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Diffstat (limited to 'trappy/plotter/StaticPlot.py')
| -rw-r--r-- | trappy/plotter/StaticPlot.py | 289 |
1 files changed, 289 insertions, 0 deletions
diff --git a/trappy/plotter/StaticPlot.py b/trappy/plotter/StaticPlot.py new file mode 100644 index 0000000..9b58108 --- /dev/null +++ b/trappy/plotter/StaticPlot.py @@ -0,0 +1,289 @@ +# 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. +# +"""Base matplotlib plotter module""" +from abc import abstractmethod, ABCMeta +from collections import defaultdict as ddict +import matplotlib.pyplot as plt +from trappy.plotter import AttrConf +from trappy.plotter.Constraint import ConstraintManager +from trappy.plotter.PlotLayout import PlotLayout +from trappy.plotter.AbstractDataPlotter import AbstractDataPlotter +from trappy.plotter.ColorMap import ColorMap + + + +class StaticPlot(AbstractDataPlotter): + """ + This class uses :mod:`trappy.plotter.Constraint.Constraint` to + represent different permutations of input parameters. These + constraints are generated by creating an instance of + :mod:`trappy.plotter.Constraint.ConstraintManager`. + + :param traces: The input data + :type traces: a list of :mod:`trappy.trace.FTrace`, + :mod:`trappy.trace.SysTrace`, :mod:`trappy.trace.BareTrace` + or :mod:`pandas.DataFrame` or a single instance of them. + + :param column: specifies the name of the column to + be plotted. + :type column: (str, 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 filters: Filter the column to be plotted as per the + specified criteria. For Example: + :: + + filters = + { + "pid": [ 3338 ], + "cpu": [0, 2, 4], + } + :type filters: dict + + :param per_line: Used to control the number of graphs + in each graph subplot row + :type per_line: int + + :param concat: Draw all the pivots on a single graph + :type concat: bool + + :param permute: Draw one plot for each of the traces specified + :type permute: bool + + :param drawstyle: This argument is forwarded to the matplotlib + corresponding :func:`matplotlib.pyplot.plot` call + + drawing style. + + .. note:: + + step plots are not currently supported for filled + graphs + + :param xlim: A tuple representing the upper and lower xlimits + :type xlim: tuple + + :param ylim: A tuple representing the upper and lower ylimits + :type ylim: tuple + + :param title: A title describing all the generated plots + :type title: str + + :param style: Created pre-styled graphs loaded from + :mod:`trappy.plotter.AttrConf.MPL_STYLE` + :type style: bool + + :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 + + :param legend_ncol: A positive integer that represents the + number of columns in the legend + :type legend_ncol: int + """ + __metaclass__ = ABCMeta + + def __init__(self, traces, templates, **kwargs): + self._fig = None + self._layout = None + super(StaticPlot, self).__init__(traces=traces, + templates=templates) + + self.set_defaults() + + for key in kwargs: + if key in AttrConf.ARGS_TO_FORWARD: + self._attr["args_to_forward"][key] = kwargs[key] + else: + self._attr[key] = kwargs[key] + + if "signals" in self._attr: + self._describe_signals() + + self._check_data() + + if "column" not in self._attr: + raise RuntimeError("Value Column not specified") + + zip_constraints = not self._attr["permute"] + self.c_mgr = ConstraintManager(traces, self._attr["column"], + self.templates, self._attr["pivot"], + self._attr["filters"], + zip_constraints=zip_constraints) + + def savefig(self, *args, **kwargs): + """Save the plot as a PNG fill. This calls into + :mod:`matplotlib.figure.savefig` + """ + + if self._fig is None: + self.view() + self._fig.savefig(*args, **kwargs) + + @abstractmethod + def set_defaults(self): + """Sets the default attrs""" + self._attr["width"] = AttrConf.WIDTH + self._attr["length"] = AttrConf.LENGTH + self._attr["per_line"] = AttrConf.PER_LINE + self._attr["concat"] = AttrConf.CONCAT + self._attr["filters"] = {} + self._attr["style"] = True + self._attr["permute"] = False + self._attr["pivot"] = AttrConf.PIVOT + self._attr["xlim"] = AttrConf.XLIM + self._attr["ylim"] = AttrConf.YLIM + self._attr["title"] = AttrConf.TITLE + self._attr["args_to_forward"] = {} + self._attr["map_label"] = {} + self._attr["_legend_handles"] = [] + self._attr["_legend_labels"] = [] + self._attr["legend_ncol"] = AttrConf.LEGEND_NCOL + + def view(self, test=False): + """Displays the graph""" + + if test: + self._attr["style"] = True + AttrConf.MPL_STYLE["interactive"] = False + + permute = self._attr["permute"] and not self._attr["concat"] + if self._attr["style"]: + with plt.rc_context(AttrConf.MPL_STYLE): + self._resolve(permute, self._attr["concat"]) + else: + self._resolve(permute, self._attr["concat"]) + + def make_title(self, constraint, pivot, permute, concat): + """Generates a title string for an axis""" + if concat: + return str(constraint) + + if permute: + return constraint.get_data_name() + elif pivot != AttrConf.PIVOT_VAL: + return "{0}: {1}".format(self._attr["pivot"], self._attr["map_label"].get(pivot, pivot)) + else: + return "" + + def add_to_legend(self, series_index, handle, constraint, pivot, concat, permute): + """ + Add series handles and names to the legend + A handle is returned from a plot on an axis + e.g. Line2D from axis.plot() + """ + self._attr["_legend_handles"][series_index] = handle + legend_labels = self._attr["_legend_labels"] + + if concat and pivot == AttrConf.PIVOT_VAL: + legend_labels[series_index] = self._attr["column"] + elif concat: + legend_labels[series_index] = "{0}: {1}".format( + self._attr["pivot"], + self._attr["map_label"].get(pivot, pivot) + ) + elif permute: + legend_labels[series_index] = constraint._template.name + ":" + constraint.column + else: + legend_labels[series_index] = str(constraint) + + def _resolve(self, permute, concat): + """Determine what data to plot on which axis""" + pivot_vals, len_pivots = self.c_mgr.generate_pivots(permute) + pivot_vals = list(pivot_vals) + + num_of_axes = len(self.c_mgr) if concat else len_pivots + + # Create a 2D Layout + self._layout = PlotLayout( + self._attr["per_line"], + num_of_axes, + width=self._attr["width"], + length=self._attr["length"], + title=self._attr['title']) + + self._fig = self._layout.get_fig() + + # Determine what constraint to plot and the corresponding pivot value + if permute: + legend_len = self.c_mgr._max_len + pivots = [y for _, y in pivot_vals] + c_dict = {c : str(c) for c in self.c_mgr} + c_list = sorted(c_dict.items(), key=lambda x: (x[1].split(":")[-1], x[1].split(":")[0])) + constraints = [c[0] for c in c_list] + cp_pairs = [(c, p) for c in constraints for p in sorted(set(pivots))] + else: + legend_len = len_pivots if concat else len(self.c_mgr) + pivots = pivot_vals + cp_pairs = [(c, p) for c in self.c_mgr for p in pivots if p in c.result] + + # Initialise legend data and colormap + self._attr["_legend_handles"] = [None] * legend_len + self._attr["_legend_labels"] = [None] * legend_len + + if "colors" in self._attr: + self._cmap = ColorMap.rgb_cmap(self._attr["colors"]) + else: + self._cmap = ColorMap(legend_len) + + # Group constraints/series with the axis they are to be plotted on + figure_data = ddict(list) + for i, (constraint, pivot) in enumerate(cp_pairs): + axis = self._layout.get_axis(constraint.trace_index if concat else i) + figure_data[axis].append((constraint, pivot)) + + # Plot each axis + for axis, series_list in figure_data.iteritems(): + self.plot_axis( + axis, + series_list, + permute, + self._attr["concat"], + self._attr["args_to_forward"] + ) + if self._attr["xlim"]: + axis.set_xlim(self._attr["xlim"]) + if self._attr["ylim"]: + axis.set_ylim(self._attr["ylim"]) + + # Show legend + legend = self._fig.legend(self._attr["_legend_handles"], + self._attr["_legend_labels"], + loc='lower center', + ncol=self._attr["legend_ncol"], + borderaxespad=0.) + legend.get_frame().set_facecolor('#F4F4F4') + + self._layout.finish(num_of_axes) + + def plot_axis(self, axis, series_list, permute, concat, args_to_forward): + """Internal Method called to plot data (series_list) on a given axis""" + raise NotImplementedError("Method Not Implemented") |