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add option to scale heatmap vmin and vmax based on avg. computed values #186

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add option to scale heatmap vmin and vmax based on avg. computed values #186

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a01b7b0
added option to heatmap
fairliereese Mar 14, 2022
7c71f57
removed prints
fairliereese Mar 14, 2022
f4e4285
fixed non-overlapping triangles issue
fairliereese Aug 24, 2022
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39 changes: 32 additions & 7 deletions ternary/heatmapping.py
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Original file line number Diff line number Diff line change
Expand Up @@ -186,7 +186,7 @@ def polygon_generator(data, scale, style, permutation=None):
yield map(project, vertices), value


def heatmap(data, scale, vmin=None, vmax=None, cmap=None, ax=None,
def heatmap(data, scale, vmin=None, vmax=None, adj_vlims=False, cmap=None, ax=None,
scientific=False, style='triangular', colorbar=True,
permutation=None, use_rgba=False, cbarlabel=None, cb_kwargs=None):
"""
Expand All @@ -203,6 +203,8 @@ def heatmap(data, scale, vmin=None, vmax=None, cmap=None, ax=None,
The minimum color value, used to normalize colors. Computed if absent.
vmax: float, None
The maximum color value, used to normalize colors. Computed if absent.
adj_vlims: bool, False
Redefine min and max color values based on computed averages.
cmap: String or matplotlib.colors.Colormap, None
The name of the Matplotlib colormap to use.
ax: Matplotlib AxesSubplot, None
Expand All @@ -229,6 +231,12 @@ def heatmap(data, scale, vmin=None, vmax=None, cmap=None, ax=None,

if not ax:
fig, ax = plt.subplots()

if vmax or vmin:
vlims_defined = True
else:
vlims_defined = False

# If use_rgba, make the RGBA values numpy arrays so that they can
# be averaged.
if use_rgba:
Expand All @@ -247,6 +255,18 @@ def heatmap(data, scale, vmin=None, vmax=None, cmap=None, ax=None,
vertices_values = polygon_generator(data, scale, style,
permutation=permutation)

# adjust limits of the colormapper if requested,
# but only if user also didn't request specific vlims
if adj_vlims and not vlims_defined:
vals = []
for _, val in vertices_values:
vals.append(val)
vmin = min(vals)
vmax = max(vals)

vertices_values = polygon_generator(data, scale, style,
permutation=permutation)

# Draw the polygons and color them
for vertices, value in vertices_values:
if value is None:
Expand All @@ -257,7 +277,7 @@ def heatmap(data, scale, vmin=None, vmax=None, cmap=None, ax=None,
color = value # rgba tuple (r,g,b,a) all in [0,1]
# Matplotlib wants a list of xs and a list of ys
xs, ys = unzip(vertices)
ax.fill(xs, ys, facecolor=color, edgecolor=color)
ax.fill(xs, ys, facecolor=color, edgecolor=None)

if not cb_kwargs:
cb_kwargs = dict()
Expand All @@ -272,8 +292,8 @@ def heatmap(data, scale, vmin=None, vmax=None, cmap=None, ax=None,

def heatmapf(func, scale=10, boundary=True, cmap=None, ax=None,
scientific=False, style='triangular', colorbar=True,
permutation=None, vmin=None, vmax=None, cbarlabel=None,
cb_kwargs=None):
permutation=None, vmin=None, vmax=None, adj_vlims=False,
cbarlabel=None, cb_kwargs=None):
"""
Computes func on heatmap partition coordinates and plots heatmap. In other
words, computes the function on lattice points of the simplex (normalized
Expand Down Expand Up @@ -303,6 +323,8 @@ def heatmapf(func, scale=10, boundary=True, cmap=None, ax=None,
The minimum color value, used to normalize colors.
vmax: float
The maximum color value, used to normalize colors.
adj_vlims: bool, False
Redefine min and max color values based on computed averages.
cb_kwargs: dict
dict of kwargs to pass to colorbar

Expand All @@ -318,7 +340,8 @@ def heatmapf(func, scale=10, boundary=True, cmap=None, ax=None,
# Pass everything to the heatmapper
ax = heatmap(data, scale, cmap=cmap, ax=ax, style=style,
scientific=scientific, colorbar=colorbar,
permutation=permutation, vmin=vmin, vmax=vmax,
permutation=permutation, vmin=vmin, vmax=vmax,
adj_vlims=adj_vlims,
cbarlabel=cbarlabel, cb_kwargs=cb_kwargs)
return ax

Expand Down Expand Up @@ -347,8 +370,8 @@ def svg_polygon(coordinates, color):
return polygon


def svg_heatmap(data, scale, filename, vmax=None, vmin=None, style='h',
permutation=None, cmap=None):
def svg_heatmap(data, scale, filename, vmax=None, vmin=None, adj_vlims=False,
style='h', permutation=None, cmap=None):
"""
Create a heatmap in SVG format. Intended for use with very large datasets,
which would require large amounts of RAM using matplotlib. You can convert
Expand All @@ -370,6 +393,8 @@ def svg_heatmap(data, scale, filename, vmax=None, vmin=None, style='h',
The minimum color value, used to normalize colors.
vmax: float
The maximum color value, used to normalize colors.
adj_vlims: bool, False
Redefine min and max color values based on computed averages.
cmap: String or matplotlib.colors.Colormap, None
The name of the Matplotlib colormap to use.
style: String, "h"
Expand Down
6 changes: 3 additions & 3 deletions ternary/ternary_axes_subplot.py
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Original file line number Diff line number Diff line change
Expand Up @@ -436,7 +436,7 @@ def plot_colored_trajectory(self, points, cmap=None, **kwargs):

def heatmap(self, data, scale=None, cmap=None, scientific=False,
style='triangular', colorbar=True, use_rgba=False,
vmin=None, vmax=None, cbarlabel=None, cb_kwargs=None):
vmin=None, vmax=None, adj_vlims=False, cbarlabel=None, cb_kwargs=None):
permutation = self._permutation
if not scale:
scale = self.get_scale()
Expand All @@ -446,12 +446,12 @@ def heatmap(self, data, scale=None, cmap=None, scientific=False,
heatmapping.heatmap(data, scale, cmap=cmap, style=style, ax=ax,
scientific=scientific, colorbar=colorbar,
permutation=permutation, use_rgba=use_rgba,
vmin=vmin, vmax=vmax, cbarlabel=cbarlabel,
vmin=vmin, vmax=vmax, adj_vlims=adj_vlims, cbarlabel=cbarlabel,
cb_kwargs=cb_kwargs)

def heatmapf(self, func, scale=None, cmap=None, boundary=True,
style='triangular', colorbar=True, scientific=False,
vmin=None, vmax=None, cbarlabel=None, cb_kwargs=None):
vmin=None, vmax=None, adj_vlims=False, cbarlabel=None, cb_kwargs=None):
if not scale:
scale = self.get_scale()
if style.lower()[0] == 'd':
Expand Down