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comparison transformations/testmod.py @ 16:368f1907ad5a

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Script to test modules for conformance to the interface.
author Arnaud Bergeron <abergeron@gmail.com>
date Thu, 28 Jan 2010 13:32:15 -0500
parents
children 22823acc1712 089f236759d9
comparison
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15:f6b6c74bb82f 16:368f1907ad5a
1 # This script is to test your modules to see if they conform to the module API
2 # defined on the wiki.
3 import random, numpy, gc, time, math
4
5 # this is an example module that does stupid image value shifting
6
7 class DummyModule(object):
8 def get_settings_names(self):
9 return ['value']
10
11 def regenerate_parameters(self, complexity):
12 self._value = random.gauss(0, 0.5*complexity)
13 return [self._value]
14
15 def transform_image(self, image):
16 return numpy.clip(image+self._value, 0, 1)
17
18 #import <your module>
19
20 # instanciate your class here (rather than DummyModule)
21 mod = DummyModule()
22
23 def error(msg):
24 print "ERROR:", msg
25 sys.exit(1)
26
27 def warn(msg):
28 print "WARNING:", msg
29
30 def timeit(f, lbl):
31
32 gc.disable()
33 t = time.time()
34 f()
35 est = time.time() - t
36 gc.enable()
37
38 loops = max(1, int(10**math.floor(math.log(10/est, 10))))
39
40 gc.disable()
41 t = time.time()
42 for _ in xrange(loops):
43 f()
44
45 print lbl, "(", loops, "loops ):", (time.time() - t)/loops, "s"
46 gc.enable()
47
48 ########################
49 # get_settings_names() #
50 ########################
51
52 print "Testing get_settings_names()"
53
54 names = mod.get_settings_names()
55
56 if type(names) is not list:
57 error("Must return a list")
58
59 if len(names) == 0:
60 error("Must return at least one element")
61
62 if not all(type(e) is str for e in names):
63 warn("The elements of the list should be strings")
64
65 ###########################
66 # regenerate_parameters() #
67 ###########################
68
69 print "Testing regenerate_parameters()"
70
71 params = mod.regenerate_parameters(0.2)
72
73 if type(params) is not list:
74 error("Must return a list")
75
76 if len(params) != len(names):
77 error("the returned parameter list must have the same length as the number of parameters")
78
79 params2 = mod.regenerate_parameters(0.2)
80 if params == params2:
81 error("the complexity parameter determines the distribution of the parameters, not their value")
82
83 mod.regenerate_parameters(0.0)
84 mod.regenerate_parameters(1.0)
85
86 mod.regenerate_parameters(0.5)
87
88 #####################
89 # transform_image() #
90 #####################
91
92 print "Testing transform_image()"
93
94 imgr = numpy.random.random_sample((32, 32)).astype(numpy.float32)
95 img1 = numpy.ones((32, 32), dtype=numpy.float32)
96 img0 = numpy.zeros((32, 32), dtype=numpy.float32)
97
98 resr = mod.transform_image(imgr)
99
100 if type(resr) is not numpy.ndarray:
101 error("Must return an ndarray")
102
103 if resr.shape != (32, 32):
104 error("Must return 32x32 array")
105
106 if resr.dtype != numpy.float32:
107 error("Must return float32 array")
108
109 res1 = mod.transform_image(img1)
110 res0 = mod.transform_image(img0)
111
112 if res1.max() > 1.0 or res0.max() > 1.0:
113 error("Must keep array values between 0 and 1")
114
115 if res1.min() < 0.0 or res0.min() < 0.0:
116 error("Must keep array values between 0 and 1")
117
118 mod.regenerate_parameters(0.0)
119 mod.transform_image(imgr)
120 mod.regenerate_parameters(1.0)
121 mod.transform_image(imgr)
122
123 print "Bonus Stage: timings"
124
125 timeit(lambda: None, "empty")
126 timeit(lambda: mod.regenerate_parameters(0.5), "regenerate_parameters()")
127 timeit(lambda: mod.transform_image(imgr), "tranform_image()")
128
129 def f():
130 mod.regenerate_parameters(0.2)
131 mod.transform_image(imgr)
132
133 timeit(f, "regen and transform")