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# Copyright 2016-2017 ARM Limited
#
# 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.
#
"""
This class sublclasses :mod:`trappy.plotter.StaticPlot.StaticPlot` to
implement a bar plot.
"""
import numpy as np
from trappy.plotter.StaticPlot import StaticPlot
class BarPlot(StaticPlot):
"""BarPlot can plot data as vertical bars
Values are plotted against their position in the list of data.
:param traces: The input data
:type traces: A single instance or a list of :mod:`trappy.trace.FTrace`,
:mod:`trappy.trace.SysTrace`, :mod:`trappy.trace.BareTrace` or
:mod:`pandas.DataFrame`.
:param column: specifies the name of the column to be plotted.
:type column: str or list(str)
:param templates: TRAPpy events
.. note::
This is not required if a :mod:`pandas.DataFrame` is
used
:type templates: :mod:`trappy.base.Base`
:param signals: A string of the type event_name:column
to indicate the value that needs to be plotted
.. note::
- Only one of `signals` or both `templates` and
`columns` should be specified
- Signals format won't work for :mod:`pandas.DataFrame`
input
:type signals: str or list(string)
:param title: A title describing the generated plots
:type title: str
:param stacked: The series are grouped by default. If you want a
stacked plot, set stacked to True.
:type stacked: bool
:param spacing: A proportion of the size of each group which
should be used as the spacing between the groups. e.g. 0.2
(default) means that 1/5 of the groups total width is used as
a spacing between groups.
:type spacing: float
"""
def __init__(self, traces, templates=None, **kwargs):
# Default keys, each can be overridden in kwargs
super(BarPlot, self).__init__(
traces=traces,
templates=templates,
**kwargs)
def set_defaults(self):
"""Sets the default attrs"""
super(BarPlot, self).set_defaults()
self._attr["spacing"] = 0.2
self._attr["stacked"] = False
def plot_axis(self, axis, series_list, permute, concat, args_to_forward):
"""Internal Method called to plot data (series_list) on a given axis"""
stacked = self._attr["stacked"]
#Figure out how many bars per group
bars_in_group = 1 if stacked else len(series_list)
#Get the width of a group
group_width = 1.0 - self._attr["spacing"]
bar_width = group_width / bars_in_group
#Keep a list of the tops of bars to plot stacks
#Start with a list of 0s to put the first bars at the bottom
value_list = [c.result[p].values for (c, p) in series_list]
end_of_previous = [0] * max(len(x) for x in value_list)
for i, (constraint, pivot) in enumerate(series_list):
result = constraint.result
bar_anchor = np.arange(len(result[pivot].values))
if not stacked:
bar_anchor = bar_anchor + i * bar_width
line_2d_list = axis.bar(
bar_anchor,
result[pivot].values,
bottom=end_of_previous,
width=bar_width,
color=self._cmap.cmap(i),
**args_to_forward
)
if stacked:
end_of_previous = [x + y for (x, y) in zip(end_of_previous, result[pivot].values)]
axis.set_title(self.make_title(constraint, pivot, permute, concat))
self.add_to_legend(i, line_2d_list[0], constraint, pivot, concat, permute)
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