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from niprov.dependencies import Dependencies |
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class Camera(object): |
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def __init__(self, dependencies): |
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self.film = dependencies.getPictureCache() |
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self.libs = dependencies.getLibraries() |
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def saveSnapshot(self, data, for_): |
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"""Plot an overview of the image and store it. |
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Uses :class:`.PictureCache` as service that provides a file-like |
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handle to save the plotted picture to. |
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Calls takeSnapshot() to do the actual plotting. |
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Args: |
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data (numpy.ndarray): Array of 2, 3 or 4 dimensions with image data. |
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""" |
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newPicture = self.film.new() |
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self.takeSnapshot(data, on=newPicture) |
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self.film.keep(newPicture, for_) |
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def takeSnapshot(self, data, on): |
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"""Plot an overview of the image using matplotlib.pyplot. |
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Args: |
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data (numpy.ndarray): Array of 2, 3 or 4 dimensions with image data. |
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on (str or file-like object): Where to save figure to. |
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""" |
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plt = self.libs.pyplot |
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## 3D |
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ndims = len(data.shape) |
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sliceOrder = [1, 0, 2] |
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fig, axs = plt.subplots(nrows=1, ncols=ndims, figsize=(8, 3), dpi=100) |
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for d in range(ndims): |
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slicing = [slice(None)]*ndims |
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slicing[sliceOrder[d]] = int(data.shape[d]/2) |
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axs[d].matshow(data[slicing].T, origin='lower', |
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cmap = plt.get_cmap('gray'), vmin = 0, vmax = data.max()) |
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axs[d].locator_params(nbins=3) |
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axs[d].tick_params(axis='both', which='major', labelsize=8) |
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plt.tight_layout() |
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plt.savefig(on) |
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ilogue /
niprov
