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DOC: refactor axes with lists
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@@ -148,13 +148,15 @@ error = reconstruction_sart - image
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print('SART (1 iteration) rms reconstruction error: %.3g'
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% np.sqrt(np.mean(error**2)))
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fig, ax = plt.subplots(2, 2, figsize=(8, 8.5), sharex=True, sharey=True,
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subplot_kw={'adjustable': 'box-forced'})
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ax1, ax2, ax3, ax4 = ax.ravel()
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ax1.set_title("Reconstruction\nSART")
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ax1.imshow(reconstruction_sart, cmap=plt.cm.Greys_r)
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ax2.set_title("Reconstruction error\nSART")
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ax2.imshow(reconstruction_sart - image, cmap=plt.cm.Greys_r, **imkwargs)
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fig, axes = plt.subplots(2, 2, figsize=(8, 8.5), sharex=True, sharey=True,
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subplot_kw={'adjustable': 'box-forced'})
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ax = axes.ravel()
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ax[0].set_title("Reconstruction\nSART")
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ax[0].imshow(reconstruction_sart, cmap=plt.cm.Greys_r)
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ax[1].set_title("Reconstruction error\nSART")
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ax[1].imshow(reconstruction_sart - image, cmap=plt.cm.Greys_r, **imkwargs)
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# Run a second iteration of SART by supplying the reconstruction
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# from the first iteration as an initial estimate
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@@ -164,10 +166,11 @@ error = reconstruction_sart2 - image
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print('SART (2 iterations) rms reconstruction error: %.3g'
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% np.sqrt(np.mean(error**2)))
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ax3.set_title("Reconstruction\nSART, 2 iterations")
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ax3.imshow(reconstruction_sart2, cmap=plt.cm.Greys_r)
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ax4.set_title("Reconstruction error\nSART, 2 iterations")
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ax4.imshow(reconstruction_sart2 - image, cmap=plt.cm.Greys_r, **imkwargs)
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ax[2].set_title("Reconstruction\nSART, 2 iterations")
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ax[2].imshow(reconstruction_sart2, cmap=plt.cm.Greys_r)
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ax[3].set_title("Reconstruction error\nSART, 2 iterations")
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ax[3].imshow(reconstruction_sart2 - image, cmap=plt.cm.Greys_r, **imkwargs)
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plt.show()
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######################################################################
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