diff options
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/core/ma.py | 22 | ||||
| -rw-r--r-- | numpy/core/tests/test_ma.py | 20 | ||||
| -rw-r--r-- | numpy/lib/function_base.py | 5 | ||||
| -rw-r--r-- | numpy/numarray/functions.py | 5 | ||||
| -rw-r--r-- | numpy/oldnumeric/functions.py | 6 | ||||
| -rw-r--r-- | numpy/oldnumeric/ma.py | 10 | ||||
| -rw-r--r-- | numpy/oldnumeric/misc.py | 4 |
7 files changed, 44 insertions, 28 deletions
diff --git a/numpy/core/ma.py b/numpy/core/ma.py index 5c93753a1..591ad801a 100644 --- a/numpy/core/ma.py +++ b/numpy/core/ma.py @@ -448,7 +448,7 @@ def nonzero(a): """returns the indices of the elements of a which are not zero and not masked """ - return asarray(filled(a, 0).nonzero()) + return numeric.asarray(filled(a, 0).nonzero()) around = masked_unary_operation(fromnumeric.round_) floor = masked_unary_operation(umath.floor) @@ -1532,7 +1532,7 @@ def resize (a, new_shape): result.set_fill_value(get_fill_value(a)) return result -def repeat(a, repeats, axis=0): +def repeat(a, repeats, axis=None): """repeat elements of a repeats times along axis repeats is a sequence of length a.shape[axis] telling how many times to repeat each element. @@ -1603,8 +1603,8 @@ def masked_array (a, mask=nomask, fill_value=None): sum = add.reduce product = multiply.reduce -def average (a, axis=0, weights=None, returned = 0): - """average(a, axis=0, weights=None) +def average (a, axis=None, weights=None, returned = 0): + """average(a, axis=None, weights=None) Computes average along indicated axis. If axis is None, average over the entire array Inputs can be integer or floating types; result is of type float. @@ -1858,7 +1858,7 @@ def swapaxes (a, axis1, axis2): mask=numeric.swapaxes(m, axis1, axis2),) -def take (a, indices, axis=0, out=None, mode='raise'): +def take (a, indices, axis=None, out=None, mode='raise'): "returns selection of items from a." m = getmask(a) # d = masked_array(a).raw_data() @@ -2168,14 +2168,14 @@ del _compress array.conj = array.conjugate = _m(conjugate) array.copy = _m(not_implemented) -def _cumprod(self, axis=0, dtype=None, out=None): +def _cumprod(self, axis=None, dtype=None, out=None): m = self.mask if m is not nomask: m = umath.logical_or.accumulate(self.mask, axis) return MaskedArray(data = self.filled(1).cumprod(axis, dtype), mask=m) array.cumprod = _m(_cumprod) -def _cumsum(self, axis=0, dtype=None, out=None): +def _cumsum(self, axis=None, dtype=None, out=None): m = self.mask if m is not nomask: m = umath.logical_or.accumulate(self.mask, axis) @@ -2214,7 +2214,7 @@ array.newbyteorder = _m(not_implemented) array.nonzero = _m(nonzero) array.prod = _m(product) -def _ptp(a,axis=0,out=None): +def _ptp(a,axis=None,out=None): return a.max(axis,out)-a.min(axis) array.ptp = _m(_ptp) array.repeat = _m(repeat) @@ -2244,15 +2244,15 @@ array.tofile = _m(not_implemented) array.trace = _m(trace) array.transpose = _m(transpose) -def _var(self,axis=0,dtype=None, out=None): +def _var(self,axis=None,dtype=None, out=None): if axis is None: - return asarray(self.compressed()).var() + return numeric.asarray(self.compressed()).var() a = self.swapaxes(axis,0) a = a - a.mean(axis=0) a *= a a /= a.count(axis=0) return a.swapaxes(0,axis).sum(axis) -def _std(self,axis=0,dtype=None, out=None): +def _std(self,axis=None, dtype=None, out=None): return (self.var(axis,dtype))**0.5 array.var = _m(_var) array.std = _m(_std) diff --git a/numpy/core/tests/test_ma.py b/numpy/core/tests/test_ma.py index 540e64c8a..3607b965b 100644 --- a/numpy/core/tests/test_ma.py +++ b/numpy/core/tests/test_ma.py @@ -267,9 +267,9 @@ class test_ma(NumpyTestCase): y4 = resize(x4, (8,)) self.failUnless( eq(concatenate([x4,x4]), y4)) self.failUnless( eq(getmask(y4),[0,0,1,0,0,0,1,0])) - y5 = repeat(x4, (2,2,2,2)) + y5 = repeat(x4, (2,2,2,2), axis=0) self.failUnless( eq(y5, [0,0,1,1,2,2,3,3])) - y6 = repeat(x4, 2) + y6 = repeat(x4, 2, axis=0) self.failUnless( eq(y5, y6)) def check_testPut(self): @@ -523,10 +523,10 @@ class test_ma(NumpyTestCase): ott = array([0.,1.,2.,3.], mask=[1,0,0,0]) ott=ott.reshape(2,2) ott[:,1] = masked - self.failUnless(eq(average(ott), [2.0, 0.0])) + self.failUnless(eq(average(ott,axis=0), [2.0, 0.0])) self.failUnless(average(ott,axis=1)[0] is masked) - self.failUnless(eq([2.,0.], average(ott))) - result, wts = average(ott, returned=1) + self.failUnless(eq([2.,0.], average(ott, axis=0))) + result, wts = average(ott, axis=0, returned=1) self.failUnless(eq(wts, [1., 0.])) def check_testAverage2(self): @@ -534,8 +534,8 @@ class test_ma(NumpyTestCase): w1 = [0,1,1,1,1,0] w2 = [[0,1,1,1,1,0],[1,0,0,0,0,1]] x=arange(6) - self.failUnless(allclose(average(x), 2.5)) - self.failUnless(allclose(average(x, weights=w1), 2.5)) + self.failUnless(allclose(average(x, axis=0), 2.5)) + self.failUnless(allclose(average(x, axis=0, weights=w1), 2.5)) y=array([arange(6), 2.0*arange(6)]) self.failUnless(allclose(average(y, None), numpy.add.reduce(numpy.arange(6))*3./12.)) self.failUnless(allclose(average(y, axis=0), numpy.arange(6) * 3./2.)) @@ -557,7 +557,7 @@ class test_ma(NumpyTestCase): self.failUnless(allclose(average(z, None), 20./6.)) self.failUnless(allclose(average(z, axis=0), [0.,1.,99.,99.,4.0, 7.5])) self.failUnless(allclose(average(z, axis=1), [2.5, 5.0])) - self.failUnless(allclose( average(z,weights=w2), [0.,1., 99., 99., 4.0, 10.0])) + self.failUnless(allclose( average(z,axis=0, weights=w2), [0.,1., 99., 99., 4.0, 10.0])) a = arange(6) b = arange(6) * 3 @@ -572,9 +572,9 @@ class test_ma(NumpyTestCase): self.failUnless(shape(w2) == shape(r2)) a2d = array([[1,2],[0,4]], float) a2dm = masked_array(a2d, [[0,0],[1,0]]) - a2da = average(a2d) + a2da = average(a2d, axis=0) self.failUnless(eq (a2da, [0.5, 3.0])) - a2dma = average(a2dm) + a2dma = average(a2dm, axis=0) self.failUnless(eq( a2dma, [1.0, 3.0])) a2dma = average(a2dm, axis=None) self.failUnless(eq(a2dma, 7./3.)) diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index 098632ead..a62b3569e 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -1,4 +1,3 @@ - __all__ = ['logspace', 'linspace', 'select', 'piecewise', 'trim_zeros', 'copy', 'iterable', #'base_repr', 'binary_repr', @@ -100,8 +99,8 @@ def histogram(a, bins=10, range=None, normed=False): else: return n, bins -def average(a, axis=0, weights=None, returned=False): - """average(a, axis=0, weights=None, returned=False) +def average(a, axis=None, weights=None, returned=False): + """average(a, axis=None weights=None, returned=False) Average the array over the given axis. If the axis is None, average over all dimensions of the array. Equivalent to a.mean(axis), but diff --git a/numpy/numarray/functions.py b/numpy/numarray/functions.py index c990fe7e9..55922e9fe 100644 --- a/numpy/numarray/functions.py +++ b/numpy/numarray/functions.py @@ -42,7 +42,7 @@ import os, sys, math, operator from numpy import dot as matrixmultiply, dot, vdot, ravel, concatenate, all,\ allclose, any, around, argsort, array_equal, array_equiv,\ - array_str, array_repr, average, CLIP, RAISE, WRAP, clip, concatenate, \ + array_str, array_repr, CLIP, RAISE, WRAP, clip, concatenate, \ diagonal, e, pi, fromfunction, indices, inner as innerproduct, nonzero, \ outer as outerproduct, kron as kroneckerproduct, lexsort, putmask, rank, \ resize, searchsorted, shape, size, sort, swapaxes, trace, transpose @@ -453,3 +453,6 @@ def newobj(self, type): def togglebyteorder(self): self.dtype=self.dtype.newbyteorder() + +def average(a, axis=0, weights=None, returned=0): + return N.average(a, axis, weights, returned) diff --git a/numpy/oldnumeric/functions.py b/numpy/oldnumeric/functions.py index e18f12aa8..4e3f12639 100644 --- a/numpy/oldnumeric/functions.py +++ b/numpy/oldnumeric/functions.py @@ -9,7 +9,8 @@ __all__ = ['take', 'repeat', 'sum', 'product', 'sometrue', 'alltrue', 'cumsum', 'cumproduct', 'compress', 'ones', 'empty', 'identity', 'zeros', 'array', 'asarray', 'nonzero', 'reshape', 'arange', 'fromstring', 'ravel', 'trace', - 'indices', 'where','sarray','cross_product', 'argmax', 'argmin'] + 'indices', 'where','sarray','cross_product', 'argmax', 'argmin', + 'average'] def take(a, indicies, axis=0): return N.take(a, indicies, axis) @@ -115,3 +116,6 @@ def where(condition, x, y): def cross_product(a, b, axis1=-1, axis2=-1): return N.cross(a, b, axis1, axis2) + +def average(a, axis=0, weights=None, returned=False): + return N.average(a, axis, weights, returned) diff --git a/numpy/oldnumeric/ma.py b/numpy/oldnumeric/ma.py index c78fcc200..857c554ec 100644 --- a/numpy/oldnumeric/ma.py +++ b/numpy/oldnumeric/ma.py @@ -2,4 +2,14 @@ # instead of None from numpy.core.ma import * +import numpy.core.ma as nca + +def repeat(a, repeats, axis=0): + return nca.repeat(a, repeats, axis) + +def average(a, axis=0, weights=None, returned=0): + return nca.average(a, axis, weights, returned) + +def take(a, indices, axis=0): + return nca.average(a, indices, axis=0) diff --git a/numpy/oldnumeric/misc.py b/numpy/oldnumeric/misc.py index e8c2e3c00..a6c13d780 100644 --- a/numpy/oldnumeric/misc.py +++ b/numpy/oldnumeric/misc.py @@ -7,7 +7,7 @@ __all__ = ['load', 'sort', 'copy_reg', 'clip', 'putmask', 'Unpickler', 'rank', 'pi', 'math', 'concatenate', 'around', 'vdot', 'transpose', 'array2string', 'diagonal', 'searchsorted', 'put', 'fromfunction', 'copy', 'resize', - 'array_repr', 'e', 'StringIO', 'pickle', 'average', + 'array_repr', 'e', 'StringIO', 'pickle', 'argsort', 'convolve', 'loads', 'cross_correlate', 'Pickler', 'dot', 'outerproduct', 'innerproduct'] @@ -22,7 +22,7 @@ from pickle import load, loads from numpy import sort, clip, putmask, rank, sign, shape, allclose, size,\ choose, swapaxes, array_str, array_repr, e, pi, \ fromfunction, resize, around, concatenate, vdot, transpose, \ - diagonal, searchsorted, put, average, argsort, convolve, dot, \ + diagonal, searchsorted, put, argsort, convolve, dot, \ outer as outerproduct, inner as innerproduct, correlate as cross_correlate from array_printer import array2string |