated=1.2.18=pyhd8ed1ab_0 @@ -61,7 +61,7 @@ dependencies: - freetype=2.13.3=ha770c72_1 - fsspec=2025.7.0=pyhd8ed1ab_0 - geoana=0.7.2=py312hc39e661_0 - - greenlet=3.2.3=py312h2ec8cdc_0 + - greenlet=3.2.4=py312h1289d80_0 - h11=0.16.0=pyhd8ed1ab_0 - h2=4.2.0=pyhd8ed1ab_0 - h5py=3.14.0=nompi_py312h3faca00_100 @@ -70,13 +70,12 @@ dependencies: - httpcore=1.0.9=pyh29332c3_0 - httpx=0.28.1=pyhd8ed1ab_0 - hyperframe=6.1.0=pyhd8ed1ab_0 - - icu=75.1=he02047a_0 - idna=3.10=pyhd8ed1ab_1 - imagesize=1.4.1=pyhd8ed1ab_0 - importlib-metadata=8.7.0=pyhe01879c_1 - importlib_metadata=8.7.0=h40b2b14_1 - iniconfig=2.0.0=pyhd8ed1ab_1 - - ipykernel=6.30.0=pyh82676e8_0 + - ipykernel=6.30.1=pyh82676e8_0 - ipython=9.4.0=pyhfa0c392_0 - ipython_genutils=0.2.0=pyhd8ed1ab_2 - ipython_pygments_lexers=1.1.1=pyhd8ed1ab_0 @@ -104,8 +103,8 @@ dependencies: - jupyterlab_server=2.27.3=pyhd8ed1ab_1 - jupyterlab_widgets=1.1.11=pyhd8ed1ab_0 - jupytext=1.17.2=pyh80e38bb_0 - - keyutils=1.6.1=h166bdaf_0 - - kiwisolver=1.4.8=py312h68727a3_1 + - keyutils=1.6.3=hb9d3cd8_0 + - kiwisolver=1.4.9=py312h0a2e395_0 - krb5=1.21.3=h659f571_0 - lark=1.2.2=pyhd8ed1ab_1 - latexcodec=2.0.1=pyh9f0ad1d_0 @@ -113,11 +112,11 @@ dependencies: - ld_impl_linux-64=2.44=h1423503_1 - lerc=4.0.0=h0aef613_1 - libaec=1.1.4=h3f801dc_0 - - libblas=3.9.0=32_hfdb39a5_mkl + - libblas=3.9.0=34_hfdb39a5_mkl - libbrotlicommon=1.1.0=hb9d3cd8_3 - libbrotlidec=1.1.0=hb9d3cd8_3 - libbrotlienc=1.1.0=hb9d3cd8_3 - - libcblas=3.9.0=32_h372d94f_mkl + - libcblas=3.9.0=34_h372d94f_mkl - libcurl=8.14.1=h332b0f4_0 - libdeflate=1.24=h86f0d12_0 - libdlf=0.3.0=pyhd8ed1ab_1 @@ -127,14 +126,14 @@ dependencies: - libffi=3.4.6=h2dba641_1 - libfreetype=2.13.3=ha770c72_1 - libfreetype6=2.13.3=h48d6fc4_1 - - libgcc=15.1.0=h767d61c_3 - - libgcc-ng=15.1.0=h69a702a_3 - - libgfortran=15.1.0=h69a702a_3 - - libgfortran5=15.1.0=hcea5267_3 - - libhwloc=2.11.2=default_h3d81e11_1002 - - libiconv=1.18=h4ce23a2_1 + - libgcc=15.1.0=h767d61c_4 + - libgcc-ng=15.1.0=h69a702a_4 + - libgfortran=15.1.0=h69a702a_4 + - libgfortran5=15.1.0=hcea5267_4 + - libhwloc=2.12.1=default_h3d81e11_1000 + - libiconv=1.18=h3b78370_2 - libjpeg-turbo=3.1.0=hb9d3cd8_0 - - liblapack=3.9.0=32_hc41d3b0_mkl + - liblapack=3.9.0=34_hc41d3b0_mkl - liblzma=5.8.1=hb9d3cd8_2 - libnghttp2=1.64.0=h161d5f1_0 - libnsl=2.0.1=hb9d3cd8_1 @@ -142,19 +141,19 @@ dependencies: - libscotch=7.0.6=hea33c07_1 - libsodium=1.0.20=h4ab18f5_0 - libspatialindex=2.0.0=he02047a_0 - - libsqlite=3.50.3=hee844dc_1 + - libsqlite=3.50.4=h0c1763c_0 - libssh2=1.11.1=hcf80075_0 - - libstdcxx=15.1.0=h8f9b012_3 - - libstdcxx-ng=15.1.0=h4852527_3 + - libstdcxx=15.1.0=h8f9b012_4 + - libstdcxx-ng=15.1.0=h4852527_4 - libtiff=4.7.0=hf01ce69_5 - libuuid=2.38.1=h0b41bf4_0 - libwebp-base=1.6.0=hd42ef1d_0 - libxcb=1.17.0=h8a09558_0 - libxcrypt=4.4.36=hd590300_1 - - libxml2=2.13.8=h4bc477f_0 + - libxml2=2.13.8=h2cb61b6_1 - libzlib=1.3.1=hb9d3cd8_2 - linkify-it-py=2.0.3=pyhd8ed1ab_1 - - llvm-openmp=20.1.8=h4922eb0_0 + - llvm-openmp=20.1.8=h4922eb0_1 - locket=1.0.0=pyhd8ed1ab_0 - markdown-it-py=2.2.0=pyhd8ed1ab_0 - markupsafe=3.0.2=py312h178313f_1 @@ -165,7 +164,7 @@ dependencies: - mdurl=0.1.2=pyhd8ed1ab_1 - metis=5.1.0=hd0bcaf9_1007 - mistune=3.1.3=pyh29332c3_0 - - mkl=2024.2.2=ha770c72_16 + - mkl=2024.2.2=ha770c72_17 - msgpack-python=1.1.1=py312h68727a3_0 - mumps-include=5.7.3=h82cca05_10 - mumps-seq=5.7.3=h06cbf8f_10 @@ -179,12 +178,12 @@ dependencies: - nbformat=5.10.4=pyhd8ed1ab_1 - ncurses=6.5=h2d0b736_3 - nest-asyncio=1.6.0=pyhd8ed1ab_1 - - notebook=7.4.4=pyhd8ed1ab_0 + - notebook=7.4.5=pyhd8ed1ab_0 - notebook-shim=0.2.4=pyhd8ed1ab_1 - numcodecs=0.15.1=py312hf9745cd_0 - numpy=1.26.4=py312heda63a1_0 - - openjpeg=2.5.3=h5fbd93e_0 - - openssl=3.5.1=h7b32b05_0 + - openjpeg=2.5.3=h55fea9a_1 + - openssl=3.5.2=h26f9b46_0 - overrides=7.7.0=pyhd8ed1ab_1 - packaging=25.0=pyh29332c3_1 - pandas=2.3.1=py312hf79963d_0 @@ -195,7 +194,7 @@ dependencies: - pexpect=4.9.0=pyhd8ed1ab_1 - pickleshare=0.7.5=pyhd8ed1ab_1004 - pillow=10.3.0=py312h287a98d_1 - - pip=25.1.1=pyh8b19718_0 + - pip=25.2=pyh8b19718_0 - platformdirs=4.3.8=pyhe01879c_0 - pluggy=1.6.0=pyhd8ed1ab_0 - prometheus_client=0.22.1=pyhd8ed1ab_0 @@ -212,7 +211,7 @@ dependencies: - pydata-sphinx-theme=0.15.4=pyhd8ed1ab_0 - pydiso=0.1.2=py312h772f2df_0 - pygments=2.19.2=pyhd8ed1ab_0 - - pylint=3.3.7=pyhe01879c_0 + - pylint=3.3.8=pyhe01879c_0 - pymatsolver=0.3.1=pyh48887ae_201 - pyparsing=3.2.3=pyhe01879c_2 - pysocks=1.7.1=pyha55dd90_7 @@ -227,7 +226,7 @@ dependencies: - python_abi=3.12=8_cp312 - pytz=2025.2=pyhd8ed1ab_0 - pyyaml=6.0.2=py312h178313f_2 - - pyzmq=27.0.0=py312hbf22597_0 + - pyzmq=27.0.1=py312h6748674_0 - readline=8.2=h8c095d6_2 - readthedocs-sphinx-ext=2.2.5=pyhd8ed1ab_1 - referencing=0.36.2=pyh29332c3_0 @@ -235,9 +234,9 @@ dependencies: - rfc3339-validator=0.1.4=pyhd8ed1ab_1 - rfc3986-validator=0.1.1=pyh9f0ad1d_0 - rfc3987-syntax=1.1.0=pyhe01879c_1 - - rpds-py=0.26.0=py312h680f630_0 + - rpds-py=0.27.0=py312h868fb18_0 - rtree=1.2.0=py312h3ed4c40_1 - - scikit-learn=1.5.2=py312h7a48858_1 + - scikit-learn=1.6.1=py312h7a48858_0 - scipy=1.14.1=py312h62794b6_2 - send2trash=1.8.3=pyh0d859eb_1 - setuptools=80.9.0=pyhff2d567_0 @@ -266,7 +265,7 @@ dependencies: - sqlalchemy=2.0.42=py312h4c3975b_0 - stack_data=0.6.3=pyhd8ed1ab_1 - tabulate=0.9.0=pyhd8ed1ab_2 - - tbb=2021.13.0=hceb3a55_1 + - tbb=2021.13.0=hb60516a_2 - tblib=3.1.0=pyhd8ed1ab_0 - terminado=0.18.1=pyh0d859eb_0 - threadpoolctl=3.6.0=pyhecae5ae_0 @@ -276,11 +275,11 @@ dependencies: - tomli=2.2.1=pyhe01879c_2 - tomlkit=0.13.3=pyha770c72_0 - toolz=1.0.0=pyhd8ed1ab_1 - - tornado=6.5.1=py312h66e93f0_0 + - tornado=6.5.2=py312h4c3975b_0 - tqdm=4.67.1=pyhd8ed1ab_1 - traitlets=5.14.3=pyhd8ed1ab_1 - trimesh=4.1.8=pyhd8ed1ab_0 - - types-python-dateutil=2.9.0.20250708=pyhd8ed1ab_0 + - types-python-dateutil=2.9.0.20250809=pyhd8ed1ab_0 - typing-extensions=4.14.1=h4440ef1_0 - typing-inspection=0.4.1=pyhd8ed1ab_0 - typing_extensions=4.14.1=pyhe01879c_0 @@ -308,9 +307,9 @@ dependencies: - zstandard=0.23.0=py312h66e93f0_2 - zstd=1.5.7=hb8e6e7a_2 - pip: - - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@020de8616b4767a596a4d0f49bce53c8d0c9da5b - - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@d567cc98901ecfa360ff2e93f8a6334a1bed24bc - - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@01a7068fdab7fba8695ad371c9fd9164760a09df + - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@1dbe97d441d65962a94e071b5c1c27d9facd2050 + - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@570ea996ae7e48ab1b8b971b23c9c73b7f5637b2 + - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@a1cf0ec4aa28705eb7de68cfedb255de6e590433 - octree-creation-app @ git+https://github.com/MiraGeoscience/octree-creation-app.git@02fbd85bf7d54b8f4336f1f0094c1c3e27714e81 - param-sweeps @ git+https://github.com/MiraGeoscience/param-sweeps.git@9ed6091534d638171957a17324e1a1e8f067b434 diff --git a/environments/py-3.12-linux-64.conda.lock.yml b/environments/py-3.12-linux-64.conda.lock.yml index a7a78c21..13b54b41 100644 --- a/environments/py-3.12-linux-64.conda.lock.yml +++ b/environments/py-3.12-linux-64.conda.lock.yml @@ -1,6 +1,6 @@ # Generated by conda-lock. # platform: linux-64 -# input_hash: 0411d0bb5b468d1fb923a36f5fc20b1e4f1af3a872d37f6492e422e64a4e5142 +# input_hash: 2e48ea762f31ce7d0e20196680dec38b885bd725bb1dc73d18f428e1faa16c06 channels: - conda-forge @@ -15,15 +15,15 @@ dependencies: - brotli-python=1.1.0=py312h2ec8cdc_3 - bzip2=1.0.8=h4bc722e_7 - c-ares=1.34.5=hb9d3cd8_0 - - ca-certificates=2025.7.14=hbd8a1cb_0 + - ca-certificates=2025.8.3=hbd8a1cb_0 - cached-property=1.5.2=hd8ed1ab_1 - cached_property=1.5.2=pyha770c72_1 - - certifi=2025.7.14=pyhd8ed1ab_0 + - certifi=2025.8.3=pyhd8ed1ab_0 - cffi=1.17.1=py312h06ac9bb_0 - click=8.2.1=pyh707e725_0 - cloudpickle=3.1.1=pyhd8ed1ab_0 - colorama=0.4.6=pyhd8ed1ab_1 - - contourpy=1.3.3=py312hd9148b4_0 + - contourpy=1.3.3=py312hd9148b4_1 - cycler=0.12.1=pyhd8ed1ab_1 - cytoolz=1.0.1=py312h66e93f0_0 - dask-core=2025.3.0=pyhd8ed1ab_0 @@ -40,22 +40,21 @@ dependencies: - hdf5=1.14.6=nompi_h6e4c0c1_103 - hpack=4.1.0=pyhd8ed1ab_0 - hyperframe=6.1.0=pyhd8ed1ab_0 - - icu=75.1=he02047a_0 - importlib-metadata=8.7.0=pyhe01879c_1 - jinja2=3.1.6=pyhd8ed1ab_0 - joblib=1.5.1=pyhd8ed1ab_0 - - keyutils=1.6.1=h166bdaf_0 - - kiwisolver=1.4.8=py312h68727a3_1 + - keyutils=1.6.3=hb9d3cd8_0 + - kiwisolver=1.4.9=py312h0a2e395_0 - krb5=1.21.3=h659f571_0 - lcms2=2.17=h717163a_0 - ld_impl_linux-64=2.44=h1423503_1 - lerc=4.0.0=h0aef613_1 - libaec=1.1.4=h3f801dc_0 - - libblas=3.9.0=32_hfdb39a5_mkl + - libblas=3.9.0=34_hfdb39a5_mkl - libbrotlicommon=1.1.0=hb9d3cd8_3 - libbrotlidec=1.1.0=hb9d3cd8_3 - libbrotlienc=1.1.0=hb9d3cd8_3 - - libcblas=3.9.0=32_h372d94f_mkl + - libcblas=3.9.0=34_h372d94f_mkl - libcurl=8.14.1=h332b0f4_0 - libdeflate=1.24=h86f0d12_0 - libdlf=0.3.0=pyhd8ed1ab_1 @@ -65,37 +64,37 @@ dependencies: - libffi=3.4.6=h2dba641_1 - libfreetype=2.13.3=ha770c72_1 - libfreetype6=2.13.3=h48d6fc4_1 - - libgcc=15.1.0=h767d61c_3 - - libgcc-ng=15.1.0=h69a702a_3 - - libgfortran=15.1.0=h69a702a_3 - - libgfortran5=15.1.0=hcea5267_3 - - libhwloc=2.11.2=default_h3d81e11_1002 - - libiconv=1.18=h4ce23a2_1 + - libgcc=15.1.0=h767d61c_4 + - libgcc-ng=15.1.0=h69a702a_4 + - libgfortran=15.1.0=h69a702a_4 + - libgfortran5=15.1.0=hcea5267_4 + - libhwloc=2.12.1=default_h3d81e11_1000 + - libiconv=1.18=h3b78370_2 - libjpeg-turbo=3.1.0=hb9d3cd8_0 - - liblapack=3.9.0=32_hc41d3b0_mkl + - liblapack=3.9.0=34_hc41d3b0_mkl - liblzma=5.8.1=hb9d3cd8_2 - libnghttp2=1.64.0=h161d5f1_0 - libnsl=2.0.1=hb9d3cd8_1 - libpng=1.6.50=h421ea60_1 - libscotch=7.0.6=hea33c07_1 - libspatialindex=2.0.0=he02047a_0 - - libsqlite=3.50.3=hee844dc_1 + - libsqlite=3.50.4=h0c1763c_0 - libssh2=1.11.1=hcf80075_0 - - libstdcxx=15.1.0=h8f9b012_3 - - libstdcxx-ng=15.1.0=h4852527_3 + - libstdcxx=15.1.0=h8f9b012_4 + - libstdcxx-ng=15.1.0=h4852527_4 - libtiff=4.7.0=hf01ce69_5 - libuuid=2.38.1=h0b41bf4_0 - libwebp-base=1.6.0=hd42ef1d_0 - libxcb=1.17.0=h8a09558_0 - libxcrypt=4.4.36=hd590300_1 - - libxml2=2.13.8=h4bc477f_0 + - libxml2=2.13.8=h2cb61b6_1 - libzlib=1.3.1=hb9d3cd8_2 - - llvm-openmp=20.1.8=h4922eb0_0 + - llvm-openmp=20.1.8=h4922eb0_1 - locket=1.0.0=pyhd8ed1ab_0 - markupsafe=3.0.2=py312h178313f_1 - matplotlib-base=3.8.4=py312h20ab3a6_2 - metis=5.1.0=hd0bcaf9_1007 - - mkl=2024.2.2=ha770c72_16 + - mkl=2024.2.2=ha770c72_17 - msgpack-python=1.1.1=py312h68727a3_0 - mumps-include=5.7.3=h82cca05_10 - mumps-seq=5.7.3=h06cbf8f_10 @@ -103,13 +102,13 @@ dependencies: - ncurses=6.5=h2d0b736_3 - numcodecs=0.15.1=py312hf9745cd_0 - numpy=1.26.4=py312heda63a1_0 - - openjpeg=2.5.3=h5fbd93e_0 - - openssl=3.5.1=h7b32b05_0 + - openjpeg=2.5.3=h55fea9a_1 + - openssl=3.5.2=h26f9b46_0 - packaging=25.0=pyh29332c3_1 - pandas=2.3.1=py312hf79963d_0 - partd=1.4.2=pyhd8ed1ab_0 - pillow=10.3.0=py312h287a98d_1 - - pip=25.1.1=pyh8b19718_0 + - pip=25.2=pyh8b19718_0 - psutil=7.0.0=py312h66e93f0_0 - pthread-stubs=0.4=hb9d3cd8_1002 - pycparser=2.22=pyh29332c3_1 @@ -128,17 +127,17 @@ dependencies: - pyyaml=6.0.2=py312h178313f_2 - readline=8.2=h8c095d6_2 - rtree=1.2.0=py312h3ed4c40_1 - - scikit-learn=1.5.2=py312h7a48858_1 + - scikit-learn=1.6.1=py312h7a48858_0 - scipy=1.14.1=py312h62794b6_2 - setuptools=80.9.0=pyhff2d567_0 - six=1.17.0=pyhe01879c_1 - sortedcontainers=2.4.0=pyhd8ed1ab_1 - - tbb=2021.13.0=hceb3a55_1 + - tbb=2021.13.0=hb60516a_2 - tblib=3.1.0=pyhd8ed1ab_0 - threadpoolctl=3.6.0=pyhecae5ae_0 - tk=8.6.13=noxft_hd72426e_102 - toolz=1.0.0=pyhd8ed1ab_1 - - tornado=6.5.1=py312h66e93f0_0 + - tornado=6.5.2=py312h4c3975b_0 - tqdm=4.67.1=pyhd8ed1ab_1 - trimesh=4.1.8=pyhd8ed1ab_0 - typing-extensions=4.14.1=h4440ef1_0 @@ -159,9 +158,9 @@ dependencies: - zstandard=0.23.0=py312h66e93f0_2 - zstd=1.5.7=hb8e6e7a_2 - pip: - - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@020de8616b4767a596a4d0f49bce53c8d0c9da5b - - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@d567cc98901ecfa360ff2e93f8a6334a1bed24bc - - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@01a7068fdab7fba8695ad371c9fd9164760a09df + - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@1dbe97d441d65962a94e071b5c1c27d9facd2050 + - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@570ea996ae7e48ab1b8b971b23c9c73b7f5637b2 + - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@a1cf0ec4aa28705eb7de68cfedb255de6e590433 - octree-creation-app @ git+https://github.com/MiraGeoscience/octree-creation-app.git@02fbd85bf7d54b8f4336f1f0094c1c3e27714e81 - param-sweeps @ git+https://github.com/MiraGeoscience/param-sweeps.git@9ed6091534d638171957a17324e1a1e8f067b434 diff --git a/environments/py-3.12-win-64-dev.conda.lock.yml b/environments/py-3.12-win-64-dev.conda.lock.yml index 5f28d3da..071d077d 100644 --- a/environments/py-3.12-win-64-dev.conda.lock.yml +++ b/environments/py-3.12-win-64-dev.conda.lock.yml @@ -1,6 +1,6 @@ # Generated by conda-lock. # platform: win-64 -# input_hash: 2b057dda003b244877434d1dd71bfa18b96472fbaeadeb2cf9c4266efbfdb4e0 +# input_hash: cad8b21157a4bd089f15f4bf7c6585be405714f5ed3e20fc6985dacc023e9965 channels: - conda-forge @@ -10,9 +10,9 @@ dependencies: - accessible-pygments=0.0.5=pyhd8ed1ab_1 - alabaster=0.7.16=pyhd8ed1ab_0 - annotated-types=0.7.0=pyhd8ed1ab_1 - - anyio=4.9.0=pyh29332c3_0 + - anyio=4.10.0=pyhe01879c_0 - argon2-cffi=25.1.0=pyhd8ed1ab_0 - - argon2-cffi-bindings=21.2.0=py312h4389bb4_5 + - argon2-cffi-bindings=25.1.0=py312he06e257_0 - arrow=1.3.0=pyhd8ed1ab_1 - asciitree=0.3.3=py_2 - astroid=3.3.11=py312h2e8e312_0 @@ -28,24 +28,24 @@ dependencies: - brotli-bin=1.1.0=h2466b09_3 - brotli-python=1.1.0=py312h275cf98_3 - bzip2=1.0.8=h2466b09_7 - - ca-certificates=2025.7.14=h4c7d964_0 + - ca-certificates=2025.8.3=h4c7d964_0 - cached-property=1.5.2=hd8ed1ab_1 - cached_property=1.5.2=pyha770c72_1 - - certifi=2025.7.14=pyhd8ed1ab_0 + - certifi=2025.8.3=pyhd8ed1ab_0 - cffi=1.17.1=py312h4389bb4_0 - - charset-normalizer=3.4.2=pyhd8ed1ab_0 + - charset-normalizer=3.4.3=pyhd8ed1ab_0 - click=8.2.1=pyh7428d3b_0 - cloudpickle=3.1.1=pyhd8ed1ab_0 - colorama=0.4.6=pyhd8ed1ab_1 - comm=0.2.3=pyhe01879c_0 - - contourpy=1.3.3=py312hf90b1b7_0 - - coverage=7.10.1=py312h05f76fc_0 + - contourpy=1.3.3=py312hf90b1b7_1 + - coverage=7.10.3=py312h05f76fc_0 - cpython=3.12.11=py312hd8ed1ab_0 - cycler=0.12.1=pyhd8ed1ab_1 - cytoolz=1.0.1=py312h4389bb4_0 - dask-core=2025.3.0=pyhd8ed1ab_0 - dataclasses=0.8=pyhc8e2a94_3 - - debugpy=1.8.15=py312ha1a9051_0 + - debugpy=1.8.16=py312ha1a9051_0 - decorator=5.2.1=pyhd8ed1ab_0 - defusedxml=0.7.1=pyhd8ed1ab_0 - deprecated=1.2.18=pyhd8ed1ab_0 @@ -61,7 +61,7 @@ dependencies: - freetype=2.13.3=h57928b3_1 - fsspec=2025.7.0=pyhd8ed1ab_0 - geoana=0.7.2=py312hbaa7e33_0 - - greenlet=3.2.3=py312h275cf98_0 + - greenlet=3.2.4=py312hbb81ca0_0 - h11=0.16.0=pyhd8ed1ab_0 - h2=4.2.0=pyhd8ed1ab_0 - h5py=3.14.0=nompi_py312h6cc2a29_100 @@ -75,8 +75,7 @@ dependencies: - importlib-metadata=8.7.0=pyhe01879c_1 - importlib_metadata=8.7.0=h40b2b14_1 - iniconfig=2.0.0=pyhd8ed1ab_1 - - intel-openmp=2024.2.1=h57928b3_1083 - - ipykernel=6.30.0=pyh3521513_0 + - ipykernel=6.30.1=pyh3521513_0 - ipython=9.4.0=pyh6be1c34_0 - ipython_genutils=0.2.0=pyhd8ed1ab_2 - ipython_pygments_lexers=1.1.1=pyhd8ed1ab_0 @@ -104,18 +103,18 @@ dependencies: - jupyterlab_server=2.27.3=pyhd8ed1ab_1 - jupyterlab_widgets=1.1.11=pyhd8ed1ab_0 - jupytext=1.17.2=pyh80e38bb_0 - - kiwisolver=1.4.8=py312hf90b1b7_1 + - kiwisolver=1.4.9=py312h78d62e6_0 - krb5=1.21.3=hdf4eb48_0 - lark=1.2.2=pyhd8ed1ab_1 - latexcodec=2.0.1=pyh9f0ad1d_0 - lcms2=2.17=hbcf6048_0 - lerc=4.0.0=h6470a55_1 - libaec=1.1.4=h20038f6_0 - - libblas=3.9.0=32_h641d27c_mkl + - libblas=3.9.0=34_h5709861_mkl - libbrotlicommon=1.1.0=h2466b09_3 - libbrotlidec=1.1.0=h2466b09_3 - libbrotlienc=1.1.0=h2466b09_3 - - libcblas=3.9.0=32_h5e41251_mkl + - libcblas=3.9.0=34_h2a3cdd5_mkl - libcurl=8.14.1=h88aaa65_0 - libdeflate=1.24=h76ddb4d_0 - libdlf=0.3.0=pyhd8ed1ab_1 @@ -123,26 +122,26 @@ dependencies: - libffi=3.4.6=h537db12_1 - libfreetype=2.13.3=h57928b3_1 - libfreetype6=2.13.3=h0b5ce68_1 - - libgcc=15.1.0=h1383e82_3 - - libgomp=15.1.0=h1383e82_3 - - libhwloc=2.11.2=default_h88281d1_1002 - - libiconv=1.18=h135ad9c_1 + - libgcc=15.1.0=h1383e82_4 + - libgomp=15.1.0=h1383e82_4 + - libhwloc=2.12.1=default_h88281d1_1000 + - libiconv=1.18=hc1393d2_2 - libjpeg-turbo=3.1.0=h2466b09_0 - - liblapack=3.9.0=32_h1aa476e_mkl + - liblapack=3.9.0=34_hf9ab0e9_mkl - liblzma=5.8.1=h2466b09_2 - libpng=1.6.50=h7351971_1 - libsodium=1.0.20=hc70643c_0 - libspatialindex=2.0.0=h5a68840_0 - - libsqlite=3.50.3=hf5d6505_1 + - libsqlite=3.50.4=hf5d6505_0 - libssh2=1.11.1=h9aa295b_0 - libtiff=4.7.0=h05922d8_5 - libwebp-base=1.6.0=h4d5522a_0 - libwinpthread=12.0.0.r4.gg4f2fc60ca=h57928b3_9 - libxcb=1.17.0=h0e4246c_0 - - libxml2=2.13.8=h442d1da_0 + - libxml2=2.13.8=h741aa76_1 - libzlib=1.3.1=h2466b09_2 - linkify-it-py=2.0.3=pyhd8ed1ab_1 - - llvm-openmp=20.1.8=hfa2b4ca_0 + - llvm-openmp=20.1.8=hfa2b4ca_1 - locket=1.0.0=pyhd8ed1ab_0 - markdown-it-py=2.2.0=pyhd8ed1ab_0 - markupsafe=3.0.2=py312h31fea79_1 @@ -152,7 +151,7 @@ dependencies: - mdit-py-plugins=0.4.2=pyhd8ed1ab_1 - mdurl=0.1.2=pyhd8ed1ab_1 - mistune=3.1.3=pyh29332c3_0 - - mkl=2024.2.2=h66d3029_15 + - mkl=2024.2.2=h57928b3_16 - msgpack-python=1.1.1=py312hd5eb7cc_0 - mumps-seq=5.7.3=hbaa6519_10 - munkres=1.1.4=pyhd8ed1ab_1 @@ -164,12 +163,12 @@ dependencies: - nbconvert-pandoc=7.16.6=hed9df3c_0 - nbformat=5.10.4=pyhd8ed1ab_1 - nest-asyncio=1.6.0=pyhd8ed1ab_1 - - notebook=7.4.4=pyhd8ed1ab_0 + - notebook=7.4.5=pyhd8ed1ab_0 - notebook-shim=0.2.4=pyhd8ed1ab_1 - numcodecs=0.15.1=py312h72972c8_0 - numpy=1.26.4=py312h8753938_0 - - openjpeg=2.5.3=h4d64b90_0 - - openssl=3.5.1=h725018a_0 + - openjpeg=2.5.3=h24db6dd_1 + - openssl=3.5.2=h725018a_0 - overrides=7.7.0=pyhd8ed1ab_1 - packaging=25.0=pyh29332c3_1 - pandas=2.3.1=py312hc128f0a_0 @@ -179,7 +178,7 @@ dependencies: - partd=1.4.2=pyhd8ed1ab_0 - pickleshare=0.7.5=pyhd8ed1ab_1004 - pillow=10.3.0=py312h381445a_1 - - pip=25.1.1=pyh8b19718_0 + - pip=25.2=pyh8b19718_0 - platformdirs=4.3.8=pyhe01879c_0 - pluggy=1.6.0=pyhd8ed1ab_0 - prometheus_client=0.22.1=pyhd8ed1ab_0 @@ -195,7 +194,7 @@ dependencies: - pydata-sphinx-theme=0.15.4=pyhd8ed1ab_0 - pydiso=0.1.2=py312h01acb21_0 - pygments=2.19.2=pyhd8ed1ab_0 - - pylint=3.3.7=pyhe01879c_0 + - pylint=3.3.8=pyhe01879c_0 - pymatsolver=0.3.1=pyh48887ae_201 - pyparsing=3.2.3=pyhe01879c_2 - pysocks=1.7.1=pyh09c184e_7 @@ -212,16 +211,16 @@ dependencies: - pywin32=311=py312h829343e_0 - pywinpty=2.0.15=py312h275cf98_0 - pyyaml=6.0.2=py312h31fea79_2 - - pyzmq=27.0.0=py312hd7027bb_0 + - pyzmq=27.0.1=py312h5b324a9_0 - readthedocs-sphinx-ext=2.2.5=pyhd8ed1ab_1 - referencing=0.36.2=pyh29332c3_0 - requests=2.32.4=pyhd8ed1ab_0 - rfc3339-validator=0.1.4=pyhd8ed1ab_1 - rfc3986-validator=0.1.1=pyh9f0ad1d_0 - rfc3987-syntax=1.1.0=pyhe01879c_1 - - rpds-py=0.26.0=py312hdabe01f_0 + - rpds-py=0.27.0=py312hdabe01f_0 - rtree=1.2.0=py312h50e5f8f_1 - - scikit-learn=1.5.2=py312h816cc57_1 + - scikit-learn=1.6.1=py312h816cc57_0 - scipy=1.14.1=py312h337df96_2 - send2trash=1.8.3=pyh5737063_1 - setuptools=80.9.0=pyhff2d567_0 @@ -250,7 +249,7 @@ dependencies: - sqlalchemy=2.0.42=py312he06e257_0 - stack_data=0.6.3=pyhd8ed1ab_1 - tabulate=0.9.0=pyhd8ed1ab_2 - - tbb=2021.13.0=h62715c5_1 + - tbb=2021.13.0=h18a62a1_2 - tblib=3.1.0=pyhd8ed1ab_0 - terminado=0.18.1=pyh5737063_0 - threadpoolctl=3.6.0=pyhecae5ae_0 @@ -260,11 +259,11 @@ dependencies: - tomli=2.2.1=pyhe01879c_2 - tomlkit=0.13.3=pyha770c72_0 - toolz=1.0.0=pyhd8ed1ab_1 - - tornado=6.5.1=py312h4389bb4_0 + - tornado=6.5.2=py312he06e257_0 - tqdm=4.67.1=pyhd8ed1ab_1 - traitlets=5.14.3=pyhd8ed1ab_1 - trimesh=4.1.8=pyhd8ed1ab_0 - - types-python-dateutil=2.9.0.20250708=pyhd8ed1ab_0 + - types-python-dateutil=2.9.0.20250809=pyhd8ed1ab_0 - typing-extensions=4.14.1=h4440ef1_0 - typing-inspection=0.4.1=pyhd8ed1ab_0 - typing_extensions=4.14.1=pyhe01879c_0 @@ -298,9 +297,9 @@ dependencies: - zstandard=0.23.0=py312h4389bb4_2 - zstd=1.5.7=hbeecb71_2 - pip: - - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@020de8616b4767a596a4d0f49bce53c8d0c9da5b - - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@d567cc98901ecfa360ff2e93f8a6334a1bed24bc - - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@01a7068fdab7fba8695ad371c9fd9164760a09df + - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@1dbe97d441d65962a94e071b5c1c27d9facd2050 + - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@570ea996ae7e48ab1b8b971b23c9c73b7f5637b2 + - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@a1cf0ec4aa28705eb7de68cfedb255de6e590433 - octree-creation-app @ git+https://github.com/MiraGeoscience/octree-creation-app.git@02fbd85bf7d54b8f4336f1f0094c1c3e27714e81 - param-sweeps @ git+https://github.com/MiraGeoscience/param-sweeps.git@9ed6091534d638171957a17324e1a1e8f067b434 diff --git a/environments/py-3.12-win-64.conda.lock.yml b/environments/py-3.12-win-64.conda.lock.yml index 4aa7a6d9..166209c4 100644 --- a/environments/py-3.12-win-64.conda.lock.yml +++ b/environments/py-3.12-win-64.conda.lock.yml @@ -1,6 +1,6 @@ # Generated by conda-lock. # platform: win-64 -# input_hash: 2b057dda003b244877434d1dd71bfa18b96472fbaeadeb2cf9c4266efbfdb4e0 +# input_hash: cad8b21157a4bd089f15f4bf7c6585be405714f5ed3e20fc6985dacc023e9965 channels: - conda-forge @@ -14,15 +14,15 @@ dependencies: - brotli-bin=1.1.0=h2466b09_3 - brotli-python=1.1.0=py312h275cf98_3 - bzip2=1.0.8=h2466b09_7 - - ca-certificates=2025.7.14=h4c7d964_0 + - ca-certificates=2025.8.3=h4c7d964_0 - cached-property=1.5.2=hd8ed1ab_1 - cached_property=1.5.2=pyha770c72_1 - - certifi=2025.7.14=pyhd8ed1ab_0 + - certifi=2025.8.3=pyhd8ed1ab_0 - cffi=1.17.1=py312h4389bb4_0 - click=8.2.1=pyh7428d3b_0 - cloudpickle=3.1.1=pyhd8ed1ab_0 - colorama=0.4.6=pyhd8ed1ab_1 - - contourpy=1.3.3=py312hf90b1b7_0 + - contourpy=1.3.3=py312hf90b1b7_1 - cycler=0.12.1=pyhd8ed1ab_1 - cytoolz=1.0.1=py312h4389bb4_0 - dask-core=2025.3.0=pyhd8ed1ab_0 @@ -40,19 +40,18 @@ dependencies: - hpack=4.1.0=pyhd8ed1ab_0 - hyperframe=6.1.0=pyhd8ed1ab_0 - importlib-metadata=8.7.0=pyhe01879c_1 - - intel-openmp=2024.2.1=h57928b3_1083 - jinja2=3.1.6=pyhd8ed1ab_0 - joblib=1.5.1=pyhd8ed1ab_0 - - kiwisolver=1.4.8=py312hf90b1b7_1 + - kiwisolver=1.4.9=py312h78d62e6_0 - krb5=1.21.3=hdf4eb48_0 - lcms2=2.17=hbcf6048_0 - lerc=4.0.0=h6470a55_1 - libaec=1.1.4=h20038f6_0 - - libblas=3.9.0=32_h641d27c_mkl + - libblas=3.9.0=34_h5709861_mkl - libbrotlicommon=1.1.0=h2466b09_3 - libbrotlidec=1.1.0=h2466b09_3 - libbrotlienc=1.1.0=h2466b09_3 - - libcblas=3.9.0=32_h5e41251_mkl + - libcblas=3.9.0=34_h2a3cdd5_mkl - libcurl=8.14.1=h88aaa65_0 - libdeflate=1.24=h76ddb4d_0 - libdlf=0.3.0=pyhd8ed1ab_1 @@ -60,40 +59,40 @@ dependencies: - libffi=3.4.6=h537db12_1 - libfreetype=2.13.3=h57928b3_1 - libfreetype6=2.13.3=h0b5ce68_1 - - libgcc=15.1.0=h1383e82_3 - - libgomp=15.1.0=h1383e82_3 - - libhwloc=2.11.2=default_h88281d1_1002 - - libiconv=1.18=h135ad9c_1 + - libgcc=15.1.0=h1383e82_4 + - libgomp=15.1.0=h1383e82_4 + - libhwloc=2.12.1=default_h88281d1_1000 + - libiconv=1.18=hc1393d2_2 - libjpeg-turbo=3.1.0=h2466b09_0 - - liblapack=3.9.0=32_h1aa476e_mkl + - liblapack=3.9.0=34_hf9ab0e9_mkl - liblzma=5.8.1=h2466b09_2 - libpng=1.6.50=h7351971_1 - libspatialindex=2.0.0=h5a68840_0 - - libsqlite=3.50.3=hf5d6505_1 + - libsqlite=3.50.4=hf5d6505_0 - libssh2=1.11.1=h9aa295b_0 - libtiff=4.7.0=h05922d8_5 - libwebp-base=1.6.0=h4d5522a_0 - libwinpthread=12.0.0.r4.gg4f2fc60ca=h57928b3_9 - libxcb=1.17.0=h0e4246c_0 - - libxml2=2.13.8=h442d1da_0 + - libxml2=2.13.8=h741aa76_1 - libzlib=1.3.1=h2466b09_2 - - llvm-openmp=20.1.8=hfa2b4ca_0 + - llvm-openmp=20.1.8=hfa2b4ca_1 - locket=1.0.0=pyhd8ed1ab_0 - markupsafe=3.0.2=py312h31fea79_1 - matplotlib-base=3.8.4=py312hfee7060_2 - - mkl=2024.2.2=h66d3029_15 + - mkl=2024.2.2=h57928b3_16 - msgpack-python=1.1.1=py312hd5eb7cc_0 - mumps-seq=5.7.3=hbaa6519_10 - munkres=1.1.4=pyhd8ed1ab_1 - numcodecs=0.15.1=py312h72972c8_0 - numpy=1.26.4=py312h8753938_0 - - openjpeg=2.5.3=h4d64b90_0 - - openssl=3.5.1=h725018a_0 + - openjpeg=2.5.3=h24db6dd_1 + - openssl=3.5.2=h725018a_0 - packaging=25.0=pyh29332c3_1 - pandas=2.3.1=py312hc128f0a_0 - partd=1.4.2=pyhd8ed1ab_0 - pillow=10.3.0=py312h381445a_1 - - pip=25.1.1=pyh8b19718_0 + - pip=25.2=pyh8b19718_0 - psutil=7.0.0=py312h4389bb4_0 - pthread-stubs=0.4=h0e40799_1002 - pycparser=2.22=pyh29332c3_1 @@ -111,17 +110,17 @@ dependencies: - pytz=2025.2=pyhd8ed1ab_0 - pyyaml=6.0.2=py312h31fea79_2 - rtree=1.2.0=py312h50e5f8f_1 - - scikit-learn=1.5.2=py312h816cc57_1 + - scikit-learn=1.6.1=py312h816cc57_0 - scipy=1.14.1=py312h337df96_2 - setuptools=80.9.0=pyhff2d567_0 - six=1.17.0=pyhe01879c_1 - sortedcontainers=2.4.0=pyhd8ed1ab_1 - - tbb=2021.13.0=h62715c5_1 + - tbb=2021.13.0=h18a62a1_2 - tblib=3.1.0=pyhd8ed1ab_0 - threadpoolctl=3.6.0=pyhecae5ae_0 - tk=8.6.13=h2c6b04d_2 - toolz=1.0.0=pyhd8ed1ab_1 - - tornado=6.5.1=py312h4389bb4_0 + - tornado=6.5.2=py312he06e257_0 - tqdm=4.67.1=pyhd8ed1ab_1 - trimesh=4.1.8=pyhd8ed1ab_0 - typing-extensions=4.14.1=h4440ef1_0 @@ -147,9 +146,9 @@ dependencies: - zstandard=0.23.0=py312h4389bb4_2 - zstd=1.5.7=hbeecb71_2 - pip: - - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@020de8616b4767a596a4d0f49bce53c8d0c9da5b - - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@d567cc98901ecfa360ff2e93f8a6334a1bed24bc - - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@01a7068fdab7fba8695ad371c9fd9164760a09df + - geoapps-utils @ git+https://github.com/MiraGeoscience/geoapps-utils.git@1dbe97d441d65962a94e071b5c1c27d9facd2050 + - geoh5py @ git+https://github.com/MiraGeoscience/geoh5py.git@570ea996ae7e48ab1b8b971b23c9c73b7f5637b2 + - mira-simpeg @ git+https://github.com/MiraGeoscience/simpeg.git@a1cf0ec4aa28705eb7de68cfedb255de6e590433 - octree-creation-app @ git+https://github.com/MiraGeoscience/octree-creation-app.git@02fbd85bf7d54b8f4336f1f0094c1c3e27714e81 - param-sweeps @ git+https://github.com/MiraGeoscience/param-sweeps.git@9ed6091534d638171957a17324e1a1e8f067b434 diff --git a/py-3.10.conda-lock.yml b/py-3.10.conda-lock.yml index 76946fd2..8c0d5231 100644 --- a/py-3.10.conda-lock.yml +++ b/py-3.10.conda-lock.yml @@ -15,8 +15,8 @@ version: 1 metadata: content_hash: - win-64: 12cc832b6afad224ba7a18f42ebe117e16cedc70424e95b2c7e3894be647d2bf - linux-64: 7b2bb2835665234d0ef442f0e4a4c9717b61f9a50ae298c50cf9cae2e9369ece + win-64: 5babf042397838038a28ac78c72c28e9b56b16d89d92d69d08e0421c96c8624b + linux-64: aa70c6c517bbe8472b7de3ce4e8d391ca7e1d86e6bfe0e2a4e53e756c6e8388b channels: - url: conda-forge used_env_vars: [] @@ -131,7 +131,7 @@ package: category: main optional: false - name: anyio - version: 4.9.0 + version: 4.10.0 manager: conda platform: linux-64 dependencies: @@ -140,14 +140,14 @@ package: python: '' sniffio: '>=1.1' typing_extensions: '>=4.5' - url: https://repo.prefix.dev/conda-forge/noarch/anyio-4.9.0-pyh29332c3_0.conda + url: https://repo.prefix.dev/conda-forge/noarch/anyio-4.10.0-pyhe01879c_0.conda hash: - md5: 9749a2c77a7c40d432ea0927662d7e52 - sha256: b28e0f78bb0c7962630001e63af25a89224ff504e135a02e50d4d80b6155d386 + md5: cc2613bfa71dec0eb2113ee21ac9ccbf + sha256: d1b50686672ebe7041e44811eda563e45b94a8354db67eca659040392ac74d63 category: dev optional: true - name: anyio - version: 4.9.0 + version: 4.10.0 manager: conda platform: win-64 dependencies: @@ -156,10 +156,10 @@ package: python: '>=3.9' sniffio: '>=1.1' typing_extensions: '>=4.5' - url: https://repo.prefix.dev/conda-forge/noarch/anyio-4.9.0-pyh29332c3_0.conda + url: https://repo.prefix.dev/conda-forge/noarch/anyio-4.10.0-pyhe01879c_0.conda hash: - md5: 9749a2c77a7c40d432ea0927662d7e52 - sha256: b28e0f78bb0c7962630001e63af25a89224ff504e135a02e50d4d80b6155d386 + md5: cc2613bfa71dec0eb2113ee21ac9ccbf + sha256: d1b50686672ebe7041e44811eda563e45b94a8354db67eca659040392ac74d63 category: dev optional: true - name: argon2-cffi @@ -191,23 +191,23 @@ package: category: dev optional: true - name: argon2-cffi-bindings - version: 21.2.0 + version: 25.1.0 manager: conda platform: linux-64 dependencies: __glibc: '>=2.17,<3.0.a0' cffi: '>=1.0.1' - libgcc: '>=13' + libgcc: '>=14' python: '>=3.10,<3.11.0a0' python_abi: 3.10.* - url: https://repo.prefix.dev/conda-forge/linux-64/argon2-cffi-bindings-21.2.0-py310ha75aee5_5.conda + url: https://repo.prefix.dev/conda-forge/linux-64/argon2-cffi-bindings-25.1.0-py310h7c4b9e2_0.conda hash: - md5: a2da54f3a705d518c95a5b6de8ad8af6 - sha256: 1050f55294476b4d9b36ca3cf22b47f2f23d6e143ad6a177025bc5e5984d5409 + md5: 3fd41ccdb9263ad51cf89b05cade6fb7 + sha256: 8abeddb7d7ae1838febc154970d514714542c3701f7de9203b3a81d06c307022 category: dev optional: true - 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name: geoapps-utils @@ -8573,12 +8547,12 @@ package: numpy: '>=1.26.0,<1.27.0' pydantic: '>=2.5.2,<3.0.0' scipy: '>=1.14.0,<1.15.0' - url: git+https://github.com/MiraGeoscience/geoapps-utils.git@020de8616b4767a596a4d0f49bce53c8d0c9da5b + url: git+https://github.com/MiraGeoscience/geoapps-utils.git@1dbe97d441d65962a94e071b5c1c27d9facd2050 hash: - sha256: 020de8616b4767a596a4d0f49bce53c8d0c9da5b + sha256: 1dbe97d441d65962a94e071b5c1c27d9facd2050 source: type: url - url: git+https://github.com/MiraGeoscience/geoapps-utils.git@020de8616b4767a596a4d0f49bce53c8d0c9da5b + url: git+https://github.com/MiraGeoscience/geoapps-utils.git@1dbe97d441d65962a94e071b5c1c27d9facd2050 category: main optional: false - name: geoh5py @@ -8590,12 +8564,12 @@ package: numpy: '>=1.26.0,<1.27.0' pillow: '>=10.3.0,<10.4.0' pydantic: '>=2.5.2,<3.0.0' - url: git+https://github.com/MiraGeoscience/geoh5py.git@d567cc98901ecfa360ff2e93f8a6334a1bed24bc + url: git+https://github.com/MiraGeoscience/geoh5py.git@570ea996ae7e48ab1b8b971b23c9c73b7f5637b2 hash: - 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name: geoapps-utils @@ -8658,12 +8632,12 @@ package: numpy: '>=1.26.0,<1.27.0' pydantic: '>=2.5.2,<3.0.0' scipy: '>=1.14.0,<1.15.0' - url: git+https://github.com/MiraGeoscience/geoapps-utils.git@020de8616b4767a596a4d0f49bce53c8d0c9da5b + url: git+https://github.com/MiraGeoscience/geoapps-utils.git@1dbe97d441d65962a94e071b5c1c27d9facd2050 hash: - sha256: 020de8616b4767a596a4d0f49bce53c8d0c9da5b + sha256: 1dbe97d441d65962a94e071b5c1c27d9facd2050 source: type: url - url: git+https://github.com/MiraGeoscience/geoapps-utils.git@020de8616b4767a596a4d0f49bce53c8d0c9da5b + url: git+https://github.com/MiraGeoscience/geoapps-utils.git@1dbe97d441d65962a94e071b5c1c27d9facd2050 category: main optional: false - name: geoh5py @@ -8675,12 +8649,12 @@ package: numpy: '>=1.26.0,<1.27.0' pillow: '>=10.3.0,<10.4.0' pydantic: '>=2.5.2,<3.0.0' - url: git+https://github.com/MiraGeoscience/geoh5py.git@d567cc98901ecfa360ff2e93f8a6334a1bed24bc + url: git+https://github.com/MiraGeoscience/geoh5py.git@570ea996ae7e48ab1b8b971b23c9c73b7f5637b2 hash: - 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url: git+https://github.com/MiraGeoscience/simpeg.git@01a7068fdab7fba8695ad371c9fd9164760a09df + url: git+https://github.com/MiraGeoscience/simpeg.git@a1cf0ec4aa28705eb7de68cfedb255de6e590433 hash: - sha256: 01a7068fdab7fba8695ad371c9fd9164760a09df + sha256: a1cf0ec4aa28705eb7de68cfedb255de6e590433 source: type: url - url: git+https://github.com/MiraGeoscience/simpeg.git@01a7068fdab7fba8695ad371c9fd9164760a09df + url: git+https://github.com/MiraGeoscience/simpeg.git@a1cf0ec4aa28705eb7de68cfedb255de6e590433 category: main optional: false - name: octree-creation-app diff --git a/py-3.12.conda-lock.yml b/py-3.12.conda-lock.yml index bfc95630..1beea778 100644 --- a/py-3.12.conda-lock.yml +++ b/py-3.12.conda-lock.yml @@ -15,8 +15,8 @@ version: 1 metadata: content_hash: - win-64: 2b057dda003b244877434d1dd71bfa18b96472fbaeadeb2cf9c4266efbfdb4e0 - linux-64: 0411d0bb5b468d1fb923a36f5fc20b1e4f1af3a872d37f6492e422e64a4e5142 + win-64: cad8b21157a4bd089f15f4bf7c6585be405714f5ed3e20fc6985dacc023e9965 + linux-64: 2e48ea762f31ce7d0e20196680dec38b885bd725bb1dc73d18f428e1faa16c06 channels: - 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name: tornado - version: 6.5.1 + version: 6.5.2 manager: conda platform: linux-64 dependencies: __glibc: '>=2.17,<3.0.a0' - libgcc: '>=13' + libgcc: '>=14' python: '>=3.12,<3.13.0a0' python_abi: 3.12.* - url: https://repo.prefix.dev/conda-forge/linux-64/tornado-6.5.1-py312h66e93f0_0.conda + url: https://repo.prefix.dev/conda-forge/linux-64/tornado-6.5.2-py312h4c3975b_0.conda hash: - md5: c532a6ee766bed75c4fa0c39e959d132 - sha256: c96be4c8bca2431d7ad7379bad94ed6d4d25cd725ae345540a531d9e26e148c9 + md5: 82dacd4832dcde0c2b7888248a3b3d7c + sha256: 891965f8e495ad5cef399db03a13df48df7add06ae131f4b77a88749c74b2060 category: main optional: false - name: tornado - version: 6.5.1 + version: 6.5.2 manager: conda platform: win-64 dependencies: python: '>=3.12,<3.13.0a0' python_abi: 3.12.* ucrt: '>=10.0.20348.0' - vc: '>=14.2,<15' - vc14_runtime: '>=14.29.30139' - url: https://repo.prefix.dev/conda-forge/win-64/tornado-6.5.1-py312h4389bb4_0.conda + vc: '>=14.3,<15' + vc14_runtime: '>=14.44.35208' + url: https://repo.prefix.dev/conda-forge/win-64/tornado-6.5.2-py312he06e257_0.conda hash: - 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url: https://repo.prefix.dev/conda-forge/noarch/types-python-dateutil-2.9.0.20250708-pyhd8ed1ab_0.conda + url: https://repo.prefix.dev/conda-forge/noarch/types-python-dateutil-2.9.0.20250809-pyhd8ed1ab_0.conda hash: - md5: b6d4c200582ead6427f49a189e2c6d65 - sha256: 843bbc8e763a96b2b4ea568cf7918b6027853d03b5d8810ab77aaa9af472a6e2 + md5: 63a644e158c4f8eeca0d1290ac25e0cc + sha256: e54a82e474f4f4b6988c6c7186e5def628c840fca81f5d103e9f78f01d5fead1 category: dev optional: true - name: typing-extensions @@ -8641,12 +8615,12 @@ package: numpy: '>=1.26.0,<1.27.0' pydantic: '>=2.5.2,<3.0.0' scipy: '>=1.14.0,<1.15.0' - url: git+https://github.com/MiraGeoscience/geoapps-utils.git@020de8616b4767a596a4d0f49bce53c8d0c9da5b + url: git+https://github.com/MiraGeoscience/geoapps-utils.git@1dbe97d441d65962a94e071b5c1c27d9facd2050 hash: - sha256: 020de8616b4767a596a4d0f49bce53c8d0c9da5b + sha256: 1dbe97d441d65962a94e071b5c1c27d9facd2050 source: type: url - url: git+https://github.com/MiraGeoscience/geoapps-utils.git@020de8616b4767a596a4d0f49bce53c8d0c9da5b + url: git+https://github.com/MiraGeoscience/geoapps-utils.git@1dbe97d441d65962a94e071b5c1c27d9facd2050 category: main optional: false - name: geoapps-utils @@ -8658,12 +8632,12 @@ package: numpy: '>=1.26.0,<1.27.0' pydantic: '>=2.5.2,<3.0.0' scipy: '>=1.14.0,<1.15.0' - url: git+https://github.com/MiraGeoscience/geoapps-utils.git@020de8616b4767a596a4d0f49bce53c8d0c9da5b + url: git+https://github.com/MiraGeoscience/geoapps-utils.git@1dbe97d441d65962a94e071b5c1c27d9facd2050 hash: - sha256: 020de8616b4767a596a4d0f49bce53c8d0c9da5b + sha256: 1dbe97d441d65962a94e071b5c1c27d9facd2050 source: type: url - url: git+https://github.com/MiraGeoscience/geoapps-utils.git@020de8616b4767a596a4d0f49bce53c8d0c9da5b + url: git+https://github.com/MiraGeoscience/geoapps-utils.git@1dbe97d441d65962a94e071b5c1c27d9facd2050 category: main optional: false - name: geoh5py @@ -8675,12 +8649,12 @@ package: numpy: '>=1.26.0,<1.27.0' pillow: '>=10.3.0,<10.4.0' pydantic: '>=2.5.2,<3.0.0' - url: git+https://github.com/MiraGeoscience/geoh5py.git@d567cc98901ecfa360ff2e93f8a6334a1bed24bc + url: git+https://github.com/MiraGeoscience/geoh5py.git@570ea996ae7e48ab1b8b971b23c9c73b7f5637b2 hash: - sha256: d567cc98901ecfa360ff2e93f8a6334a1bed24bc + sha256: 570ea996ae7e48ab1b8b971b23c9c73b7f5637b2 source: type: url - url: git+https://github.com/MiraGeoscience/geoh5py.git@d567cc98901ecfa360ff2e93f8a6334a1bed24bc + url: git+https://github.com/MiraGeoscience/geoh5py.git@570ea996ae7e48ab1b8b971b23c9c73b7f5637b2 category: main optional: false - name: geoh5py @@ -8692,16 +8666,16 @@ package: numpy: '>=1.26.0,<1.27.0' pillow: '>=10.3.0,<10.4.0' pydantic: '>=2.5.2,<3.0.0' - url: git+https://github.com/MiraGeoscience/geoh5py.git@d567cc98901ecfa360ff2e93f8a6334a1bed24bc + url: git+https://github.com/MiraGeoscience/geoh5py.git@570ea996ae7e48ab1b8b971b23c9c73b7f5637b2 hash: - sha256: d567cc98901ecfa360ff2e93f8a6334a1bed24bc + sha256: 570ea996ae7e48ab1b8b971b23c9c73b7f5637b2 source: type: url - url: git+https://github.com/MiraGeoscience/geoh5py.git@d567cc98901ecfa360ff2e93f8a6334a1bed24bc + url: git+https://github.com/MiraGeoscience/geoh5py.git@570ea996ae7e48ab1b8b971b23c9c73b7f5637b2 category: main optional: false - name: mira-simpeg - version: 0.23.0.1a5.dev45+g01a7068fd + version: 0.23.0.1.post2.dev38+mira.ga1cf0ec4a manager: pip platform: linux-64 dependencies: @@ -8713,16 +8687,16 @@ package: numpy: '>=1.22' pymatsolver: '>=0.3' scipy: '>=1.8' - url: git+https://github.com/MiraGeoscience/simpeg.git@01a7068fdab7fba8695ad371c9fd9164760a09df + url: git+https://github.com/MiraGeoscience/simpeg.git@a1cf0ec4aa28705eb7de68cfedb255de6e590433 hash: - sha256: 01a7068fdab7fba8695ad371c9fd9164760a09df + sha256: a1cf0ec4aa28705eb7de68cfedb255de6e590433 source: type: url - url: git+https://github.com/MiraGeoscience/simpeg.git@01a7068fdab7fba8695ad371c9fd9164760a09df + url: git+https://github.com/MiraGeoscience/simpeg.git@a1cf0ec4aa28705eb7de68cfedb255de6e590433 category: main optional: false - name: mira-simpeg - version: 0.23.0.1a5.dev45+g01a7068fd + version: 0.23.0.1.post2.dev38+mira.ga1cf0ec4a manager: pip platform: win-64 dependencies: @@ -8734,12 +8708,12 @@ package: numpy: '>=1.22' pymatsolver: '>=0.3' scipy: '>=1.8' - url: git+https://github.com/MiraGeoscience/simpeg.git@01a7068fdab7fba8695ad371c9fd9164760a09df + url: git+https://github.com/MiraGeoscience/simpeg.git@a1cf0ec4aa28705eb7de68cfedb255de6e590433 hash: - sha256: 01a7068fdab7fba8695ad371c9fd9164760a09df + sha256: a1cf0ec4aa28705eb7de68cfedb255de6e590433 source: type: url - url: git+https://github.com/MiraGeoscience/simpeg.git@01a7068fdab7fba8695ad371c9fd9164760a09df + url: git+https://github.com/MiraGeoscience/simpeg.git@a1cf0ec4aa28705eb7de68cfedb255de6e590433 category: main optional: false - name: octree-creation-app From 28445f1f5beca6e0fb0a185a71a18cc160b6824b Mon Sep 17 00:00:00 2001 From: dominiquef Date: Mon, 11 Aug 2025 11:00:41 -0700 Subject: [PATCH 9/9] Add authors --- docs/case_studies/Forrestania/forrestania.ipynb | 8 ++++++++ docs/case_studies/Forrestania/open_code.ipynb | 2 +- .../Forrestania/python_code/joint_grav_mag.ipynb | 7 +++++++ .../python_code/unconstrained_gravity_inv_training.ipynb | 8 ++++++++ .../unconstrained_magnetics_inv_training.ipynb | 7 +++++++ 5 files changed, 31 insertions(+), 1 deletion(-) diff --git a/docs/case_studies/Forrestania/forrestania.ipynb b/docs/case_studies/Forrestania/forrestania.ipynb index b46d457a..42f420ed 100644 --- a/docs/case_studies/Forrestania/forrestania.ipynb +++ b/docs/case_studies/Forrestania/forrestania.ipynb @@ -29,6 +29,14 @@ "\n", "- [Gravity](gravity-code)\n", "- [Magnetics](magnetics-code)\n", + "```\n", + "\n", + "```{table}\n", + "| **Authors** | |\n", + "| :--- | :--- |\n", + "| [Glenn Pears](https://www.mirageoscience.com/consulting-services/geological-consultants-and-geophysical-consultants/#gp) | glennp@mirageoscience.com |\n", + "| [Polyanna Rowe](https://github.com/polyye) | polyannar@mirageoscience.com |\n", + "| [Dominique Fournier](https://github.com/domfournier) | dominiquef@mirageoscience.com |\n", "```" ] }, diff --git a/docs/case_studies/Forrestania/open_code.ipynb b/docs/case_studies/Forrestania/open_code.ipynb index d0c1ad6d..fbfdae81 100644 --- a/docs/case_studies/Forrestania/open_code.ipynb +++ b/docs/case_studies/Forrestania/open_code.ipynb @@ -14,7 +14,7 @@ "---\n", "```\n", "\n", - "This section demonstrates the processing and inversion of the Forrestania datasets using purely open-source packages. For an equivalent and streamlined version, see the parent [Forrestania](#Forrestania) case study.\n", + "This section demonstrates the processing and inversion of the Forrestania datasets using purely open-source packages. For an equivalent and streamlined version, see the parent [Forrestania](forrestania-main) case study.\n", "\n", "- [Gravity inversion](gravity-code)\n", "- [Magnetics inversion](magnetics-code)\n", diff --git a/docs/case_studies/Forrestania/python_code/joint_grav_mag.ipynb b/docs/case_studies/Forrestania/python_code/joint_grav_mag.ipynb index 22612194..0545cd65 100644 --- a/docs/case_studies/Forrestania/python_code/joint_grav_mag.ipynb +++ b/docs/case_studies/Forrestania/python_code/joint_grav_mag.ipynb @@ -35,6 +35,13 @@ "> This workflow closely follows the methodology and structure of the official [SimPEG Tutorials](https://simpeg.xyz/user-tutorials/).\n", "\n", "```{figure} ../images/open_code.png\n", + "```\n", + "\n", + "```{table}\n", + "| **Authors** | |\n", + "| :--- | :--- |\n", + "| [Polyanna Rowe](https://github.com/polyye) | polyannar@mirageoscience.com |\n", + "| [Dominique Fournier](https://github.com/domfournier) | dominiquef@mirageoscience.com |\n", "```" ] }, diff --git a/docs/case_studies/Forrestania/python_code/unconstrained_gravity_inv_training.ipynb b/docs/case_studies/Forrestania/python_code/unconstrained_gravity_inv_training.ipynb index 073d96cf..547c2425 100644 --- a/docs/case_studies/Forrestania/python_code/unconstrained_gravity_inv_training.ipynb +++ b/docs/case_studies/Forrestania/python_code/unconstrained_gravity_inv_training.ipynb @@ -21,6 +21,14 @@ "---\n", "name: Landing Image\n", "---\n", + "```\n", + "\n", + "\n", + "```{table}\n", + "| **Authors** | |\n", + "| :--- | :--- |\n", + "| [Polyanna Rowe](https://github.com/polyye) | polyannar@mirageoscience.com |\n", + "| [Dominique Fournier](https://github.com/domfournier) | dominiquef@mirageoscience.com |\n", "```" ] }, diff --git a/docs/case_studies/Forrestania/python_code/unconstrained_magnetics_inv_training.ipynb b/docs/case_studies/Forrestania/python_code/unconstrained_magnetics_inv_training.ipynb index 91011447..198cdb3f 100644 --- a/docs/case_studies/Forrestania/python_code/unconstrained_magnetics_inv_training.ipynb +++ b/docs/case_studies/Forrestania/python_code/unconstrained_magnetics_inv_training.ipynb @@ -22,6 +22,13 @@ "---\n", "name: Landing Image\n", "---\n", + "```\n", + "\n", + "```{table}\n", + "| **Authors** | |\n", + "| :--- | :--- |\n", + "| [Polyanna Rowe](https://github.com/polyye) | polyannar@mirageoscience.com |\n", + "| [Dominique Fournier](https://github.com/domfournier) | dominiquef@mirageoscience.com |\n", "```" ] },