# Copyright 2016-present CERN – European Organization for Nuclear Research
#
# 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 itertools import cycle
from typing import List, Tuple
import matplotlib as mpl
from qf_lib.plotting.charts.chart import Chart
[docs]class LineChart(Chart):
"""
Simple line chart. It can plot both QFSeries and DataFrames.
By default the ``start_x`` and ``end_x`` will be determined by the series added to the chart. So whatever
the earliest data point is will determine the ``start_x``.
Parameters
----------
start_x: Any
if not set to None, the chart x-axis will begin at the specified ``start_x`` value
end_x: Any
if not set to None, the chart x-axis will end at the specified ``end_x`` value.
upper_y: Anny
the upper bound of the y-axis.
lower_y: Anny
the lower bound of the y-axis.
log_scale: bool
use log scale.
rotate_x_axis: bool
rotate the x-axis.
"""
def __init__(self, start_x: any = None, end_x: any = None, upper_y: any = None, lower_y: any = None,
log_scale: bool = False, rotate_x_axis=False):
super().__init__(start_x, end_x, upper_y, lower_y)
self.log_scale = log_scale
self._rotate_x_axis = rotate_x_axis
[docs] def plot(self, figsize: Tuple[float, float] = None) -> None:
self._setup_axes_if_necessary(figsize)
if self.log_scale:
self.axes.set_yscale('log')
self._adjust_style()
if self._rotate_x_axis:
self.figure.autofmt_xdate()
self._apply_decorators()
self.axes.set_xmargin(0)
[docs] def apply_data_element_decorators(self, data_element_decorators: List["DataElementDecorator"]):
colors = cycle(Chart.get_axes_colors())
for data_element in data_element_decorators:
plot_settings = data_element.plot_settings.copy()
plot_settings.setdefault("color", next(colors))
series = data_element.data
trimmed_series = self._trim_data(series)
axes = self._ax
if data_element.use_secondary_axes:
mpl.rcParams['axes.spines.right'] = True # Ensure that the right axes spine is shown.
self.setup_secondary_axes_if_necessary()
axes = self._secondary_axes
handle = axes.plot(trimmed_series, **plot_settings)[0]
data_element.legend_artist = handle