Change color normalization in plt_slices
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@ -9,6 +9,10 @@ from matplotlib.colors import Normalize, LogNorm, SymLogNorm
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from matplotlib.cm import ScalarMappable
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def quantize(x):
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return 2 ** round(log2(x), ndigits=1)
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def plt_slices(*fields, size=64, title=None, cmap=None, norm=None):
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"""Plot slices of fields of more than 2 spatial dimensions.
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"""
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@ -39,9 +43,6 @@ def plt_slices(*fields, size=64, title=None, cmap=None, norm=None):
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gridspec_kw={'height_ratios': nc * [im_size] + [cbar_height]}
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)
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def quantize(x):
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return 2 ** round(log2(x), ndigits=1)
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for f, (field, cmap_col, norm_col) in enumerate(zip(fields, cmap, norm)):
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all_non_neg = (field >= 0).all()
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all_non_pos = (field <= 0).all()
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@ -61,19 +62,19 @@ def plt_slices(*fields, size=64, title=None, cmap=None, norm=None):
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if all_non_neg:
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if h1 > 0.1 * h2:
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norm_col = Normalize(vmin=0, vmax=quantize(2 * h2))
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norm_col = Normalize(vmin=0, vmax=quantize(h2))
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else:
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norm_col = LogNorm(vmin=quantize(0.5 * l2), vmax=quantize(2 * h2))
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norm_col = LogNorm(vmin=quantize(l2), vmax=quantize(h2))
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elif all_non_pos:
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warnings.warn('no implementation for all non-positive values')
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warnings.warn('no implementation for all non-positive values yet')
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norm_col = None
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else:
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if w1 > 0.1 * w2:
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vlim = quantize(2.5 * w1)
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vlim = quantize(max(-l2, h2))
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if w1 > 0.1 * w2 or l1 * h1 >= 0:
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norm_col = Normalize(vmin=-vlim, vmax=vlim)
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else:
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vlim = quantize(w2)
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norm_col = SymLogNorm(linthresh=0.1 * w1, vmin=-vlim, vmax=vlim)
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linthresh = 0.1 * quantize(min(-l1, h1))
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norm_col = SymLogNorm(linthresh=linthresh, vmin=-vlim, vmax=vlim)
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for c in range(field.shape[0]):
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s = (c,) + (0,) * (nd - 2) + (slice(64),) * 2
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