def test_matplotlibimage(self):
tm._skip_if_no_matplotlib()
import numpy as np
import matplotlib.pyplot as plt
img = np.random.randint(0, 255, (100, 100, 3))
ax = plt.imshow(img)
img = cesiumpy.entities.material.TemporaryImage(ax.figure)
m = cesiumpy.entities.material.ImageMaterialProperty(img)
self.assertTrue(
re.match(
"""new Cesium\\.ImageMaterialProperty\\({image : "\w+\\.png"}\\)""",
m.script))
img = cesiumpy.entities.material.TemporaryImage(ax)
m = cesiumpy.entities.material.ImageMaterialProperty(img)
self.assertTrue(
re.match(
"""new Cesium\\.ImageMaterialProperty\\({image : "\w+\\.png"}\\)""",
m.script))
plt.close()
fig, axes = plt.subplots(2, 2)
msg = "Unable to trim a Figure contains multiple Axes"
with nose.tools.assert_raises_regexp(ValueError, msg):
img = cesiumpy.entities.material.TemporaryImage(fig)
cesiumpy.entities.material.ImageMaterialProperty(img)
plt.close()
def test_SingleTimeImageryProvider_tempfile(self):
tm._skip_if_no_matplotlib()
import numpy as np
import matplotlib.pyplot as plt
img = np.random.randint(0, 255, (100, 100, 3))
ax = plt.imshow(img)
img = cesiumpy.entities.material.TemporaryImage(ax.figure)
m = cesiumpy.SingleTileImageryProvider(img, rectangle=(-120.0, 40.0, -100, 60))
self.assertTrue(re.match("""new Cesium\\.SingleTileImageryProvider\\(\\{url : "\w+\\.png", rectangle : Cesium\\.Rectangle\\.fromDegrees\\(-120\\.0, 40\\.0, -100\\.0, 60\\.0\\)\\}\\)""", m.script))
plt.close()
def test_SingleTimeImageryProvider_tempfile(self):
tm._skip_if_no_matplotlib()
import numpy as np
import matplotlib.pyplot as plt
img = np.random.randint(0, 255, (100, 100, 3))
ax = plt.imshow(img)
img = cesiumpy.entities.material.TemporaryImage(ax.figure)
m = cesiumpy.SingleTileImageryProvider(img,
rectangle=(-120.0, 40.0, -100,
60))
self.assertTrue(
re.match(
"""new Cesium\\.SingleTileImageryProvider\\(\\{url : "\w+\\.png", rectangle : Cesium\\.Rectangle\\.fromDegrees\\(-120\\.0, 40\\.0, -100\\.0, 60\\.0\\)\\}\\)""",
m.script))
plt.close()
def test_contour_xyz(self):
_skip_if_no_matplotlib()
import numpy as np
import matplotlib.mlab as mlab
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)
viewer = cesiumpy.Viewer()
viewer.plot.contour(X, Y, Z)
self.assertEqual(len(viewer.entities), 7)
self.assertTrue(all(isinstance(x, cesiumpy.Polyline)
for x in viewer.entities))
self.assertEqual(viewer.entities[0].material,
cesiumpy.color.Color(0.0, 0.0, 0.5, 1.0))
def test_contour_xyz(self):
_skip_if_no_matplotlib()
import numpy as np
import matplotlib.mlab as mlab
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)
viewer = cesiumpy.Viewer()
viewer.plot.contour(X, Y, Z)
self.assertEqual(len(viewer.entities), 7)
self.assertTrue(
all(isinstance(x, cesiumpy.Polyline) for x in viewer.entities))
self.assertEqual(viewer.entities[0].material,
cesiumpy.color.Color(0.0, 0.0, 0.5, 1.0))
def test_matplotlibimage(self):
tm._skip_if_no_matplotlib()
import numpy as np
import matplotlib.pyplot as plt
img = np.random.randint(0, 255, (100, 100, 3))
ax = plt.imshow(img)
img = cesiumpy.entities.material.TemporaryImage(ax.figure)
m = cesiumpy.entities.material.ImageMaterialProperty(img)
self.assertTrue(re.match("""new Cesium\\.ImageMaterialProperty\\({image : "\w+\\.png"}\\)""", m.script))
img = cesiumpy.entities.material.TemporaryImage(ax)
m = cesiumpy.entities.material.ImageMaterialProperty(img)
self.assertTrue(re.match("""new Cesium\\.ImageMaterialProperty\\({image : "\w+\\.png"}\\)""", m.script))
plt.close()
fig, axes = plt.subplots(2, 2)
msg = "Unable to trim a Figure contains multiple Axes"
with nose.tools.assert_raises_regexp(ValueError, msg):
img = cesiumpy.entities.material.TemporaryImage(fig)
cesiumpy.entities.material.ImageMaterialProperty(img)
plt.close()
def test_cmap(self):
tm._skip_if_no_matplotlib()
import matplotlib.pyplot as plt
mpl_cmap = plt.get_cmap('winter')
cmap = cesiumpy.color.get_cmap('winter')
exp = """ColorMap("winter")"""
self.assertEqual(repr(cmap), exp)
res = cmap(3)
exp = mpl_cmap(3)
self.assertEqual(res.red, exp[0])
self.assertEqual(res.green, exp[1])
self.assertEqual(res.blue, exp[2])
self.assertEqual(res.alpha, exp[3])
res = cmap([2, 4])
exp = mpl_cmap([2, 4])
for r, e in zip(res, exp):
self.assertEqual(r.red, e[0])
self.assertEqual(r.green, e[1])
self.assertEqual(r.blue, e[2])
self.assertEqual(r.alpha, e[3])
def test_cmap(self):
tm._skip_if_no_matplotlib()
import matplotlib.pyplot as plt
mpl_cmap = plt.get_cmap('winter')
cmap = cesiumpy.color.get_cmap('winter')
exp = """ColorMap("winter")"""
self.assertEqual(repr(cmap), exp)
res = cmap(3)
exp = mpl_cmap(3)
self.assertEqual(res.red, exp[0])
self.assertEqual(res.green, exp[1])
self.assertEqual(res.blue, exp[2])
self.assertEqual(res.alpha, exp[3])
res = cmap([2, 4])
exp = mpl_cmap([2, 4])
for r, e in zip(res, exp):
self.assertEqual(r.red, e[0])
self.assertEqual(r.green, e[1])
self.assertEqual(r.blue, e[2])
self.assertEqual(r.alpha, e[3])
