def plot(self, level, per_line=3):
"""Temporary function to plot data. Expected to be
implemented in plotter
"""
num_plots = self._first_agg.topology.level_span(level)
result_1 = self._first_agg.aggregate(level=level, **self._agg_kwargs)
result_2 = self._second_agg.aggregate(level=level, **self._agg_kwargs)
layout = PlotLayout(per_line, num_plots)
plot_index = 0
for group_id, result_group in enumerate(result_1):
s_x = result_group
s_y = result_2[group_id]
s_x = self._resample(s_x)
s_y = self._resample(s_y)
s_x, s_y = shift_series(s_x, s_y, self._shift)
ymax = 1.25 + max(max(s_x.values), max(s_y.values)) + 1
ymin = min(min(s_x.values), min(s_y.values)) - 1
ylim = [ymin, ymax]
ylim = [-1, 3]
axis = layout.get_axis(plot_index)
axis.plot(s_x.index, s_x.values)
axis.plot(s_y.index, s_y.values)
axis.set_ylim(ylim)
plot_index += 1
layout.finish(plot_index)
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
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"]
)
# 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(self, level, per_line=3):
"""Temporary function to plot data. Expected to be
implemented in plotter
:param level: Topological Level (level in :mod:`trappy.stats.Topology`)
:type level: str
:param per_line: Number of plots per line
:type per_line: int
"""
from trappy.plotter.PlotLayout import PlotLayout
num_plots = self._first_agg.topology.level_span(level)
result_1 = self._first_agg.aggregate(level=level, **self._agg_kwargs)
result_2 = self._second_agg.aggregate(level=level, **self._agg_kwargs)
layout = PlotLayout(per_line, num_plots)
plot_index = 0
for group_id, result_group in enumerate(result_1):
s_x = result_group
s_y = result_2[group_id]
s_x = self._resample(s_x)
s_y = self._resample(s_y)
s_x, s_y = shift_series(s_x, s_y, self._shift)
ymax = 1.25 + max(max(s_x.values), max(s_y.values)) + 1
ymin = min(min(s_x.values), min(s_y.values)) - 1
ylim = [ymin, ymax]
ylim = [-1, 3]
axis = layout.get_axis(plot_index)
axis.plot(s_x.index, s_x.values)
axis.plot(s_y.index, s_y.values)
axis.set_ylim(ylim)
plot_index += 1
layout.finish(plot_index)
def plot(self, level, per_line=3):
"""Temporary function to plot data. Expected to be
implemented in plotter
:param level: Topological Level (level in :mod:`trappy.stats.Topology`)
:type level: str
:param per_line: Number of plots per line
:type per_line: int
"""
from trappy.plotter.PlotLayout import PlotLayout
num_plots = self._first_agg.topology.level_span(level)
result_1 = self._first_agg.aggregate(level=level, **self._agg_kwargs)
result_2 = self._second_agg.aggregate(level=level, **self._agg_kwargs)
layout = PlotLayout(per_line, num_plots)
plot_index = 0
for group_id, result_group in enumerate(result_1):
s_x = result_group
s_y = result_2[group_id]
s_x = self._resample(s_x)
s_y = self._resample(s_y)
s_x, s_y = shift_series(s_x, s_y, self._shift)
ymax = 1.25 + max(max(s_x.values), max(s_y.values)) + 1
ymin = min(min(s_x.values), min(s_y.values)) - 1
ylim = [ymin, ymax]
ylim = [-1, 3]
axis = layout.get_axis(plot_index)
axis.plot(s_x.index, s_x.values)
axis.plot(s_y.index, s_y.values)
axis.set_ylim(ylim)
plot_index += 1
layout.finish(plot_index)
class StaticPlot(with_metaclass(ABCMeta, 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
"""
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.items():
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")
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.items():
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)
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` 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)
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.XLIM
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
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"]
)
# 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")
class LinePlot(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 run: The input data
:type run: :mod:`trappy.run.Run` or :mod:`pandas.DataFrame`, list or single
: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 fill: Fill the area under the plots
:type fill: bool
:param permute: Draw one plot for each of the runs 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 style: Created pre-styled graphs loaded from
:mod:`trappy.plotter.AttrConf.MPL_STYLE`
:type style: bool
"""
def __init__(self, runs, templates=None, **kwargs):
# Default keys, each can be overridden in kwargs
self._attr = {}
self.runs = runs
self.templates = templates
self.set_defaults()
self._fig = None
self._layout = None
self._check_data()
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 "column" not in self._attr:
raise RuntimeError("Value Column not specified")
zip_constraints = not self._attr["permute"]
self.c_mgr = ConstraintManager(
runs,
self._attr["column"],
templates,
self._attr["pivot"],
self._attr["filters"], zip_constraints)
self._check_add_scatter()
super(LinePlot, self).__init__()
def savefig(self, *args, **kwargs):
"""Save the plot as a PNG fill. This calls into
:mod:`matplotlib.figure.savefig`
"""
if self._fig == None:
self.view()
self._fig.savefig(*args, **kwargs)
def view(self, test=False):
"""Displays the graph"""
if test:
self._attr["style"] = True
AttrConf.MPL_STYLE["interactive"] = False
if self._attr["concat"]:
if self._attr["style"]:
with plt.rc_context(AttrConf.MPL_STYLE):
self._plot_concat()
else:
self._plot_concat()
else:
if self._attr["style"]:
with plt.rc_context(AttrConf.MPL_STYLE):
self._plot(self._attr["permute"])
else:
self._plot(self._attr["permute"])
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["fill"] = AttrConf.FILL
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.XLIM
self._attr["args_to_forward"] = {}
self._attr["scatter"] = AttrConf.PLOT_SCATTER
def _check_add_scatter(self):
"""Check if a scatter plot is needed
and augment the forwarded args accordingly"""
if self._attr["scatter"]:
self._attr["args_to_forward"]["linestyle"] = ""
self._attr["args_to_forward"]["marker"] = "o"
if "point_size" in self._attr:
self._attr["args_to_forward"]["markersize"] = \
self._attr["point_size"]
def _plot(self, permute):
"""Internal Method called to draw the plot"""
pivot_vals, len_pivots = self.c_mgr.generate_pivots(permute)
# Create a 2D Layout
self._layout = PlotLayout(
self._attr["per_line"],
len_pivots,
width=self._attr["width"],
length=self._attr["length"])
self._fig = self._layout.get_fig()
legend_str = []
plot_index = 0
if permute:
legend = [None] * self.c_mgr._max_len
cmap = ColorMap(self.c_mgr._max_len)
else:
legend = [None] * len(self.c_mgr)
cmap = ColorMap(len(self.c_mgr))
for p_val in pivot_vals:
l_index = 0
for constraint in self.c_mgr:
if permute:
run_idx, pivot = p_val
if constraint.run_index != run_idx:
continue
legend_str.append(constraint._column)
l_index = self.c_mgr.get_column_index(constraint)
title = constraint.get_data_name() + ":"
else:
pivot = p_val
legend_str.append(str(constraint))
title = ""
result = constraint.result
if pivot in result:
axis = self._layout.get_axis(plot_index)
line_2d_list = axis.plot(
result[pivot].index,
result[pivot].values,
color=cmap.cmap(l_index),
**self._attr["args_to_forward"])
if self._attr["fill"]:
drawstyle = line_2d_list[0].get_drawstyle()
# This has been fixed in upstream matplotlib
if drawstyle.startswith("steps"):
raise UserWarning("matplotlib does not support fill for step plots")
xdat, ydat = line_2d_list[0].get_data(orig=False)
axis.fill_between(xdat,
axis.get_ylim()[0],
ydat,
facecolor=cmap.cmap(l_index),
alpha=AttrConf.ALPHA)
legend[l_index] = line_2d_list[0]
if self._attr["xlim"] != None:
axis.set_xlim(self._attr["xlim"])
if self._attr["ylim"] != None:
axis.set_ylim(self._attr["ylim"])
else:
axis = self._layout.get_axis(plot_index)
axis.plot([], [], **self._attr["args_to_forward"])
l_index += 1
if pivot == AttrConf.PIVOT_VAL:
title += ",".join(self._attr["column"])
else:
title += "{0}: {1}".format(self._attr["pivot"], pivot)
axis.set_title(title)
plot_index += 1
for l_idx, legend_line in enumerate(legend):
if not legend_line:
del legend[l_idx]
del legend_str[l_idx]
self._fig.legend(legend, legend_str)
self._layout.finish(len_pivots)
def _plot_concat(self):
"""Plot all lines on a single figure"""
pivot_vals, len_pivots = self.c_mgr.generate_pivots()
cmap = ColorMap(len_pivots)
self._layout = PlotLayout(self._attr["per_line"], len(self.c_mgr),
width=self._attr["width"],
length=self._attr["length"])
self._fig = self._layout.get_fig()
legend = [None] * len_pivots
legend_str = [""] * len_pivots
plot_index = 0
for constraint in self.c_mgr:
result = constraint.result
title = str(constraint)
result = constraint.result
pivot_index = 0
for pivot in pivot_vals:
if pivot in result:
axis = self._layout.get_axis(plot_index)
line_2d_list = axis.plot(
result[pivot].index,
result[pivot].values,
color=cmap.cmap(pivot_index),
**self._attr["args_to_forward"])
if self._attr["xlim"] != None:
axis.set_xlim(self._attr["xlim"])
if self._attr["ylim"] != None:
axis.set_ylim(self._attr["ylim"])
legend[pivot_index] = line_2d_list[0]
if self._attr["fill"]:
drawstyle = line_2d_list[0].get_drawstyle()
if drawstyle.startswith("steps"):
# This has been fixed in upstream matplotlib
raise UserWarning("matplotlib does not support fill for step plots")
xdat, ydat = line_2d_list[0].get_data(orig=False)
axis.fill_between(xdat,
axis.get_ylim()[0],
ydat,
facecolor=cmap.cmap(pivot_index),
alpha=AttrConf.ALPHA)
if pivot == AttrConf.PIVOT_VAL:
legend_str[pivot_index] = self._attr["column"]
else:
legend_str[pivot_index] = "{0}: {1}".format(self._attr["pivot"], pivot)
else:
axis = self._layout.get_axis(plot_index)
axis.plot(
[],
[],
color=cmap.cmap(pivot_index),
**self._attr["args_to_forward"])
pivot_index += 1
plot_index += 1
self._fig.legend(legend, legend_str)
plot_index = 0
for constraint in self.c_mgr:
self._layout.get_axis(plot_index).set_title(str(constraint))
plot_index += 1
self._layout.finish(len(self.c_mgr))
def _plot_concat(self):
"""Plot all lines on a single figure"""
pivot_vals, len_pivots = self.c_mgr.generate_pivots()
cmap = ColorMap(len_pivots)
self._layout = PlotLayout(self._attr["per_line"], len(self.c_mgr),
width=self._attr["width"],
length=self._attr["length"])
self._fig = self._layout.get_fig()
legend = [None] * len_pivots
legend_str = [""] * len_pivots
plot_index = 0
for constraint in self.c_mgr:
result = constraint.result
title = str(constraint)
result = constraint.result
pivot_index = 0
for pivot in pivot_vals:
if pivot in result:
axis = self._layout.get_axis(plot_index)
line_2d_list = axis.plot(
result[pivot].index,
result[pivot].values,
color=cmap.cmap(pivot_index),
**self._attr["args_to_forward"])
if self._attr["xlim"] != None:
axis.set_xlim(self._attr["xlim"])
if self._attr["ylim"] != None:
axis.set_ylim(self._attr["ylim"])
legend[pivot_index] = line_2d_list[0]
if self._attr["fill"]:
drawstyle = line_2d_list[0].get_drawstyle()
if drawstyle.startswith("steps"):
# This has been fixed in upstream matplotlib
raise UserWarning("matplotlib does not support fill for step plots")
xdat, ydat = line_2d_list[0].get_data(orig=False)
axis.fill_between(xdat,
axis.get_ylim()[0],
ydat,
facecolor=cmap.cmap(pivot_index),
alpha=AttrConf.ALPHA)
if pivot == AttrConf.PIVOT_VAL:
legend_str[pivot_index] = self._attr["column"]
else:
legend_str[pivot_index] = "{0}: {1}".format(self._attr["pivot"], pivot)
else:
axis = self._layout.get_axis(plot_index)
axis.plot(
[],
[],
color=cmap.cmap(pivot_index),
**self._attr["args_to_forward"])
pivot_index += 1
plot_index += 1
self._fig.legend(legend, legend_str)
plot_index = 0
for constraint in self.c_mgr:
self._layout.get_axis(plot_index).set_title(str(constraint))
plot_index += 1
self._layout.finish(len(self.c_mgr))
def _plot(self, permute):
"""Internal Method called to draw the plot"""
pivot_vals, len_pivots = self.c_mgr.generate_pivots(permute)
# Create a 2D Layout
self._layout = PlotLayout(
self._attr["per_line"],
len_pivots,
width=self._attr["width"],
length=self._attr["length"])
self._fig = self._layout.get_fig()
legend_str = []
plot_index = 0
if permute:
legend = [None] * self.c_mgr._max_len
cmap = ColorMap(self.c_mgr._max_len)
else:
legend = [None] * len(self.c_mgr)
cmap = ColorMap(len(self.c_mgr))
for p_val in pivot_vals:
l_index = 0
for constraint in self.c_mgr:
if permute:
run_idx, pivot = p_val
if constraint.run_index != run_idx:
continue
legend_str.append(constraint._column)
l_index = self.c_mgr.get_column_index(constraint)
title = constraint.get_data_name() + ":"
else:
pivot = p_val
legend_str.append(str(constraint))
title = ""
result = constraint.result
if pivot in result:
axis = self._layout.get_axis(plot_index)
line_2d_list = axis.plot(
result[pivot].index,
result[pivot].values,
color=cmap.cmap(l_index),
**self._attr["args_to_forward"])
if self._attr["fill"]:
drawstyle = line_2d_list[0].get_drawstyle()
# This has been fixed in upstream matplotlib
if drawstyle.startswith("steps"):
raise UserWarning("matplotlib does not support fill for step plots")
xdat, ydat = line_2d_list[0].get_data(orig=False)
axis.fill_between(xdat,
axis.get_ylim()[0],
ydat,
facecolor=cmap.cmap(l_index),
alpha=AttrConf.ALPHA)
legend[l_index] = line_2d_list[0]
if self._attr["xlim"] != None:
axis.set_xlim(self._attr["xlim"])
if self._attr["ylim"] != None:
axis.set_ylim(self._attr["ylim"])
else:
axis = self._layout.get_axis(plot_index)
axis.plot([], [], **self._attr["args_to_forward"])
l_index += 1
if pivot == AttrConf.PIVOT_VAL:
title += ",".join(self._attr["column"])
else:
title += "{0}: {1}".format(self._attr["pivot"], pivot)
axis.set_title(title)
plot_index += 1
for l_idx, legend_line in enumerate(legend):
if not legend_line:
del legend[l_idx]
del legend_str[l_idx]
self._fig.legend(legend, legend_str)
self._layout.finish(len_pivots)
def _plot_concat(self):
"""Plot all lines on a single figure"""
pivot_vals, len_pivots = self.c_mgr.generate_pivots()
cmap = ColorMap(len_pivots)
self._layout = PlotLayout(self._attr["per_line"],
len(self.c_mgr),
width=self._attr["width"],
length=self._attr["length"])
self._fig = self._layout.get_fig()
legend = [None] * len_pivots
legend_str = [""] * len_pivots
plot_index = 0
for constraint in self.c_mgr:
result = constraint.result
title = str(constraint)
result = constraint.result
pivot_index = 0
for pivot in pivot_vals:
if pivot in result:
axis = self._layout.get_axis(plot_index)
line_2d_list = axis.plot(result[pivot].index,
result[pivot].values,
color=cmap.cmap(pivot_index),
**self._attr["args_to_forward"])
if self._attr["xlim"] != None:
axis.set_xlim(self._attr["xlim"])
if self._attr["ylim"] != None:
axis.set_ylim(self._attr["ylim"])
legend[pivot_index] = line_2d_list[0]
if self._attr["fill"]:
drawstyle = line_2d_list[0].get_drawstyle()
if drawstyle.startswith("steps"):
# This has been fixed in upstream matplotlib
raise UserWarning(
"matplotlib does not support fill for step plots"
)
xdat, ydat = line_2d_list[0].get_data(orig=False)
axis.fill_between(xdat,
axis.get_ylim()[0],
ydat,
facecolor=cmap.cmap(pivot_index),
alpha=AttrConf.ALPHA)
if pivot == AttrConf.PIVOT_VAL:
legend_str[pivot_index] = self._attr["column"]
else:
legend_str[pivot_index] = "{0}: {1}".format(
self._attr["pivot"], pivot)
else:
axis = self._layout.get_axis(plot_index)
axis.plot([], [],
color=cmap.cmap(pivot_index),
**self._attr["args_to_forward"])
pivot_index += 1
plot_index += 1
self._fig.legend(legend, legend_str)
plot_index = 0
for constraint in self.c_mgr:
self._layout.get_axis(plot_index).set_title(str(constraint))
plot_index += 1
self._layout.finish(len(self.c_mgr))
class LinePlot(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 run: The input data
:type run: :mod:`trappy.run.Run` or :mod:`pandas.DataFrame`, list or single
: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 fill: Fill the area under the plots
:type fill: bool
:param permute: Draw one plot for each of the runs 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 style: Created pre-styled graphs loaded from
:mod:`trappy.plotter.AttrConf.MPL_STYLE`
:type style: bool
"""
def __init__(self, runs, templates=None, **kwargs):
# Default keys, each can be overridden in kwargs
self._attr = {}
self.runs = runs
self.templates = templates
self.set_defaults()
self._fig = None
self._layout = None
self._check_data()
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 "column" not in self._attr:
raise RuntimeError("Value Column not specified")
zip_constraints = not self._attr["permute"]
self.c_mgr = ConstraintManager(runs, self._attr["column"], templates,
self._attr["pivot"],
self._attr["filters"], zip_constraints)
self._check_add_scatter()
super(LinePlot, self).__init__()
def savefig(self, *args, **kwargs):
"""Save the plot as a PNG fill. This calls into
:mod:`matplotlib.figure.savefig`
"""
if self._fig == None:
self.view()
self._fig.savefig(*args, **kwargs)
def view(self, test=False):
"""Displays the graph"""
if test:
self._attr["style"] = True
AttrConf.MPL_STYLE["interactive"] = False
if self._attr["concat"]:
if self._attr["style"]:
with plt.rc_context(AttrConf.MPL_STYLE):
self._plot_concat()
else:
self._plot_concat()
else:
if self._attr["style"]:
with plt.rc_context(AttrConf.MPL_STYLE):
self._plot(self._attr["permute"])
else:
self._plot(self._attr["permute"])
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["fill"] = AttrConf.FILL
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.XLIM
self._attr["args_to_forward"] = {}
self._attr["scatter"] = AttrConf.PLOT_SCATTER
def _check_add_scatter(self):
"""Check if a scatter plot is needed
and augment the forwarded args accordingly"""
if self._attr["scatter"]:
self._attr["args_to_forward"]["linestyle"] = ""
self._attr["args_to_forward"]["marker"] = "o"
if "point_size" in self._attr:
self._attr["args_to_forward"]["markersize"] = \
self._attr["point_size"]
def _plot(self, permute):
"""Internal Method called to draw the plot"""
pivot_vals, len_pivots = self.c_mgr.generate_pivots(permute)
# Create a 2D Layout
self._layout = PlotLayout(self._attr["per_line"],
len_pivots,
width=self._attr["width"],
length=self._attr["length"])
self._fig = self._layout.get_fig()
legend_str = []
plot_index = 0
if permute:
legend = [None] * self.c_mgr._max_len
cmap = ColorMap(self.c_mgr._max_len)
else:
legend = [None] * len(self.c_mgr)
cmap = ColorMap(len(self.c_mgr))
for p_val in pivot_vals:
l_index = 0
for constraint in self.c_mgr:
if permute:
run_idx, pivot = p_val
if constraint.run_index != run_idx:
continue
legend_str.append(constraint._column)
l_index = self.c_mgr.get_column_index(constraint)
title = constraint.get_data_name() + ":"
else:
pivot = p_val
legend_str.append(str(constraint))
title = ""
result = constraint.result
if pivot in result:
axis = self._layout.get_axis(plot_index)
line_2d_list = axis.plot(result[pivot].index,
result[pivot].values,
color=cmap.cmap(l_index),
**self._attr["args_to_forward"])
if self._attr["fill"]:
drawstyle = line_2d_list[0].get_drawstyle()
# This has been fixed in upstream matplotlib
if drawstyle.startswith("steps"):
raise UserWarning(
"matplotlib does not support fill for step plots"
)
xdat, ydat = line_2d_list[0].get_data(orig=False)
axis.fill_between(xdat,
axis.get_ylim()[0],
ydat,
facecolor=cmap.cmap(l_index),
alpha=AttrConf.ALPHA)
legend[l_index] = line_2d_list[0]
if self._attr["xlim"] != None:
axis.set_xlim(self._attr["xlim"])
if self._attr["ylim"] != None:
axis.set_ylim(self._attr["ylim"])
else:
axis = self._layout.get_axis(plot_index)
axis.plot([], [], **self._attr["args_to_forward"])
l_index += 1
if pivot == AttrConf.PIVOT_VAL:
title += ",".join(self._attr["column"])
else:
title += "{0}: {1}".format(self._attr["pivot"], pivot)
axis.set_title(title)
plot_index += 1
for l_idx, legend_line in enumerate(legend):
if not legend_line:
del legend[l_idx]
del legend_str[l_idx]
self._fig.legend(legend, legend_str)
self._layout.finish(len_pivots)
def _plot_concat(self):
"""Plot all lines on a single figure"""
pivot_vals, len_pivots = self.c_mgr.generate_pivots()
cmap = ColorMap(len_pivots)
self._layout = PlotLayout(self._attr["per_line"],
len(self.c_mgr),
width=self._attr["width"],
length=self._attr["length"])
self._fig = self._layout.get_fig()
legend = [None] * len_pivots
legend_str = [""] * len_pivots
plot_index = 0
for constraint in self.c_mgr:
result = constraint.result
title = str(constraint)
result = constraint.result
pivot_index = 0
for pivot in pivot_vals:
if pivot in result:
axis = self._layout.get_axis(plot_index)
line_2d_list = axis.plot(result[pivot].index,
result[pivot].values,
color=cmap.cmap(pivot_index),
**self._attr["args_to_forward"])
if self._attr["xlim"] != None:
axis.set_xlim(self._attr["xlim"])
if self._attr["ylim"] != None:
axis.set_ylim(self._attr["ylim"])
legend[pivot_index] = line_2d_list[0]
if self._attr["fill"]:
drawstyle = line_2d_list[0].get_drawstyle()
if drawstyle.startswith("steps"):
# This has been fixed in upstream matplotlib
raise UserWarning(
"matplotlib does not support fill for step plots"
)
xdat, ydat = line_2d_list[0].get_data(orig=False)
axis.fill_between(xdat,
axis.get_ylim()[0],
ydat,
facecolor=cmap.cmap(pivot_index),
alpha=AttrConf.ALPHA)
if pivot == AttrConf.PIVOT_VAL:
legend_str[pivot_index] = self._attr["column"]
else:
legend_str[pivot_index] = "{0}: {1}".format(
self._attr["pivot"], pivot)
else:
axis = self._layout.get_axis(plot_index)
axis.plot([], [],
color=cmap.cmap(pivot_index),
**self._attr["args_to_forward"])
pivot_index += 1
plot_index += 1
self._fig.legend(legend, legend_str)
plot_index = 0
for constraint in self.c_mgr:
self._layout.get_axis(plot_index).set_title(str(constraint))
plot_index += 1
self._layout.finish(len(self.c_mgr))
def _plot(self, permute):
"""Internal Method called to draw the plot"""
pivot_vals, len_pivots = self.c_mgr.generate_pivots(permute)
# Create a 2D Layout
self._layout = PlotLayout(self._attr["per_line"],
len_pivots,
width=self._attr["width"],
length=self._attr["length"])
self._fig = self._layout.get_fig()
legend_str = []
plot_index = 0
if permute:
legend = [None] * self.c_mgr._max_len
cmap = ColorMap(self.c_mgr._max_len)
else:
legend = [None] * len(self.c_mgr)
cmap = ColorMap(len(self.c_mgr))
for p_val in pivot_vals:
l_index = 0
for constraint in self.c_mgr:
if permute:
run_idx, pivot = p_val
if constraint.run_index != run_idx:
continue
legend_str.append(constraint._column)
l_index = self.c_mgr.get_column_index(constraint)
title = constraint.get_data_name() + ":"
else:
pivot = p_val
legend_str.append(str(constraint))
title = ""
result = constraint.result
if pivot in result:
axis = self._layout.get_axis(plot_index)
line_2d_list = axis.plot(result[pivot].index,
result[pivot].values,
color=cmap.cmap(l_index),
**self._attr["args_to_forward"])
if self._attr["fill"]:
drawstyle = line_2d_list[0].get_drawstyle()
# This has been fixed in upstream matplotlib
if drawstyle.startswith("steps"):
raise UserWarning(
"matplotlib does not support fill for step plots"
)
xdat, ydat = line_2d_list[0].get_data(orig=False)
axis.fill_between(xdat,
axis.get_ylim()[0],
ydat,
facecolor=cmap.cmap(l_index),
alpha=AttrConf.ALPHA)
legend[l_index] = line_2d_list[0]
if self._attr["xlim"] != None:
axis.set_xlim(self._attr["xlim"])
if self._attr["ylim"] != None:
axis.set_ylim(self._attr["ylim"])
else:
axis = self._layout.get_axis(plot_index)
axis.plot([], [], **self._attr["args_to_forward"])
l_index += 1
if pivot == AttrConf.PIVOT_VAL:
title += ",".join(self._attr["column"])
else:
title += "{0}: {1}".format(self._attr["pivot"], pivot)
axis.set_title(title)
plot_index += 1
for l_idx, legend_line in enumerate(legend):
if not legend_line:
del legend[l_idx]
del legend_str[l_idx]
self._fig.legend(legend, legend_str)
self._layout.finish(len_pivots)
class LinePlot(AbstractDataPlotter):
"""The plots are plotted by default against the dataframe index
The column="col_name" specifies the name of the column to
be plotted
filters =
{
"pid": [ 3338 ],
"cpu": [0, 2, 4],
}
The above filters will filter the column to be plotted as per the
specified criteria.
per_line input is used to control the number of graphs
in each graph subplot row
concat, Draws all the graphs on a single plot
permute, draws one plot for each of the runs specified
"""
def __init__(self, runs, templates=None, **kwargs):
# Default keys, each can be overridden in kwargs
self._attr = {}
self.runs = runs
self.templates = templates
self.set_defaults()
self._fig = None
self._layout = None
self._check_data()
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 "column" not in self._attr:
raise RuntimeError("Value Column not specified")
zip_constraints = not self._attr["permute"]
self.c_mgr = ConstraintManager(runs, self._attr["column"], templates,
self._attr["pivot"],
self._attr["filters"], zip_constraints)
super(LinePlot, self).__init__()
def savefig(self, *args, **kwargs):
if self._fig == None:
self.view()
self._fig.savefig(*args, **kwargs)
def view(self, test=False):
"""Displays the graph"""
if test:
self._attr["style"] = True
AttrConf.MPL_STYLE["interactive"] = False
if self._attr["concat"]:
if self._attr["style"]:
with plt.rc_context(AttrConf.MPL_STYLE):
self._plot_concat()
else:
self._plot_concat()
else:
if self._attr["style"]:
with plt.rc_context(AttrConf.MPL_STYLE):
self._plot(self._attr["permute"])
else:
self._plot(self._attr["permute"])
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["fill"] = AttrConf.FILL
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.XLIM
self._attr["args_to_forward"] = {}
def _plot(self, permute):
"""Internal Method called to draw the plot"""
pivot_vals, len_pivots = self.c_mgr.generate_pivots(permute)
# Create a 2D Layout
self._layout = PlotLayout(self._attr["per_line"],
len_pivots,
width=self._attr["width"],
length=self._attr["length"])
self._fig = self._layout.get_fig()
legend_str = []
plot_index = 0
if permute:
legend = [None] * self.c_mgr._max_len
cmap = ColorMap(self.c_mgr._max_len)
else:
legend = [None] * len(self.c_mgr)
cmap = ColorMap(len(self.c_mgr))
for p_val in pivot_vals:
l_index = 0
for constraint in self.c_mgr:
if permute:
run_idx, pivot = p_val
if constraint.run_index != run_idx:
continue
legend_str.append(constraint._column)
l_index = self.c_mgr.get_column_index(constraint)
title = constraint.get_data_name() + ":"
else:
pivot = p_val
legend_str.append(str(constraint))
title = ""
result = constraint.result
if pivot in result:
axis = self._layout.get_axis(plot_index)
line_2d_list = axis.plot(result[pivot].index,
result[pivot].values,
color=cmap.cmap(l_index),
**self._attr["args_to_forward"])
if self._attr["fill"]:
drawstyle = line_2d_list[0].get_drawstyle()
# This has been fixed in upstream matplotlib
if drawstyle.startswith("steps"):
raise UserWarning(
"matplotlib does not support fill for step plots"
)
xdat, ydat = line_2d_list[0].get_data(orig=False)
axis.fill_between(xdat,
axis.get_ylim()[0],
ydat,
facecolor=cmap.cmap(l_index),
alpha=AttrConf.ALPHA)
legend[l_index] = line_2d_list[0]
if self._attr["xlim"] != None:
axis.set_xlim(self._attr["xlim"])
if self._attr["ylim"] != None:
axis.set_ylim(self._attr["ylim"])
else:
axis = self._layout.get_axis(plot_index)
axis.plot([], [], **self._attr["args_to_forward"])
l_index += 1
if pivot == AttrConf.PIVOT_VAL:
title += ",".join(self._attr["column"])
else:
title += "{0}: {1}".format(self._attr["pivot"], pivot)
axis.set_title(title)
plot_index += 1
for l_idx, legend_line in enumerate(legend):
if not legend_line:
del legend[l_idx]
del legend_str[l_idx]
self._fig.legend(legend, legend_str)
self._layout.finish(len_pivots)
def _plot_concat(self):
"""Plot all lines on a single figure"""
pivot_vals, len_pivots = self.c_mgr.generate_pivots()
cmap = ColorMap(len_pivots)
self._layout = PlotLayout(self._attr["per_line"],
len(self.c_mgr),
width=self._attr["width"],
length=self._attr["length"])
self._fig = self._layout.get_fig()
legend = [None] * len_pivots
legend_str = [""] * len_pivots
plot_index = 0
for constraint in self.c_mgr:
result = constraint.result
title = str(constraint)
result = constraint.result
pivot_index = 0
for pivot in pivot_vals:
if pivot in result:
axis = self._layout.get_axis(plot_index)
line_2d_list = axis.plot(result[pivot].index,
result[pivot].values,
color=cmap.cmap(pivot_index),
**self._attr["args_to_forward"])
if self._attr["xlim"] != None:
axis.set_xlim(self._attr["xlim"])
if self._attr["ylim"] != None:
axis.set_ylim(self._attr["ylim"])
legend[pivot_index] = line_2d_list[0]
if self._attr["fill"]:
drawstyle = line_2d_list[0].get_drawstyle()
if drawstyle.startswith("steps"):
# This has been fixed in upstream matplotlib
raise UserWarning(
"matplotlib does not support fill for step plots"
)
xdat, ydat = line_2d_list[0].get_data(orig=False)
axis.fill_between(xdat,
axis.get_ylim()[0],
ydat,
facecolor=cmap.cmap(pivot_index),
alpha=AttrConf.ALPHA)
if pivot == AttrConf.PIVOT_VAL:
legend_str[pivot_index] = self._attr["column"]
else:
legend_str[pivot_index] = "{0}: {1}".format(
self._attr["pivot"], pivot)
else:
axis = self._layout.get_axis(plot_index)
axis.plot([], [],
color=cmap.cmap(pivot_index),
**self._attr["args_to_forward"])
pivot_index += 1
plot_index += 1
self._fig.legend(legend, legend_str)
plot_index = 0
for constraint in self.c_mgr:
self._layout.get_axis(plot_index).set_title(str(constraint))
plot_index += 1
self._layout.finish(len(self.c_mgr))
