1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
|
# Copyright 2017 The Chromium OS Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
#
# Ignore indention messages, since legacy scripts use 2 spaces instead of 4.
# pylint: disable=bad-indentation,docstring-section-indent
# pylint: disable=docstring-trailing-quotes
"""Calculates statistics for lists of data and pretty print them."""
# Note: This is a py2/3 compatible file.
from __future__ import print_function
import collections
import json
import logging
import math
import os
import numpy
STATS_PREFIX = "@@"
NAN_TAG = "*"
NAN_DESCRIPTION = "%s domains contain NaN samples" % NAN_TAG
LONG_UNIT = {
"": "N/A",
"mW": "milliwatt",
"uW": "microwatt",
"mV": "millivolt",
"uA": "microamp",
"uV": "microvolt",
}
class StatsManagerError(Exception):
"""Errors in StatsManager class."""
pass
class StatsManager(object):
"""Calculates statistics for several lists of data(float).
Example usage:
>>> stats = StatsManager(title='Title Banner')
>>> stats.AddSample(TIME_KEY, 50.0)
>>> stats.AddSample(TIME_KEY, 25.0)
>>> stats.AddSample(TIME_KEY, 40.0)
>>> stats.AddSample(TIME_KEY, 10.0)
>>> stats.AddSample(TIME_KEY, 10.0)
>>> stats.AddSample('frobnicate', 11.5)
>>> stats.AddSample('frobnicate', 9.0)
>>> stats.AddSample('foobar', 11111.0)
>>> stats.AddSample('foobar', 22222.0)
>>> stats.CalculateStats()
>>> print(stats.SummaryToString())
` @@--------------------------------------------------------------
` @@ Title Banner
@@--------------------------------------------------------------
@@ NAME COUNT MEAN STDDEV MAX MIN
@@ sample_msecs 4 31.25 15.16 50.00 10.00
@@ foobar 2 16666.50 5555.50 22222.00 11111.00
@@ frobnicate 2 10.25 1.25 11.50 9.00
` @@--------------------------------------------------------------
Attributes:
_data: dict of list of readings for each domain(key)
_unit: dict of unit for each domain(key)
_smid: id supplied to differentiate data output to other StatsManager
instances that potentially save to the same directory
if smid all output files will be named |smid|_|fname|
_title: title to add as banner to formatted summary. If no title,
no banner gets added
_order: list of formatting order for domains. Domains not listed are
displayed in sorted order
_hide_domains: collection of domains to hide when formatting summary string
_accept_nan: flag to indicate if NaN samples are acceptable
_nan_domains: set to keep track of which domains contain NaN samples
_summary: dict of stats per domain (key): min, max, count, mean, stddev
_logger = StatsManager logger
Note:
_summary is empty until CalculateStats() is called, and is updated when
CalculateStats() is called.
"""
# pylint: disable=W0102
def __init__(self, smid="", title="", order=[], hide_domains=[], accept_nan=True):
"""Initialize infrastructure for data and their statistics."""
self._title = title
self._data = collections.defaultdict(list)
self._unit = collections.defaultdict(str)
self._smid = smid
self._order = order
self._hide_domains = hide_domains
self._accept_nan = accept_nan
self._nan_domains = set()
self._summary = {}
self._logger = logging.getLogger(type(self).__name__)
def AddSample(self, domain, sample):
"""Add one sample for a domain.
Args:
domain: the domain name for the sample.
sample: one time sample for domain, expect type float.
Raises:
StatsManagerError: if trying to add NaN and |_accept_nan| is false
"""
try:
sample = float(sample)
except ValueError:
# if we don't accept nan this will be caught below
self._logger.debug(
"sample %s for domain %s is not a number. Making NaN", sample, domain
)
sample = float("NaN")
if not self._accept_nan and math.isnan(sample):
raise StatsManagerError("accept_nan is false. Cannot add NaN sample.")
self._data[domain].append(sample)
if math.isnan(sample):
self._nan_domains.add(domain)
def SetUnit(self, domain, unit):
"""Set the unit for a domain.
There can be only one unit for each domain. Setting unit twice will
overwrite the original unit.
Args:
domain: the domain name.
unit: unit of the domain.
"""
if domain in self._unit:
self._logger.warning(
"overwriting the unit of %s, old unit is %s, new " "unit is %s.",
domain,
self._unit[domain],
unit,
)
self._unit[domain] = unit
def CalculateStats(self):
"""Calculate stats for all domain-data pairs.
First erases all previous stats, then calculate stats for all data.
"""
self._summary = {}
for domain, data in self._data.items():
data_np = numpy.array(data)
self._summary[domain] = {
"mean": numpy.nanmean(data_np),
"min": numpy.nanmin(data_np),
"max": numpy.nanmax(data_np),
"stddev": numpy.nanstd(data_np),
"count": data_np.size,
}
@property
def DomainsToDisplay(self):
"""List of domains that the manager will output in summaries."""
return set(self._summary.keys()) - set(self._hide_domains)
@property
def NanInOutput(self):
"""Return whether any of the domains to display have NaN values."""
return bool(len(set(self._nan_domains) & self.DomainsToDisplay))
def _SummaryTable(self):
"""Generate the matrix to output as a summary.
Returns:
A 2d matrix of headers and their data for each domain
e.g.
[[NAME, COUNT, MEAN, STDDEV, MAX, MIN],
[pp5000_mw, 10, 50, 0, 50, 50]]
"""
headers = ("NAME", "COUNT", "MEAN", "STDDEV", "MAX", "MIN")
table = [headers]
# determine what domains to display & and the order
domains_to_display = self.DomainsToDisplay
display_order = [key for key in self._order if key in domains_to_display]
domains_to_display -= set(display_order)
display_order.extend(sorted(domains_to_display))
for domain in display_order:
stats = self._summary[domain]
if not domain.endswith(self._unit[domain]):
domain = "%s_%s" % (domain, self._unit[domain])
if domain in self._nan_domains:
domain = "%s%s" % (domain, NAN_TAG)
row = [domain]
row.append(str(stats["count"]))
for entry in headers[2:]:
row.append("%.2f" % stats[entry.lower()])
table.append(row)
return table
def SummaryToMarkdownString(self):
"""Format the summary into a b/ compatible markdown table string.
This requires this sort of output format
| header1 | header2 | header3 | ...
| --------- | --------- | --------- | ...
| sample1h1 | sample1h2 | sample1h3 | ...
.
.
.
Returns:
formatted summary string.
"""
# All we need to do before processing is insert a row of '-' between
# the headers, and the data
table = self._SummaryTable()
columns = len(table[0])
# Using '-:' to allow the numbers to be right aligned
sep_row = ["-"] + ["-:"] * (columns - 1)
table.insert(1, sep_row)
text_rows = ["|".join(r) for r in table]
body = "\n".join(["|%s|" % r for r in text_rows])
if self._title:
title_section = "**%s** \n\n" % self._title
body = title_section + body
# Make sure that the body is terminated with a newline.
return body + "\n"
def SummaryToString(self, prefix=STATS_PREFIX):
"""Format summary into a string, ready for pretty print.
See class description for format example.
Args:
prefix: start every row in summary string with prefix, for easier reading.
Returns:
formatted summary string.
"""
table = self._SummaryTable()
max_col_width = []
for col_idx in range(len(table[0])):
col_item_widths = [len(row[col_idx]) for row in table]
max_col_width.append(max(col_item_widths))
formatted_lines = []
for row in table:
formatted_row = prefix + " "
for i in range(len(row)):
formatted_row += row[i].rjust(max_col_width[i] + 2)
formatted_lines.append(formatted_row)
if self.NanInOutput:
formatted_lines.append("%s %s" % (prefix, NAN_DESCRIPTION))
if self._title:
line_length = len(formatted_lines[0])
dec_length = len(prefix)
# trim title to be at most as long as the longest line without the prefix
title = self._title[: (line_length - dec_length)]
# line is a seperator line consisting of -----
line = "%s%s" % (prefix, "-" * (line_length - dec_length))
# prepend the prefix to the centered title
padded_title = "%s%s" % (prefix, title.center(line_length)[dec_length:])
formatted_lines = [line, padded_title, line] + formatted_lines + [line]
formatted_output = "\n".join(formatted_lines)
return formatted_output
def GetSummary(self):
"""Getter for summary."""
return self._summary
def _MakeUniqueFName(self, fname):
"""prepend |_smid| to fname & rotate fname to ensure uniqueness.
Before saving a file through the StatsManager, make sure that the filename
is unique, first by prepending the smid if any and otherwise by appending
increasing integer suffixes until the filename is unique.
If |smid| is defined /path/to/example/file.txt becomes
/path/to/example/{smid}_file.txt.
The rotation works by changing /path/to/example/somename.txt to
/path/to/example/somename1.txt if the first one already exists on the
system.
Note: this is not thread-safe. While it makes sense to use StatsManager
in a threaded data-collection, the data retrieval should happen in a
single threaded environment to ensure files don't get potentially clobbered.
Args:
fname: filename to ensure uniqueness.
Returns:
{smid_}fname{tag}.[b].ext
the smid portion gets prepended if |smid| is defined
the tag portion gets appended if necessary to ensure unique fname
"""
fdir = os.path.dirname(fname)
base, ext = os.path.splitext(os.path.basename(fname))
if self._smid:
base = "%s_%s" % (self._smid, base)
unique_fname = os.path.join(fdir, "%s%s" % (base, ext))
tag = 0
while os.path.exists(unique_fname):
old_fname = unique_fname
unique_fname = os.path.join(fdir, "%s%d%s" % (base, tag, ext))
self._logger.warning(
"Attempted to store stats information at %s, but "
"file already exists. Attempting to store at %s "
"now.",
old_fname,
unique_fname,
)
tag += 1
return unique_fname
def SaveSummary(self, directory, fname="summary.txt", prefix=STATS_PREFIX):
"""Save summary to file.
Args:
directory: directory to save the summary in.
fname: filename to save summary under.
prefix: start every row in summary string with prefix, for easier reading.
Returns:
full path of summary save location
"""
summary_str = self.SummaryToString(prefix=prefix) + "\n"
return self._SaveSummary(summary_str, directory, fname)
def SaveSummaryJSON(self, directory, fname="summary.json"):
"""Save summary (only MEAN) into a JSON file.
Args:
directory: directory to save the JSON summary in.
fname: filename to save summary under.
Returns:
full path of summary save location
"""
data = {}
for domain in self._summary:
unit = LONG_UNIT.get(self._unit[domain], self._unit[domain])
data_entry = {"mean": self._summary[domain]["mean"], "unit": unit}
data[domain] = data_entry
summary_str = json.dumps(data, indent=2)
return self._SaveSummary(summary_str, directory, fname)
def SaveSummaryMD(self, directory, fname="summary.md"):
"""Save summary into a MD file to paste into b/.
Args:
directory: directory to save the MD summary in.
fname: filename to save summary under.
Returns:
full path of summary save location
"""
summary_str = self.SummaryToMarkdownString()
return self._SaveSummary(summary_str, directory, fname)
def _SaveSummary(self, output_str, directory, fname):
"""Wrote |output_str| to |fname|.
Args:
output_str: formatted output string
directory: directory to save the summary in.
fname: filename to save summary under.
Returns:
full path of summary save location
"""
if not os.path.exists(directory):
os.makedirs(directory)
fname = self._MakeUniqueFName(os.path.join(directory, fname))
with open(fname, "w") as f:
f.write(output_str)
return fname
def GetRawData(self):
"""Getter for all raw_data."""
return self._data
def SaveRawData(self, directory, dirname="raw_data"):
"""Save raw data to file.
Args:
directory: directory to create the raw data folder in.
dirname: folder in which raw data live.
Returns:
list of full path of each domain's raw data save location
"""
if not os.path.exists(directory):
os.makedirs(directory)
dirname = os.path.join(directory, dirname)
if not os.path.exists(dirname):
os.makedirs(dirname)
fnames = []
for domain, data in self._data.items():
if not domain.endswith(self._unit[domain]):
domain = "%s_%s" % (domain, self._unit[domain])
fname = self._MakeUniqueFName(os.path.join(dirname, "%s.txt" % domain))
with open(fname, "w") as f:
f.write("\n".join("%.2f" % sample for sample in data) + "\n")
fnames.append(fname)
return fnames
|