398 lines
11 KiB
Python
Executable File
398 lines
11 KiB
Python
Executable File
#!/usr/bin/python3
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#
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# Copyright (C) 2005, 2006, 2007 Arnaldo Carvalho de Melo
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#
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# This program is free software; you can redistribute it and/or modify it
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# under the terms of version 2 of the GNU General Public License as
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# published by the Free Software Foundation.
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from datetime import timedelta
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class trace_points:
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def __init__(self, hooks):
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self.entry = "entry" in hooks
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self.exit = "exit" in hooks
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def __repr__(self):
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return str(self.__dict__.values())
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__str__ = __repr__
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class change_point:
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def __init__(self, tstamp, value, seq):
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self.tstamp = tstamp
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self.value = value
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self.seq = seq
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class class_field:
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def __init__(self, line, class_def_file):
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field, self.name, cgtraced, self.grab_expr, \
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self.collector_fmt, hooks, self.plot_fmt = line.strip().split(':')
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self.field = int(field)
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self.cg = cgtraced == "yes"
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self.hooks = trace_points(hooks.split(','))
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self.value = None
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self.last_value = None
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self.changes = []
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self._load_text_table(class_def_file)
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def _text_table_tokenizer(self, line):
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tokens = line.split(":")
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return int(tokens[0]), tokens[1][:-1]
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def _load_text_table(self, class_def_file):
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try:
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f = file("%s.%s.table" % (class_def_file, self.name))
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except:
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self.table = {}
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return
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self.table = dict([self._text_table_tokenizer(line) for line in f.readlines()])
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f.close()
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def set_last_value(self, tstamp, seq):
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if self.value != None:
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if self.cg and self.changed():
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self.changes.append(change_point(tstamp, self.value, seq))
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self.last_value = self.value
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def changed(self):
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return self.value != None and self.value != self.last_value
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def __repr__(self):
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return self.name
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__str__ = __repr__
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class class_method:
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def __init__(self, line):
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fields = line.strip().split(':')
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self.function_id = fields[0]
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self.name = fields[1]
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self.print_return_value = fields[-1]
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self.function_id = int(self.function_id)
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self.print_return_value = self.print_return_value == "yes"
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self.calls = 0
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self.total_time = timedelta()
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self.last_tstamp = None
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self.times = []
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self.exits = {}
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def begin(self, tstamp):
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self.calls += 1
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self.last_tstamp = tstamp
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def end(self, tstamp):
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tstamp_delta = tstamp - self.last_tstamp
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if tstamp_delta < timedelta():
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tstamp_delta = timedelta()
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self.total_time += tstamp_delta
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self.times.append(tstamp_delta.seconds * 1000000 + tstamp_delta.microseconds)
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def plot(self, directory, entries, samples, nr_samples, verbose = False):
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from matplotlib import use as muse
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muse('Agg')
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from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
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from matplotlib.figure import Figure
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from matplotlib.ticker import FuncFormatter, FixedFormatter, LinearLocator
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from matplotlib.mlab import std as std_deviation
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from matplotlib.mlab import mean
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from time import asctime
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yfont = { 'fontname' : 'Bitstream Vera Sans',
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'color' : 'r',
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'fontsize' : 8 }
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xfont = { 'fontname' : 'Bitstream Vera Sans',
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'color' : 'b',
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'fontsize' : 8 }
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titlefont = { 'fontname' : 'Bitstream Vera Sans',
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'color' : 'g',
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'fontweight' : 'bold',
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'fontsize' : 10 }
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inches = 0.00666667
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width = 950 * inches
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height = 680 * inches
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fig = Figure(figsize = (width, height))
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canvas = FigureCanvas(fig)
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ax = fig.add_subplot(111)
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ax.grid(False)
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xtickfontsize = 5
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ytickfontsize = 5
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plot_type = 'b-'
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field_mean = mean(samples)
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yaxis_plot_fmt = FuncFormatter(pylab_formatter_ms)
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ax.plot(entries, samples, "b-")
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ax.set_xlabel("samples", xfont)
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ax.set_ylabel("time", yfont)
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for label in ax.get_xticklabels():
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label.set(fontsize = xtickfontsize)
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for label in ax.get_yticklabels():
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label.set(fontsize = ytickfontsize)
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ax.yaxis.set_major_formatter(yaxis_plot_fmt)
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ax.set_title("%d %s samples (%s)" % (nr_samples, self.name, asctime()), titlefont)
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canvas.print_figure("%s/methods/%s.png" % (directory, self.name))
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del fig, canvas, ax
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class class_definition:
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def __init__(self, class_def_file = None, class_methods_file = None):
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self.fields = {}
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self.methods = {}
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self.tstamp = None
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self.last_tstamp = None
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self.last_method = None
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self.epoch = None
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if class_def_file:
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f = file(class_def_file)
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for line in f.readlines():
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field = class_field(line, class_def_file)
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self.fields[field.name] = field
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f.close()
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if class_methods_file:
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f = file(class_methods_file)
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self.methods = dict([self._method_tokenizer(line) for line in f.readlines()])
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f.close()
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def _method_tokenizer(self, line):
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method = class_method(line)
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return method.function_id, method
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def set_last_values(self, seq = 0):
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self.last_method = self.current_method()
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for field in self.fields.values():
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field.set_last_value(self.tstamp, seq)
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self.last_tstamp = self.tstamp
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def parse_record(self, line):
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nsec, record = line[:-1].split(' ', 1)
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line_fields = record.split(':')
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self.tstamp = timedelta(microseconds = int(nsec) / 1000)
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if self.epoch == None:
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self.epoch = self.tstamp
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self.tstamp -= self.epoch
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action = line_fields[0][0]
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nr_fields = len(line_fields)
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for field in self.fields.values():
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if field.field >= nr_fields or \
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(action == 'i' and not field.hooks.entry) or \
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(action == 'o' and not field.hooks.exit):
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field.value = None
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continue
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field.value = line_fields[field.field]
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def parse_file(self, filename, process_record = None, verbose = False,
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my_object = None):
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f = file(filename)
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current_object = None
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object_stack = []
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if verbose:
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nr_lines = 0
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while True:
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line = f.readline()
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if not line:
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break
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if verbose:
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nr_lines += 1
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print("\r%d" % nr_lines,)
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self.parse_record(line)
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method = self.current_method()
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# print method.name
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if my_object:
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if self.fields["action"].value[0] == 'i':
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current_object = self.fields["object"].value
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object_stack.append(current_object)
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else:
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current_object = object_stack.pop()
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if current_object != my_object:
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continue
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if self.fields["action"].value[0] == 'i':
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method.begin(self.tstamp)
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else:
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method.end(self.tstamp)
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seq = 0
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if process_record:
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seq = process_record()
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self.set_last_values(seq)
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f.close()
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if verbose:
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print
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def current_method(self):
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return self.methods[int(self.fields["function_id"].value)]
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def plot_methods(self, callgraph, verbose = False):
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for current_method in self.methods.values():
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nr_samples = len(current_method.times)
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if nr_samples < 4:
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continue
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if verbose:
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print("plot_methods: plotting %s method (%d samples)" % \
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(current_method.name, nr_samples))
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entries = [float("%d.0" % entry) for entry in range(nr_samples)]
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samples = current_method.times
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current_method.plot(callgraph, entries, samples,
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nr_samples, verbose)
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def pylab_formatter_kbps(x):
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mb = 1024 * 1024
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if x > mb:
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return "%d,%d Mbps" % (x / mb, x % mb)
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else:
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return "%d,%d Kbps" % (x / 1024, x % 1024)
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def pylab_formatter_ms(x, pos = 0):
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ms = x / 1000
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us = x % 1000
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s = "%d" % ms
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if us > 0:
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s += ".%03d" % us
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s = s.rstrip('0')
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s += "ms"
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return s
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def pylab_formatter(x, pos = 0):
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if current_plot_fmt == "kbps":
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return pylab_formatter_kbps(x)
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elif current_plot_fmt == "ms":
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return pylab_formatter_ms(x)
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else:
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return "%s" % str(int(x))
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def plot_field(name, directory, tstamps, samples, nr_samples, plot_fmt = None,
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table = None, verbose = False):
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global current_plot_fmt
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from matplotlib import use as muse
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muse('Agg')
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from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
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from matplotlib.figure import Figure
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from matplotlib.ticker import FuncFormatter, FixedFormatter, LinearLocator
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from matplotlib.mlab import std as std_deviation
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from matplotlib.mlab import mean
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from time import asctime
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yfont = { 'fontname' : 'Bitstream Vera Sans',
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'color' : 'r',
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'fontsize' : 8 }
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xfont = { 'fontname' : 'Bitstream Vera Sans',
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'color' : 'b',
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'fontsize' : 8 }
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titlefont = { 'fontname' : 'Bitstream Vera Sans',
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'color' : 'g',
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'fontweight' : 'bold',
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'fontsize' : 10 }
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inches = 0.00666667
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width = 950 * inches
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height = 680 * inches
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fig = Figure(figsize = (width, height))
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canvas = FigureCanvas(fig)
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ax = fig.add_subplot(111)
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ax.grid(False)
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xtickfontsize = 5
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ytickfontsize = 5
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current_plot_fmt = plot_fmt
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field_mean = None
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plot_type = 'b-'
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if current_plot_fmt == "filter_dev":
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std = std_deviation(samples) * 2
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if verbose:
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print("filter_dev(%s) std=%d" % (name, std))
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for i in range(nr_samples):
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if samples[i] > std:
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if verbose:
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print("%s: filtering out %d" % (name, samples[i]))
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samples[i] = 0
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field_mean = mean(samples)
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yaxis_plot_fmt = FuncFormatter(pylab_formatter)
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elif current_plot_fmt == "table":
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ax.grid(True)
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plot_type = 'bo-'
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max_value = max(samples)
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without_zero = 1
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if table.has_key(0):
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without_zero = 0
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max_value += 1
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ax.yaxis.set_major_locator(LinearLocator(max_value))
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tstamps = range(nr_samples)
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seq = [ " " ] * max_value
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for key in table.keys():
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if key in samples:
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seq[key - without_zero] = "%s(%d)" % (table[key], key)
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ytickfontsize = 4
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yaxis_plot_fmt = FixedFormatter(seq)
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else:
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field_mean = mean(samples)
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yaxis_plot_fmt = FuncFormatter(pylab_formatter)
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ax.plot(tstamps, samples, plot_type)
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ax.set_xlabel("time", xfont)
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yname = name
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if field_mean:
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yname += " (mean=%s)" % pylab_formatter(field_mean)
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ax.set_ylabel(yname, yfont)
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for label in ax.get_xticklabels():
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label.set(fontsize = xtickfontsize)
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for label in ax.get_yticklabels():
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label.set(fontsize = ytickfontsize)
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ax.yaxis.set_major_formatter(yaxis_plot_fmt)
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ax.set_title("%d %s samples (%s)" % (nr_samples, name, asctime()), titlefont)
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canvas.print_figure("%s/%s.png" % (directory, name))
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del fig, canvas, ax
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def plot(class_def, callgraph, verbose = False):
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for current_field in class_def.fields.values():
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nr_samples = len(current_field.changes)
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if nr_samples < 4:
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continue
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if verbose:
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print("ostra-plot: plotting %s field (%d samples)" % (current_field.name, nr_samples))
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tstamps = [float("%d.%06d" % (entry.tstamp.seconds, entry.tstamp.microseconds)) \
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for entry in current_field.changes]
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try:
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samples = [int(entry.value) for entry in current_field.changes]
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except:
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continue
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plot_field(current_field.name, callgraph, tstamps, samples,
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nr_samples, current_field.plot_fmt,
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current_field.table, verbose)
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if __name__ == '__main__':
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import sys
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c = class_definition(sys.argv[1], sys.argv[2])
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for field in c.fields.values():
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print("%s: %s" % (field, field.table))
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for method in c.methods.values():
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print("%d: %s" % (method.function_id, method.name))
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