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_Grid2D_plot():
grid = Grid2D((-20, 20), (-40, 40), step=0.5)
ax = grid.plot()
npt.assert_equal(isinstance(ax, Axes), True)
npt.assert_almost_equal(ax.get_xlim(), (-22, 22))
# You can change the scaling:
ax = grid.plot(transform=lambda x, y: (2 * x, 2 * y))
npt.assert_equal(isinstance(ax, Axes), True)
npt.assert_almost_equal(ax.get_xlim(), (-44, 44))
# You can change the figure size
ax = grid.plot(figsize=(9, 7))
npt.assert_almost_equal(ax.figure.get_size_inches(), (9, 7))
# You can change the style (smoke test):
ax = grid.plot(style='hull')
ax = grid.plot(style='cell')
ax = grid.plot(style='scatter')
# Step might be a tuple (smoke test):
Grid2D((-5, 5), (-5, 5), step=(0.5, 1)).plot(style='cell')
def test_Grid2D_make_rectangular_grid():
# Range is a multiple of step size:
grid = Grid2D((-1, 1), (0, 0), step=1)
npt.assert_almost_equal(grid.x, [[-1, 0, 1]])
npt.assert_almost_equal(grid.y, [[0, 0, 0]])
for mlt in [0.01, 0.1, 1, 10, 100]:
grid = Grid2D((-10 * mlt, 10 * mlt), (-10 * mlt, 10 * mlt),
step=5 * mlt)
npt.assert_almost_equal(grid.x[0], mlt * np.array([-10, -5, 0, 5, 10]))
npt.assert_almost_equal(grid.y[:, 0],
mlt * np.array([-10, -5, 0, 5, 10]))
# Another way to verify this is to manually check the step size:
for step in [0.25, 0.5, 1, 2]:
grid = Grid2D((-20, 20), (-40, 40), step=step)
npt.assert_equal(len(np.unique(np.diff(grid.x[0, :]))), 1)
npt.assert_equal(len(np.unique(np.diff(grid.y[:, 0]))), 1)
npt.assert_almost_equal(np.unique(np.diff(grid.x[0, :]))[0], step)
npt.assert_almost_equal(np.unique(np.diff(grid.y[:, 0]))[0], step)
# Step size just a little too small/big to fit into range. In this case,
# the step size gets adjusted so that the range is as specified by the
# user:
grid = Grid2D((-1, 1), (0, 0), step=0.33)
npt.assert_almost_equal(grid.x, [[-1, -2 / 3, -1 / 3, 0, 1 / 3, 2 / 3, 1]])
npt.assert_almost_equal(grid.y, [[0, 0, 0, 0, 0, 0, 0]])
grid = Grid2D((-1, 1), (0, 0), step=0.34)
npt.assert_almost_equal(grid.x, [[-1, -2 / 3, -1 / 3, 0, 1 / 3, 2 / 3, 1]])
npt.assert_almost_equal(grid.y, [[0, 0, 0, 0, 0, 0, 0]])
# Different step size for x and y:
grid = Grid2D((-1, 1), (0, 0), step=(0.5, 1))
npt.assert_almost_equal(grid.x, [[-1, -0.5, 0, 0.5, 1]])
npt.assert_almost_equal(grid.y, [[0, 0, 0, 0, 0]])
grid = Grid2D((0, 0), (-1, 1), step=(2, 0.5))
npt.assert_almost_equal(grid.x, [[0], [0], [0], [0], [0]])
npt.assert_almost_equal(grid.y[:, 0], [-1, -0.5, 0, 0.5, 1])
# Same step size, but given explicitly:
npt.assert_almost_equal(
Grid2D((-3, 3), (8, 12), step=0.123).x,
Grid2D((-3, 3), (8, 12), step=(0.123, 0.123)).x)
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_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.get_brightest_frame()
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)
ax = percept.plot(cmap='inferno')
npt.assert_equal(ax.collections[0].cmap, plt.cm.inferno)
# Specify figsize:
ax = percept.plot(kind='pcolor', figsize=(6, 4))
npt.assert_almost_equal(ax.figure.get_size_inches(), (6, 4))
# 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)
def test_Grid2D(x_range, y_range):
grid = Grid2D(x_range, y_range, step=1, grid_type='rectangular')
npt.assert_equal(grid.x_range, x_range)
npt.assert_equal(grid.y_range, y_range)
npt.assert_equal(grid.step, 1)
npt.assert_equal(grid.type, 'rectangular')
# Grid is created with indexing='xy', so check coordinates:
npt.assert_equal(
grid.x.shape,
(np.abs(np.diff(y_range)) + 1, np.abs(np.diff(x_range)) + 1))
npt.assert_equal(grid.x.shape, grid.y.shape)
npt.assert_equal(grid.x.shape, grid.shape)
npt.assert_almost_equal(grid.x[0, 0], x_range[0])
npt.assert_almost_equal(grid.x[0, -1], x_range[1])
npt.assert_almost_equal(grid.x[-1, 0], x_range[0])
npt.assert_almost_equal(grid.x[-1, -1], x_range[1])
npt.assert_almost_equal(grid.y[0, 0], y_range[0])
npt.assert_almost_equal(grid.y[0, -1], y_range[0])
npt.assert_almost_equal(grid.y[-1, 0], y_range[1])
npt.assert_almost_equal(grid.y[-1, -1], y_range[1])
def test_Grid2D_plot():
grid = Grid2D((-20, 20), (-40, 40), step=0.5)
ax = grid.plot()
npt.assert_equal(isinstance(ax, Axes), True)
