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
|
# coding: utf-8
# /*##########################################################################
#
# Copyright (c) 2016-2017 European Synchrotron Radiation Facility
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
#
# ###########################################################################*/
"""This module provides combination of statistics as single operation.
For now it provides min/max (and optionally positive min) and indices
of first occurences (i.e., argmin/argmax) in a single pass.
"""
__authors__ = ["T. Vincent"]
__license__ = "MIT"
__date__ = "20/12/2016"
cimport cython
# Replacement from libc.math cimport isnan
# which is not available on Windows for Python2.7
cdef extern from "isnan.h":
bint isnan(double x) nogil
import numpy
ctypedef fused _number:
float
double
signed char
signed short
signed int
signed long
unsigned char
unsigned short
unsigned int
unsigned long long
class _MinMaxResult(object):
"""Object storing result from :func:`min_max`"""
def __init__(self, minimum, min_pos, maximum,
argmin, argmin_pos, argmax):
self._minimum = minimum
self._min_positive = min_pos
self._maximum = maximum
self._argmin = argmin
self._argmin_positive = argmin_pos
self._argmax = argmax
minimum = property(
lambda self: self._minimum,
doc="Minimum value of the array")
maximum = property(
lambda self: self._maximum,
doc="Maximum value of the array")
argmin = property(
lambda self: self._argmin,
doc="Index of the first occurence of the minimum value")
argmax = property(
lambda self: self._argmax,
doc="Index of the first occurence of the maximum value")
min_positive = property(
lambda self: self._min_positive,
doc="""Strictly positive minimum value
It is None if no value is strictly positive.
""")
argmin_positive = property(
lambda self: self._argmin_positive,
doc="""Index of the strictly positive minimum value.
It is None if no value is strictly positive.
It is the index of the first occurence.""")
def __getitem__(self, key):
if key == 0:
return self.minimum
elif key == 1:
return self.maximum
else:
raise IndexError("Index out of range")
@cython.initializedcheck(False)
@cython.boundscheck(False)
@cython.wraparound(False)
def _min_max(_number[::1] data, bint min_positive=False):
"""See :func:`min_max` for documentation."""
cdef:
_number value, minimum, minpos, maximum
unsigned int length
unsigned int index = 0
unsigned int min_index = 0
unsigned int min_pos_index = 0
unsigned int max_index = 0
length = len(data)
if length == 0:
raise ValueError('Zero-size array')
with nogil:
# Init starting values
value = data[0]
minimum = value
maximum = value
if min_positive and value > 0:
min_pos = value
else:
min_pos = 0
if _number in cython.floating:
# For floating, loop until first not NaN value
for index in range(length):
value = data[index]
if not isnan(value):
minimum = value
min_index = index
maximum = value
max_index = index
break
if not min_positive:
for index in range(index, length):
value = data[index]
if value > maximum:
maximum = value
max_index = index
elif value < minimum:
minimum = value
min_index = index
else:
# Loop until min_pos is defined
for index in range(index, length):
value = data[index]
if value > maximum:
maximum = value
max_index = index
elif value < minimum:
minimum = value
min_index = index
if value > 0:
min_pos = value
min_pos_index = index
break
# Loop until the end
for index in range(index+1, length):
value = data[index]
if value > maximum:
maximum = value
max_index = index
else:
if value < minimum:
minimum = value
min_index = index
if value > 0 and value < min_pos:
min_pos = value
min_pos_index = index
return _MinMaxResult(minimum,
min_pos if min_pos > 0 else None,
maximum,
min_index,
min_pos_index if min_pos > 0 else None,
max_index)
def min_max(data not None, bint min_positive=False):
"""Returns min, max and optionally strictly positive min of data.
It also computes the indices of first occurence of min/max.
NaNs are ignored while computing min/max unless all data is NaNs,
in which case returned min/max are NaNs.
Examples:
>>> import numpy
>>> data = numpy.arange(10)
Usage as a function returning min and max:
>>> min_, max_ = min_max(data)
Usage as a function returning a result object to access all information:
>>> result = min_max(data) # Do not get positive min
>>> result.minimum, result.argmin
0, 0
>>> result.maximum, result.argmax
9, 10
>>> result.min_positive, result.argmin_positive # Not computed
None, None
Getting strictly positive min information:
>>> result = min_max(data, min_positive=True)
>>> result.min_positive, result.argmin_positive # Computed
1, 1
:param data: Array-like dataset
:param bool min_positive: True to compute the positive min and argmin
Default: False.
:returns: An object with minimum, maximum and min_positive attributes
and the indices of first occurence in the flattened data:
argmin, argmax and argmin_positive attributes.
If all data is <= 0 or min_positive argument is False, then
min_positive and argmin_positive are None.
:raises: ValueError if data is empty
"""
return _min_max(numpy.ascontiguousarray(data).ravel(), min_positive)
|
