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SciPy

numpy.ndarray

classnumpy.ndarray[source]

An array object represents a multidimensional, homogeneous arrayof fixed-size items. An associated data-type object describes theformat of each element in the array (its byte-order, how many bytes itoccupies in memory, whether it is an integer, a floating point number,or something else, etc.)

Arrays should be constructed usingarray,zeros orempty (referto the See Also section below). The parameters given here refer toa low-level method (ndarray(...)) for instantiating an array.

For more information, refer to thenumpy module and examine themethods and attributes of an array.

Parameters:

(for the __new__ method; see Notes below)

shape : tuple of ints

Shape of created array.

dtype : data-type, optional

Any object that can be interpreted as a numpy data type.

buffer : object exposing buffer interface, optional

Used to fill the array with data.

offset : int, optional

Offset of array data in buffer.

strides : tuple of ints, optional

Strides of data in memory.

order : {‘C’, ‘F’}, optional

Row-major (C-style) or column-major (Fortran-style) order.

See also

array
Construct an array.
zeros
Create an array, each element of which is zero.
empty
Create an array, but leave its allocated memory unchanged (i.e., it contains “garbage”).
dtype
Create a data-type.

Notes

There are two modes of creating an array using__new__:

  1. Ifbuffer is None, then onlyshape,dtype, andorderare used.
  2. Ifbuffer is an object exposing the buffer interface, thenall keywords are interpreted.

No__init__ method is needed because the array is fully initializedafter the__new__ method.

Examples

These examples illustrate the low-levelndarray constructor. Referto theSee Also section above for easier ways of constructing anndarray.

First mode,buffer is None:

>>>np.ndarray(shape=(2,2),dtype=float,order='F')array([[ -1.13698227e+002,   4.25087011e-303],       [  2.88528414e-306,   3.27025015e-309]])         #random

Second mode:

>>>np.ndarray((2,),buffer=np.array([1,2,3]),...offset=np.int_().itemsize,...dtype=int)# offset = 1*itemsize, i.e. skip first elementarray([2, 3])

Attributes

TSame as self.transpose(), except that self is returned if self.ndim < 2.
dataPython buffer object pointing to the start of the array’s data.
dtypeData-type of the array’s elements.
flagsInformation about the memory layout of the array.
flatA 1-D iterator over the array.
imagThe imaginary part of the array.
realThe real part of the array.
sizeNumber of elements in the array.
itemsizeLength of one array element in bytes.
nbytesTotal bytes consumed by the elements of the array.
ndimNumber of array dimensions.
shapeTuple of array dimensions.
stridesTuple of bytes to step in each dimension when traversing an array.
ctypesAn object to simplify the interaction of the array with the ctypes module.
baseBase object if memory is from some other object.

Methods

all([axis, out, keepdims])Returns True if all elements evaluate to True.
any([axis, out, keepdims])Returns True if any of the elements ofa evaluate to True.
argmax([axis, out])Return indices of the maximum values along the given axis.
argmin([axis, out])Return indices of the minimum values along the given axis ofa.
argpartition(kth[, axis, kind, order])Returns the indices that would partition this array.
argsort([axis, kind, order])Returns the indices that would sort this array.
astype(dtype[, order, casting, subok, copy])Copy of the array, cast to a specified type.
byteswap(inplace)Swap the bytes of the array elements
choose(choices[, out, mode])Use an index array to construct a new array from a set of choices.
clip([min, max, out])Return an array whose values are limited to[min,max].
compress(condition[, axis, out])Return selected slices of this array along given axis.
conj()Complex-conjugate all elements.
conjugate()Return the complex conjugate, element-wise.
copy([order])Return a copy of the array.
cumprod([axis, dtype, out])Return the cumulative product of the elements along the given axis.
cumsum([axis, dtype, out])Return the cumulative sum of the elements along the given axis.
diagonal([offset, axis1, axis2])Return specified diagonals.
dot(b[, out])Dot product of two arrays.
dump(file)Dump a pickle of the array to the specified file.
dumps()Returns the pickle of the array as a string.
fill(value)Fill the array with a scalar value.
flatten([order])Return a copy of the array collapsed into one dimension.
getfield(dtype[, offset])Returns a field of the given array as a certain type.
item(*args)Copy an element of an array to a standard Python scalar and return it.
itemset(*args)Insert scalar into an array (scalar is cast to array’s dtype, if possible)
max([axis, out])Return the maximum along a given axis.
mean([axis, dtype, out, keepdims])Returns the average of the array elements along given axis.
min([axis, out, keepdims])Return the minimum along a given axis.
newbyteorder([new_order])Return the array with the same data viewed with a different byte order.
nonzero()Return the indices of the elements that are non-zero.
partition(kth[, axis, kind, order])Rearranges the elements in the array in such a way that value of the element in kth position is in the position it would be in a sorted array.
prod([axis, dtype, out, keepdims])Return the product of the array elements over the given axis
ptp([axis, out])Peak to peak (maximum - minimum) value along a given axis.
put(indices, values[, mode])Seta.flat[n]=values[n] for alln in indices.
ravel([order])Return a flattened array.
repeat(repeats[, axis])Repeat elements of an array.
reshape(shape[, order])Returns an array containing the same data with a new shape.
resize(new_shape[, refcheck])Change shape and size of array in-place.
round([decimals, out])Returna with each element rounded to the given number of decimals.
searchsorted(v[, side, sorter])Find indices where elements of v should be inserted in a to maintain order.
setfield(val, dtype[, offset])Put a value into a specified place in a field defined by a data-type.
setflags([write, align, uic])Set array flags WRITEABLE, ALIGNED, and UPDATEIFCOPY, respectively.
sort([axis, kind, order])Sort an array, in-place.
squeeze([axis])Remove single-dimensional entries from the shape ofa.
std([axis, dtype, out, ddof, keepdims])Returns the standard deviation of the array elements along given axis.
sum([axis, dtype, out, keepdims])Return the sum of the array elements over the given axis.
swapaxes(axis1, axis2)Return a view of the array withaxis1 andaxis2 interchanged.
take(indices[, axis, out, mode])Return an array formed from the elements ofa at the given indices.
tobytes([order])Construct Python bytes containing the raw data bytes in the array.
tofile(fid[, sep, format])Write array to a file as text or binary (default).
tolist()Return the array as a (possibly nested) list.
tostring([order])Construct Python bytes containing the raw data bytes in the array.
trace([offset, axis1, axis2, dtype, out])Return the sum along diagonals of the array.
transpose(*axes)Returns a view of the array with axes transposed.
var([axis, dtype, out, ddof, keepdims])Returns the variance of the array elements, along given axis.
view([dtype, type])New view of array with the same data.

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