Lines Matching refs:np
2 import numpy as np namespace
10 ar=np.zeros(np.array(a.shape) * 2)
19 a=np.array([1.,-3.,4.,0.,-10.,8.])
46 a=np.array([1.,-3.,4.,0.5,-10.,8.])
74 a=np.zeros((12,3))
75 w=np.array([[2.0] * 12])[0]
92 scaled= np.dot(a.T , w)
94 ref=scaled/np.sum(w)
97 points = np.array(a).reshape(12*3)
111 s = np.random.randn(nb)
112 w = np.random.randn(nb)
114 ref=np.dot(s,w)/np.sum(w)
123 s = np.abs(np.random.randn(nb))
124 s = s / np.sum(s)
137 sa = np.abs(np.random.randn(nb))
138 sa = sa / np.sum(sa)
140 sb = np.abs(np.random.randn(nb))
141 sb = sb / np.sum(sb)
154 s = np.abs(np.random.randn(nb))
155 s = s / np.sum(s)
164 sa = np.abs(np.random.randn(nb))
165 sa = sa / np.sum(sa)
167 sb = np.abs(np.random.randn(nb))
168 sb = sb / np.sum(sb)
176 ref=np.log(np.dot(sa,sb))
179 sa = np.log(sa)
180 sb = np.log(sb)
187 sa = np.random.randn(nb)
189 ref = np.exp(sa)
202 sa = np.abs(np.random.randn(nb)) + 0.001
204 ref = np.log(sa)
217 a=np.array([[4,12,-16],[12,37,-43],[-16,-43,98]])
232 tmp = np.copy(m[j,:])
233 m[j,:] = np.copy(m[k,:])
240 p=np.identity(n)
256 p=np.identity(n)
269 a = np.array([[3, 0, 0, 0], [2, 1, 0, 0], [1, 0, 1, 0], [1, 1, 1, 1]])
270 b = np.array([[4,2,4,2],[8,4,8,4]]).T
276 b = np.array([[4,2,4,2],[8,4,8,4]]).T
282 b = np.array([[4,2,4,2],[8,4,8,4]]).T
289 a = np.array([[3, 0, 0, 0], [2, 1, 0, 0], [1, 0, 1, 0], [1, 1, 1, 1]])
290 b = np.array([[4,2,4,2],[8,4,8,4]]).T
296 b = np.array([[4,2,4,2],[8,4,8,4]]).T
302 b = np.array([[4,2,4,2],[8,4,8,4]]).T
309 a = np.array([[3, 0, 0, 0], [2, 1, 0, 0], [1, 0, 1, 0], [1, 1, 1, 1]])
310 b = np.array([[4,2,4,2],[8,4,8,4]]).T
320 a = np.array([[3, 0, 0, 0], [2, 1, 0, 0], [1, 0, 1, 0], [1, 1, 1, 1]])
331 s = np.random.randn(nb)
332 ref = np.abs(s)
339 sa = np.random.randn(nb)
340 sb = np.random.randn(nb)
348 sa = np.random.randn(nb)
349 sb = np.random.randn(nb)
357 sa = np.random.randn(nb)
358 sb = np.random.randn(nb)
366 sa = np.random.randn(nb)
367 sb = np.random.randn(nb)
375 sa = np.random.randn(nb)
383 sa = np.random.randn(nb)
391 sa = np.random.randn(nb)
399 sa = np.random.randn(nb)
400 ref = np.mean(sa)
407 sa = np.random.randn(nb)
408 ref = np.sum(sa * sa)
415 sa = np.random.randn(nb)
423 sa = np.random.randn(nb)
432 ref = np.ones(nb)*4.0
438 sa = np.random.randn(nb)
460 assert ((filtered_x == np.hstack([ra,rb])).all)
463 sa = np.random.randn(nb)
465 ref = np.abs(ca)
475 sa = np.random.randn(nb)
477 ref = np.abs(ca) * np.abs(ca)
487 sa = np.random.randn(nb)
489 sb = np.random.randn(nb)