# 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 get_agg_title
import altair as alt
from lux.utils.utils import matplotlib_setup
[docs]class LineChart(MatplotlibChart):
"""
LineChart is a subclass of MatplotlibChart that render as a line charts.
All rendering properties for line charts are set here.
See Also
--------
matplotlib.org
"""
def __init__(self, dobj, fig, ax):
super().__init__(dobj, fig, ax)
def __repr__(self):
return f"Line Chart <{str(self.vis)}>"
[docs] def initialize_chart(self):
self.tooltip = False # tooltip looks weird for line chart
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:]
self.data = self.data.dropna(subset=[x_attr.attribute, y_attr.attribute])
df = self.data
x_pts = df[x_attr.attribute]
y_pts = df[y_attr.attribute]
plot_code = ""
color_attr = self.vis.get_attr_by_channel("color")
if len(color_attr) == 1:
self.fig, self.ax = matplotlib_setup(6, 4)
color_attr_name = color_attr[0].attribute
color_attr_type = color_attr[0].data_type
colors = df[color_attr_name].values
unique = list(set(colors))
d_x = {}
d_y = {}
for i in unique:
d_x[i] = []
d_y[i] = []
for i in range(len(colors)):
d_x[colors[i]].append(x_pts[i])
d_y[colors[i]].append(y_pts[i])
for i in range(len(unique)):
self.ax.plot(d_x[unique[i]], d_y[unique[i]], label=unique[i])
plot_code += f"""ax.plot(
{d_x}[{unique}[{i}]],
{d_y}[{unique}[{i}]],
label={unique}[{i}])\n"""
self.ax.legend(
title=color_attr_name, bbox_to_anchor=(1.05, 1), loc="upper left", ncol=1, frameon=False
)
plot_code += f"""ax.legend(
title='{color_attr_name}',
bbox_to_anchor=(1.05, 1),
loc='upper left',
ncol=1,
frameon=False,)\n"""
else:
self.ax.plot(x_pts, y_pts)
plot_code += f"ax.plot(x_pts, y_pts)\n"
x_label = ""
y_label = ""
if y_attr.data_model == "measure":
agg_title = get_agg_title(y_attr)
self.ax.set_xlabel(x_attr_abv)
self.ax.set_ylabel(agg_title)
x_label = x_attr_abv
y_label = agg_title
else:
agg_title = get_agg_title(x_attr)
self.ax.set_xlabel(agg_title)
self.ax.set_ylabel(y_attr_abv)
x_label = agg_title
y_label = y_attr_abv
self.code += "import numpy as np\n"
self.code += "from math import nan\n"
self.code += "from pandas import Timestamp\n"
self.code += f"df = pd.DataFrame({str(self.data.to_dict())})\n"
self.code += f"fig, ax = plt.subplots()\n"
self.code += f"x_pts = df['{x_attr.attribute}']\n"
self.code += f"y_pts = df['{y_attr.attribute}']\n"
self.code += plot_code
self.code += f"ax.set_xlabel('{x_label}')\n"
self.code += f"ax.set_ylabel('{y_label}')\n"