IMP  2.2.0
The Integrative Modeling Platform
History.py
1 #!/usr/bin/env python
2 
3 """@namespace IMP.isd.History
4  Classes to store output from replicas.
5 """
6 
7 import numpy
8 import sys
9 
10 
11 class History:
12 
13  """Class that contains the output of one replica, used by the
14  Analysis class.
15  """
16 
17  def __init__(self, filename):
18  self.filename = filename
19  self.data = {}
20 
21  def create_category(self, name):
22  self.data[name] = {}
23 
24  def create_entry(self, cat, name):
25  if not cat in self.data:
26  self.create_category(cat)
27  self.data[cat][name] = []
28 
29  def add_data(self, cat, name, data):
30  self.data[cat][name].append(data)
31 
32  def sanity_check(self):
33  """checks if all entries have same length and are of constant type"""
34  goodlen = None
35  had_warnings = False
36  for cat in self.data:
37  for name in self.data[cat]:
38  if goodlen is None:
39  goodlen = len(self.data[cat][name])
40  if len(self.data[cat][name]) != goodlen:
41  print "category %s entry %s : length %s expected, got %s"\
42  % (cat, name, goodlen, len(self.data[cat][name]))
43  break
44  goodtype = type(self.data[cat][name][0])
45  for ent in self.data[cat][name]:
46  if not isinstance(ent, goodtype):
47  print "category %s entry %s : %s expected, got %s"\
48  % (cat, name, goodtype, type(ent))
49  break
50 
51  def get_data(self, cat, name):
52  return self.data[cat][name]
53 
54  def get_categories(self):
55  i = sorted(self.data.keys())
56  if 'step' in i:
57  i.remove('step')
58  i = ['step'] + i
59  return i
60 
61  def get_entries(self, cat):
62  i = sorted(self.data[cat].keys())
63  if 'step' in i:
64  i.remove('step')
65  i = ['step'] + i
66  return i
67 
68  def remove_NAs(self):
69  for cat in self.data:
70  for name in self.data[cat]:
71  self.data[cat][name] = [i for i in self.data[cat][name]
72  if i != 'N/A']
73 
74  def toc(self, out=sys.stdout):
75  """print the "table of contents" of this History
76  tendency is a comparison of the last 200 frames, and whether it goes up
77  or down.
78  mean100 is the average over the last 100 frames
79  """
80  if not isinstance(out, file):
81  out = open(out, 'w')
82  out.write(
83  "category\tkey_name\tn_frames\ttype\taverage\tstd\tmean100\ttendency\n")
84  for cat in self.data:
85  out.write(cat + '\n')
86  for name in self.data[cat]:
87  ent = self.data[cat][name]
88  tp = type(ent[-1])
89  if tp == float:
90  tp = 'float'
91  elif tp == int:
92  tp = 'int'
93  if tp == 'float':
94  try:
95  ent = numpy.array(ent)
96  avg = numpy.mean(ent)
97  avg100 = numpy.mean(ent[-100:])
98  avg200 = numpy.mean(ent[-200:-100])
99  st = numpy.std(ent)
100  st200 = numpy.std(ent[-200])
101  if st200 == 0 or abs(avg200 - avg100) / st200 > 3:
102  if avg200 > avg100:
103  tend = '\\'
104  else:
105  tend = '/'
106  else:
107  tend = '--'
108  out.write(
109  "\t%20s\t%12d\t%20s\t%10f\t%10f\t%10f\t%5s\n" %
110  (name, len(ent), tp, avg, st, avg100, tend))
111  continue
112  except:
113  pass
114  out.write("\t%20s\t%12d\t%20s\n" % (name, len(ent), tp))
def sanity_check
checks if all entries have same length and are of constant type
Definition: History.py:32
def toc
print the "table of contents" of this History tendency is a comparison of the last 200 frames...
Definition: History.py:74
Class that contains the output of one replica, used by the Analysis class.
Definition: History.py:11