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Merge pull request #15 from slumnitz/utils
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include utility functions `shift_colormap` and `truncate_colormap`
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ljwolf authored Jun 28, 2018
2 parents e73f1a1 + f443a61 commit a4fd3c7
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94 changes: 94 additions & 0 deletions splot/_viz_utils.py
Original file line number Diff line number Diff line change
Expand Up @@ -195,3 +195,97 @@ def calc_data_aspect(plot_height, plot_width, bounds):
ymin -= (ymax - ymin) / 2 * margin
ymax += (ymax - ymin) / 2 * margin
return xmin, xmax, ymin, ymax


#Utility functions for viz of continuous variables

#Utility function #1 - forces diverging colormap to be centered at zero
def shift_colormap(cmap, start=0, midpoint=0.5, stop=1.0, name='shiftedcmap'):
'''
Function to offset the "center" of a colormap. Useful for
data with a negative min and positive max and you want the
middle of the colormap's dynamic range to be at zero
Parameters
----------
cmap : matplotlib colormap
colormap to be altered
start : float, optional
Offset from lowest point in the colormap's range.
Should be between 0.0 and `midpoint`.
Default =0.0 (no lower ofset).
midpoint : float, optional
The new center of the colormap.Should be between 0.0 and
1.0. In general, this should be 1 - vmax/(vmax + abs(vmin)).
For example if your data range from -15.0 to +5.0 and
you want the center of the colormap at 0.0, `midpoint`
should be set to 1 - 5/(5 + 15)) or 0.75.
Default =0.5 (no shift).
stop : float, optional
Offset from highets point in the colormap's range.
Should be between `midpoint` and 1.0.
Default =1.0 (no upper ofset).
name : str, optional
Name of the new colormap.
Returns
-------
new_cmap : A new colormap that has been shifted.
'''

cdict = {
'red': [],
'green': [],
'blue': [],
'alpha': []
}

# regular index to compute the colors
reg_index = np.linspace(start, stop, 257)

# shifted index to match the data
shift_index = np.hstack([
np.linspace(0.0, midpoint, 128, endpoint=False),
np.linspace(midpoint, 1.0, 129, endpoint=True)
])

for ri, si in zip(reg_index, shift_index):
r, g, b, a = cmap(ri)

cdict['red'].append((si, r, r))
cdict['green'].append((si, g, g))
cdict['blue'].append((si, b, b))
cdict['alpha'].append((si, a, a))

new_cmap = mpl.colors.LinearSegmentedColormap(name, cdict)
plt.register_cmap(cmap=new_cmap)
return new_cmap


#Utility #2 - truncate colorcap in order to grab only positive or negative portion
def truncate_colormap(cmap, minval=0.0, maxval=1.0, n=100):
'''
Function to truncate a colormap by selecting a subset of
the original colormap's values
Parameters
----------
cmap : Mmatplotlib colormap
Colormap to be altered
minval : float, optional
Minimum value of the original colormap to include
in the truncated colormap. Default =0.0.
maxval : Maximum value of the original colormap to
include in the truncated colormap. Default =1.0.
n : int, optional
Number of intervals between the min and max values
for the gradient of the truncated colormap. Default =100.
Returns
-------
new_cmap : A new colormap that has been shifted.
'''
new_cmap = mpl.colors.LinearSegmentedColormap.from_list(
'trunc({n},{a:.2f},{b:.2f})'.format(n=cmap.name, a=minval, b=maxval),
cmap(np.linspace(minval, maxval, n)))
return new_cmap

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