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| 1 | +# -*- coding: utf-8 -*- |
| 2 | +# |
| 3 | +# Licensed under the terms of the BSD 3-Clause |
| 4 | +# (see plotpy/LICENSE for details) |
| 5 | + |
| 6 | +"""Regression tests for cached log10 data refresh in ``ImageItem.set_data``. |
| 7 | +
|
| 8 | +When the Z-axis is in logarithmic scale, ``ImageItem`` keeps a cached |
| 9 | +``_log_data`` array. Prior to the fix, calling ``set_data`` did not refresh |
| 10 | +that cache, so the displayed image kept reflecting the previous values until |
| 11 | +the user toggled the log scale off and on again. |
| 12 | +""" |
| 13 | + |
| 14 | +from __future__ import annotations |
| 15 | + |
| 16 | +import numpy as np |
| 17 | +from guidata.qthelpers import qt_app_context |
| 18 | + |
| 19 | +from plotpy.builder import make |
| 20 | + |
| 21 | + |
| 22 | +def _make_item(data: np.ndarray): |
| 23 | + """Return an ``ImageItem`` ready for log-scale tests.""" |
| 24 | + return make.image(data, interpolation="nearest") |
| 25 | + |
| 26 | + |
| 27 | +def test_set_data_refreshes_log_data_when_log_scale_enabled() -> None: |
| 28 | + """``set_data`` must recompute ``_log_data`` when log scale is active.""" |
| 29 | + with qt_app_context(exec_loop=False): |
| 30 | + first = np.array([[1.0, 10.0], [100.0, 1000.0]]) |
| 31 | + item = _make_item(first) |
| 32 | + item.set_zaxis_log_state(True) |
| 33 | + np.testing.assert_array_almost_equal(item._log_data, np.log10(first.clip(1))) |
| 34 | + |
| 35 | + second = np.array([[10.0, 100.0], [1000.0, 10000.0]]) |
| 36 | + item.set_data(second) |
| 37 | + |
| 38 | + # The cache must reflect the new data, not the previous one. |
| 39 | + np.testing.assert_array_almost_equal(item._log_data, np.log10(second.clip(1))) |
| 40 | + # And the LUT range must be derived from the refreshed log data. |
| 41 | + lut_min, lut_max = item.get_lut_range() |
| 42 | + assert lut_min == np.log10(second.clip(1)).min() |
| 43 | + assert lut_max == np.log10(second.clip(1)).max() |
| 44 | + |
| 45 | + |
| 46 | +def test_set_data_keeps_lut_range_in_log_mode() -> None: |
| 47 | + """``keep_lut_range`` must be honored even when log scale is active.""" |
| 48 | + with qt_app_context(exec_loop=False): |
| 49 | + first = np.array([[1.0, 10.0], [100.0, 1000.0]]) |
| 50 | + item = _make_item(first) |
| 51 | + item.set_zaxis_log_state(True) |
| 52 | + item.set_lut_range((0.5, 2.5)) |
| 53 | + item.param.keep_lut_range = True |
| 54 | + |
| 55 | + second = np.array([[10.0, 100.0], [1000.0, 10000.0]]) |
| 56 | + item.set_data(second) |
| 57 | + |
| 58 | + # Cache must still be refreshed (display correctness)… |
| 59 | + np.testing.assert_array_almost_equal(item._log_data, np.log10(second.clip(1))) |
| 60 | + # …but the LUT range must remain frozen as requested by the user. |
| 61 | + assert item.get_lut_range() == (0.5, 2.5) |
| 62 | + |
| 63 | + |
| 64 | +def test_set_data_does_not_create_log_data_when_log_scale_disabled() -> None: |
| 65 | + """When log scale is off, ``set_data`` must not create ``_log_data``.""" |
| 66 | + with qt_app_context(exec_loop=False): |
| 67 | + item = _make_item(np.array([[1.0, 2.0], [3.0, 4.0]])) |
| 68 | + assert item._log_data is None |
| 69 | + item.set_data(np.array([[5.0, 6.0], [7.0, 8.0]])) |
| 70 | + assert item._log_data is None |
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