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
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
|
from __future__ import absolute_import, print_function
import random
import parser
import numpy as np
from numpy.testing import TestCase, assert_array_equal, run_module_suite
from scipy.weave import size_check
from scipy.weave.ast_tools import harvest_variables
class TestMakeSameLength(TestCase):
def generic_check(self,x,y,desired):
actual = size_check.make_same_length(x,y)
desired = desired
assert_array_equal(actual,desired)
def test_scalar(self):
x,y = (),()
desired = np.array(()), np.array(())
self.generic_check(x,y,desired)
def test_x_scalar(self):
x,y = (),(1,2)
desired = np.array((1,1)), np.array((1,2))
self.generic_check(x,y,desired)
def test_y_scalar(self):
x,y = (1,2),()
desired = np.array((1,2)), np.array((1,1))
self.generic_check(x,y,desired)
def test_x_short(self):
x,y = (1,2),(1,2,3)
desired = np.array((1,1,2)), np.array((1,2,3))
self.generic_check(x,y,desired)
def test_y_short(self):
x,y = (1,2,3),(1,2)
desired = np.array((1,2,3)), np.array((1,1,2))
self.generic_check(x,y,desired)
class TestBinaryOpSize(TestCase):
def generic_check(self,x,y,desired):
actual = size_check.binary_op_size(x,y)
desired = desired
assert_array_equal(actual,desired)
def generic_error_check(self,x,y):
self.assertRaises(ValueError, size_check.binary_op_size, x, y)
def desired_type(self,val):
return np.array(val)
def test_scalar(self):
x,y = (),()
desired = self.desired_type(())
self.generic_check(x,y,desired)
def test_x1(self):
x,y = (1,),()
desired = self.desired_type((1,))
self.generic_check(x,y,desired)
def test_y1(self):
x,y = (),(1,)
desired = self.desired_type((1,))
self.generic_check(x,y,desired)
def test_x_y(self):
x,y = (5,),(5,)
desired = self.desired_type((5,))
self.generic_check(x,y,desired)
def test_x_y2(self):
x,y = (5,10),(5,10)
desired = self.desired_type((5,10))
self.generic_check(x,y,desired)
def test_x_y3(self):
x,y = (5,10),(1,10)
desired = self.desired_type((5,10))
self.generic_check(x,y,desired)
def test_x_y4(self):
x,y = (1,10),(5,10)
desired = self.desired_type((5,10))
self.generic_check(x,y,desired)
def test_x_y5(self):
x,y = (5,1),(1,10)
desired = self.desired_type((5,10))
self.generic_check(x,y,desired)
def test_x_y6(self):
x,y = (1,10),(5,1)
desired = self.desired_type((5,10))
self.generic_check(x,y,desired)
def test_x_y7(self):
x,y = (5,4,3,2,1),(3,2,1)
desired = self.desired_type((5,4,3,2,1))
self.generic_check(x,y,desired)
def test_error1(self):
x,y = (5,),(4,)
self.generic_error_check(x,y)
def test_error2(self):
x,y = (5,5),(4,5)
self.generic_error_check(x,y)
class TestDummyArray(TestBinaryOpSize):
def generic_check(self,x,y,desired):
if isinstance(x, tuple):
x = np.ones(x)
if isinstance(y, tuple):
y = np.ones(y)
xx = size_check.dummy_array(x)
yy = size_check.dummy_array(y)
ops = ['+', '-', '/', '*', '<<', '>>']
for op in ops:
actual = eval('xx' + op + 'yy')
desired = desired
assert_array_equal(actual,desired)
def desired_type(self,val):
return size_check.dummy_array(np.array(val),1)
class TestDummyArrayIndexing(TestCase):
def generic_check(self,ary,expr,desired):
a = size_check.dummy_array(ary)
actual = eval(expr).shape
assert_array_equal(actual,desired, expr)
def generic_wrap(self,a,expr):
desired = np.array(eval(expr).shape)
try:
self.generic_check(a,expr,desired)
except IndexError:
if 0 not in desired:
msg = '%s raised IndexError in dummy_array, but forms\n' \
'valid array shape -> %s' % (expr, str(desired))
raise AttributeError(msg)
def generic_1d(self,expr):
a = np.arange(10)
self.generic_wrap(a,expr)
def generic_2d(self,expr):
a = np.ones((10,20))
self.generic_wrap(a,expr)
def generic_3d(self,expr):
a = np.ones((10,20,1))
self.generic_wrap(a,expr)
def generic_1d_index(self,expr):
a = np.arange(10)
desired = np.array(())
self.generic_check(a,expr,desired)
def test_1d_index_0(self):
self.generic_1d_index('a[0]')
def test_1d_index_1(self):
self.generic_1d_index('a[4]')
def test_1d_index_2(self):
self.generic_1d_index('a[-4]')
def test_1d_index_3(self):
try:
self.generic_1d('a[12]')
except IndexError:
pass
def test_1d_index_calculated(self):
self.generic_1d_index('a[0+1]')
def test_1d_0(self):
self.generic_1d('a[:]')
def test_1d_1(self):
self.generic_1d('a[1:]')
def test_1d_2(self):
self.generic_1d('a[-1:]')
def test_1d_3(self):
self.generic_1d('a[-11:]')
def test_1d_4(self):
self.generic_1d('a[:1]')
def test_1d_5(self):
self.generic_1d('a[:-1]')
def test_1d_6(self):
self.generic_1d('a[:-11]')
def test_1d_7(self):
self.generic_1d('a[1:5]')
def test_1d_8(self):
self.generic_1d('a[1:-5]')
def test_1d_9(self):
# don't support zero length slicing at the moment.
try:
self.generic_1d('a[-1:-5]')
except IndexError:
pass
def test_1d_10(self):
self.generic_1d('a[-5:-1]')
def test_1d_stride_0(self):
self.generic_1d('a[::1]')
def test_1d_stride_1(self):
self.generic_1d('a[::-1]')
def test_1d_stride_2(self):
self.generic_1d('a[1::1]')
def test_1d_stride_3(self):
self.generic_1d('a[1::-1]')
def test_1d_stride_4(self):
# don't support zero length slicing at the moment.
try:
self.generic_1d('a[1:5:-1]')
except IndexError:
pass
def test_1d_stride_5(self):
self.generic_1d('a[5:1:-1]')
def test_1d_stride_6(self):
self.generic_1d('a[:4:1]')
def test_1d_stride_7(self):
self.generic_1d('a[:4:-1]')
def test_1d_stride_8(self):
self.generic_1d('a[:-4:1]')
def test_1d_stride_9(self):
self.generic_1d('a[:-4:-1]')
def test_1d_stride_10(self):
self.generic_1d('a[:-3:2]')
def test_1d_stride_11(self):
self.generic_1d('a[:-3:-2]')
def test_1d_stride_12(self):
self.generic_1d('a[:-3:-7]')
def test_1d_random(self):
# throw a bunch of different indexes at it for good measure.
choices = map(lambda x: repr(x),range(50)) + range(50) + ['']*50
for i in range(100):
try:
beg = random.choice(choices)
end = random.choice(choices)
step = random.choice(choices)
if step in ['0',0]:
step = 'None'
self.generic_1d('a[%s:%s:%s]' % (beg,end,step))
except IndexError:
pass
def test_2d_0(self):
self.generic_2d('a[:]')
def test_2d_1(self):
self.generic_2d('a[:2]')
def test_2d_2(self):
self.generic_2d('a[:,:]')
def test_2d_random(self):
# throw a bunch of different indexes at it for good measure.
choices = map(lambda x: repr(x),range(50)) + range(50) + ['']*50
for i in range(100):
try:
beg = random.choice(choices)
end = random.choice(choices)
step = random.choice(choices)
beg2 = random.choice(choices)
end2 = random.choice(choices)
step2 = random.choice(choices)
if step in ['0',0]:
step = 'None'
if step2 in ['0',0]:
step2 = 'None'
expr = 'a[%s:%s:%s,%s:%s:%s]' % (beg,end,step,beg2,end2,step2)
self.generic_2d(expr)
except IndexError:
pass
def test_3d_random(self):
# throw a bunch of different indexes at it for good measure.
choices = map(lambda x: repr(x),range(50)) + range(50) + ['']*50
for i in range(100):
try:
idx = []
for i in range(9):
val = random.choice(choices)
if (i+1) % 3 == 0 and val in ['0',0]:
val = 'None'
idx.append(val)
expr = 'a[%s:%s:%s,%s:%s:%s,%s:%s:%s]' % tuple(idx)
self.generic_3d(expr)
except IndexError:
pass
class TestReduction(TestCase):
def test_1d_0(self):
a = np.ones((5,))
actual = size_check.reduction(a,0)
desired = size_check.dummy_array((),1)
assert_array_equal(actual.shape,desired.shape)
def test_2d_0(self):
a = np.ones((5,10))
actual = size_check.reduction(a,0)
desired = size_check.dummy_array((10,),1)
assert_array_equal(actual.shape,desired.shape)
def test_2d_1(self):
a = np.ones((5,10))
actual = size_check.reduction(a,1)
desired = size_check.dummy_array((5,),1)
assert_array_equal(actual.shape,desired.shape)
def test_3d_0(self):
a = np.ones((5,6,7))
actual = size_check.reduction(a,1)
desired = size_check.dummy_array((5,7),1)
assert_array_equal(actual.shape,desired.shape)
def test_error0(self):
a = np.ones((5,))
try:
size_check.reduction(a,-2)
except ValueError:
pass
def test_error1(self):
a = np.ones((5,))
try:
size_check.reduction(a,1)
except ValueError:
pass
class TestExpressions(TestCase):
def generic_check(self,expr,desired,**kw):
ast_list = parser.expr(expr).tolist()
args = harvest_variables(ast_list)
loc = locals().update(kw)
for var in args:
s = '%s = size_check.dummy_array(%s)' % (var,var)
exec(s,loc)
try:
actual = eval(expr,locals()).shape
except:
actual = 'failed'
if actual is 'failed' and desired is 'failed':
return
assert_array_equal(actual,desired, expr)
def generic_wrap(self,expr,**kw):
try:
x = np.array(eval(expr,kw))
try:
desired = x.shape
except:
desired = np.zeros(())
except:
desired = 'failed'
self.generic_check(expr,desired,**kw)
def test_generic_1d(self):
a = np.arange(10)
expr = 'a[:]'
self.generic_wrap(expr,a=a)
expr = 'a[:] + a'
self.generic_wrap(expr,a=a)
bad_expr = 'a[4:] + a'
self.generic_wrap(bad_expr,a=a)
a = np.arange(10)
b = np.ones((1,10))
expr = 'a + b'
self.generic_wrap(expr,a=a,b=b)
bad_expr = 'a[:5] + b'
self.generic_wrap(bad_expr,a=a,b=b)
def test_single_index(self):
a = np.arange(10)
expr = 'a[5] + a[3]'
self.generic_wrap(expr,a=a)
def test_calculated_index(self):
a = np.arange(10)
nx = 0
expr = 'a[5] + a[nx+3]'
size_check.check_expr(expr,locals())
def test_calculated_index2(self):
a = np.arange(10)
nx = 0
expr = 'a[1:5] + a[nx+1:5+nx]'
size_check.check_expr(expr,locals())
def generic_2d(self,expr):
a = np.ones((10,20))
self.generic_wrap(a,expr)
def generic_3d(self,expr):
a = np.ones((10,20,1))
self.generic_wrap(a,expr)
if __name__ == "__main__":
run_module_suite()
|
