%PDF- %PDF-
Direktori : /opt/cloudlinux/venv/lib64/python3.11/site-packages/numpy/ma/ |
Current File : //opt/cloudlinux/venv/lib64/python3.11/site-packages/numpy/ma/timer_comparison.py |
import timeit from functools import reduce import numpy as np from numpy import float_ import numpy.core.fromnumeric as fromnumeric from numpy.testing import build_err_msg pi = np.pi class ModuleTester: def __init__(self, module): self.module = module self.allequal = module.allequal self.arange = module.arange self.array = module.array self.concatenate = module.concatenate self.count = module.count self.equal = module.equal self.filled = module.filled self.getmask = module.getmask self.getmaskarray = module.getmaskarray self.id = id self.inner = module.inner self.make_mask = module.make_mask self.masked = module.masked self.masked_array = module.masked_array self.masked_values = module.masked_values self.mask_or = module.mask_or self.nomask = module.nomask self.ones = module.ones self.outer = module.outer self.repeat = module.repeat self.resize = module.resize self.sort = module.sort self.take = module.take self.transpose = module.transpose self.zeros = module.zeros self.MaskType = module.MaskType try: self.umath = module.umath except AttributeError: self.umath = module.core.umath self.testnames = [] def assert_array_compare(self, comparison, x, y, err_msg='', header='', fill_value=True): """ Assert that a comparison of two masked arrays is satisfied elementwise. """ xf = self.filled(x) yf = self.filled(y) m = self.mask_or(self.getmask(x), self.getmask(y)) x = self.filled(self.masked_array(xf, mask=m), fill_value) y = self.filled(self.masked_array(yf, mask=m), fill_value) if (x.dtype.char != "O"): x = x.astype(float_) if isinstance(x, np.ndarray) and x.size > 1: x[np.isnan(x)] = 0 elif np.isnan(x): x = 0 if (y.dtype.char != "O"): y = y.astype(float_) if isinstance(y, np.ndarray) and y.size > 1: y[np.isnan(y)] = 0 elif np.isnan(y): y = 0 try: cond = (x.shape == () or y.shape == ()) or x.shape == y.shape if not cond: msg = build_err_msg([x, y], err_msg + f'\n(shapes {x.shape}, {y.shape} mismatch)', header=header, names=('x', 'y')) assert cond, msg val = comparison(x, y) if m is not self.nomask and fill_value: val = self.masked_array(val, mask=m) if isinstance(val, bool): cond = val reduced = [0] else: reduced = val.ravel() cond = reduced.all() reduced = reduced.tolist() if not cond: match = 100-100.0*reduced.count(1)/len(reduced) msg = build_err_msg([x, y], err_msg + '\n(mismatch %s%%)' % (match,), header=header, names=('x', 'y')) assert cond, msg except ValueError as e: msg = build_err_msg([x, y], err_msg, header=header, names=('x', 'y')) raise ValueError(msg) from e def assert_array_equal(self, x, y, err_msg=''): """ Checks the elementwise equality of two masked arrays. """ self.assert_array_compare(self.equal, x, y, err_msg=err_msg, header='Arrays are not equal') @np.errstate(all='ignore') def test_0(self): """ Tests creation """ x = np.array([1., 1., 1., -2., pi/2.0, 4., 5., -10., 10., 1., 2., 3.]) m = [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0] xm = self.masked_array(x, mask=m) xm[0] @np.errstate(all='ignore') def test_1(self): """ Tests creation """ x = np.array([1., 1., 1., -2., pi/2.0, 4., 5., -10., 10., 1., 2., 3.]) y = np.array([5., 0., 3., 2., -1., -4., 0., -10., 10., 1., 0., 3.]) m1 = [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0] m2 = [0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1] xm = self.masked_array(x, mask=m1) ym = self.masked_array(y, mask=m2) xf = np.where(m1, 1.e+20, x) xm.set_fill_value(1.e+20) assert((xm-ym).filled(0).any()) s = x.shape assert(xm.size == reduce(lambda x, y:x*y, s)) assert(self.count(xm) == len(m1) - reduce(lambda x, y:x+y, m1)) for s in [(4, 3), (6, 2)]: x.shape = s y.shape = s xm.shape = s ym.shape = s xf.shape = s assert(self.count(xm) == len(m1) - reduce(lambda x, y:x+y, m1)) @np.errstate(all='ignore') def test_2(self): """ Tests conversions and indexing. """ x1 = np.array([1, 2, 4, 3]) x2 = self.array(x1, mask=[1, 0, 0, 0]) x3 = self.array(x1, mask=[0, 1, 0, 1]) x4 = self.array(x1) # test conversion to strings, no errors str(x2) repr(x2) # tests of indexing assert type(x2[1]) is type(x1[1]) assert x1[1] == x2[1] x1[2] = 9 x2[2] = 9 self.assert_array_equal(x1, x2) x1[1:3] = 99 x2[1:3] = 99 x2[1] = self.masked x2[1:3] = self.masked x2[:] = x1 x2[1] = self.masked x3[:] = self.masked_array([1, 2, 3, 4], [0, 1, 1, 0]) x4[:] = self.masked_array([1, 2, 3, 4], [0, 1, 1, 0]) x1 = np.arange(5)*1.0 x2 = self.masked_values(x1, 3.0) x1 = self.array([1, 'hello', 2, 3], object) x2 = np.array([1, 'hello', 2, 3], object) # check that no error occurs. x1[1] x2[1] assert x1[1:1].shape == (0,) # Tests copy-size n = [0, 0, 1, 0, 0] m = self.make_mask(n) m2 = self.make_mask(m) assert(m is m2) m3 = self.make_mask(m, copy=1) assert(m is not m3) @np.errstate(all='ignore') def test_3(self): """ Tests resize/repeat """ x4 = self.arange(4) x4[2] = self.masked y4 = self.resize(x4, (8,)) assert self.allequal(self.concatenate([x4, x4]), y4) assert self.allequal(self.getmask(y4), [0, 0, 1, 0, 0, 0, 1, 0]) y5 = self.repeat(x4, (2, 2, 2, 2), axis=0) self.assert_array_equal(y5, [0, 0, 1, 1, 2, 2, 3, 3]) y6 = self.repeat(x4, 2, axis=0) assert self.allequal(y5, y6) y7 = x4.repeat((2, 2, 2, 2), axis=0) assert self.allequal(y5, y7) y8 = x4.repeat(2, 0) assert self.allequal(y5, y8) @np.errstate(all='ignore') def test_4(self): """ Test of take, transpose, inner, outer products. """ x = self.arange(24) y = np.arange(24) x[5:6] = self.masked x = x.reshape(2, 3, 4) y = y.reshape(2, 3, 4) assert self.allequal(np.transpose(y, (2, 0, 1)), self.transpose(x, (2, 0, 1))) assert self.allequal(np.take(y, (2, 0, 1), 1), self.take(x, (2, 0, 1), 1)) assert self.allequal(np.inner(self.filled(x, 0), self.filled(y, 0)), self.inner(x, y)) assert self.allequal(np.outer(self.filled(x, 0), self.filled(y, 0)), self.outer(x, y)) y = self.array(['abc', 1, 'def', 2, 3], object) y[2] = self.masked t = self.take(y, [0, 3, 4]) assert t[0] == 'abc' assert t[1] == 2 assert t[2] == 3 @np.errstate(all='ignore') def test_5(self): """ Tests inplace w/ scalar """ x = self.arange(10) y = self.arange(10) xm = self.arange(10) xm[2] = self.masked x += 1 assert self.allequal(x, y+1) xm += 1 assert self.allequal(xm, y+1) x = self.arange(10) xm = self.arange(10) xm[2] = self.masked x -= 1 assert self.allequal(x, y-1) xm -= 1 assert self.allequal(xm, y-1) x = self.arange(10)*1.0 xm = self.arange(10)*1.0 xm[2] = self.masked x *= 2.0 assert self.allequal(x, y*2) xm *= 2.0 assert self.allequal(xm, y*2) x = self.arange(10)*2 xm = self.arange(10)*2 xm[2] = self.masked x /= 2 assert self.allequal(x, y) xm /= 2 assert self.allequal(xm, y) x = self.arange(10)*1.0 xm = self.arange(10)*1.0 xm[2] = self.masked x /= 2.0 assert self.allequal(x, y/2.0) xm /= self.arange(10) self.assert_array_equal(xm, self.ones((10,))) x = self.arange(10).astype(float_) xm = self.arange(10) xm[2] = self.masked x += 1. assert self.allequal(x, y + 1.) @np.errstate(all='ignore') def test_6(self): """ Tests inplace w/ array """ x = self.arange(10, dtype=float_) y = self.arange(10) xm = self.arange(10, dtype=float_) xm[2] = self.masked m = xm.mask a = self.arange(10, dtype=float_) a[-1] = self.masked x += a xm += a assert self.allequal(x, y+a) assert self.allequal(xm, y+a) assert self.allequal(xm.mask, self.mask_or(m, a.mask)) x = self.arange(10, dtype=float_) xm = self.arange(10, dtype=float_) xm[2] = self.masked m = xm.mask a = self.arange(10, dtype=float_) a[-1] = self.masked x -= a xm -= a assert self.allequal(x, y-a) assert self.allequal(xm, y-a) assert self.allequal(xm.mask, self.mask_or(m, a.mask)) x = self.arange(10, dtype=float_) xm = self.arange(10, dtype=float_) xm[2] = self.masked m = xm.mask a = self.arange(10, dtype=float_) a[-1] = self.masked x *= a xm *= a assert self.allequal(x, y*a) assert self.allequal(xm, y*a) assert self.allequal(xm.mask, self.mask_or(m, a.mask)) x = self.arange(10, dtype=float_) xm = self.arange(10, dtype=float_) xm[2] = self.masked m = xm.mask a = self.arange(10, dtype=float_) a[-1] = self.masked x /= a xm /= a @np.errstate(all='ignore') def test_7(self): "Tests ufunc" d = (self.array([1.0, 0, -1, pi/2]*2, mask=[0, 1]+[0]*6), self.array([1.0, 0, -1, pi/2]*2, mask=[1, 0]+[0]*6),) for f in ['sqrt', 'log', 'log10', 'exp', 'conjugate', # 'sin', 'cos', 'tan', # 'arcsin', 'arccos', 'arctan', # 'sinh', 'cosh', 'tanh', # 'arcsinh', # 'arccosh', # 'arctanh', # 'absolute', 'fabs', 'negative', # # 'nonzero', 'around', # 'floor', 'ceil', # # 'sometrue', 'alltrue', # 'logical_not', # 'add', 'subtract', 'multiply', # 'divide', 'true_divide', 'floor_divide', # 'remainder', 'fmod', 'hypot', 'arctan2', # 'equal', 'not_equal', 'less_equal', 'greater_equal', # 'less', 'greater', # 'logical_and', 'logical_or', 'logical_xor', ]: try: uf = getattr(self.umath, f) except AttributeError: uf = getattr(fromnumeric, f) mf = getattr(self.module, f) args = d[:uf.nin] ur = uf(*args) mr = mf(*args) self.assert_array_equal(ur.filled(0), mr.filled(0), f) self.assert_array_equal(ur._mask, mr._mask) @np.errstate(all='ignore') def test_99(self): # test average ott = self.array([0., 1., 2., 3.], mask=[1, 0, 0, 0]) self.assert_array_equal(2.0, self.average(ott, axis=0)) self.assert_array_equal(2.0, self.average(ott, weights=[1., 1., 2., 1.])) result, wts = self.average(ott, weights=[1., 1., 2., 1.], returned=1) self.assert_array_equal(2.0, result) assert(wts == 4.0) ott[:] = self.masked assert(self.average(ott, axis=0) is self.masked) ott = self.array([0., 1., 2., 3.], mask=[1, 0, 0, 0]) ott = ott.reshape(2, 2) ott[:, 1] = self.masked self.assert_array_equal(self.average(ott, axis=0), [2.0, 0.0]) assert(self.average(ott, axis=1)[0] is self.masked) self.assert_array_equal([2., 0.], self.average(ott, axis=0)) result, wts = self.average(ott, axis=0, returned=1) self.assert_array_equal(wts, [1., 0.]) w1 = [0, 1, 1, 1, 1, 0] w2 = [[0, 1, 1, 1, 1, 0], [1, 0, 0, 0, 0, 1]] x = self.arange(6) self.assert_array_equal(self.average(x, axis=0), 2.5) self.assert_array_equal(self.average(x, axis=0, weights=w1), 2.5) y = self.array([self.arange(6), 2.0*self.arange(6)]) self.assert_array_equal(self.average(y, None), np.add.reduce(np.arange(6))*3./12.) self.assert_array_equal(self.average(y, axis=0), np.arange(6) * 3./2.) self.assert_array_equal(self.average(y, axis=1), [self.average(x, axis=0), self.average(x, axis=0) * 2.0]) self.assert_array_equal(self.average(y, None, weights=w2), 20./6.) self.assert_array_equal(self.average(y, axis=0, weights=w2), [0., 1., 2., 3., 4., 10.]) self.assert_array_equal(self.average(y, axis=1), [self.average(x, axis=0), self.average(x, axis=0) * 2.0]) m1 = self.zeros(6) m2 = [0, 0, 1, 1, 0, 0] m3 = [[0, 0, 1, 1, 0, 0], [0, 1, 1, 1, 1, 0]] m4 = self.ones(6) m5 = [0, 1, 1, 1, 1, 1] self.assert_array_equal(self.average(self.masked_array(x, m1), axis=0), 2.5) self.assert_array_equal(self.average(self.masked_array(x, m2), axis=0), 2.5) self.assert_array_equal(self.average(self.masked_array(x, m5), axis=0), 0.0) self.assert_array_equal(self.count(self.average(self.masked_array(x, m4), axis=0)), 0) z = self.masked_array(y, m3) self.assert_array_equal(self.average(z, None), 20./6.) self.assert_array_equal(self.average(z, axis=0), [0., 1., 99., 99., 4.0, 7.5]) self.assert_array_equal(self.average(z, axis=1), [2.5, 5.0]) self.assert_array_equal(self.average(z, axis=0, weights=w2), [0., 1., 99., 99., 4.0, 10.0]) @np.errstate(all='ignore') def test_A(self): x = self.arange(24) x[5:6] = self.masked x = x.reshape(2, 3, 4) if __name__ == '__main__': setup_base = ("from __main__ import ModuleTester \n" "import numpy\n" "tester = ModuleTester(module)\n") setup_cur = "import numpy.ma.core as module\n" + setup_base (nrepeat, nloop) = (10, 10) for i in range(1, 8): func = 'tester.test_%i()' % i cur = timeit.Timer(func, setup_cur).repeat(nrepeat, nloop*10) cur = np.sort(cur) print("#%i" % i + 50*'.') print(eval("ModuleTester.test_%i.__doc__" % i)) print(f'core_current : {cur[0]:.3f} - {cur[1]:.3f}')