Miscellaneous routines (scipy.misc)

Warning

This documentation is work-in-progress and unorganized.

Various utilities that don’t have another home.

scipy.misc.who(vardict=None)

Print the Numpy arrays in the given dictionary.

If there is no dictionary passed in or vardict is None then returns Numpy arrays in the globals() dictionary (all Numpy arrays in the namespace).

Parameters :

vardict : dict, optional

A dictionary possibly containing ndarrays. Default is globals().

Returns :

out : None

Returns ‘None’.

Notes

Prints out the name, shape, bytes and type of all of the ndarrays present in vardict.

Examples

>>> a = np.arange(10)
>>> b = np.ones(20)
>>> np.who()
Name            Shape            Bytes            Type
===========================================================
a               10               40               int32
b               20               160              float64
Upper bound on total bytes  =       200

>>> d = {'x': np.arange(2.0), 'y': np.arange(3.0), 'txt': 'Some str',
... 'idx':5}
>>> np.whos(d)
Name            Shape            Bytes            Type
===========================================================
y               3                24               float64
x               2                16               float64
Upper bound on total bytes  =       40

scipy.misc.source(object, output=<open file '<stdout>', mode 'w' at 0x2b70e407e198>)

Print or write to a file the source code for a Numpy object.

The source code is only returned for objects written in Python. Many functions and classes are defined in C and will therefore not return useful information.

Parameters :

object : numpy object

Input object. This can be any object (function, class, module, ...).

output : file object, optional

If output not supplied then source code is printed to screen (sys.stdout). File object must be created with either write ‘w’ or append ‘a’ modes.

See also

lookfor, info

Examples

>>> np.source(np.interp)
In file: /usr/lib/python2.6/dist-packages/numpy/lib/function_base.py
def interp(x, xp, fp, left=None, right=None):
    """.... (full docstring printed)"""
    if isinstance(x, (float, int, number)):
        return compiled_interp([x], xp, fp, left, right).item()
    else:
        return compiled_interp(x, xp, fp, left, right)

The source code is only returned for objects written in Python.

>>> np.source(np.array)
Not available for this object.

scipy.misc.info(object=None, maxwidth=76, output=<open file '<stdout>', mode 'w' at 0x2b70e407e198>, toplevel='scipy')

Get help information for a function, class, or module.

Parameters :

object : object or str, optional

Input object or name to get information about. If object is a numpy object, its docstring is given. If it is a string, available modules are searched for matching objects. If None, information about info itself is returned.

maxwidth : int, optional

Printing width.

output : file like object, optional

File like object that the output is written to, default is stdout. The object has to be opened in ‘w’ or ‘a’ mode.

toplevel : str, optional

Start search at this level.

See also

source, lookfor

Notes

When used interactively with an object, np.info(obj) is equivalent to help(obj) on the Python prompt or obj? on the IPython prompt.

Examples

>>> np.info(np.polyval) 
   polyval(p, x)
     Evaluate the polynomial p at x.
     ...

When using a string for object it is possible to get multiple results.

>>> np.info('fft') 
     *** Found in numpy ***
Core FFT routines
...
     *** Found in numpy.fft ***
 fft(a, n=None, axis=-1)
...
     *** Repeat reference found in numpy.fft.fftpack ***
     *** Total of 3 references found. ***

scipy.misc.fromimage(im, flatten=0)

Return a copy of a PIL image as a numpy array.

Parameters :

im : PIL image

Input image.

flatten : bool

If true, convert the output to grey-scale.

Returns :

img_array : ndarray

The different colour bands/channels are stored in the third dimension, such that a grey-image is MxN, an RGB-image MxNx3 and an RGBA-image MxNx4.

scipy.misc.toimage(arr, high=255, low=0, cmin=None, cmax=None, pal=None, mode=None, channel_axis=None)

Takes a numpy array and returns a PIL image. The mode of the PIL image depends on the array shape, the pal keyword, and the mode keyword.

For 2-D arrays, if pal is a valid (N,3) byte-array giving the RGB values (from 0 to 255) then mode=’P’, otherwise mode=’L’, unless mode is given as ‘F’ or ‘I’ in which case a float and/or integer array is made

For 3-D arrays, the channel_axis argument tells which dimension of the

array holds the channel data.

For 3-D arrays if one of the dimensions is 3, the mode is ‘RGB’

by default or ‘YCbCr’ if selected.

if the

The numpy array must be either 2 dimensional or 3 dimensional.

scipy.misc.imsave(name, arr)

Save an array to an image file.

Parameters :

im : PIL image

Input image.

flatten : bool

If true, convert the output to grey-scale.

Returns :

img_array : ndarray

The different colour bands/channels are stored in the third dimension, such that a grey-image is MxN, an RGB-image MxNx3 and an RGBA-image MxNx4.

scipy.misc.imread(name, flatten=0)

Read an image file from a filename.

Parameters :

name : str

The file name to be read.

flatten : bool, optional

If True, flattens the color layers into a single gray-scale layer.

Returns :

: nd_array :

The array obtained by reading image.

Notes

The image is flattened by calling convert(‘F’) on the resulting image object.

scipy.misc.bytescale(data, cmin=None, cmax=None, high=255, low=0)

Parameters :

im : PIL image

Input image.

flatten : bool

If true, convert the output to grey-scale

Returns :

img_array : ndarray

The different colour bands/channels are stored in the third dimension, such that a grey-image is MxN, an RGB-image MxNx3 and an RGBA-image MxNx4.

scipy.misc.imrotate(arr, angle, interp='bilinear')

Rotate an image counter-clockwise by angle degrees.

Parameters :

arr : nd_array

Input array of image to be rotated.

angle : float

The angle of rotation.

interp : str, optional

Interpolation

Returns :

: nd_array :

The rotated array of image.

Notes

Interpolation methods can be: * ‘nearest’ : for nearest neighbor * ‘bilinear’ : for bilinear * ‘cubic’ : cubic * ‘bicubic’ : for bicubic

scipy.misc.imresize(arr, size)

Resize an image.

Parameters :

arr : nd_array

The array of image to be resized.

size : int, float or tuple

• int - Percentage of current size.
• float - Fraction of current size.
• tuple - Size of the output image.

Returns :

: nd_array :

The resized array of image.

scipy.misc.imshow(arr)

Simple showing of an image through an external viewer.

scipy.misc.imfilter(arr, ftype)

Simple filtering of an image.

Parameters :

arr : ndarray

The array of Image in which the filter is to be applied.

ftype : str

The filter that has to be applied. Legal values are: ‘blur’, ‘contour’, ‘detail’, ‘edge_enhance’, ‘edge_enhance_more’, ‘emboss’, ‘find_edges’, ‘smooth’, ‘smooth_more’, ‘sharpen’.

Returns :

res : nd_array

The array with filter applied.

Raises :

ValueError :

Unknown filter type. . If the filter you are trying to apply is unsupported.

scipy.misc.factorial(n, exact=0)

n! = special.gamma(n+1)

If exact==0, then floating point precision is used, otherwise exact long integer is computed.

Notes:

• Array argument accepted only for exact=0 case.
• If n<0, the return value is 0.

scipy.misc.factorial2(n, exact=False)

Double factorial.

This is the factorial with every second value is skipped, i.e., 7!! = 7 * 5 * 3 * 1. It can be approximated numerically as:

n!! = special.gamma(n/2+1)*2**((m+1)/2)/sqrt(pi)  n odd
    = 2**(n/2) * (n/2)!                           n even

Parameters :

n : int, array-like

Calculate n!!. Arrays are only supported with exact set to False. If n < 0, the return value is 0.

exact : bool, optional

The result can be approximated rapidly using the gamma-formula above (default). If exact is set to True, calculate the answer exactly using integer arithmetic.

Returns :

nff : float or int

Double factorial of n, as an int or a float depending on exact.

References

[R89]

Wikipedia, “Double Factorial”, http://en.wikipedia.org/wiki/Factorial#Double_factorial

scipy.misc.factorialk(n, k, exact=1)

n(!!...!) = multifactorial of order k k times

Parameters :

n : int, array-like

Calculate multifactorial. Arrays are only supported with exact set to False. If n < 0, the return value is 0.

exact : bool, optional

If exact is set to True, calculate the answer exactly using integer arithmetic.

Returns :

val : int

Multi factorial of n.

Raises :

NotImplementedError :

Raises when exact is False

scipy.misc.comb(N, k, exact=0)

Combinations of N things taken k at a time.

Parameters :

N : int, array

Nunmber of things.

k : int, array

Numner of elements taken.

exact : int, optional

If exact is 0, then floating point precision is used, otherwise exact long integer is computed.

Returns :

val : int, array

The total number of combinations.

Notes

• Array arguments accepted only for exact=0 case.
• If k > N, N < 0, or k < 0, then a 0 is returned.

scipy.misc.central_diff_weights(Np, ndiv=1)

Return weights for an Np-point central derivative of order ndiv assuming equally-spaced function points.

If weights are in the vector w, then derivative is w[0] * f(x-ho*dx) + ... + w[-1] * f(x+h0*dx)

Notes

Can be inaccurate for large number of points.

scipy.misc.derivative(func, x0, dx=1.0, n=1, args=(), order=3)

Find the n-th derivative of a function at point x0.

Given a function, use a central difference formula with spacing dx to compute the n-th derivative at x0.

Parameters :

func : function

Input function.

x0 : float

The point at which nth derivative is found.

dx : int, optional

Spacing.

n : int, optional

Order of the derivative. Default is 1.

args : tuple, optional

Arguments

order : int, optional

Number of points to use, must be odd.

Notes

Decreasing the step size too small can result in round-off error.

scipy.misc.pade(an, m)

Given Taylor series coefficients in an, return a Pade approximation to the function as the ratio of two polynomials p / q where the order of q is m.