numpy.fliplr(m) [source] Flip array in the left/right direction. Flip the entries in each row in the left/right direction. Columns are preserved, but appear in a different order than before. Parameters: m : array_like Input array, must be at least 2-D. Returns: f : ndarray A view of m with the columns reversed. Since a view is returned, this operation is . See also flipud Flip array in the up/down direction. rot90 Rotate array counterclockwise. Notes Equivalent to A[:,::-1].

numpy.dstack(tup) [source] Stack arrays in sequence depth wise (along third axis). Takes a sequence of arrays and stack them along the third axis to make a single array. Rebuilds arrays divided by dsplit. This is a simple way to stack 2D arrays (images) into a single 3D array for processing. Parameters: tup : sequence of arrays Arrays to stack. All of them must have the same shape along all but the third axis. Returns: stacked : ndarray The array formed by stacking the given arrays.

classmethod Polynomial.cast(series, domain=None, window=None) [source] Convert series to series of this class. The series is expected to be an instance of some polynomial series of one of the types supported by by the numpy.polynomial module, but could be some other class that supports the convert method. New in version 1.7.0. Parameters: series : series The series instance to be converted. domain : {None, array_like}, optional If given, the array must be of the form [beg, end], where

numpy.polynomial.hermite.hermgrid3d(x, y, z, c) [source] Evaluate a 3-D Hermite series on the Cartesian product of x, y, and z. This function returns the values: where the points (a, b, c) consist of all triples formed by taking a from x, b from y, and c from z. The resulting points form a grid with x in the first dimension, y in the second, and z in the third. The parameters x, y, and z are converted to arrays only if they are tuples or a lists, otherwise they are treated as a scalars.

numpy.ma.make_mask_none(newshape, dtype=None) [source] Return a boolean mask of the given shape, filled with False. This function returns a boolean ndarray with all entries False, that can be used in common mask manipulations. If a complex dtype is specified, the type of each field is converted to a boolean type. Parameters: newshape : tuple A tuple indicating the shape of the mask. dtype : {None, dtype}, optional If None, use a MaskType instance. Otherwise, use a new datatype with the

Laguerre.truncate(size) [source] Truncate series to length size. Reduce the series to length size by discarding the high degree terms. The value of size must be a positive integer. This can be useful in least squares where the coefficients of the high degree terms may be very small. Parameters: size : positive int The series is reduced to length size by discarding the high degree terms. The value of size must be a positive integer. Returns: new_series : series New instance of series w

numpy.apply_along_axis(func1d, axis, arr, *args, **kwargs) [source] Apply a function to 1-D slices along the given axis. Execute func1d(a, *args) where func1d operates on 1-D arrays and a is a 1-D slice of arr along axis. Parameters: func1d : function This function should accept 1-D arrays. It is applied to 1-D slices of arr along the specified axis. axis : integer Axis along which arr is sliced. arr : ndarray Input array. args : any Additional arguments to func1d. kwargs: any Add

recarray.astype(dtype, order='K', casting='unsafe', subok=True, copy=True) Copy of the array, cast to a specified type. Parameters: dtype : str or dtype Typecode or data-type to which the array is cast. order : {?C?, ?F?, ?A?, ?K?}, optional Controls the memory layout order of the result. ?C? means C order, ?F? means Fortran order, ?A? means ?F? order if all the arrays are Fortran contiguous, ?C? order otherwise, and ?K? means as close to the order the array elements appear in memory as

Arrayterator.shape The shape of the array to be iterated over. For an example, see Arrayterator.

Laguerre.convert(domain=None, kind=None, window=None) [source] Convert series to a different kind and/or domain and/or window. Parameters: domain : array_like, optional The domain of the converted series. If the value is None, the default domain of kind is used. kind : class, optional The polynomial series type class to which the current instance should be converted. If kind is None, then the class of the current instance is used. window : array_like, optional The window of the conver