gryf/coach
1
0
Fork 0
mirror of https://github.com/gryf/coach.git synced 2025-12-17 11:10:20 +01:00
Code Issues Projects Releases Wiki Activity

update nec and value optimization agents to work with recurrent middleware

Browse Source
This commit is contained in:
Zach Dwiel
2017-11-03 13:58:42 -07:00
parent 93a54c7e8e
commit 6c79a442f2
12 changed files with 138 additions and 72 deletions
Download Patch File Download Diff File Expand all files Collapse all files

35
utils.py
View File

@@ -1,5 +1,5 @@
#
# Copyright (c) 2017 Intel Corporation
# Copyright (c) 2017 Intel Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
@@ -180,6 +180,10 @@ def threaded_cmd_line_run(run_cmd, id=-1):
class Signal(object):
"""
Stores a stream of values and provides methods like get_mean and get_max
which returns the statistics about accumulated values.
"""
def __init__(self, name):
self.name = name
self.sample_count = 0
@@ -190,39 +194,36 @@ class Signal(object):
self.values = []
def add_sample(self, sample):
"""
:param sample: either a single value or an array of values
"""
self.values.append(sample)
def _get_values(self):
if type(self.values[0]) == np.ndarray:
return np.concatenate(self.values)
else:
return self.values
def get_mean(self):
if len(self.values) == 0:
return ''
if type(self.values[0]) == np.ndarray:
return np.mean(np.concatenate(self.values))
else:
return np.mean(self.values)
return np.mean(self._get_values())
def get_max(self):
if len(self.values) == 0:
return ''
if type(self.values[0]) == np.ndarray:
return np.max(np.concatenate(self.values))
else:
return np.max(self.values)
return np.max(self._get_values())
def get_min(self):
if len(self.values) == 0:
return ''
if type(self.values[0]) == np.ndarray:
return np.min(np.concatenate(self.values))
else:
return np.min(self.values)
return np.min(self._get_values())
def get_stdev(self):
if len(self.values) == 0:
return ''
if type(self.values[0]) == np.ndarray:
return np.std(np.concatenate(self.values))
else:
return np.std(self.values)
return np.std(self._get_values())
def force_list(var):