diff options
Diffstat (limited to 'numpy/core/fromnumeric.py')
| -rw-r--r-- | numpy/core/fromnumeric.py | 166 |
1 files changed, 119 insertions, 47 deletions
diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py index 7cde300d9..9f433d17b 100644 --- a/numpy/core/fromnumeric.py +++ b/numpy/core/fromnumeric.py @@ -257,7 +257,7 @@ def put(a, ind, v, mode='raise'): def swapaxes(a, axis1, axis2): """Return a view of array a with axis1 and axis2 interchanged. - + Parameters ---------- a : array_like @@ -369,13 +369,13 @@ def sort(a, axis=-1, kind='quicksort', order=None): order. The three available algorithms have the following properties: - =========== ======= ============= ============ ======= + =========== ======= ============= ============ ======= kind speed worst case work space stable - =========== ======= ============= ============ ======= - 'quicksort' 1 O(n^2) 0 no - 'mergesort' 2 O(n*log(n)) ~n/2 yes - 'heapsort' 3 O(n*log(n)) 0 no - =========== ======= ============= ============ ======= + =========== ======= ============= ============ ======= + 'quicksort' 1 O(n^2) 0 no + 'mergesort' 2 O(n*log(n)) ~n/2 yes + 'heapsort' 3 O(n*log(n)) 0 no + =========== ======= ============= ============ ======= All the sort algorithms make temporary copies of the data when the sort is not along the last axis. Consequently, sorts along @@ -880,7 +880,7 @@ def compress(condition, a, axis=None, out=None): [3]]) >>> np.compress([0,1,1], a) array([2, 3]) - + """ try: compress = a.compress @@ -1051,22 +1051,59 @@ def product (a, axis=None, dtype=None, out=None): return prod(axis, dtype, out) -def sometrue (a, axis=None, out=None): - """Check if any of the elements of `a` are true. +def sometrue(a, axis=None, out=None): + """ + Assert whether some values are true. - Performs a logical_or over the given axis and returns the result + `sometrue` performs a logical_or over the given axis. Parameters ---------- - a : {array_like} - Array on which to operate + a : array_like + Array on which to operate. + axis : {None, integer} + Axis to perform the operation over. + If `None` (default), perform over flattened array. + out : {None, array}, optional + Array into which the product can be placed. Its type is preserved + and it must be of the right shape to hold the output. + + See Also + -------- + ndarray.any : equivalent method + + Examples + -------- + >>> b = numpy.array([True, False, True, True]) + >>> numpy.sometrue(b) + True + >>> a = numpy.array([1, 5, 2, 7]) + >>> numpy.sometrue(a >= 5) + True + + """ + try: + any = a.any + except AttributeError: + return _wrapit(a, 'any', axis, out) + return any(axis, out) + + +def alltrue (a, axis=None, out=None): + """Check if all of the elements of `a` are true. + + Performs a logical_and over the given axis and returns the result + + Parameters + ---------- + a : array_like axis : {None, integer} Axis to perform the operation over. If None, perform over flattened array. out : {None, array}, optional Array into which the product can be placed. Its type is preserved and it must be of the right shape to hold the output. - + See Also -------- ndarray.any : equivalent method @@ -1086,14 +1123,14 @@ def alltrue (a, axis=None, out=None): Parameters ---------- - a : {array_like} + a : array_like axis : {None, integer} Axis to perform the operation over. If None, perform over flattened array. out : {None, array}, optional Array into which the product can be placed. Its type is preserved and it must be of the right shape to hold the output. - + See Also -------- ndarray.all : equivalent method @@ -1108,19 +1145,19 @@ def alltrue (a, axis=None, out=None): def any(a,axis=None, out=None): """Check if any of the elements of `a` are true. - + Performs a logical_or over the given axis and returns the result Parameters ---------- - a : {array_like} + a : array_like axis : {None, integer} Axis to perform the operation over. If None, perform over flattened array and return a scalar. out : {None, array}, optional Array into which the product can be placed. Its type is preserved and it must be of the right shape to hold the output. - + See Also -------- ndarray.any : equivalent method @@ -1135,19 +1172,19 @@ def any(a,axis=None, out=None): def all(a,axis=None, out=None): """Check if all of the elements of `a` are true. - + Performs a logical_and over the given axis and returns the result Parameters ---------- - a : {array_like} + a : array_like axis : {None, integer} Axis to perform the operation over. If None, perform over flattened array and return a scalar. out : {None, array}, optional Array into which the product can be placed. Its type is preserved and it must be of the right shape to hold the output. - + See Also -------- ndarray.all : equivalent method @@ -1161,10 +1198,8 @@ def all(a,axis=None, out=None): def cumsum (a, axis=None, dtype=None, out=None): - """Return the cumulative sum of the elements along the given axis. - - The cumulative sum is calculated over the flattened array by - default, otherwise over the specified axis. + """ + Return the cumulative sum of the elements along a given axis. Parameters ---------- @@ -1172,13 +1207,13 @@ def cumsum (a, axis=None, dtype=None, out=None): Input array or object that can be converted to an array. axis : {None, -1, int}, optional Axis along which the sum is computed. The default - (``axis``= None) is to compute over the flattened array. + (`axis` = `None`) is to compute over the flattened array. dtype : {None, dtype}, optional - Determines the type of the returned array and of the accumulator - where the elements are summed. If dtype has the value None and - the type of a is an integer type of precision less than the default - platform integer, then the default platform integer precision is - used. Otherwise, the dtype is the same as that of a. + Type of the returned array and of the accumulator in which the + elements are summed. If `dtype` is not specified, it defaults + to the dtype of `a`, unless `a` has an integer dtype with a + precision less than that of the default platform integer. In + that case, the default platform integer is used. out : ndarray, optional Alternative output array in which to place the result. It must have the same shape and buffer length as the expected output @@ -1187,14 +1222,30 @@ def cumsum (a, axis=None, dtype=None, out=None): Returns ------- cumsum : ndarray. - A new array holding the result is returned unless ``out`` is - specified, in which case a reference to ``out`` is returned. + A new array holding the result is returned unless `out` is + specified, in which case a reference to `out` is returned. Notes ----- Arithmetic is modular when using integer types, and no error is raised on overflow. + + Examples + -------- + >>> import numpy + >>> a=numpy.array([[1,2,3],[4,5,6]]) + >>> numpy.cumsum(a) # cumulative sum = intermediate summing results & total sum. Default axis=None results in raveling the array first. + array([ 1, 3, 6, 10, 15, 21]) + >>> numpy.cumsum(a,dtype=float) # specifies type of output value(s) + array([ 1., 3., 6., 10., 15., 21.]) + >>> numpy.cumsum(a,axis=0) # sum over rows for each of the 3 columns + array([[1, 2, 3], + [5, 7, 9]]) + >>> numpy.cumsum(a,axis=1) # sum over columns for each of the 2 rows + array([[ 1, 3, 6], + [ 4, 9, 15]]) + """ try: cumsum = a.cumsum @@ -1273,7 +1324,7 @@ def amax(a, axis=None, out=None): Alternative output array in which to place the result. Must be of the same shape and buffer length as the expected output. - Results + Returns ------- amax : array_like New array holding the result, unless ``out`` was specified. @@ -1311,7 +1362,7 @@ def amin(a, axis=None, out=None): Alternative output array in which to place the result. Must be of the same shape and buffer length as the expected output. - Results + Returns ------- amin : array_like New array holding the result, unless ``out`` was specified. @@ -1336,7 +1387,8 @@ def amin(a, axis=None, out=None): def alen(a): - """Return the length of a Python object interpreted as an array + """ + Return the length of a Python object interpreted as an array of at least 1 dimension. Parameters @@ -1346,14 +1398,14 @@ def alen(a): Returns ------- alen : int - Length of the first dimension of a. + Length of the first dimension of `a`. Examples -------- - >>> z = np.zeros((7,4,5)) + >>> z = numpy.zeros((7,4,5)) >>> z.shape[0] 7 - >>> np.alen(z) + >>> numpy.alen(z) 7 """ @@ -1421,7 +1473,8 @@ def prod(a, axis=None, dtype=None, out=None): def cumprod(a, axis=None, dtype=None, out=None): - """Return the cumulative product of the elements along the given axis. + """ + Return the cumulative product of the elements along the given axis. The cumulative product is taken over the flattened array by default, otherwise over the specified axis. @@ -1432,13 +1485,13 @@ def cumprod(a, axis=None, dtype=None, out=None): Input array or object that can be converted to an array. axis : {None, -1, int}, optional Axis along which the product is computed. The default - (``axis``= None) is to compute over the flattened array. + (`axis` = `None`) is to compute over the flattened array. dtype : {None, dtype}, optional - Determines the type of the returned array and of the accumulator - where the elements are multiplied. If dtype has the value None and - the type of a is an integer type of precision less than the default + Type of the returned array and of the accumulator + where the elements are multiplied. If `dtype` has the value `None` and + the type of `a` is an integer type of precision less than the default platform integer, then the default platform integer precision is - used. Otherwise, the dtype is the same as that of a. + used. Otherwise, the `dtype` is the same as that of `a`. out : ndarray, optional Alternative output array in which to place the result. It must have the same shape and buffer length as the expected output @@ -1447,7 +1500,7 @@ def cumprod(a, axis=None, dtype=None, out=None): Returns ------- cumprod : ndarray. - A new array holding the result is returned unless out is + A new array holding the result is returned unless `out` is specified, in which case a reference to out is returned. Notes @@ -1455,6 +1508,25 @@ def cumprod(a, axis=None, dtype=None, out=None): Arithmetic is modular when using integer types, and no error is raised on overflow. + Examples + -------- + >>> a=numpy.array([[1,2,3],[4,5,6]]) + >>> a=numpy.array([1,2,3]) + >>> numpy.cumprod(a) # intermediate results 1, 1*2 + ... # total product 1*2*3 = 6 + array([1, 2, 6]) + >>> a=numpy.array([[1,2,3],[4,5,6]]) + >>> numpy.cumprod(a,dtype=float) # specify type of output + array([ 1., 2., 6., 24., 120., 720.]) + >>> numpy.cumprod(a,axis=0) # for each of the 3 columns: + ... # product and intermediate results + array([[ 1, 2, 3], + [ 4, 10, 18]]) + >>> numpy.cumprod(a,axis=1) # for each of the two rows: + ... # product and intermediate results + array([[ 1, 2, 6], + [ 4, 20, 120]]) + """ try: cumprod = a.cumprod |