本文整理匯總了Python中matplotlib._image.pcolor方法的典型用法代碼示例。如果您正苦於以下問題：Python _image.pcolor方法的具體用法？Python _image.pcolor怎麽用？Python _image.pcolor使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類matplotlib._image的用法示例。
在下文中一共展示了_image.pcolor方法的4個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: make_image
# 需要導入模塊: from matplotlib import _image [as 別名]
# 或者: from matplotlib._image import pcolor [as 別名]
def make_image(self, magnification=1.0):
if self._A is None:
raise RuntimeError('You must first set the image array')
A = self._A
if len(A.shape) == 2:
if A.dtype != np.uint8:
A = self.to_rgba(A, bytes=True)
self.is_grayscale = self.cmap.is_gray()
else:
A = np.repeat(A[:, :, np.newaxis], 4, 2)
A[:, :, 3] = 255
self.is_grayscale = True
else:
if A.dtype != np.uint8:
A = (255*A).astype(np.uint8)
if A.shape[2] == 3:
B = np.zeros(tuple(list(A.shape[0:2]) + [4]), np.uint8)
B[:, :, 0:3] = A
B[:, :, 3] = 255
A = B
self.is_grayscale = False
x0, y0, v_width, v_height = self.axes.viewLim.bounds
l, b, r, t = self.axes.bbox.extents
width = (round(r) + 0.5) - (round(l) - 0.5)
height = (round(t) + 0.5) - (round(b) - 0.5)
width *= magnification
height *= magnification
im = _image.pcolor(self._Ax, self._Ay, A,
height, width,
(x0, x0+v_width, y0, y0+v_height),
self._interpd[self._interpolation])
fc = self.axes.patch.get_facecolor()
bg = mcolors.colorConverter.to_rgba(fc, 0)
im.set_bg(*bg)
im.is_grayscale = self.is_grayscale
return im 示例2: make_image
# 需要導入模塊: from matplotlib import _image [as 別名]
# 或者: from matplotlib._image import pcolor [as 別名]
def make_image(self, renderer, magnification=1.0, unsampled=False):
# docstring inherited
if self._A is None:
raise RuntimeError('You must first set the image array')
if unsampled:
raise ValueError('unsampled not supported on NonUniformImage')
A = self._A
if A.ndim == 2:
if A.dtype != np.uint8:
A = self.to_rgba(A, bytes=True)
self.is_grayscale = self.cmap.is_gray()
else:
A = np.repeat(A[:, :, np.newaxis], 4, 2)
A[:, :, 3] = 255
self.is_grayscale = True
else:
if A.dtype != np.uint8:
A = (255*A).astype(np.uint8)
if A.shape[2] == 3:
B = np.zeros(tuple([*A.shape[0:2], 4]), np.uint8)
B[:, :, 0:3] = A
B[:, :, 3] = 255
A = B
self.is_grayscale = False
x0, y0, v_width, v_height = self.axes.viewLim.bounds
l, b, r, t = self.axes.bbox.extents
width = (np.round(r) + 0.5) - (np.round(l) - 0.5)
height = (np.round(t) + 0.5) - (np.round(b) - 0.5)
width *= magnification
height *= magnification
im = _image.pcolor(self._Ax, self._Ay, A,
int(height), int(width),
(x0, x0+v_width, y0, y0+v_height),
_interpd_[self._interpolation])
return im, l, b, IdentityTransform() 示例3: make_image
# 需要導入模塊: from matplotlib import _image [as 別名]
# 或者: from matplotlib._image import pcolor [as 別名]
def make_image(self, renderer, magnification=1.0, unsampled=False):
if self._A is None:
raise RuntimeError('You must first set the image array')
if unsampled:
raise ValueError('unsampled not supported on NonUniformImage')
A = self._A
if A.ndim == 2:
if A.dtype != np.uint8:
A = self.to_rgba(A, bytes=True)
self.is_grayscale = self.cmap.is_gray()
else:
A = np.repeat(A[:, :, np.newaxis], 4, 2)
A[:, :, 3] = 255
self.is_grayscale = True
else:
if A.dtype != np.uint8:
A = (255*A).astype(np.uint8)
if A.shape[2] == 3:
B = np.zeros(tuple([*A.shape[0:2], 4]), np.uint8)
B[:, :, 0:3] = A
B[:, :, 3] = 255
A = B
self.is_grayscale = False
x0, y0, v_width, v_height = self.axes.viewLim.bounds
l, b, r, t = self.axes.bbox.extents
width = (np.round(r) + 0.5) - (np.round(l) - 0.5)
height = (np.round(t) + 0.5) - (np.round(b) - 0.5)
width *= magnification
height *= magnification
im = _image.pcolor(self._Ax, self._Ay, A,
int(height), int(width),
(x0, x0+v_width, y0, y0+v_height),
_interpd_[self._interpolation])
return im, l, b, IdentityTransform() 示例4: make_image
# 需要導入模塊: from matplotlib import _image [as 別名]
# 或者: from matplotlib._image import pcolor [as 別名]
def make_image(self, renderer, magnification=1.0, unsampled=False):
if self._A is None:
raise RuntimeError('You must first set the image array')
if unsampled:
raise ValueError('unsampled not supported on NonUniformImage')
A = self._A
if A.ndim == 2:
if A.dtype != np.uint8:
A = self.to_rgba(A, bytes=True)
self.is_grayscale = self.cmap.is_gray()
else:
A = np.repeat(A[:, :, np.newaxis], 4, 2)
A[:, :, 3] = 255
self.is_grayscale = True
else:
if A.dtype != np.uint8:
A = (255*A).astype(np.uint8)
if A.shape[2] == 3:
B = np.zeros(tuple(list(A.shape[0:2]) + [4]), np.uint8)
B[:, :, 0:3] = A
B[:, :, 3] = 255
A = B
self.is_grayscale = False
x0, y0, v_width, v_height = self.axes.viewLim.bounds
l, b, r, t = self.axes.bbox.extents
width = (np.round(r) + 0.5) - (np.round(l) - 0.5)
height = (np.round(t) + 0.5) - (np.round(b) - 0.5)
width *= magnification
height *= magnification
im = _image.pcolor(self._Ax, self._Ay, A,
int(height), int(width),
(x0, x0+v_width, y0, y0+v_height),
_interpd_[self._interpolation])
return im, l, b, IdentityTransform()