def _checks_and_wrangling(self, x, w):
# Manage the input data in the same fashion as mpl
if np.isscalar(x):
x = [x]
input_empty = (np.size(x) == 0)
# Massage 'x' for processing.
if input_empty:
x = np.array([[]])
else:
x = cbook._reshape_2D(x)
self.n_data_sets = len(x) # number of datasets
# We need to do to 'weights' what was done to 'x'
if w is not None:
w = cbook._reshape_2D(w)
if w is not None and len(w) != self.n_data_sets:
raise ValueError('weights should have the same shape as x')
if w is not None:
for xi, wi in zip(x, w):
if wi is not None and len(wi) != len(xi):
raise ValueError('weights should have the same shape as x')
return x, w
python类cbook()的实例源码
def test_colorbar_example1():
with cbook.get_sample_data('grace_hopper.png') as fp:
data = np.array(plt.imread(fp))
fig = plt.figure(figsize=(8, 6))
ax = fig.add_subplot("111", aspect='equal')
mappable = ax.imshow(data[..., 0], cmap='viridis')
colorbar = Colorbar(mappable, location='lower left')
colorbar.set_ticks([0.0, 0.5, 1.0])
ax.add_artist(colorbar)
def test_colorbar_example2():
with cbook.get_sample_data('grace_hopper.png') as fp:
data = np.array(plt.imread(fp))
fig = plt.figure(figsize=(8, 6))
ax = fig.add_subplot("111", aspect='equal')
norm = matplotlib.colors.Normalize(vmin=-1.0, vmax=1.0)
mappable = ax.imshow(data[..., 0], cmap='viridis', norm=norm)
colorbar = Colorbar(mappable, location='lower left')
colorbar.set_ticks([-1.0, 0, 1.0])
ax.add_artist(colorbar)