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// Copyright (c) 2019 by the SciSharp Team
// Code generated by CodeMinion: https://github.com/SciSharp/CodeMinion
using System;
using System.Collections;
using System.Collections.Generic;
using System.IO;
using System.Linq;
using System.Runtime.InteropServices;
using System.Text;
using Python.Runtime;
using Python.Included;
using Numpy.Models;
namespace Numpy
{
public static partial class np
{
/// <summary>
/// Compute the bit-wise AND of two arrays element-wise.
///
/// Computes the bit-wise AND of the underlying binary representation of
/// the integers in the input arrays. This ufunc implements the C/Python
/// operator &.
/// </summary>
/// <param name="x2">
/// Only integer and boolean types are handled.
/// </param>
/// <param name="x1">
/// Only integer and boolean types are handled.
/// </param>
/// <param name="@out">
/// A location into which the result is stored. If provided, it must have
/// a shape that the inputs broadcast to. If not provided or None,
/// a freshly-allocated array is returned. A tuple (possible only as a
/// keyword argument) must have length equal to the number of outputs.
/// </param>
/// <param name="@where">
/// Values of True indicate to calculate the ufunc at that position, values
/// of False indicate to leave the value in the output alone.
/// </param>
/// <returns>
/// Result.
/// This is a scalar if both x1 and x2 are scalars.
/// </returns>
public static NDarray bitwise_and(NDarray x2, NDarray x1, NDarray @out = null, NDarray @where = null)
=> NumPy.Instance.bitwise_and(x2, x1, @out:@out, @where:@where);
/// <summary>
/// Compute the bit-wise OR of two arrays element-wise.
///
/// Computes the bit-wise OR of the underlying binary representation of
/// the integers in the input arrays. This ufunc implements the C/Python
/// operator |.
/// </summary>
/// <param name="x2">
/// Only integer and boolean types are handled.
/// </param>
/// <param name="x1">
/// Only integer and boolean types are handled.
/// </param>
/// <param name="@out">
/// A location into which the result is stored. If provided, it must have
/// a shape that the inputs broadcast to. If not provided or None,
/// a freshly-allocated array is returned. A tuple (possible only as a
/// keyword argument) must have length equal to the number of outputs.
/// </param>
/// <param name="@where">
/// Values of True indicate to calculate the ufunc at that position, values
/// of False indicate to leave the value in the output alone.
/// </param>
/// <returns>
/// Result.
/// This is a scalar if both x1 and x2 are scalars.
/// </returns>
public static NDarray bitwise_or(NDarray x2, NDarray x1, NDarray @out = null, NDarray @where = null)
=> NumPy.Instance.bitwise_or(x2, x1, @out:@out, @where:@where);
/// <summary>
/// Compute the bit-wise XOR of two arrays element-wise.
///
/// Computes the bit-wise XOR of the underlying binary representation of
/// the integers in the input arrays. This ufunc implements the C/Python
/// operator ^.
/// </summary>
/// <param name="x2">
/// Only integer and boolean types are handled.
/// </param>
/// <param name="x1">
/// Only integer and boolean types are handled.
/// </param>
/// <param name="@out">
/// A location into which the result is stored. If provided, it must have
/// a shape that the inputs broadcast to. If not provided or None,
/// a freshly-allocated array is returned. A tuple (possible only as a
/// keyword argument) must have length equal to the number of outputs.
/// </param>
/// <param name="@where">
/// Values of True indicate to calculate the ufunc at that position, values
/// of False indicate to leave the value in the output alone.
/// </param>
/// <returns>
/// Result.
/// This is a scalar if both x1 and x2 are scalars.
/// </returns>
public static NDarray bitwise_xor(NDarray x2, NDarray x1, NDarray @out = null, NDarray @where = null)
=> NumPy.Instance.bitwise_xor(x2, x1, @out:@out, @where:@where);
/// <summary>
/// Compute bit-wise inversion, or bit-wise NOT, element-wise.
///
/// Computes the bit-wise NOT of the underlying binary representation of
/// the integers in the input arrays. This ufunc implements the C/Python
/// operator ~.
///
/// For signed integer inputs, the two’s complement is returned. In a
/// two’s-complement system negative numbers are represented by the two’s
/// complement of the absolute value. This is the most common method of
/// representing signed integers on computers [1]. A N-bit
/// two’s-complement system can represent every integer in the range
/// to .
///
/// Notes
///
/// bitwise_not is an alias for invert:
///
/// References
/// </summary>
/// <param name="x">
/// Only integer and boolean types are handled.
/// </param>
/// <param name="@out">
/// A location into which the result is stored. If provided, it must have
/// a shape that the inputs broadcast to. If not provided or None,
/// a freshly-allocated array is returned. A tuple (possible only as a
/// keyword argument) must have length equal to the number of outputs.
/// </param>
/// <param name="@where">
/// Values of True indicate to calculate the ufunc at that position, values
/// of False indicate to leave the value in the output alone.
/// </param>
/// <returns>
/// Result.
/// This is a scalar if x is a scalar.
/// </returns>
public static NDarray invert(NDarray x, NDarray @out = null, NDarray @where = null)
=> NumPy.Instance.invert(x, @out:@out, @where:@where);
/// <summary>
/// Shift the bits of an integer to the left.
///
/// Bits are shifted to the left by appending x2 0s at the right of x1.
/// Since the internal representation of numbers is in binary format, this
/// operation is equivalent to multiplying x1 by 2**x2.
/// </summary>
/// <param name="x1">
/// Input values.
/// </param>
/// <param name="x2">
/// Number of zeros to append to x1. Has to be non-negative.
/// </param>
/// <param name="@out">
/// A location into which the result is stored. If provided, it must have
/// a shape that the inputs broadcast to. If not provided or None,
/// a freshly-allocated array is returned. A tuple (possible only as a
/// keyword argument) must have length equal to the number of outputs.
/// </param>
/// <param name="@where">
/// Values of True indicate to calculate the ufunc at that position, values
/// of False indicate to leave the value in the output alone.
/// </param>
/// <returns>
/// Return x1 with bits shifted x2 times to the left.
/// This is a scalar if both x1 and x2 are scalars.
/// </returns>
public static NDarray<int> left_shift(NDarray<int> x1, NDarray<int> x2, NDarray @out = null, NDarray @where = null)
=> NumPy.Instance.left_shift(x1, x2, @out:@out, @where:@where);
/// <summary>
/// Shift the bits of an integer to the right.
///
/// Bits are shifted to the right x2. Because the internal
/// representation of numbers is in binary format, this operation is
/// equivalent to dividing x1 by 2**x2.
/// </summary>
/// <param name="x1">
/// Input values.
/// </param>
/// <param name="x2">
/// Number of bits to remove at the right of x1.
/// </param>
/// <param name="@out">
/// A location into which the result is stored. If provided, it must have
/// a shape that the inputs broadcast to. If not provided or None,
/// a freshly-allocated array is returned. A tuple (possible only as a
/// keyword argument) must have length equal to the number of outputs.
/// </param>
/// <param name="@where">
/// Values of True indicate to calculate the ufunc at that position, values
/// of False indicate to leave the value in the output alone.
/// </param>
/// <returns>
/// Return x1 with bits shifted x2 times to the right.
/// This is a scalar if both x1 and x2 are scalars.
/// </returns>
public static NDarray right_shift(NDarray x1, NDarray x2, NDarray @out = null, NDarray @where = null)
=> NumPy.Instance.right_shift(x1, x2, @out:@out, @where:@where);
/// <summary>
/// Packs the elements of a binary-valued array into bits in a uint8 array.
///
/// The result is padded to full bytes by inserting zero bits at the end.
/// </summary>
/// <param name="myarray">
/// An array of integers or booleans whose elements should be packed to
/// bits.
/// </param>
/// <param name="axis">
/// The dimension over which bit-packing is done.
/// None implies packing the flattened array.
/// </param>
/// <returns>
/// Array of type uint8 whose elements represent bits corresponding to the
/// logical (0 or nonzero) value of the input elements. The shape of
/// packed has the same number of dimensions as the input (unless axis
/// is None, in which case the output is 1-D).
/// </returns>
public static NDarray packbits(NDarray myarray, int? axis = null)
=> NumPy.Instance.packbits(myarray, axis:axis);
/// <summary>
/// Unpacks elements of a uint8 array into a binary-valued output array.
///
/// Each element of myarray represents a bit-field that should be unpacked
/// into a binary-valued output array. The shape of the output array is either
/// 1-D (if axis is None) or the same shape as the input array with unpacking
/// done along the axis specified.
/// </summary>
/// <param name="myarray">
/// Input array.
/// </param>
/// <param name="axis">
/// The dimension over which bit-unpacking is done.
/// None implies unpacking the flattened array.
/// </param>
/// <returns>
/// The elements are binary-valued (0 or 1).
/// </returns>
public static NDarray unpackbits(NDarray myarray, int? axis = null)
=> NumPy.Instance.unpackbits(myarray, axis:axis);
/// <summary>
/// Return the binary representation of the input number as a string.
///
/// For negative numbers, if width is not given, a minus sign is added to the
/// front. If width is given, the two’s complement of the number is
/// returned, with respect to that width.
///
/// In a two’s-complement system negative numbers are represented by the two’s
/// complement of the absolute value. This is the most common method of
/// representing signed integers on computers [1]. A N-bit two’s-complement
/// system can represent every integer in the range
/// to .
///
/// Notes
///
/// binary_repr is equivalent to using base_repr with base 2, but about 25x
/// faster.
///
/// References
/// </summary>
/// <param name="num">
/// Only an integer decimal number can be used.
/// </param>
/// <param name="width">
/// The length of the returned string if num is positive, or the length
/// of the two’s complement if num is negative, provided that width is
/// at least a sufficient number of bits for num to be represented in the
/// designated form.
///
/// If the width value is insufficient, it will be ignored, and num will
/// be returned in binary (num > 0) or two’s complement (num < 0) form
/// with its width equal to the minimum number of bits needed to represent
/// the number in the designated form. This behavior is deprecated and will
/// later raise an error.
/// </param>
/// <returns>
/// Binary representation of num or two’s complement of num.
/// </returns>
public static string binary_repr(int num, int? width = null)
=> NumPy.Instance.binary_repr(num, width:width);
}
}