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rasterio.plot: fix parameters section title (#3346)
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@ -31,7 +31,7 @@ def get_plt():
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raise ImportError(msg)
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def show(source, with_bounds=True, contour=False, contour_label_kws=None, indexes=None,
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def show(source, with_bounds=True, contour=False, contour_label_kws=None, indexes=None,
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ax=None, title=None, transform=None, percent_range=None, adjust=True, **kwargs):
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"""Display a raster or raster band using matplotlib.
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@ -58,7 +58,7 @@ def show(source, with_bounds=True, contour=False, contour_label_kws=None, indexe
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transform : Affine, optional
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Defines the affine transform if source is an array
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percent_range: tuple, optional
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percent_range[0], the minimum value (cumulative percentage) of the histogram for histogram streching,
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percent_range[0], the minimum value (cumulative percentage) of the histogram for histogram streching,
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percent_range[1], the maximum value (cumulative percentage) of the histogram for histogram streching
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default percent_range is set to (2, 98).
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adjust : bool
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@ -130,8 +130,8 @@ def show(source, with_bounds=True, contour=False, contour_label_kws=None, indexe
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if adjust:
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if percent_range:
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arr = contrast_strech(arr, percent_range)
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else:
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if arr.ndim == 2:
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else:
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if arr.ndim == 2:
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arr = adjust_band(arr)
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elif arr.ndim >= 3:
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# Adjust each band by the min/max so it will plot as RGB.
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@ -339,19 +339,20 @@ def show_hist(
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def contrast_strech(arr, percent_range=(2.0, 98.0)):
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"""
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Histogram streching for better image visualization.
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Parameters
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Parameters
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----------
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arr : array-like in the image form of (rows, columns, bands)
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image to reshape
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image to reshape
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percent_range: tuple, optional
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percent_range[0], the minimum values (cumulative percentage) of the histogram for histogram streching,
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percent_range[0], the minimum values (cumulative percentage) of the histogram for histogram streching,
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percent_range[1], the maximum value (cumulative percentage) of the histogram for histogram streching
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default percent_range is set to (2, 98).
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"""
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"""
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arr_hist = np.nanpercentile(np.array(arr), (percent_range[0], percent_range[1]))
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arr = (arr - arr_hist[0])/(arr_hist[1]-arr_hist[0])
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arr = (arr - arr_hist[0])/(arr_hist[1]-arr_hist[0])
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arr = np.clip(arr, 0, 1)
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return arr
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return arr
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def adjust_band(band, kind=None):
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