DataSource.open(path, mode='r') [source] Open and return file-like object. If path is an URL, it will be downloaded, stored in the DataSource directory and opened from there. Parameters: path : str Local file path or URL to open. mode : {?r?, ?w?, ?a?}, optional Mode to open path. Mode ?r? for reading, ?w? for writing, ?a? to append. Available modes depend on the type of object specified by path. Default is ?r?. Returns: out : file object File object.

ndarray.setflags(write=None, align=None, uic=None) Set array flags WRITEABLE, ALIGNED, and UPDATEIFCOPY, respectively. These Boolean-valued flags affect how numpy interprets the memory area used by a (see Notes below). The ALIGNED flag can only be set to True if the data is actually aligned according to the type. The UPDATEIFCOPY flag can never be set to True. The flag WRITEABLE can only be set to True if the array owns its own memory, or the ultimate owner of the memory exposes a writeable

ndarray.setfield(val, dtype, offset=0) Put a value into a specified place in a field defined by a data-type. Place val into a?s field defined by dtype and beginning offset bytes into the field. Parameters: val : object Value to be placed in field. dtype : dtype object Data-type of the field in which to place val. offset : int, optional The number of bytes into the field at which to place val. Returns: None See also getfield Examples >>> x = np.eye(3) >>> x.getf

numpy.polynomial.hermite_e.hermeadd(c1, c2) [source] Add one Hermite series to another. Returns the sum of two Hermite series c1 + c2. The arguments are sequences of coefficients ordered from lowest order term to highest, i.e., [1,2,3] represents the series P_0 + 2*P_1 + 3*P_2. Parameters: c1, c2 : array_like 1-D arrays of Hermite series coefficients ordered from low to high. Returns: out : ndarray Array representing the Hermite series of their sum. See also hermesub, hermemul, her

matrix.setflags(write=None, align=None, uic=None) Set array flags WRITEABLE, ALIGNED, and UPDATEIFCOPY, respectively. These Boolean-valued flags affect how numpy interprets the memory area used by a (see Notes below). The ALIGNED flag can only be set to True if the data is actually aligned according to the type. The UPDATEIFCOPY flag can never be set to True. The flag WRITEABLE can only be set to True if the array owns its own memory, or the ultimate owner of the memory exposes a writeable

Legendre.copy() [source] Return a copy. Returns: new_series : series Copy of self.

classmethod HermiteE.identity(domain=None, window=None) [source] Identity function. If p is the returned series, then p(x) == x for all values of x. Parameters: domain : {None, array_like}, optional If given, the array must be of the form [beg, end], where beg and end are the endpoints of the domain. If None is given then the class domain is used. The default is None. window : {None, array_like}, optional If given, the resulting array must be if the form [beg, end], where beg and end ar

numpy.testing.assert_warns(warning_class, *args, **kwargs) [source] Fail unless the given callable throws the specified warning. A warning of class warning_class should be thrown by the callable when invoked with arguments args and keyword arguments kwargs. If a different type of warning is thrown, it will not be caught, and the test case will be deemed to have suffered an error. If called with all arguments other than the warning class omitted, may be used as a context manager: with asser

ndarray.__xor__ x.__xor__(y) <==> x^y

numpy.core.defchararray.mod(a, values) [source] Return (a % i), that is pre-Python 2.6 string formatting (iterpolation), element-wise for a pair of array_likes of str or unicode. Parameters: a : array_like of str or unicode values : array_like of values These values will be element-wise interpolated into the string. Returns: out : ndarray Output array of str or unicode, depending on input types See also str.__mod__