def test_Percept_save(dtype):
ndarray = np.arange(256, dtype=dtype).repeat(31).reshape((-1, 16, 16))
percept = Percept(ndarray.transpose((2, 0, 1)))
# Save multiple frames as a gif or movie:
for fname in ['test.mp4', 'test.avi', 'test.mov', 'test.wmv', 'test.gif']:
percept.save(fname)
npt.assert_equal(os.path.isfile(fname), True)
# Normalized to [0, 255] with some loss of precision:
for mov in mimread(fname):
npt.assert_equal(np.min(mov) <= 2, True)
npt.assert_equal(np.max(mov) >= 250, True)
os.remove(fname)
# Cannot save multiple frames image:
fname = 'test.jpg'
with pytest.raises(ValueError):
percept.save(fname)
# But, can save single frame as image:
percept = Percept(ndarray[..., :1])
for fname in ['test.jpg', 'test.png', 'test.tif', 'test.gif']:
percept.save(fname)
npt.assert_equal(os.path.isfile(fname), True)
img = img_as_float(imread(fname))
npt.assert_almost_equal(np.min(img), 0, decimal=3)
npt.assert_almost_equal(np.max(img), 1.0, decimal=3)
os.remove(fname)
def test_Percept():
# Automatic axes:
ndarray = np.arange(15).reshape((3, 5, 1))
percept = Percept(ndarray, metadata='meta')
npt.assert_equal(percept.shape, ndarray.shape)
npt.assert_equal(percept.metadata, 'meta')
npt.assert_equal(hasattr(percept, 'xdva'), True)
npt.assert_almost_equal(percept.xdva, np.arange(ndarray.shape[1]))
npt.assert_equal(hasattr(percept, 'ydva'), True)
npt.assert_almost_equal(percept.ydva, np.arange(ndarray.shape[0]))
npt.assert_equal(hasattr(percept, 'time'), True)
npt.assert_almost_equal(percept.time, np.arange(ndarray.shape[2]))
# Specific labels:
percept = Percept(ndarray, time=0.4)
npt.assert_almost_equal(percept.time, [0.4])
percept = Percept(ndarray, time=[0.4])
npt.assert_almost_equal(percept.time, [0.4])
# Labels from a grid.
y_range = (-1, 1)
x_range = (-2, 2)
grid = GridXY(x_range, y_range)
percept = Percept(ndarray, space=grid)
npt.assert_almost_equal(percept.xdva, grid._xflat)
npt.assert_almost_equal(percept.ydva, grid._yflat)
npt.assert_almost_equal(percept.time, [0])
grid = GridXY(x_range, y_range)
percept = Percept(ndarray, space=grid)
npt.assert_almost_equal(percept.xdva, grid._xflat)
npt.assert_almost_equal(percept.ydva, grid._yflat)
npt.assert_almost_equal(percept.time, [0])
def test_Percept_save():
ndarray = np.zeros((2, 3, 4))
ndarray[..., 1] = 1
ndarray[..., 2] = 2
ndarray[..., 3] = 3
percept = Percept(ndarray)
# Save multiple frames as a gif or movie:
for fname in ['test.mp4', 'test.avi', 'test.mov', 'test.wmv', 'test.gif']:
print(fname)
percept.save(fname)
npt.assert_equal(os.path.isfile(fname), True)
os.remove(fname)
# Cannot save multiple frames image:
fname = 'test.jpg'
with pytest.raises(ValueError):
percept.save(fname)
# But, can save single frame as image:
percept = Percept(ndarray[..., :1])
for fname in ['test.jpg', 'test.png', 'test.tif', 'test.gif']:
percept.save(fname)
npt.assert_equal(os.path.isfile(fname), True)
os.remove(fname)
def test_Percept_play():
ndarray = np.zeros((2, 4, 3))
ndarray[..., 1] = 1
ndarray[..., 2] = 2
percept = Percept(ndarray)
ani = percept.play()
npt.assert_equal(isinstance(ani, FuncAnimation), True)
def test_Percept_argmax():
percept = Percept(np.arange(30).reshape((3, 5, 2)))
npt.assert_almost_equal(percept.argmax(), 29)
npt.assert_almost_equal(percept.argmax(axis="frames"), 1)
with pytest.raises(TypeError):
percept.argmax(axis=(0, 1))
with pytest.raises(ValueError):
percept.argmax(axis='invalid')
def test_Percept__iter__():
ndarray = np.zeros((2, 4, 3))
ndarray[..., 1] = 1
ndarray[..., 2] = 2
percept = Percept(ndarray)
for i, frame in enumerate(percept):
npt.assert_equal(frame.shape, (2, 4))
npt.assert_almost_equal(frame, i)
def test_Percept():
# Automatic axes:
ndarray = np.arange(15).reshape((3, 5, 1))
percept = Percept(ndarray, metadata='meta')
npt.assert_equal(percept.shape, ndarray.shape)
npt.assert_equal(percept.metadata, 'meta')
npt.assert_equal(hasattr(percept, 'xdva'), True)
npt.assert_almost_equal(percept.xdva, np.arange(ndarray.shape[1]))
npt.assert_equal(hasattr(percept, 'ydva'), True)
npt.assert_almost_equal(percept.ydva, np.arange(ndarray.shape[0]))
# Singleton dimensions can be None:
npt.assert_equal(hasattr(percept, 'time'), True)
npt.assert_equal(percept.time, None)
# Specific labels:
percept = Percept(ndarray, time=0.4)
npt.assert_almost_equal(percept.time, [0.4])
percept = Percept(ndarray, time=[0.4])
npt.assert_almost_equal(percept.time, [0.4])
# Labels from a grid.
y_range = (-1, 1)
x_range = (-2, 2)
grid = Grid2D(x_range, y_range)
percept = Percept(ndarray, space=grid)
npt.assert_almost_equal(percept.xdva, grid._xflat)
npt.assert_almost_equal(percept.ydva, grid._yflat)
npt.assert_equal(percept.time, None)
grid = Grid2D(x_range, y_range)
percept = Percept(ndarray, space=grid, time=0)
npt.assert_almost_equal(percept.xdva, grid._xflat)
npt.assert_almost_equal(percept.ydva, grid._yflat)
npt.assert_almost_equal(percept.time, [0])
with pytest.raises(TypeError):
Percept(ndarray, space={'x': [0, 1, 2], 'y': [0, 1, 2, 3, 4]})
def test_Percept_max():
percept = Percept(np.arange(30).reshape((3, 5, 2)))
npt.assert_almost_equal(percept.max(), 29)
npt.assert_almost_equal(percept.max(axis="frames"), percept.data[..., 1])
npt.assert_almost_equal(percept.max(),
percept.data.ravel()[percept.argmax()])
npt.assert_almost_equal(percept.max(axis='frames'),
percept.data[...,
percept.argmax(axis='frames')])
with pytest.raises(TypeError):
percept.max(axis=(0, 1))
with pytest.raises(ValueError):
percept.max(axis='invalid')
def test_Percept():
# Automatic axes:
ndarray = np.arange(15).reshape((3, 5, 1))
percept = Percept(ndarray, metadata='meta')
npt.assert_equal(percept.shape, ndarray.shape)
npt.assert_equal(percept.metadata, 'meta')
npt.assert_equal(hasattr(percept, 'xdva'), True)
npt.assert_almost_equal(percept.xdva, np.arange(ndarray.shape[1]))
npt.assert_equal(hasattr(percept, 'ydva'), True)
npt.assert_almost_equal(percept.ydva, np.arange(ndarray.shape[0]))
# Singleton dimensions can be None:
npt.assert_equal(hasattr(percept, 'time'), True)
npt.assert_equal(percept.time, None)
# Specific labels:
percept = Percept(ndarray, time=0.4)
npt.assert_almost_equal(percept.time, [0.4])
percept = Percept(ndarray, time=[0.4])
npt.assert_almost_equal(percept.time, [0.4])
# Labels from a grid.
y_range = (-1, 1)
x_range = (-2, 2)
grid = Grid2D(x_range, y_range)
percept = Percept(ndarray, space=grid)
npt.assert_almost_equal(percept.xdva, grid._xflat)
npt.assert_almost_equal(percept.ydva, grid._yflat)
npt.assert_equal(percept.time, None)
grid = Grid2D(x_range, y_range)
percept = Percept(ndarray, space=grid, time=0)
npt.assert_almost_equal(percept.xdva, grid._xflat)
npt.assert_almost_equal(percept.ydva, grid._yflat)
npt.assert_almost_equal(percept.time, [0])
# Gray levels
for n_gray in [2, 4]:
percept = Percept(np.arange(49, dtype=float).reshape((7, 7, 1)),
n_gray=n_gray)
npt.assert_equal(len(np.unique(percept.data)), n_gray)
with pytest.raises(TypeError):
Percept(ndarray, space={'x': [0, 1, 2], 'y': [0, 1, 2, 3, 4]})
with pytest.raises(ValueError):
Percept(ndarray, n_gray=1.2)
with pytest.raises(ValueError):
Percept(ndarray, n_gray=-3)
# Noise:
data = np.arange(100, dtype=float).reshape((5, 5, 4))
npt.assert_almost_equal(Percept(data, noise=0).data, data)
npt.assert_almost_equal(Percept(data, noise=0.0).data, data)
for noise in [0.5, 1.0]:
percept = Percept(data, noise=noise)
n_white = sum(np.isclose(percept.data.ravel(), 99.0))
n_black = sum(np.isclose(percept.data.ravel(), 0.0))
npt.assert_equal(abs(n_white - 0.5 * noise * data.size) <= 2, True)
npt.assert_equal(abs(n_black - 0.5 * noise * data.size) <= 2, True)
def test_Percept_play(n_frames):
ndarray = np.random.rand(2, 4, n_frames)
percept = Percept(ndarray)
ani = percept.play()
npt.assert_equal(isinstance(ani, FuncAnimation), True)
npt.assert_equal(len(list(ani.frame_seq)), n_frames)
def test_Percept_plot():
y_range = (-1, 1)
x_range = (-2, 2)
grid = Grid2D(x_range, y_range)
percept = Percept(np.arange(15).reshape((3, 5, 1)), space=grid)
# Basic usage of pcolor:
ax = percept.plot(kind='pcolor')
npt.assert_equal(isinstance(ax, Subplot), True)
npt.assert_almost_equal(ax.axis(), [*x_range, *y_range])
frame = percept.max(axis='frames')
npt.assert_almost_equal(ax.collections[0].get_clim(),
[frame.min(), frame.max()])
# Basic usage of hex:
ax = percept.plot(kind='hex')
npt.assert_equal(isinstance(ax, Subplot), True)
npt.assert_almost_equal(
ax.axis(),
[percept.xdva[0], percept.xdva[-1], percept.ydva[0], percept.ydva[-1]])
npt.assert_almost_equal(
ax.collections[0].get_clim(),
[percept.data[..., 0].min(), percept.data[..., 0].max()])
# Verify color map:
npt.assert_equal(ax.collections[0].cmap, plt.cm.gray)
# Specify figsize:
ax = percept.plot(kind='pcolor', figsize=(6, 4))
npt.assert_almost_equal(ax.figure.get_size_inches(), (6, 4))
# Test vmin and vmax
ax.clear()
ax = percept.plot(vmin=2, vmax=4)
npt.assert_equal(ax.collections[0].get_clim(), (2., 4.))
# Invalid calls:
with pytest.raises(ValueError):
percept.plot(kind='invalid')
with pytest.raises(TypeError):
percept.plot(ax='invalid')
def test_Percept_get_brightest_frame():
percept = Percept(np.arange(30).reshape((3, 5, 2)))
npt.assert_almost_equal(percept.get_brightest_frame(), percept.data[...,
1])
def test_Percept_plot():
y_range = (-1, 1)
x_range = (-2, 2)
grid = GridXY(x_range, y_range)
percept = Percept(np.arange(15).reshape((3, 5, 1)), space=grid)
# Basic usage of pcolor:
ax = percept.plot(kind='pcolor')
npt.assert_equal(isinstance(ax, Subplot), True)
npt.assert_almost_equal(
ax.axis(),
[0, len(percept.xdva), 0, len(percept.ydva)])
npt.assert_almost_equal(
ax.collections[0].get_clim(),
[percept.data.min(), percept.data.max()])
# Basic usage of hex:
ax = percept.plot(kind='hex')
npt.assert_equal(isinstance(ax, Subplot), True)
npt.assert_almost_equal(
ax.axis(),
[percept.xdva[0], percept.xdva[-1], percept.ydva[0], percept.ydva[-1]])
npt.assert_almost_equal(
ax.collections[0].get_clim(),
[percept.data[..., 0].min(), percept.data[..., 0].max()])
# Verify color map:
npt.assert_equal(ax.collections[0].cmap, plt.cm.gray)
ax = percept.plot(cmap='inferno')
npt.assert_equal(ax.collections[0].cmap, plt.cm.inferno)
# Invalid calls:
with pytest.raises(ValueError):
percept.plot(kind='invalid')
with pytest.raises(TypeError):
percept.plot(ax='invalid')
# TODO
with pytest.raises(NotImplementedError):
percept.plot(time=3.3)
