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IMP Reference Guide  2.20.0
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 from __future__ import print_function
8 import numpy
9 import sys
10 
11 
12 class History:
13 
14  """Class that contains the output of one replica, used by the
15  Analysis class.
16  """
17 
18  def __init__(self, filename):
19  self.filename = filename
20  self.data = {}
21 
22  def create_category(self, name):
23  self.data[name] = {}
24 
25  def create_entry(self, cat, name):
26  if cat not in self.data:
27  self.create_category(cat)
28  self.data[cat][name] = []
29 
30  def add_data(self, cat, name, data):
31  self.data[cat][name].append(data)
32 
33  def sanity_check(self):
34  """checks if all entries have same length and are of constant type"""
35  goodlen = None
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 isinstance(out, str):
81  out = open(out, 'w')
82  out.write(
83  "category\tkey_name\tn_frames\ttype\taverage\tstd\tmean100\t"
84  "tendency\n")
85  for cat in self.data:
86  out.write(cat + '\n')
87  for name in self.data[cat]:
88  ent = self.data[cat][name]
89  tp = type(ent[-1])
90  if tp == float:
91  tp = 'float'
92  elif tp == int:
93  tp = 'int'
94  if tp == 'float':
95  try:
96  ent = numpy.array(ent)
97  avg = numpy.mean(ent)
98  avg100 = numpy.mean(ent[-100:])
99  avg200 = numpy.mean(ent[-200:-100])
100  st = numpy.std(ent)
101  st200 = numpy.std(ent[-200])
102  if st200 == 0 or abs(avg200 - avg100) / st200 > 3:
103  if avg200 > avg100:
104  tend = '\'
105  else:
106  tend = '/'
107  else:
108  tend = '--'
109  out.write(
110  "\t%20s\t%12d\t%20s\t%10f\t%10f\t%10f\t%5s\n" %
111  (name, len(ent), tp, avg, st, avg100, tend))
112  continue
113  except:
114  pass
115  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:33
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:12