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Copy pathtest_contour.py
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377 lines (278 loc) · 11 KB
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from __future__ import (absolute_import, division, print_function,
unicode_literals)
import datetime
import numpy as np
from matplotlib import mlab
from matplotlib.testing.decorators import image_comparison
from matplotlib import pyplot as plt
from numpy.testing import assert_array_almost_equal
import pytest
import warnings
import re
def test_contour_shape_1d_valid():
x = np.arange(10)
y = np.arange(9)
z = np.random.random((9, 10))
fig = plt.figure()
ax = fig.add_subplot(111)
ax.contour(x, y, z)
def test_contour_shape_2d_valid():
x = np.arange(10)
y = np.arange(9)
xg, yg = np.meshgrid(x, y)
z = np.random.random((9, 10))
fig = plt.figure()
ax = fig.add_subplot(111)
ax.contour(xg, yg, z)
def test_contour_shape_mismatch_1():
x = np.arange(9)
y = np.arange(9)
z = np.random.random((9, 10))
fig = plt.figure()
ax = fig.add_subplot(111)
with pytest.raises(TypeError) as excinfo:
ax.contour(x, y, z)
excinfo.match(r'Length of x must be number of columns in z.')
def test_contour_shape_mismatch_2():
x = np.arange(10)
y = np.arange(10)
z = np.random.random((9, 10))
fig = plt.figure()
ax = fig.add_subplot(111)
with pytest.raises(TypeError) as excinfo:
ax.contour(x, y, z)
excinfo.match(r'Length of y must be number of rows in z.')
def test_contour_shape_mismatch_3():
x = np.arange(10)
y = np.arange(10)
xg, yg = np.meshgrid(x, y)
z = np.random.random((9, 10))
fig = plt.figure()
ax = fig.add_subplot(111)
with pytest.raises(TypeError) as excinfo:
ax.contour(xg, y, z)
excinfo.match(r'Number of dimensions of x and y should match.')
with pytest.raises(TypeError) as excinfo:
ax.contour(x, yg, z)
excinfo.match(r'Number of dimensions of x and y should match.')
def test_contour_shape_mismatch_4():
g = np.random.random((9, 10))
b = np.random.random((9, 9))
z = np.random.random((9, 10))
fig = plt.figure()
ax = fig.add_subplot(111)
with pytest.raises(TypeError) as excinfo:
ax.contour(b, g, z)
excinfo.match(r'Shape of x does not match that of z: found \(9L?, 9L?\) ' +
r'instead of \(9L?, 10L?\)')
with pytest.raises(TypeError) as excinfo:
ax.contour(g, b, z)
excinfo.match(r'Shape of y does not match that of z: found \(9L?, 9L?\) ' +
r'instead of \(9L?, 10L?\)')
def test_contour_shape_invalid_1():
x = np.random.random((3, 3, 3))
y = np.random.random((3, 3, 3))
z = np.random.random((9, 10))
fig = plt.figure()
ax = fig.add_subplot(111)
with pytest.raises(TypeError) as excinfo:
ax.contour(x, y, z)
excinfo.match(r'Inputs x and y must be 1D or 2D.')
def test_contour_shape_invalid_2():
x = np.random.random((3, 3, 3))
y = np.random.random((3, 3, 3))
z = np.random.random((3, 3, 3))
fig = plt.figure()
ax = fig.add_subplot(111)
with pytest.raises(TypeError) as excinfo:
ax.contour(x, y, z)
excinfo.match(r'Input z must be a 2D array.')
def test_contour_empty_levels():
x = np.arange(9)
z = np.random.random((9, 9))
fig, ax = plt.subplots()
with pytest.warns(UserWarning) as record:
ax.contour(x, x, z, levels=[])
assert len(record) == 1
def test_contour_uniform_z():
x = np.arange(9)
z = np.ones((9, 9))
fig, ax = plt.subplots()
with pytest.warns(UserWarning) as record:
ax.contour(x, x, z)
assert len(record) == 1
@image_comparison(baseline_images=['contour_manual_labels'])
def test_contour_manual_labels():
x, y = np.meshgrid(np.arange(0, 10), np.arange(0, 10))
z = np.max(np.dstack([abs(x), abs(y)]), 2)
plt.figure(figsize=(6, 2))
cs = plt.contour(x, y, z)
pts = np.array([(1.5, 3.0), (1.5, 4.4), (1.5, 6.0)])
plt.clabel(cs, manual=pts)
@image_comparison(baseline_images=['contour_labels_size_color'],
extensions=['png'], remove_text=True)
def test_contour_labels_size_color():
x, y = np.meshgrid(np.arange(0, 10), np.arange(0, 10))
z = np.max(np.dstack([abs(x), abs(y)]), 2)
plt.figure(figsize=(6, 2))
cs = plt.contour(x, y, z)
pts = np.array([(1.5, 3.0), (1.5, 4.4), (1.5, 6.0)])
plt.clabel(cs, manual=pts, fontsize='small', colors=('r', 'g'))
@image_comparison(baseline_images=['contour_manual_colors_and_levels'],
extensions=['png'], remove_text=True)
def test_given_colors_levels_and_extends():
_, axes = plt.subplots(2, 4)
data = np.arange(12).reshape(3, 4)
colors = ['red', 'yellow', 'pink', 'blue', 'black']
levels = [2, 4, 8, 10]
for i, ax in enumerate(axes.flatten()):
filled = i % 2 == 0.
extend = ['neither', 'min', 'max', 'both'][i // 2]
if filled:
# If filled, we have 3 colors with no extension,
# 4 colors with one extension, and 5 colors with both extensions
first_color = 1 if extend in ['max', 'neither'] else None
last_color = -1 if extend in ['min', 'neither'] else None
c = ax.contourf(data, colors=colors[first_color:last_color],
levels=levels, extend=extend)
else:
# If not filled, we have 4 levels and 4 colors
c = ax.contour(data, colors=colors[:-1],
levels=levels, extend=extend)
plt.colorbar(c, ax=ax)
@image_comparison(baseline_images=['contour_datetime_axis'],
extensions=['png'], remove_text=False)
def test_contour_datetime_axis():
fig = plt.figure()
fig.subplots_adjust(hspace=0.4, top=0.98, bottom=.15)
base = datetime.datetime(2013, 1, 1)
x = np.array([base + datetime.timedelta(days=d) for d in range(20)])
y = np.arange(20)
z1, z2 = np.meshgrid(np.arange(20), np.arange(20))
z = z1 * z2
plt.subplot(221)
plt.contour(x, y, z)
plt.subplot(222)
plt.contourf(x, y, z)
x = np.repeat(x[np.newaxis], 20, axis=0)
y = np.repeat(y[:, np.newaxis], 20, axis=1)
plt.subplot(223)
plt.contour(x, y, z)
plt.subplot(224)
plt.contourf(x, y, z)
for ax in fig.get_axes():
for label in ax.get_xticklabels():
label.set_ha('right')
label.set_rotation(30)
@image_comparison(baseline_images=['contour_test_label_transforms'],
extensions=['png'], remove_text=True)
def test_labels():
# Adapted from pylab_examples example code: contour_demo.py
# see issues #2475, #2843, and #2818 for explanation
delta = 0.025
x = np.arange(-3.0, 3.0, delta)
y = np.arange(-2.0, 2.0, delta)
X, Y = np.meshgrid(x, y)
Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
# difference of Gaussians
Z = 10.0 * (Z2 - Z1)
fig, ax = plt.subplots(1, 1)
CS = ax.contour(X, Y, Z)
disp_units = [(216, 177), (359, 290), (521, 406)]
data_units = [(-2, .5), (0, -1.5), (2.8, 1)]
CS.clabel()
for x, y in data_units:
CS.add_label_near(x, y, inline=True, transform=None)
for x, y in disp_units:
CS.add_label_near(x, y, inline=True, transform=False)
@image_comparison(baseline_images=['contour_corner_mask_False',
'contour_corner_mask_True'],
extensions=['png'], remove_text=True)
def test_corner_mask():
n = 60
mask_level = 0.95
noise_amp = 1.0
np.random.seed([1])
x, y = np.meshgrid(np.linspace(0, 2.0, n), np.linspace(0, 2.0, n))
z = np.cos(7*x)*np.sin(8*y) + noise_amp*np.random.rand(n, n)
mask = np.where(np.random.rand(n, n) >= mask_level, True, False)
z = np.ma.array(z, mask=mask)
for corner_mask in [False, True]:
fig = plt.figure()
plt.contourf(z, corner_mask=corner_mask)
def test_contourf_decreasing_levels():
# github issue 5477.
z = [[0.1, 0.3], [0.5, 0.7]]
plt.figure()
with pytest.raises(ValueError):
plt.contourf(z, [1.0, 0.0])
# Legacy contouring algorithm gives a warning rather than raising an error,
# plus a DeprecationWarning.
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
plt.contourf(z, [1.0, 0.0], corner_mask='legacy')
assert len(w) == 2
def test_vminvmax_warning():
z = [[0.1, 0.3], [0.5, 0.7]]
plt.figure()
cs = plt.contourf(z, [0.0, 1.0])
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
cs.vmin
assert len(w) == 1
msg = "vmin is deprecated and will be removed in 2.2 "
assert str(w[0].message).startswith(msg)
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
cs.vmax
assert len(w) == 1
msg = "vmax is deprecated and will be removed in 2.2 "
assert str(w[0].message).startswith(msg)
def test_contourf_symmetric_locator():
# github issue 7271
z = np.arange(12).reshape((3, 4))
locator = plt.MaxNLocator(nbins=4, symmetric=True)
cs = plt.contourf(z, locator=locator)
assert_array_almost_equal(cs.levels, np.linspace(-12, 12, 5))
def test_contour_1x1_array():
# github issue 8197
with pytest.raises(TypeError) as excinfo:
plt.contour([[0]])
excinfo.match(r'Input z must be at least a 2x2 array.')
with pytest.raises(TypeError) as excinfo:
plt.contour([0], [0], [[0]])
excinfo.match(r'Input z must be at least a 2x2 array.')
def test_internal_cpp_api():
# Following github issue 8197.
import matplotlib._contour as _contour
with pytest.raises(TypeError) as excinfo:
qcg = _contour.QuadContourGenerator()
excinfo.match(r'function takes exactly 6 arguments \(0 given\)')
with pytest.raises(ValueError) as excinfo:
qcg = _contour.QuadContourGenerator(1, 2, 3, 4, 5, 6)
excinfo.match(r'Expected 2-dimensional array, got 0')
with pytest.raises(ValueError) as excinfo:
qcg = _contour.QuadContourGenerator([[0]], [[0]], [[]], None, True, 0)
excinfo.match(r'x, y and z must all be 2D arrays with the same dimensions')
with pytest.raises(ValueError) as excinfo:
qcg = _contour.QuadContourGenerator([[0]], [[0]], [[0]], None, True, 0)
excinfo.match(r'x, y and z must all be at least 2x2 arrays')
arr = [[0, 1], [2, 3]]
with pytest.raises(ValueError) as excinfo:
qcg = _contour.QuadContourGenerator(arr, arr, arr, [[0]], True, 0)
excinfo.match(r'If mask is set it must be a 2D array with the same ' +
r'dimensions as x.')
qcg = _contour.QuadContourGenerator(arr, arr, arr, None, True, 0)
with pytest.raises(ValueError) as excinfo:
qcg.create_filled_contour(1, 0)
excinfo.match(r'filled contour levels must be increasing')
def test_circular_contour_warning():
# Check that almost circular contours don't throw a warning
with pytest.warns(None) as record:
x, y = np.meshgrid(np.linspace(-2, 2, 4), np.linspace(-2, 2, 4))
r = np.sqrt(x ** 2 + y ** 2)
plt.figure()
cs = plt.contour(x, y, r)
plt.clabel(cs)
assert len(record) == 0