tests for pruneOutsideBox

Author: theRealSuperMario

test/test_cleanfigure.py

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+import pytest
+from tikzplotlib import cleanfigure
+import numpy as np
+from matplotlib import pyplot as plt
+
+RC_PARAMS = {"figure.figsize": [5, 5], "figure.dpi": 220, "pgf.rcfonts": False}
+
+
+def test_pruneOutsideBox():
+    """test against matlab2tikz implementation
+
+    octave code to generate baseline results. Note that octave has indexing 1...N, whereas python has indexing 0...N-1.
+    ```octave
+        x = linspace(1, 100, 20);
+        y1 = linspace(1, 100, 20);
+
+        figure
+        plot(x, y1)
+        xlim([20, 80])
+        ylim([20, 80])    
+        cleanfigure;
+    ```
+    """
+    x = np.linspace(1, 100, 20)
+    y = np.linspace(1, 100, 20)
+
+    with plt.rc_context(rc=RC_PARAMS):
+        fig, ax = plt.subplots(1, 1, figsize=(5, 5))
+        (l,) = ax.plot(x, y)
+        ax.set_ylim([20, 80])
+        ax.set_xlim([20, 80])
+        cleanfigure.pruneOutsideBox(fig, ax, l)
+        plt.show()
+
+
+def test_replaceDataWithNaN():
+    """test against matlab2tikz implementation
+
+    octave code to generate baseline results. Note that octave has indexing 1...N, whereas python has indexing 0...N-1.
+    ```octave
+        x = linspace(1, 100, 20);
+        y1 = linspace(1, 100, 20);
+
+        figure
+        plot(x, y1)
+        xlim([20, 80])
+        ylim([20, 80])    
+        cleanfigure;
+    ```
+    """
+    id_replace = np.array([0, 16])
+    data = np.stack([np.linspace(1, 100, 20)] * 2, axis=1)
+
+    newdata = cleanfigure.replaceDataWithNaN(data, id_replace)
+    assert newdata.shape == data.shape
+    assert np.any(np.isnan(newdata))
+
+
+def test_removeData():
+    """test against matlab2tikz implementation
+
+    octave code to generate baseline results. Note that octave has indexing 1...N, whereas python has indexing 0...N-1.
+    ```octave
+        x = linspace(1, 100, 20);
+        y1 = linspace(1, 100, 20);
+
+        figure
+        plot(x, y1)
+        xlim([20, 80])
+        ylim([20, 80])    
+        cleanfigure;
+    ```
+    """
+    id_remove = np.array([1, 2, 3, 17, 18, 19])
+    data = np.stack([np.linspace(1, 100, 20)] * 2, axis=1)
+
+    newdata = cleanfigure.removeData(data, id_remove)
+    assert newdata.shape == (14, 2)
+
+
+def test_removeNaNs():
+    """test against matlab2tikz implementation
+
+    octave code to generate baseline results. Note that octave has indexing 1...N, whereas python has indexing 0...N-1.
+    ```octave
+        x = linspace(1, 100, 20);
+        y1 = linspace(1, 100, 20);
+
+        figure
+        plot(x, y1)
+        xlim([20, 80])
+        ylim([20, 80])    
+        cleanfigure;
+    ```
+    """
+    id_replace = np.array([0, 16])
+    id_remove = np.array([1, 2, 3, 17, 18, 19])
+    data = np.stack([np.linspace(1, 100, 20)] * 2, axis=1)
+    newdata = cleanfigure.replaceDataWithNaN(data, id_replace)
+    newdata = cleanfigure.removeData(newdata, id_remove)
+    newdata = cleanfigure.removeNaNs(newdata)
+    assert not np.any(np.isnan(newdata))
+    assert newdata.shape == (12, 2)
+
+
+def test_isInBox():
+    """octave code to generate baseline results
+
+
+        ```octave
+            x = 1:10;
+            y = 1:10;
+            data = [x', y'];
+            xlim = [3, 7];
+            ylim = [3, 7];
+            mask = isInBox(data, xlim, ylim)
+        ```
+    """
+    x = np.linspace(1, 100, 20)
+    y = np.linspace(1, 100, 20)
+    data = np.stack([x, y], axis=1)
+    xLim = np.array([20, 80])
+    yLim = np.array([20, 80])
+    tol = 1.0e-10
+    relaxedXLim = xLim + np.array([-tol, tol])
+    relaxedYLim = yLim + np.array([-tol, tol])
+    mask = cleanfigure.isInBox(data, relaxedXLim, relaxedYLim)
+    assert int(np.sum(mask)) == 12
+
+
+def test_getVisualLimits():
+    x = np.linspace(1, 100, 20)
+    y = np.linspace(1, 100, 20)
+
+    with plt.rc_context(rc=RC_PARAMS):
+        fig, ax = plt.subplots(1, 1, figsize=(5, 5))
+        (l,) = ax.plot(x, y)
+        ax.set_xlim([20, 80])
+        ax.set_ylim([20, 80])
+        xLim, yLim = cleanfigure.getVisualLimits(fig, ax)
+        assert np.allclose(xLim, np.array([20, 80]))
+        assert np.allclose(yLim, np.array([20, 80]))
+
+
+def test_interactiveManipulation():
+    """Create a plot, then remove some data, and see if the graph is updated
+    """
+    x = np.linspace(1, 100, 20)
+    y = np.linspace(1, 100, 20)
+    id_remove = np.arange(0, 10)
+
+    with plt.rc_context(rc=RC_PARAMS):
+        fig, ax = plt.subplots(1, 1, figsize=(5, 5))
+        (l,) = ax.plot(x, y)
+        xData, yData = cleanfigure.getVisualData(ax, l)
+        data = np.stack([xData, yData], axis=1)
+        data = cleanfigure.removeData(data, id_remove)
+        l.set_xdata(data[:, 0])
+        l.set_ydata(data[:, 1])
+        plt.show()
+