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theRealSuperMariotheRealSuperMario
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simplified testing
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‎test/test_cleanfigure.py

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@@ -77,182 +77,6 @@ def test_pruneOutsideBox3D(self):
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plt.close("all")
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def test_replaceDataWithNaN():
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"""test against matlab2tikz implementation.
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octave code to generate baseline results.
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Note that octave has indexing 1...N, whereas python has indexing 0...N-1.
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```octave
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x = linspace(1, 100, 20);
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y1 = linspace(1, 100, 20);
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figure
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plot(x, y1)
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xlim([20, 80])
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ylim([20, 80])
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cleanfigure;
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```
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"""
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id_replace = np.array([0, 16])
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xData = np.linspace(1, 100, 20)
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yData = xData.copy()
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data = np.stack([xData, yData], axis=1)
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newdata = cleanfigure._replace_data_with_NaN(data, id_replace, False)
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assert newdata.shape == data.shape
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assert np.any(np.isnan(newdata))
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def test_removeData():
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"""test against matlab2tikz implementation.
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octave code to generate baseline results.
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Note that octave has indexing 1...N, whereas python has indexing 0...N-1.
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```octave
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x = linspace(1, 100, 20);
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y1 = linspace(1, 100, 20);
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figure
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plot(x, y1)
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xlim([20, 80])
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ylim([20, 80])
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cleanfigure;
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```
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"""
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id_remove = np.array([1, 2, 3, 17, 18, 19])
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xData = np.linspace(1, 100, 20)
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yData = xData.copy()
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data = np.stack([xData, yData], axis=1)
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newdata = cleanfigure._remove_data(data, id_remove, False)
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assert newdata.shape == (14, 2)
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def test_removeNaNs():
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"""test against matlab2tikz implementation
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octave code to generate baseline results. Note that octave has indexing 1...N, whereas python has indexing 0...N-1.
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```octave
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x = linspace(1, 100, 20);
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y1 = linspace(1, 100, 20);
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figure
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plot(x, y1)
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xlim([20, 80])
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ylim([20, 80])
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cleanfigure;
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```
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"""
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id_replace = np.array([0, 16])
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id_remove = np.array([1, 2, 3, 17, 18, 19])
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xData = np.linspace(1, 100, 20)
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yData = xData.copy()
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data = cleanfigure._stack_data_2D(xData, yData)
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data = cleanfigure._replace_data_with_NaN(data, id_replace, False)
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data = cleanfigure._remove_data(data, id_remove, False)
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data = cleanfigure._remove_NaNs(data)
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assert not np.any(np.isnan(data))
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assert data.shape == (12, 2)
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def test_isInBox():
160-
"""octave code to generate baseline results
161-
162-
```octave
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x = 1:10;
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y = 1:10;
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data = [x', y'];
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xlim = [3, 7];
167-
ylim = [3, 7];
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mask = isInBox(data, xlim, ylim)
169-
```
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"""
171-
x = np.linspace(1, 100, 20)
172-
y = np.linspace(1, 100, 20)
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data = np.stack([x, y], axis=1)
174-
xLim = np.array([20, 80])
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yLim = np.array([20, 80])
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tol = 1.0e-10
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relaxedXLim = xLim + np.array([-tol, tol])
178-
relaxedYLim = yLim + np.array([-tol, tol])
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mask = cleanfigure._isInBox(data, relaxedXLim, relaxedYLim)
180-
assert int(np.sum(mask)) == 12
181-
182-
183-
def test_getVisualLimits():
184-
"""octave code
185-
```octave
186-
addpath ("../matlab2tikz/src")
187-
188-
x = linspace(1, 100, 20);
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y1 = linspace(1, 100, 20);
190-
191-
figure
192-
plot(x, y1)
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xlim([20, 80])
194-
ylim([20, 80])
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set(gcf,'Units','Inches');
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set(gcf,'Position',[2.5 2.5 5 5])
197-
cleanfigure;
198-
```
199-
"""
200-
x = np.linspace(1, 100, 20)
201-
y = np.linspace(1, 100, 20)
202-
203-
with plt.rc_context(rc=RC_PARAMS):
204-
fig, ax = plt.subplots(1, 1, figsize=(5, 5))
205-
(l,) = ax.plot(x, y)
206-
ax.set_xlim([20, 80])
207-
ax.set_ylim([20, 80])
208-
xLim, yLim = cleanfigure._get_visual_limits(fig, ax)
209-
assert np.allclose(xLim, np.array([20, 80]))
210-
assert np.allclose(yLim, np.array([20, 80]))
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plt.close("all")
212-
213-
214-
def test_opheimSimplify():
215-
"""test path simplification
216-
217-
octave code
218-
```octave
219-
addpath ("../matlab2tikz/src")
220-
221-
x = linspace(1, 100, 20);
222-
y1 = linspace(1, 100, 20);
223-
224-
figure
225-
plot(x, y1)
226-
xlim([20, 80])
227-
ylim([20, 80])
228-
set(gcf,'Units','Inches');
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set(gcf,'Position',[2.5 2.5 5 5])
230-
cleanfigure;
231-
```
232-
"""
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x = np.array(
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[
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21.842106,
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27.052631,
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32.263157,
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37.473682,
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42.68421,
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47.894737,
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53.105263,
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58.31579,
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63.526318,
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68.73684,
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73.947365,
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79.1579,
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]
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)
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y = x.copy()
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tol = 0.02
251-
mask = cleanfigure._opheim_simplify(x, y, tol)
252-
assert mask.shape == (12,)
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assert np.allclose(mask * 1, np.array([1] + [0] * 10 + [1]))
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25680
@pytest.mark.parametrize(
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"function, result", [("plot", False), ("step", True)],
25882
)
@@ -797,136 +621,6 @@ def test_subplot(self):
797621
plt.close("all")
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799623

800-
def test_segmentVisible():
801-
"""test against matlab2tikz implementation
802-
803-
octave code to generate baseline results. Note that octave has indexing 1...N, whereas python has indexing 0...N-1.
804-
```octave
805-
x = linspace(1, 100, 20);
806-
y1 = linspace(1, 100, 20);
807-
808-
figure
809-
plot(x, y1)
810-
xlim([20, 80])
811-
ylim([20, 80])
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cleanfigure;
813-
```
814-
"""
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816-
y = np.linspace(1, 100, 20)
817-
x = y.copy()
818-
data = np.stack([x, y], axis=1)
819-
dataIsInBox = np.array([0] * 4 + [1] * 12 + [0] * 4) == 1
820-
xLim = np.array([20, 80])
821-
yLim = np.array([20, 80])
822-
mask = cleanfigure._segment_visible(data, dataIsInBox, xLim, yLim)
823-
assert np.allclose(mask * 1, np.array([0] * 3 + [1] * 13 + [0] * 3))
824-
825-
826-
def test_crossLines():
827-
"""test against matplotlib2tikz implementation"""
828-
y = np.linspace(1, 100, 20)
829-
x = y.copy()
830-
data = np.stack([x, y], axis=1)
831-
X1 = data[:-1, :]
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X2 = data[1:, :]
833-
X3 = np.array([80, 20])
834-
X4 = np.array([80, 80])
835-
Lambda = cleanfigure._cross_lines(X1, X2, X3, X4)
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837-
expected_result = np.array(
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[
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[15.16162, 1.00000],
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[14.16162, 1.00000],
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[13.16162, 1.00000],
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[12.16162, 1.00000],
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[11.16162, 1.00000],
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[10.16162, 1.00000],
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[9.16162, 1.00000],
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[8.16162, 1.00000],
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[7.16162, 1.00000],
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[6.16162, 1.00000],
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[5.16162, 1.00000],
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[4.16162, 1.00000],
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[3.16162, 1.00000],
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[2.16162, 1.00000],
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[1.16162, 1.00000],
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[0.16162, 1.00000],
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[-0.83838, 1.00000],
856-
[-1.83838, 1.00000],
857-
[-2.83838, 1.00000],
858-
]
859-
)
860-
assert np.allclose(Lambda, expected_result, rtol=1.0e-4)
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863-
def test_segmentsIntersect():
864-
"""test against matplotlib2tikz implementation"""
865-
y = np.linspace(1, 100, 20)
866-
x = y.copy()
867-
data = np.stack([x, y], axis=1)
868-
X1 = data[:-1, :]
869-
X2 = data[1:, :]
870-
X3 = np.array([80, 20])
871-
X4 = np.array([80, 80])
872-
mask = cleanfigure._segments_intersect(X1, X2, X3, X4)
873-
assert np.allclose(mask * 1, np.zeros_like(mask))
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875-
876-
def test_pixelate():
877-
xToPix = 49.952
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yToPix = 49.952
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xData = np.array(
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[
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21.842,
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27.053,
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32.263,
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37.474,
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42.684,
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47.895,
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53.105,
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58.316,
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63.526,
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68.737,
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73.947,
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79.158,
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]
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)
895-
yData = xData.copy()
896-
mask = cleanfigure._pixelate(xData, yData, xToPix, yToPix)
897-
assert mask.shape == (12,)
898-
assert np.all(mask)
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def test_corners3D():
902-
xlim = ylim = zlim = np.array([-5, 5])
903-
corners = cleanfigure._corners3D(xlim, ylim, zlim)
904-
905-
assert corners.shape == (8, 3)
906-
assert np.sum(corners) == 0
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908-
909-
def test_corners2D():
910-
xLim = np.array([20, 80])
911-
yLim = np.array([20, 80])
912-
corners = cleanfigure._corners2D(xLim, yLim)
913-
914-
import itertools
915-
916-
expected_output = tuple(np.array(t) for t in itertools.product([20, 80], [20, 80]))
917-
assert np.allclose(corners, expected_output)
918-
919-
920-
def test_getHeightWidthInPixels():
921-
with plt.rc_context(rc=RC_PARAMS):
922-
fig, axes = plt.subplots(1, 1, figsize=(5, 5))
923-
w, h = cleanfigure._get_width_height_in_pixels(fig, [600, 400])
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assert w == 600 and h == 400
925-
w, h = cleanfigure._get_width_height_in_pixels(fig, 600)
926-
assert w == h
927-
plt.close("all")
928-
929-
930624
def test_memory():
931625
import matplotlib.pyplot as plt
932626
import numpy as np

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