Python matplotlib._image.pcolor() Examples

The following are 10 code examples of matplotlib._image.pcolor(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module matplotlib._image , or try the search function .
Example #1
Source File: image.py    From Computable with MIT License 5 votes vote down vote up 
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
Example #2
Source File: image.py    From Mastering-Elasticsearch-7.0 with MIT License 5 votes vote down vote up 
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()
Example #3
Source File: image.py    From matplotlib-4-abaqus with MIT License 5 votes vote down vote up 
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
Example #4
Source File: image.py    From neural-network-animation with MIT License 5 votes vote down vote up 
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
Example #5
Source File: image.py    From GraphicDesignPatternByPython with MIT License 5 votes vote down vote up 
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()
Example #6
Source File: image.py    From python3_ios with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
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()
Example #7
Source File: image.py    From ImageFusion with MIT License 5 votes vote down vote up 
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
Example #8
Source File: image.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
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()
Example #9
Source File: image.py    From CogAlg with MIT License 5 votes vote down vote up 
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()
Example #10
Source File: image.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
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()