test_old_ma.py 32 KB

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  1. from functools import reduce
  2. import numpy as np
  3. import numpy.core.umath as umath
  4. import numpy.core.fromnumeric as fromnumeric
  5. from numpy.testing import (
  6. assert_, assert_raises, assert_equal,
  7. )
  8. from numpy.ma import (
  9. MaskType, MaskedArray, absolute, add, all, allclose, allequal, alltrue,
  10. arange, arccos, arcsin, arctan, arctan2, array, average, choose,
  11. concatenate, conjugate, cos, cosh, count, divide, equal, exp, filled,
  12. getmask, greater, greater_equal, inner, isMaskedArray, less,
  13. less_equal, log, log10, make_mask, masked, masked_array, masked_equal,
  14. masked_greater, masked_greater_equal, masked_inside, masked_less,
  15. masked_less_equal, masked_not_equal, masked_outside,
  16. masked_print_option, masked_values, masked_where, maximum, minimum,
  17. multiply, nomask, nonzero, not_equal, ones, outer, product, put, ravel,
  18. repeat, resize, shape, sin, sinh, sometrue, sort, sqrt, subtract, sum,
  19. take, tan, tanh, transpose, where, zeros,
  20. )
  21. from numpy.compat import pickle
  22. pi = np.pi
  23. def eq(v, w, msg=''):
  24. result = allclose(v, w)
  25. if not result:
  26. print(f'Not eq:{msg}\n{v}\n----{w}')
  27. return result
  28. class TestMa:
  29. def setup(self):
  30. x = np.array([1., 1., 1., -2., pi/2.0, 4., 5., -10., 10., 1., 2., 3.])
  31. y = np.array([5., 0., 3., 2., -1., -4., 0., -10., 10., 1., 0., 3.])
  32. a10 = 10.
  33. m1 = [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
  34. m2 = [0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1]
  35. xm = array(x, mask=m1)
  36. ym = array(y, mask=m2)
  37. z = np.array([-.5, 0., .5, .8])
  38. zm = array(z, mask=[0, 1, 0, 0])
  39. xf = np.where(m1, 1e+20, x)
  40. s = x.shape
  41. xm.set_fill_value(1e+20)
  42. self.d = (x, y, a10, m1, m2, xm, ym, z, zm, xf, s)
  43. def test_testBasic1d(self):
  44. # Test of basic array creation and properties in 1 dimension.
  45. (x, y, a10, m1, m2, xm, ym, z, zm, xf, s) = self.d
  46. assert_(not isMaskedArray(x))
  47. assert_(isMaskedArray(xm))
  48. assert_equal(shape(xm), s)
  49. assert_equal(xm.shape, s)
  50. assert_equal(xm.dtype, x.dtype)
  51. assert_equal(xm.size, reduce(lambda x, y:x * y, s))
  52. assert_equal(count(xm), len(m1) - reduce(lambda x, y:x + y, m1))
  53. assert_(eq(xm, xf))
  54. assert_(eq(filled(xm, 1.e20), xf))
  55. assert_(eq(x, xm))
  56. def test_testBasic2d(self):
  57. # Test of basic array creation and properties in 2 dimensions.
  58. for s in [(4, 3), (6, 2)]:
  59. (x, y, a10, m1, m2, xm, ym, z, zm, xf, s) = self.d
  60. x.shape = s
  61. y.shape = s
  62. xm.shape = s
  63. ym.shape = s
  64. xf.shape = s
  65. assert_(not isMaskedArray(x))
  66. assert_(isMaskedArray(xm))
  67. assert_equal(shape(xm), s)
  68. assert_equal(xm.shape, s)
  69. assert_equal(xm.size, reduce(lambda x, y:x * y, s))
  70. assert_equal(count(xm),
  71. len(m1) - reduce(lambda x, y:x + y, m1))
  72. assert_(eq(xm, xf))
  73. assert_(eq(filled(xm, 1.e20), xf))
  74. assert_(eq(x, xm))
  75. self.setup()
  76. def test_testArithmetic(self):
  77. # Test of basic arithmetic.
  78. (x, y, a10, m1, m2, xm, ym, z, zm, xf, s) = self.d
  79. a2d = array([[1, 2], [0, 4]])
  80. a2dm = masked_array(a2d, [[0, 0], [1, 0]])
  81. assert_(eq(a2d * a2d, a2d * a2dm))
  82. assert_(eq(a2d + a2d, a2d + a2dm))
  83. assert_(eq(a2d - a2d, a2d - a2dm))
  84. for s in [(12,), (4, 3), (2, 6)]:
  85. x = x.reshape(s)
  86. y = y.reshape(s)
  87. xm = xm.reshape(s)
  88. ym = ym.reshape(s)
  89. xf = xf.reshape(s)
  90. assert_(eq(-x, -xm))
  91. assert_(eq(x + y, xm + ym))
  92. assert_(eq(x - y, xm - ym))
  93. assert_(eq(x * y, xm * ym))
  94. with np.errstate(divide='ignore', invalid='ignore'):
  95. assert_(eq(x / y, xm / ym))
  96. assert_(eq(a10 + y, a10 + ym))
  97. assert_(eq(a10 - y, a10 - ym))
  98. assert_(eq(a10 * y, a10 * ym))
  99. with np.errstate(divide='ignore', invalid='ignore'):
  100. assert_(eq(a10 / y, a10 / ym))
  101. assert_(eq(x + a10, xm + a10))
  102. assert_(eq(x - a10, xm - a10))
  103. assert_(eq(x * a10, xm * a10))
  104. assert_(eq(x / a10, xm / a10))
  105. assert_(eq(x ** 2, xm ** 2))
  106. assert_(eq(abs(x) ** 2.5, abs(xm) ** 2.5))
  107. assert_(eq(x ** y, xm ** ym))
  108. assert_(eq(np.add(x, y), add(xm, ym)))
  109. assert_(eq(np.subtract(x, y), subtract(xm, ym)))
  110. assert_(eq(np.multiply(x, y), multiply(xm, ym)))
  111. with np.errstate(divide='ignore', invalid='ignore'):
  112. assert_(eq(np.divide(x, y), divide(xm, ym)))
  113. def test_testMixedArithmetic(self):
  114. na = np.array([1])
  115. ma = array([1])
  116. assert_(isinstance(na + ma, MaskedArray))
  117. assert_(isinstance(ma + na, MaskedArray))
  118. def test_testUfuncs1(self):
  119. # Test various functions such as sin, cos.
  120. (x, y, a10, m1, m2, xm, ym, z, zm, xf, s) = self.d
  121. assert_(eq(np.cos(x), cos(xm)))
  122. assert_(eq(np.cosh(x), cosh(xm)))
  123. assert_(eq(np.sin(x), sin(xm)))
  124. assert_(eq(np.sinh(x), sinh(xm)))
  125. assert_(eq(np.tan(x), tan(xm)))
  126. assert_(eq(np.tanh(x), tanh(xm)))
  127. with np.errstate(divide='ignore', invalid='ignore'):
  128. assert_(eq(np.sqrt(abs(x)), sqrt(xm)))
  129. assert_(eq(np.log(abs(x)), log(xm)))
  130. assert_(eq(np.log10(abs(x)), log10(xm)))
  131. assert_(eq(np.exp(x), exp(xm)))
  132. assert_(eq(np.arcsin(z), arcsin(zm)))
  133. assert_(eq(np.arccos(z), arccos(zm)))
  134. assert_(eq(np.arctan(z), arctan(zm)))
  135. assert_(eq(np.arctan2(x, y), arctan2(xm, ym)))
  136. assert_(eq(np.absolute(x), absolute(xm)))
  137. assert_(eq(np.equal(x, y), equal(xm, ym)))
  138. assert_(eq(np.not_equal(x, y), not_equal(xm, ym)))
  139. assert_(eq(np.less(x, y), less(xm, ym)))
  140. assert_(eq(np.greater(x, y), greater(xm, ym)))
  141. assert_(eq(np.less_equal(x, y), less_equal(xm, ym)))
  142. assert_(eq(np.greater_equal(x, y), greater_equal(xm, ym)))
  143. assert_(eq(np.conjugate(x), conjugate(xm)))
  144. assert_(eq(np.concatenate((x, y)), concatenate((xm, ym))))
  145. assert_(eq(np.concatenate((x, y)), concatenate((x, y))))
  146. assert_(eq(np.concatenate((x, y)), concatenate((xm, y))))
  147. assert_(eq(np.concatenate((x, y, x)), concatenate((x, ym, x))))
  148. def test_xtestCount(self):
  149. # Test count
  150. ott = array([0., 1., 2., 3.], mask=[1, 0, 0, 0])
  151. assert_(count(ott).dtype.type is np.intp)
  152. assert_equal(3, count(ott))
  153. assert_equal(1, count(1))
  154. assert_(eq(0, array(1, mask=[1])))
  155. ott = ott.reshape((2, 2))
  156. assert_(count(ott).dtype.type is np.intp)
  157. assert_(isinstance(count(ott, 0), np.ndarray))
  158. assert_(count(ott).dtype.type is np.intp)
  159. assert_(eq(3, count(ott)))
  160. assert_(getmask(count(ott, 0)) is nomask)
  161. assert_(eq([1, 2], count(ott, 0)))
  162. def test_testMinMax(self):
  163. # Test minimum and maximum.
  164. (x, y, a10, m1, m2, xm, ym, z, zm, xf, s) = self.d
  165. xr = np.ravel(x) # max doesn't work if shaped
  166. xmr = ravel(xm)
  167. # true because of careful selection of data
  168. assert_(eq(max(xr), maximum.reduce(xmr)))
  169. assert_(eq(min(xr), minimum.reduce(xmr)))
  170. def test_testAddSumProd(self):
  171. # Test add, sum, product.
  172. (x, y, a10, m1, m2, xm, ym, z, zm, xf, s) = self.d
  173. assert_(eq(np.add.reduce(x), add.reduce(x)))
  174. assert_(eq(np.add.accumulate(x), add.accumulate(x)))
  175. assert_(eq(4, sum(array(4), axis=0)))
  176. assert_(eq(4, sum(array(4), axis=0)))
  177. assert_(eq(np.sum(x, axis=0), sum(x, axis=0)))
  178. assert_(eq(np.sum(filled(xm, 0), axis=0), sum(xm, axis=0)))
  179. assert_(eq(np.sum(x, 0), sum(x, 0)))
  180. assert_(eq(np.product(x, axis=0), product(x, axis=0)))
  181. assert_(eq(np.product(x, 0), product(x, 0)))
  182. assert_(eq(np.product(filled(xm, 1), axis=0),
  183. product(xm, axis=0)))
  184. if len(s) > 1:
  185. assert_(eq(np.concatenate((x, y), 1),
  186. concatenate((xm, ym), 1)))
  187. assert_(eq(np.add.reduce(x, 1), add.reduce(x, 1)))
  188. assert_(eq(np.sum(x, 1), sum(x, 1)))
  189. assert_(eq(np.product(x, 1), product(x, 1)))
  190. def test_testCI(self):
  191. # Test of conversions and indexing
  192. x1 = np.array([1, 2, 4, 3])
  193. x2 = array(x1, mask=[1, 0, 0, 0])
  194. x3 = array(x1, mask=[0, 1, 0, 1])
  195. x4 = array(x1)
  196. # test conversion to strings
  197. str(x2) # raises?
  198. repr(x2) # raises?
  199. assert_(eq(np.sort(x1), sort(x2, fill_value=0)))
  200. # tests of indexing
  201. assert_(type(x2[1]) is type(x1[1]))
  202. assert_(x1[1] == x2[1])
  203. assert_(x2[0] is masked)
  204. assert_(eq(x1[2], x2[2]))
  205. assert_(eq(x1[2:5], x2[2:5]))
  206. assert_(eq(x1[:], x2[:]))
  207. assert_(eq(x1[1:], x3[1:]))
  208. x1[2] = 9
  209. x2[2] = 9
  210. assert_(eq(x1, x2))
  211. x1[1:3] = 99
  212. x2[1:3] = 99
  213. assert_(eq(x1, x2))
  214. x2[1] = masked
  215. assert_(eq(x1, x2))
  216. x2[1:3] = masked
  217. assert_(eq(x1, x2))
  218. x2[:] = x1
  219. x2[1] = masked
  220. assert_(allequal(getmask(x2), array([0, 1, 0, 0])))
  221. x3[:] = masked_array([1, 2, 3, 4], [0, 1, 1, 0])
  222. assert_(allequal(getmask(x3), array([0, 1, 1, 0])))
  223. x4[:] = masked_array([1, 2, 3, 4], [0, 1, 1, 0])
  224. assert_(allequal(getmask(x4), array([0, 1, 1, 0])))
  225. assert_(allequal(x4, array([1, 2, 3, 4])))
  226. x1 = np.arange(5) * 1.0
  227. x2 = masked_values(x1, 3.0)
  228. assert_(eq(x1, x2))
  229. assert_(allequal(array([0, 0, 0, 1, 0], MaskType), x2.mask))
  230. assert_(eq(3.0, x2.fill_value))
  231. x1 = array([1, 'hello', 2, 3], object)
  232. x2 = np.array([1, 'hello', 2, 3], object)
  233. s1 = x1[1]
  234. s2 = x2[1]
  235. assert_equal(type(s2), str)
  236. assert_equal(type(s1), str)
  237. assert_equal(s1, s2)
  238. assert_(x1[1:1].shape == (0,))
  239. def test_testCopySize(self):
  240. # Tests of some subtle points of copying and sizing.
  241. n = [0, 0, 1, 0, 0]
  242. m = make_mask(n)
  243. m2 = make_mask(m)
  244. assert_(m is m2)
  245. m3 = make_mask(m, copy=True)
  246. assert_(m is not m3)
  247. x1 = np.arange(5)
  248. y1 = array(x1, mask=m)
  249. assert_(y1._data is not x1)
  250. assert_(allequal(x1, y1._data))
  251. assert_(y1._mask is m)
  252. y1a = array(y1, copy=0)
  253. # For copy=False, one might expect that the array would just
  254. # passed on, i.e., that it would be "is" instead of "==".
  255. # See gh-4043 for discussion.
  256. assert_(y1a._mask.__array_interface__ ==
  257. y1._mask.__array_interface__)
  258. y2 = array(x1, mask=m3, copy=0)
  259. assert_(y2._mask is m3)
  260. assert_(y2[2] is masked)
  261. y2[2] = 9
  262. assert_(y2[2] is not masked)
  263. assert_(y2._mask is m3)
  264. assert_(allequal(y2.mask, 0))
  265. y2a = array(x1, mask=m, copy=1)
  266. assert_(y2a._mask is not m)
  267. assert_(y2a[2] is masked)
  268. y2a[2] = 9
  269. assert_(y2a[2] is not masked)
  270. assert_(y2a._mask is not m)
  271. assert_(allequal(y2a.mask, 0))
  272. y3 = array(x1 * 1.0, mask=m)
  273. assert_(filled(y3).dtype is (x1 * 1.0).dtype)
  274. x4 = arange(4)
  275. x4[2] = masked
  276. y4 = resize(x4, (8,))
  277. assert_(eq(concatenate([x4, x4]), y4))
  278. assert_(eq(getmask(y4), [0, 0, 1, 0, 0, 0, 1, 0]))
  279. y5 = repeat(x4, (2, 2, 2, 2), axis=0)
  280. assert_(eq(y5, [0, 0, 1, 1, 2, 2, 3, 3]))
  281. y6 = repeat(x4, 2, axis=0)
  282. assert_(eq(y5, y6))
  283. def test_testPut(self):
  284. # Test of put
  285. d = arange(5)
  286. n = [0, 0, 0, 1, 1]
  287. m = make_mask(n)
  288. m2 = m.copy()
  289. x = array(d, mask=m)
  290. assert_(x[3] is masked)
  291. assert_(x[4] is masked)
  292. x[[1, 4]] = [10, 40]
  293. assert_(x._mask is m)
  294. assert_(x[3] is masked)
  295. assert_(x[4] is not masked)
  296. assert_(eq(x, [0, 10, 2, -1, 40]))
  297. x = array(d, mask=m2, copy=True)
  298. x.put([0, 1, 2], [-1, 100, 200])
  299. assert_(x._mask is not m2)
  300. assert_(x[3] is masked)
  301. assert_(x[4] is masked)
  302. assert_(eq(x, [-1, 100, 200, 0, 0]))
  303. def test_testPut2(self):
  304. # Test of put
  305. d = arange(5)
  306. x = array(d, mask=[0, 0, 0, 0, 0])
  307. z = array([10, 40], mask=[1, 0])
  308. assert_(x[2] is not masked)
  309. assert_(x[3] is not masked)
  310. x[2:4] = z
  311. assert_(x[2] is masked)
  312. assert_(x[3] is not masked)
  313. assert_(eq(x, [0, 1, 10, 40, 4]))
  314. d = arange(5)
  315. x = array(d, mask=[0, 0, 0, 0, 0])
  316. y = x[2:4]
  317. z = array([10, 40], mask=[1, 0])
  318. assert_(x[2] is not masked)
  319. assert_(x[3] is not masked)
  320. y[:] = z
  321. assert_(y[0] is masked)
  322. assert_(y[1] is not masked)
  323. assert_(eq(y, [10, 40]))
  324. assert_(x[2] is masked)
  325. assert_(x[3] is not masked)
  326. assert_(eq(x, [0, 1, 10, 40, 4]))
  327. def test_testMaPut(self):
  328. (x, y, a10, m1, m2, xm, ym, z, zm, xf, s) = self.d
  329. m = [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1]
  330. i = np.nonzero(m)[0]
  331. put(ym, i, zm)
  332. assert_(all(take(ym, i, axis=0) == zm))
  333. def test_testOddFeatures(self):
  334. # Test of other odd features
  335. x = arange(20)
  336. x = x.reshape(4, 5)
  337. x.flat[5] = 12
  338. assert_(x[1, 0] == 12)
  339. z = x + 10j * x
  340. assert_(eq(z.real, x))
  341. assert_(eq(z.imag, 10 * x))
  342. assert_(eq((z * conjugate(z)).real, 101 * x * x))
  343. z.imag[...] = 0.0
  344. x = arange(10)
  345. x[3] = masked
  346. assert_(str(x[3]) == str(masked))
  347. c = x >= 8
  348. assert_(count(where(c, masked, masked)) == 0)
  349. assert_(shape(where(c, masked, masked)) == c.shape)
  350. z = where(c, x, masked)
  351. assert_(z.dtype is x.dtype)
  352. assert_(z[3] is masked)
  353. assert_(z[4] is masked)
  354. assert_(z[7] is masked)
  355. assert_(z[8] is not masked)
  356. assert_(z[9] is not masked)
  357. assert_(eq(x, z))
  358. z = where(c, masked, x)
  359. assert_(z.dtype is x.dtype)
  360. assert_(z[3] is masked)
  361. assert_(z[4] is not masked)
  362. assert_(z[7] is not masked)
  363. assert_(z[8] is masked)
  364. assert_(z[9] is masked)
  365. z = masked_where(c, x)
  366. assert_(z.dtype is x.dtype)
  367. assert_(z[3] is masked)
  368. assert_(z[4] is not masked)
  369. assert_(z[7] is not masked)
  370. assert_(z[8] is masked)
  371. assert_(z[9] is masked)
  372. assert_(eq(x, z))
  373. x = array([1., 2., 3., 4., 5.])
  374. c = array([1, 1, 1, 0, 0])
  375. x[2] = masked
  376. z = where(c, x, -x)
  377. assert_(eq(z, [1., 2., 0., -4., -5]))
  378. c[0] = masked
  379. z = where(c, x, -x)
  380. assert_(eq(z, [1., 2., 0., -4., -5]))
  381. assert_(z[0] is masked)
  382. assert_(z[1] is not masked)
  383. assert_(z[2] is masked)
  384. assert_(eq(masked_where(greater(x, 2), x), masked_greater(x, 2)))
  385. assert_(eq(masked_where(greater_equal(x, 2), x),
  386. masked_greater_equal(x, 2)))
  387. assert_(eq(masked_where(less(x, 2), x), masked_less(x, 2)))
  388. assert_(eq(masked_where(less_equal(x, 2), x), masked_less_equal(x, 2)))
  389. assert_(eq(masked_where(not_equal(x, 2), x), masked_not_equal(x, 2)))
  390. assert_(eq(masked_where(equal(x, 2), x), masked_equal(x, 2)))
  391. assert_(eq(masked_where(not_equal(x, 2), x), masked_not_equal(x, 2)))
  392. assert_(eq(masked_inside(list(range(5)), 1, 3), [0, 199, 199, 199, 4]))
  393. assert_(eq(masked_outside(list(range(5)), 1, 3), [199, 1, 2, 3, 199]))
  394. assert_(eq(masked_inside(array(list(range(5)),
  395. mask=[1, 0, 0, 0, 0]), 1, 3).mask,
  396. [1, 1, 1, 1, 0]))
  397. assert_(eq(masked_outside(array(list(range(5)),
  398. mask=[0, 1, 0, 0, 0]), 1, 3).mask,
  399. [1, 1, 0, 0, 1]))
  400. assert_(eq(masked_equal(array(list(range(5)),
  401. mask=[1, 0, 0, 0, 0]), 2).mask,
  402. [1, 0, 1, 0, 0]))
  403. assert_(eq(masked_not_equal(array([2, 2, 1, 2, 1],
  404. mask=[1, 0, 0, 0, 0]), 2).mask,
  405. [1, 0, 1, 0, 1]))
  406. assert_(eq(masked_where([1, 1, 0, 0, 0], [1, 2, 3, 4, 5]),
  407. [99, 99, 3, 4, 5]))
  408. atest = ones((10, 10, 10), dtype=np.float32)
  409. btest = zeros(atest.shape, MaskType)
  410. ctest = masked_where(btest, atest)
  411. assert_(eq(atest, ctest))
  412. z = choose(c, (-x, x))
  413. assert_(eq(z, [1., 2., 0., -4., -5]))
  414. assert_(z[0] is masked)
  415. assert_(z[1] is not masked)
  416. assert_(z[2] is masked)
  417. x = arange(6)
  418. x[5] = masked
  419. y = arange(6) * 10
  420. y[2] = masked
  421. c = array([1, 1, 1, 0, 0, 0], mask=[1, 0, 0, 0, 0, 0])
  422. cm = c.filled(1)
  423. z = where(c, x, y)
  424. zm = where(cm, x, y)
  425. assert_(eq(z, zm))
  426. assert_(getmask(zm) is nomask)
  427. assert_(eq(zm, [0, 1, 2, 30, 40, 50]))
  428. z = where(c, masked, 1)
  429. assert_(eq(z, [99, 99, 99, 1, 1, 1]))
  430. z = where(c, 1, masked)
  431. assert_(eq(z, [99, 1, 1, 99, 99, 99]))
  432. def test_testMinMax2(self):
  433. # Test of minimum, maximum.
  434. assert_(eq(minimum([1, 2, 3], [4, 0, 9]), [1, 0, 3]))
  435. assert_(eq(maximum([1, 2, 3], [4, 0, 9]), [4, 2, 9]))
  436. x = arange(5)
  437. y = arange(5) - 2
  438. x[3] = masked
  439. y[0] = masked
  440. assert_(eq(minimum(x, y), where(less(x, y), x, y)))
  441. assert_(eq(maximum(x, y), where(greater(x, y), x, y)))
  442. assert_(minimum.reduce(x) == 0)
  443. assert_(maximum.reduce(x) == 4)
  444. def test_testTakeTransposeInnerOuter(self):
  445. # Test of take, transpose, inner, outer products
  446. x = arange(24)
  447. y = np.arange(24)
  448. x[5:6] = masked
  449. x = x.reshape(2, 3, 4)
  450. y = y.reshape(2, 3, 4)
  451. assert_(eq(np.transpose(y, (2, 0, 1)), transpose(x, (2, 0, 1))))
  452. assert_(eq(np.take(y, (2, 0, 1), 1), take(x, (2, 0, 1), 1)))
  453. assert_(eq(np.inner(filled(x, 0), filled(y, 0)),
  454. inner(x, y)))
  455. assert_(eq(np.outer(filled(x, 0), filled(y, 0)),
  456. outer(x, y)))
  457. y = array(['abc', 1, 'def', 2, 3], object)
  458. y[2] = masked
  459. t = take(y, [0, 3, 4])
  460. assert_(t[0] == 'abc')
  461. assert_(t[1] == 2)
  462. assert_(t[2] == 3)
  463. def test_testInplace(self):
  464. # Test of inplace operations and rich comparisons
  465. y = arange(10)
  466. x = arange(10)
  467. xm = arange(10)
  468. xm[2] = masked
  469. x += 1
  470. assert_(eq(x, y + 1))
  471. xm += 1
  472. assert_(eq(x, y + 1))
  473. x = arange(10)
  474. xm = arange(10)
  475. xm[2] = masked
  476. x -= 1
  477. assert_(eq(x, y - 1))
  478. xm -= 1
  479. assert_(eq(xm, y - 1))
  480. x = arange(10) * 1.0
  481. xm = arange(10) * 1.0
  482. xm[2] = masked
  483. x *= 2.0
  484. assert_(eq(x, y * 2))
  485. xm *= 2.0
  486. assert_(eq(xm, y * 2))
  487. x = arange(10) * 2
  488. xm = arange(10)
  489. xm[2] = masked
  490. x //= 2
  491. assert_(eq(x, y))
  492. xm //= 2
  493. assert_(eq(x, y))
  494. x = arange(10) * 1.0
  495. xm = arange(10) * 1.0
  496. xm[2] = masked
  497. x /= 2.0
  498. assert_(eq(x, y / 2.0))
  499. xm /= arange(10)
  500. assert_(eq(xm, ones((10,))))
  501. x = arange(10).astype(np.float32)
  502. xm = arange(10)
  503. xm[2] = masked
  504. x += 1.
  505. assert_(eq(x, y + 1.))
  506. def test_testPickle(self):
  507. # Test of pickling
  508. x = arange(12)
  509. x[4:10:2] = masked
  510. x = x.reshape(4, 3)
  511. for proto in range(2, pickle.HIGHEST_PROTOCOL + 1):
  512. s = pickle.dumps(x, protocol=proto)
  513. y = pickle.loads(s)
  514. assert_(eq(x, y))
  515. def test_testMasked(self):
  516. # Test of masked element
  517. xx = arange(6)
  518. xx[1] = masked
  519. assert_(str(masked) == '--')
  520. assert_(xx[1] is masked)
  521. assert_equal(filled(xx[1], 0), 0)
  522. def test_testAverage1(self):
  523. # Test of average.
  524. ott = array([0., 1., 2., 3.], mask=[1, 0, 0, 0])
  525. assert_(eq(2.0, average(ott, axis=0)))
  526. assert_(eq(2.0, average(ott, weights=[1., 1., 2., 1.])))
  527. result, wts = average(ott, weights=[1., 1., 2., 1.], returned=True)
  528. assert_(eq(2.0, result))
  529. assert_(wts == 4.0)
  530. ott[:] = masked
  531. assert_(average(ott, axis=0) is masked)
  532. ott = array([0., 1., 2., 3.], mask=[1, 0, 0, 0])
  533. ott = ott.reshape(2, 2)
  534. ott[:, 1] = masked
  535. assert_(eq(average(ott, axis=0), [2.0, 0.0]))
  536. assert_(average(ott, axis=1)[0] is masked)
  537. assert_(eq([2., 0.], average(ott, axis=0)))
  538. result, wts = average(ott, axis=0, returned=True)
  539. assert_(eq(wts, [1., 0.]))
  540. def test_testAverage2(self):
  541. # More tests of average.
  542. w1 = [0, 1, 1, 1, 1, 0]
  543. w2 = [[0, 1, 1, 1, 1, 0], [1, 0, 0, 0, 0, 1]]
  544. x = arange(6)
  545. assert_(allclose(average(x, axis=0), 2.5))
  546. assert_(allclose(average(x, axis=0, weights=w1), 2.5))
  547. y = array([arange(6), 2.0 * arange(6)])
  548. assert_(allclose(average(y, None),
  549. np.add.reduce(np.arange(6)) * 3. / 12.))
  550. assert_(allclose(average(y, axis=0), np.arange(6) * 3. / 2.))
  551. assert_(allclose(average(y, axis=1),
  552. [average(x, axis=0), average(x, axis=0)*2.0]))
  553. assert_(allclose(average(y, None, weights=w2), 20. / 6.))
  554. assert_(allclose(average(y, axis=0, weights=w2),
  555. [0., 1., 2., 3., 4., 10.]))
  556. assert_(allclose(average(y, axis=1),
  557. [average(x, axis=0), average(x, axis=0)*2.0]))
  558. m1 = zeros(6)
  559. m2 = [0, 0, 1, 1, 0, 0]
  560. m3 = [[0, 0, 1, 1, 0, 0], [0, 1, 1, 1, 1, 0]]
  561. m4 = ones(6)
  562. m5 = [0, 1, 1, 1, 1, 1]
  563. assert_(allclose(average(masked_array(x, m1), axis=0), 2.5))
  564. assert_(allclose(average(masked_array(x, m2), axis=0), 2.5))
  565. assert_(average(masked_array(x, m4), axis=0) is masked)
  566. assert_equal(average(masked_array(x, m5), axis=0), 0.0)
  567. assert_equal(count(average(masked_array(x, m4), axis=0)), 0)
  568. z = masked_array(y, m3)
  569. assert_(allclose(average(z, None), 20. / 6.))
  570. assert_(allclose(average(z, axis=0),
  571. [0., 1., 99., 99., 4.0, 7.5]))
  572. assert_(allclose(average(z, axis=1), [2.5, 5.0]))
  573. assert_(allclose(average(z, axis=0, weights=w2),
  574. [0., 1., 99., 99., 4.0, 10.0]))
  575. a = arange(6)
  576. b = arange(6) * 3
  577. r1, w1 = average([[a, b], [b, a]], axis=1, returned=True)
  578. assert_equal(shape(r1), shape(w1))
  579. assert_equal(r1.shape, w1.shape)
  580. r2, w2 = average(ones((2, 2, 3)), axis=0, weights=[3, 1], returned=True)
  581. assert_equal(shape(w2), shape(r2))
  582. r2, w2 = average(ones((2, 2, 3)), returned=True)
  583. assert_equal(shape(w2), shape(r2))
  584. r2, w2 = average(ones((2, 2, 3)), weights=ones((2, 2, 3)), returned=True)
  585. assert_(shape(w2) == shape(r2))
  586. a2d = array([[1, 2], [0, 4]], float)
  587. a2dm = masked_array(a2d, [[0, 0], [1, 0]])
  588. a2da = average(a2d, axis=0)
  589. assert_(eq(a2da, [0.5, 3.0]))
  590. a2dma = average(a2dm, axis=0)
  591. assert_(eq(a2dma, [1.0, 3.0]))
  592. a2dma = average(a2dm, axis=None)
  593. assert_(eq(a2dma, 7. / 3.))
  594. a2dma = average(a2dm, axis=1)
  595. assert_(eq(a2dma, [1.5, 4.0]))
  596. def test_testToPython(self):
  597. assert_equal(1, int(array(1)))
  598. assert_equal(1.0, float(array(1)))
  599. assert_equal(1, int(array([[[1]]])))
  600. assert_equal(1.0, float(array([[1]])))
  601. assert_raises(TypeError, float, array([1, 1]))
  602. assert_raises(ValueError, bool, array([0, 1]))
  603. assert_raises(ValueError, bool, array([0, 0], mask=[0, 1]))
  604. def test_testScalarArithmetic(self):
  605. xm = array(0, mask=1)
  606. #TODO FIXME: Find out what the following raises a warning in r8247
  607. with np.errstate(divide='ignore'):
  608. assert_((1 / array(0)).mask)
  609. assert_((1 + xm).mask)
  610. assert_((-xm).mask)
  611. assert_((-xm).mask)
  612. assert_(maximum(xm, xm).mask)
  613. assert_(minimum(xm, xm).mask)
  614. assert_(xm.filled().dtype is xm._data.dtype)
  615. x = array(0, mask=0)
  616. assert_(x.filled() == x._data)
  617. assert_equal(str(xm), str(masked_print_option))
  618. def test_testArrayMethods(self):
  619. a = array([1, 3, 2])
  620. assert_(eq(a.any(), a._data.any()))
  621. assert_(eq(a.all(), a._data.all()))
  622. assert_(eq(a.argmax(), a._data.argmax()))
  623. assert_(eq(a.argmin(), a._data.argmin()))
  624. assert_(eq(a.choose(0, 1, 2, 3, 4),
  625. a._data.choose(0, 1, 2, 3, 4)))
  626. assert_(eq(a.compress([1, 0, 1]), a._data.compress([1, 0, 1])))
  627. assert_(eq(a.conj(), a._data.conj()))
  628. assert_(eq(a.conjugate(), a._data.conjugate()))
  629. m = array([[1, 2], [3, 4]])
  630. assert_(eq(m.diagonal(), m._data.diagonal()))
  631. assert_(eq(a.sum(), a._data.sum()))
  632. assert_(eq(a.take([1, 2]), a._data.take([1, 2])))
  633. assert_(eq(m.transpose(), m._data.transpose()))
  634. def test_testArrayAttributes(self):
  635. a = array([1, 3, 2])
  636. assert_equal(a.ndim, 1)
  637. def test_testAPI(self):
  638. assert_(not [m for m in dir(np.ndarray)
  639. if m not in dir(MaskedArray) and
  640. not m.startswith('_')])
  641. def test_testSingleElementSubscript(self):
  642. a = array([1, 3, 2])
  643. b = array([1, 3, 2], mask=[1, 0, 1])
  644. assert_equal(a[0].shape, ())
  645. assert_equal(b[0].shape, ())
  646. assert_equal(b[1].shape, ())
  647. class TestUfuncs:
  648. def setup(self):
  649. self.d = (array([1.0, 0, -1, pi / 2] * 2, mask=[0, 1] + [0] * 6),
  650. array([1.0, 0, -1, pi / 2] * 2, mask=[1, 0] + [0] * 6),)
  651. def test_testUfuncRegression(self):
  652. f_invalid_ignore = [
  653. 'sqrt', 'arctanh', 'arcsin', 'arccos',
  654. 'arccosh', 'arctanh', 'log', 'log10', 'divide',
  655. 'true_divide', 'floor_divide', 'remainder', 'fmod']
  656. for f in ['sqrt', 'log', 'log10', 'exp', 'conjugate',
  657. 'sin', 'cos', 'tan',
  658. 'arcsin', 'arccos', 'arctan',
  659. 'sinh', 'cosh', 'tanh',
  660. 'arcsinh',
  661. 'arccosh',
  662. 'arctanh',
  663. 'absolute', 'fabs', 'negative',
  664. 'floor', 'ceil',
  665. 'logical_not',
  666. 'add', 'subtract', 'multiply',
  667. 'divide', 'true_divide', 'floor_divide',
  668. 'remainder', 'fmod', 'hypot', 'arctan2',
  669. 'equal', 'not_equal', 'less_equal', 'greater_equal',
  670. 'less', 'greater',
  671. 'logical_and', 'logical_or', 'logical_xor']:
  672. try:
  673. uf = getattr(umath, f)
  674. except AttributeError:
  675. uf = getattr(fromnumeric, f)
  676. mf = getattr(np.ma, f)
  677. args = self.d[:uf.nin]
  678. with np.errstate():
  679. if f in f_invalid_ignore:
  680. np.seterr(invalid='ignore')
  681. if f in ['arctanh', 'log', 'log10']:
  682. np.seterr(divide='ignore')
  683. ur = uf(*args)
  684. mr = mf(*args)
  685. assert_(eq(ur.filled(0), mr.filled(0), f))
  686. assert_(eqmask(ur.mask, mr.mask))
  687. def test_reduce(self):
  688. a = self.d[0]
  689. assert_(not alltrue(a, axis=0))
  690. assert_(sometrue(a, axis=0))
  691. assert_equal(sum(a[:3], axis=0), 0)
  692. assert_equal(product(a, axis=0), 0)
  693. def test_minmax(self):
  694. a = arange(1, 13).reshape(3, 4)
  695. amask = masked_where(a < 5, a)
  696. assert_equal(amask.max(), a.max())
  697. assert_equal(amask.min(), 5)
  698. assert_((amask.max(0) == a.max(0)).all())
  699. assert_((amask.min(0) == [5, 6, 7, 8]).all())
  700. assert_(amask.max(1)[0].mask)
  701. assert_(amask.min(1)[0].mask)
  702. def test_nonzero(self):
  703. for t in "?bhilqpBHILQPfdgFDGO":
  704. x = array([1, 0, 2, 0], mask=[0, 0, 1, 1])
  705. assert_(eq(nonzero(x), [0]))
  706. class TestArrayMethods:
  707. def setup(self):
  708. x = np.array([8.375, 7.545, 8.828, 8.5, 1.757, 5.928,
  709. 8.43, 7.78, 9.865, 5.878, 8.979, 4.732,
  710. 3.012, 6.022, 5.095, 3.116, 5.238, 3.957,
  711. 6.04, 9.63, 7.712, 3.382, 4.489, 6.479,
  712. 7.189, 9.645, 5.395, 4.961, 9.894, 2.893,
  713. 7.357, 9.828, 6.272, 3.758, 6.693, 0.993])
  714. X = x.reshape(6, 6)
  715. XX = x.reshape(3, 2, 2, 3)
  716. m = np.array([0, 1, 0, 1, 0, 0,
  717. 1, 0, 1, 1, 0, 1,
  718. 0, 0, 0, 1, 0, 1,
  719. 0, 0, 0, 1, 1, 1,
  720. 1, 0, 0, 1, 0, 0,
  721. 0, 0, 1, 0, 1, 0])
  722. mx = array(data=x, mask=m)
  723. mX = array(data=X, mask=m.reshape(X.shape))
  724. mXX = array(data=XX, mask=m.reshape(XX.shape))
  725. self.d = (x, X, XX, m, mx, mX, mXX)
  726. def test_trace(self):
  727. (x, X, XX, m, mx, mX, mXX,) = self.d
  728. mXdiag = mX.diagonal()
  729. assert_equal(mX.trace(), mX.diagonal().compressed().sum())
  730. assert_(eq(mX.trace(),
  731. X.trace() - sum(mXdiag.mask * X.diagonal(),
  732. axis=0)))
  733. def test_clip(self):
  734. (x, X, XX, m, mx, mX, mXX,) = self.d
  735. clipped = mx.clip(2, 8)
  736. assert_(eq(clipped.mask, mx.mask))
  737. assert_(eq(clipped._data, x.clip(2, 8)))
  738. assert_(eq(clipped._data, mx._data.clip(2, 8)))
  739. def test_ptp(self):
  740. (x, X, XX, m, mx, mX, mXX,) = self.d
  741. (n, m) = X.shape
  742. assert_equal(mx.ptp(), mx.compressed().ptp())
  743. rows = np.zeros(n, np.float_)
  744. cols = np.zeros(m, np.float_)
  745. for k in range(m):
  746. cols[k] = mX[:, k].compressed().ptp()
  747. for k in range(n):
  748. rows[k] = mX[k].compressed().ptp()
  749. assert_(eq(mX.ptp(0), cols))
  750. assert_(eq(mX.ptp(1), rows))
  751. def test_swapaxes(self):
  752. (x, X, XX, m, mx, mX, mXX,) = self.d
  753. mXswapped = mX.swapaxes(0, 1)
  754. assert_(eq(mXswapped[-1], mX[:, -1]))
  755. mXXswapped = mXX.swapaxes(0, 2)
  756. assert_equal(mXXswapped.shape, (2, 2, 3, 3))
  757. def test_cumprod(self):
  758. (x, X, XX, m, mx, mX, mXX,) = self.d
  759. mXcp = mX.cumprod(0)
  760. assert_(eq(mXcp._data, mX.filled(1).cumprod(0)))
  761. mXcp = mX.cumprod(1)
  762. assert_(eq(mXcp._data, mX.filled(1).cumprod(1)))
  763. def test_cumsum(self):
  764. (x, X, XX, m, mx, mX, mXX,) = self.d
  765. mXcp = mX.cumsum(0)
  766. assert_(eq(mXcp._data, mX.filled(0).cumsum(0)))
  767. mXcp = mX.cumsum(1)
  768. assert_(eq(mXcp._data, mX.filled(0).cumsum(1)))
  769. def test_varstd(self):
  770. (x, X, XX, m, mx, mX, mXX,) = self.d
  771. assert_(eq(mX.var(axis=None), mX.compressed().var()))
  772. assert_(eq(mX.std(axis=None), mX.compressed().std()))
  773. assert_(eq(mXX.var(axis=3).shape, XX.var(axis=3).shape))
  774. assert_(eq(mX.var().shape, X.var().shape))
  775. (mXvar0, mXvar1) = (mX.var(axis=0), mX.var(axis=1))
  776. for k in range(6):
  777. assert_(eq(mXvar1[k], mX[k].compressed().var()))
  778. assert_(eq(mXvar0[k], mX[:, k].compressed().var()))
  779. assert_(eq(np.sqrt(mXvar0[k]),
  780. mX[:, k].compressed().std()))
  781. def eqmask(m1, m2):
  782. if m1 is nomask:
  783. return m2 is nomask
  784. if m2 is nomask:
  785. return m1 is nomask
  786. return (m1 == m2).all()