def heatmap(d, scale, vmin=None, vmax=None, cmap=None, ax=None,
scientific=False, style='triangular', colorbar=True):
"""
Plots heatmap of given color values.
Parameters
----------
d: dictionary
A dictionary mapping the i, j polygon to the heatmap color, where
i + j + k = scale.
scale: Integer
The scale used to partition the simplex.
vmin: float, 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.
cmap: String or matplotlib.colors.Colormap, None
The name of the Matplotlib colormap to use.
ax: Matplotlib AxesSubplot, None
The subplot to draw on.
scientific: Bool, False
Whether to use scientific notation for colorbar numbers.
style: String, "triangular"
The style of the heatmap, "triangular" or "hexagonal".
colorbar: bool, True
Show colorbar.
Returns
-------
ax: The matplotlib axis
"""
if not ax:
fig, ax = pyplot.subplots()
cmap = get_cmap(cmap)
if not vmin:
vmin = min(d.values())
if not vmax:
vmax = max(d.values())
style = style.lower()[0]
if style not in ["t", "h"]:
raise ValueError("Heatmap style must be 'triangular' or 'hexagonal'")
if style == "h":
mapping_functions = [(hexagon_coordinates, d.items())]
else:
mapping_functions = [(triangle_coordinates, d.items()), (alt_triangle_coordinates, alt_value_iterator(d))]
# Color data triangles or hexagons
for vertex_function, iterator in mapping_functions:
for key, value in iterator:
if value is not None:
i, j = key
k = scale - i - j
vertices = vertex_function(i, j, k)
color = colormapper(value, vmin, vmax, cmap=cmap)
# Matplotlib wants a list of xs and a list of ys
xs, ys = unzip(vertices)
ax.fill(xs, ys, facecolor=color, edgecolor=color)
if colorbar:
colorbar_hack(ax, vmin, vmax, cmap, scientific=scientific)
return ax
def svg_heatmap(data, scale, filename, vmax=None, vmin=None, 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
the image to another format with e.g. ImageMagick:
convert -density 1200 -resize -rotate 180 1000x1000 your.svg your.png
Parameters
----------
data: dictionary or k, v generator
A dictionary mapping the i, j polygon to the heatmap color, where
i + j + k = scale. If using a generator, style must be 'h'.
scale: Integer
The scale used to partition the simplex.
filename: string
The filename to write the SVG data to.
vmin: float
The minimum color value, used to normalize colors.
vmax: float
The maximum color value, used to normalize colors.
cmap: String or matplotlib.colors.Colormap, None
The name of the Matplotlib colormap to use.
style: String, "h"
The style of the heatmap, "triangular", "dual-triangular" or "hexagonal"
permutation: string, None
A permutation of the coordinates
"""
style = style.lower()[0]
if style not in ["t", "h", 'd']:
raise ValueError("Heatmap style must be 'triangular', 'dual-triangular', or 'hexagonal'")
if not isinstance(data, dict):
if not style == 'h':
raise ValueError, "Data can only be given as a generator for hexagonal style heatmaps because of blending for adjacent polygons."
elif vmax is None or vmin is None:
raise ValueError, "vmax and vmin must be supplied for data given as a generator."
cmap = get_cmap(cmap)
if not vmin:
vmin = min(data.values())
if not vmax:
vmax = max(data.values())
height = scale * numpy.sqrt(3) / 2 + 2
output_file = open(filename, 'w')
output_file.write('<svg height="%s" width="%s">\n' % (height, scale))
vertices_values = polygon_generator(data, scale, style,
permutation=permutation)
# Draw the polygons and color them
for vertices, value in vertices_values:
color = colormapper(value, vmin, vmax, cmap=cmap)
output_file.write(svg_polygon(vertices, color))
output_file.write('</svg>\n')
def svg_heatmap(data,
scale,
filename,
vmax=None,
vmin=None,
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
the image to another format with e.g. ImageMagick:
convert -density 1200 -resize -rotate 180 1000x1000 your.svg your.png
Parameters
----------
data: dictionary or k, v generator
A dictionary mapping the i, j polygon to the heatmap color, where
i + j + k = scale. If using a generator, style must be 'h'.
scale: Integer
The scale used to partition the simplex.
filename: string
The filename to write the SVG data to.
vmin: float
The minimum color value, used to normalize colors.
vmax: float
The maximum color value, used to normalize colors.
cmap: String or matplotlib.colors.Colormap, None
The name of the Matplotlib colormap to use.
style: String, "h"
The style of the heatmap, "triangular", "dual-triangular" or "hexagonal"
permutation: string, None
A permutation of the coordinates
"""
style = style.lower()[0]
if style not in ["t", "h", 'd']:
raise ValueError(
"Heatmap style must be 'triangular', 'dual-triangular', or 'hexagonal'"
)
if not isinstance(data, dict):
if not style == 'h':
raise ValueError, "Data can only be given as a generator for hexagonal style heatmaps because of blending for adjacent polygons."
elif vmax is None or vmin is None:
raise ValueError, "vmax and vmin must be supplied for data given as a generator."
cmap = get_cmap(cmap)
if not vmin:
vmin = min(data.values())
if not vmax:
vmax = max(data.values())
height = scale * numpy.sqrt(3) / 2 + 2
output_file = open(filename, 'w')
output_file.write('<svg height="%s" width="%s">\n' % (height, scale))
vertices_values = polygon_generator(data,
scale,
style,
permutation=permutation)
# Draw the polygons and color them
for vertices, value in vertices_values:
color = colormapper(value, vmin, vmax, cmap=cmap)
output_file.write(svg_polygon(vertices, color))
output_file.write('</svg>\n')
def heatmap(data, scale, vmin=None, vmax=None, cmap=None, ax=None,
scientific=False, style='triangular', colorbar=True,
permutation=None, colormap=True):
"""
Plots heatmap of given color values.
Parameters
----------
data: dictionary
A dictionary mapping the i, j polygon to the heatmap color, where
i + j + k = scale.
scale: Integer
The scale used to partition the simplex.
vmin: float, 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.
cmap: String or matplotlib.colors.Colormap, None
The name of the Matplotlib colormap to use.
ax: Matplotlib AxesSubplot, None
The subplot to draw on.
scientific: Bool, False
Whether to use scientific notation for colorbar numbers.
style: String, "triangular"
The style of the heatmap, "triangular", "dual-triangular" or "hexagonal"
colorbar: bool, True
Show colorbar.
permutation: string, None
A permutation of the coordinates
Returns
-------
ax: The matplotlib axis
"""
if not ax:
fig, ax = pyplot.subplots()
# If not colormap, then make the RGBA values numpy arrays so that they can
# be averaged.
if not colormap:
for k, v in data.items():
data[k] = numpy.array(v)
else:
cmap = get_cmap(cmap)
if not vmin:
vmin = min(data.values())
if not vmax:
vmax = max(data.values())
style = style.lower()[0]
if style not in ["t", "h", 'd']:
raise ValueError("Heatmap style must be 'triangular', 'dual-triangular', or 'hexagonal'")
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:
continue
if colormap:
color = colormapper(value, vmin, vmax, cmap=cmap)
else:
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)
if colorbar and colormap:
colorbar_hack(ax, vmin, vmax, cmap, scientific=scientific)
return ax
def heatmap(data,
scale,
vmin=None,
vmax=None,
cmap=None,
ax=None,
scientific=False,
style='triangular',
colorbar=True,
permutation=None):
"""
Plots heatmap of given color values.
Parameters
----------
data: dictionary
A dictionary mapping the i, j polygon to the heatmap color, where
i + j + k = scale.
scale: Integer
The scale used to partition the simplex.
vmin: float, 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.
cmap: String or matplotlib.colors.Colormap, None
The name of the Matplotlib colormap to use.
ax: Matplotlib AxesSubplot, None
The subplot to draw on.
scientific: Bool, False
Whether to use scientific notation for colorbar numbers.
style: String, "triangular"
The style of the heatmap, "triangular", "dual-triangular" or "hexagonal"
colorbar: bool, True
Show colorbar.
permutation: string, None
A permutation of the coordinates
Returns
-------
ax: The matplotlib axis
"""
if not ax:
fig, ax = pyplot.subplots()
cmap = get_cmap(cmap)
if not vmin:
vmin = min(data.values())
if not vmax:
vmax = max(data.values())
style = style.lower()[0]
if style not in ["t", "h", 'd']:
raise ValueError(
"Heatmap style must be 'triangular', 'dual-triangular', or 'hexagonal'"
)
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:
continue
color = colormapper(value, vmin, vmax, cmap=cmap)
# Matplotlib wants a list of xs and a list of ys
xs, ys = unzip(vertices)
ax.fill(xs, ys, facecolor=color, edgecolor=color)
if colorbar:
colorbar_hack(ax, vmin, vmax, cmap, scientific=scientific)
return ax