ndarray.min(axis=None, out=None, keepdims=False) Return the minimum along a given axis. Refer to numpy.amin for full documentation. See also numpy.amin equivalent function

ndarray.mean(axis=None, dtype=None, out=None, keepdims=False) Returns the average of the array elements along given axis. Refer to numpy.mean for full documentation. See also numpy.mean equivalent function

ndarray.max(axis=None, out=None) Return the maximum along a given axis. Refer to numpy.amax for full documentation. See also numpy.amax equivalent function

ndarray.itemsize Length of one array element in bytes. Examples >>> x = np.array([1,2,3], dtype=np.float64) >>> x.itemsize 8 >>> x = np.array([1,2,3], dtype=np.complex128) >>> x.itemsize 16

ndarray.itemset(*args) Insert scalar into an array (scalar is cast to array?s dtype, if possible) There must be at least 1 argument, and define the last argument as item. Then, a.itemset(*args) is equivalent to but faster than a[args] = item. The item should be a scalar value and args must select a single item in the array a. Parameters: *args : Arguments If one argument: a scalar, only used in case a is of size 1. If two arguments: the last argument is the value to be set and must be a s

ndarray.item(*args) Copy an element of an array to a standard Python scalar and return it. Parameters: *args : Arguments (variable number and type) none: in this case, the method only works for arrays with one element (a.size == 1), which element is copied into a standard Python scalar object and returned. int_type: this argument is interpreted as a flat index into the array, specifying which element to copy and return. tuple of int_types: functions as does a single int_type argument, exc

ndarray.imag The imaginary part of the array. Examples >>> x = np.sqrt([1+0j, 0+1j]) >>> x.imag array([ 0. , 0.70710678]) >>> x.imag.dtype dtype('float64')

ndarray.getfield(dtype, offset=0) Returns a field of the given array as a certain type. A field is a view of the array data with a given data-type. The values in the view are determined by the given type and the offset into the current array in bytes. The offset needs to be such that the view dtype fits in the array dtype; for example an array of dtype complex128 has 16-byte elements. If taking a view with a 32-bit integer (4 bytes), the offset needs to be between 0 and 12 bytes. Parameters

ndarray.flatten(order='C') Return a copy of the array collapsed into one dimension. Parameters: order : {?C?, ?F?, ?A?, ?K?}, optional ?C? means to flatten in row-major (C-style) order. ?F? means to flatten in column-major (Fortran- style) order. ?A? means to flatten in column-major order if a is Fortran contiguous in memory, row-major order otherwise. ?K? means to flatten a in the order the elements occur in memory. The default is ?C?. Returns: y : ndarray A copy of the input array,

ndarray.flat A 1-D iterator over the array. This is a numpy.flatiter instance, which acts similarly to, but is not a subclass of, Python?s built-in iterator object. See also flatten Return a copy of the array collapsed into one dimension. flatiter Examples >>> x = np.arange(1, 7).reshape(2, 3) >>> x array([[1, 2, 3], [4, 5, 6]]) >>> x.flat[3] 4 >>> x.T array([[1, 4], [2, 5], [3, 6]]) >>> x.T.flat[3] 5 >>> type(x