# Copyright 2019-2020 The Lux Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from lux.vislib.matplotlib.MatplotlibChart import MatplotlibChart
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from lux.utils.utils import matplotlib_setup
[docs]class Heatmap(MatplotlibChart):
"""
Heatmap is a subclass of MatplotlibChart that render as a heatmap.
All rendering properties for heatmap are set here.
See Also
--------
matplotlib.org
"""
def __init__(self, vis, fig, ax):
super().__init__(vis, fig, ax)
def __repr__(self):
return f"Heatmap <{str(self.vis)}>"
[docs] def initialize_chart(self):
# return NotImplemented
x_attr = self.vis.get_attr_by_channel("x")[0]
y_attr = self.vis.get_attr_by_channel("y")[0]
x_attr_abv = x_attr.attribute
y_attr_abv = y_attr.attribute
if len(x_attr.attribute) > 25:
x_attr_abv = x_attr.attribute[:15] + "..." + x_attr.attribute[-10:]
if len(y_attr.attribute) > 25:
y_attr_abv = y_attr.attribute[:15] + "..." + y_attr.attribute[-10:]
df = self.data
plot_code = ""
color_attr = self.vis.get_attr_by_channel("color")
color_attr_name = ""
color_map = "Blues"
if len(color_attr) == 1:
self.fig, self.ax = matplotlib_setup(6, 4)
color_attr_name = color_attr[0].attribute
df = pd.pivot_table(data=df, index="xBinStart", values=color_attr_name, columns="yBinStart")
color_map = "viridis"
plot_code += f"""df = pd.pivot_table(
data=df,
index='xBinStart',
values='{color_attr_name}',
columns='yBinStart')\n"""
else:
df = pd.pivot_table(data=df, index="xBinStart", values="count", columns="yBinStart")
df = df.apply(lambda x: np.log(x), axis=1)
plot_code += f"""df = pd.pivot_table(
df,
index='xBinStart',
values='count',
columns='yBinStart')\n"""
plot_code += f"df = df.apply(lambda x: np.log(x), axis=1)\n"
df = df.values
plt.imshow(df, cmap=color_map)
self.ax.set_aspect("auto")
plt.gca().invert_yaxis()
colorbar_code = ""
if len(color_attr) == 1:
cbar = plt.colorbar(label=color_attr_name)
cbar.outline.set_linewidth(0)
colorbar_code += f"cbar = plt.colorbar(label='{color_attr_name}')\n"
colorbar_code += f"cbar.outline.set_linewidth(0)\n"
self.ax.set_xlabel(x_attr_abv)
self.ax.set_ylabel(y_attr_abv)
self.ax.grid(False)
self.code += "import numpy as np\n"
self.code += "from math import nan\n"
self.code += f"df = pd.DataFrame({str(self.data.to_dict())})\n"
self.code += plot_code
self.code += f"df = df.values\n"
self.code += f"fig, ax = plt.subplots()\n"
self.code += f"plt.imshow(df, cmap='{color_map}')\n"
self.code += f"ax.set_aspect('auto')\n"
self.code += f"plt.gca().invert_yaxis()\n"
self.code += colorbar_code
self.code += f"ax.set_xlabel('{x_attr_abv}')\n"
self.code += f"ax.set_ylabel('{y_attr_abv}')\n"
self.code += f"ax.grid(False)\n"