Namespace NumSharp

NumPy-compatible AxisError exception. Raised when an axis argument is out of bounds for the array's dimensions.

Exception that corresponds to Python/NumPy's IndexError. Raised when a sequence subscript is out of range, or when an index type is invalid (e.g. float/complex index on an ndarray).

Kwargs

MT19937

Mersenne Twister MT19937 pseudo-random number generator. This implementation matches NumPy's MT19937 exactly, producing identical sequences for the same seed.

MethodImplOptionsConstants

Method implementation option constants for use with MethodImplAttribute.

MultiIterator

NDArray

Container protocol implementation for NDArray. Provides Python-compatible container protocol methods: contains, hash, len, iter, getitem, setitem

A class that serves as numpy.random.RandomState in python. Uses MT19937 (Mersenne Twister) for NumPy-compatible random number generation.

NumSharpException

Slice

NDArray can be indexed using slicing
A slice is constructed by start:stop:step notation

Examples:

a[start:stop] # items start through stop-1
a[start:] # items start through the rest of the array
a[:stop] # items from the beginning through stop-1

The key point to remember is that the :stop value represents the first value that is not
in the selected slice. So, the difference between stop and start is the number of elements
selected (if step is 1, the default).

There is also the step value, which can be used with any of the above:
a[:] # a copy of the whole array
a[start:stop:step] # start through not past stop, by step

The other feature is that start or stop may be a negative number, which means it counts
from the end of the array instead of the beginning. So:
a[-1] # last item in the array
a[-2:] # last two items in the array
a[:-2] # everything except the last two items
Similarly, step may be a negative number:

a[::- 1] # all items in the array, reversed
a[1::- 1] # the first two items, reversed
a[:-3:-1] # the last two items, reversed
a[-3::- 1] # everything except the last two items, reversed

NumSharp is kind to the programmer if there are fewer items than
you ask for. For example, if you ask for a[:-2] and a only contains one element, you get an
empty list instead of an error.Sometimes you would prefer the error, so you have to be aware
that this may happen.

Adapted from Greg Hewgill's answer on Stackoverflow: https://stackoverflow.com/questions/509211/understanding-slice-notation

Note: special IsIndex == true
It will pick only a single value at Start in this dimension effectively reducing the Shape of the sliced matrix by 1 dimension.
It can be used to reduce an N-dimensional array/matrix to a (N-1)-dimensional array/matrix

Example:
a=[[1, 2], [3, 4]]
a[:, 1] returns the second column of that 2x2 matrix as a 1-D vector

TensorEngine

TypeError

Exception that corresponds to Python/NumPy's TypeError. Raised when an operation or function receives an argument of inappropriate type.

ValueError

NumPy-compatible ValueError exception. Raised when an operation receives an argument with the right type but inappropriate value.

finfo

Machine limits for floating point types.

iinfo

Machine limits for integer types.

np

API bridge between NumSharp and Python NumPy

np.Broadcast

DateTime64

A 64-bit signed tick count representing a date/time value with full long range and a NaT sentinel, matching NumPy's np.datetime64 semantics. Used as a conversion-helper type in Converts.

NDArray._Unsafe

NDArray._Unsafe._Pinning

NativeRandomState

Represents the stored state of MT19937 random number generator. This format is compatible with NumPy's random state.

Shape

Broadcasting operations for Shape.

SliceDef

IIndex

Represents a class that can be served as an index, e.g. ndarray[new Slice(...)]

INumSharpException

NDIterator

ArrayFlags