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Update NDArray stubs: fixed method signatures, added missing methods,… #1

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3 changes: 2 additions & 1 deletion composer.json
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Original file line number Diff line number Diff line change
Expand Up @@ -16,7 +16,8 @@
"homepage": "https://www.numpower.org",
"require": {
"php": ">=8.2",
"ext-numpower": "0.6.0"
"ext-numpower": "0.6.0",
"ext-gd": "*"
},
"minimum-stability": "stable",
"prefer-stable": true
Expand Down
189 changes: 164 additions & 25 deletions stubs/numpower.stubs.php
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Expand Up @@ -114,7 +114,7 @@ public static function reciprocal(NDArray|array|float|int $a): NDArray|float|int
* @param NDArray|array|float|int $b Input array
* @return NDArray|float|int $a ** $b
*/
public static function pow(NDArray|array|float|int $a, NDArray|array|float|int $b): NDArray|float|int {};
public static function pow(NDArray|array|float|int $a, NDArray|array|float|int $b): NDArray|float|int {}

/**
* Subtract two arrays element-wise
Expand Down Expand Up @@ -201,17 +201,19 @@ public static function logb(NDArray|array|float|int $array): NDArray|float|int {
* Finds the maximum value in the array.
*
* @param NDArray|array|float|int $a Input array
* @param int|null $axis If $a is an array, this specifies the axis along which to perform the operation. If NULL, the operation is applied across all elements.
* @return float|int
*/
public static function max(NDArray|array|float|int $a): float|int {}
public static function max(NDArray|array|float|int $a, ?int $axis = null): float|int {}

/**
* Finds the minimum value in the array.
*
* @param NDArray|array|float|int $a Input array
* @param int|null $axis If $a is an array, this specifies the axis along which to perform the operation. If NULL, the operation is applied across all elements.
* @return float|int
*/
public static function min(NDArray|array|float|int $a): float|int {}
public static function min(NDArray|array|float|int $a, ?int $axis = null): float|int {}

/**
* Calculates the element-wise inverse hyperbolic cosine (arccosineh) of an array,
Expand Down Expand Up @@ -376,29 +378,29 @@ public static function trunc(NDArray|array|float|int $array): NDArray|float|int

/**
* Calculates the product of all elements in the array over a given axis
* along which a product is performed. The default, axis=NULL,
* along which a product is performed. The default, axis=null,
* will calculate the product of all the elements in the input array.
*
* @param NDArray|array|float|int $a Input array
* @param int|null $axis The axis to perform the product. If `$axis` is NULL, will calculate the product of all the elements of `$a`.
* @return NDArray|float|int The product of `$a`. If `$axis` is not NULL, the specified axis is removed.
* @param int|null $axis The axis to perform the product. If `$axis` is null, will calculate the product of all the elements of `$a`.
* @return NDArray|float|int The product of `$a`. If `$axis` is not null, the specified axis is removed.
*/
public static function prod(NDArray|array|float|int $a, ?int $axis = NULL): NDArray|float|int {}
public static function prod(NDArray|array|float|int $a, ?int $axis = null): NDArray|float|int {}

/**
* Calculates the sum of all elements in the array over a given axis
* along which a sum is performed. The default, axis=NULL,
* along which a sum is performed. The default, axis=null,
* will calculate the product of all the elements in the input array.
*
* @param NDArray|array|float|int $a Input array
* @param int|null $axis Specifies the axis along which the sum is performed. By default, ($axis=NULL),
* @param int|null $axis Specifies the axis along which the sum is performed. By default, ($axis=null),
* the function sums all elements of the input array.
* @return NDArray|float|int The function returns the summed array along the
* specified axis, resulting in an array with the same shape as the input array,
* but with the specified axis removed. If the input array is 0-dimensional
* or if axis=NULL, a scalar value is returned.
* or if axis=null, a scalar value is returned.
*/
public static function sum(NDArray|array|float|int $a, ?int $axis = NULL): NDArray|float|int {}
public static function sum(NDArray|array|float|int $a, ?int $axis = null): NDArray|float|int {}

/**
* Calculates the element-wise inverse cosine (arccosine) of an array,
Expand Down Expand Up @@ -541,7 +543,7 @@ public static function convolve2d(NDArray|array $a, NDArray|array $b, string $mo
* @param NDArray|array|float|int|null $weights
* @return float|int
*/
public static function average(NDArray|array|float|int $array, NDArray|array|float|int|null $weights = NULL): float|int {}
public static function average(NDArray|array|float|int $array, NDArray|array|float|int|null $weights = null): float|int {}

/**
* The arithmetic mean of the elements in the array. It computes the sum
Expand All @@ -550,18 +552,20 @@ public static function average(NDArray|array|float|int $array, NDArray|array|flo
* Same as calling `nd::sum($a) / $a->size()`
*
* @param NDArray|array|float|int $a
* @param int|null $axis If $a is an array, this specifies the axis along which to perform the operation. If NULL, the operation is applied across all elements.
* @return float|int
*/
public static function mean(NDArray|array|float|int $a): float|int {}
public static function mean(NDArray|array|float|int $a, ?int $axis = null): float|int {}

/**
* The median of the elements in the array. It sorts the array, and if the number of elements is odd,
* it returns the middle value; if the number of elements is even, it returns the average of the two middle values
*
* @param NDArray|array|float|int $a
* @param int|null $axis If $a is an array, this specifies the axis along which to perform the operation. If NULL, the operation is applied across all elements.
* @return float|int
*/
public static function median(NDArray|array|float|int $a): float|int {}
public static function median(NDArray|array|float|int $a, ?int $axis = null): float|int {}

/**
* Computes the specified quantile of the elements in the array. A quantile represents a
Expand All @@ -580,18 +584,20 @@ public static function quantile(NDArray|array|float|int $a, float|int $q): float
* or dispersion in the data.
*
* @param NDArray|array|float|int $a
* @param int|null $axis If $a is an array, this specifies the axis along which to perform the operation. If NULL, the operation is applied across all elements.
* @return float|int
*/
public static function std(NDArray|array|float|int $a): float|int {}
public static function std(NDArray|array|float|int $a, ?int $axis = null): float|int {}

/**
* Calculates the variance of the elements in the array. It measures the average of the
* squared differences between each element and the mean.
*
* @param NDArray|array|float|int $array
* @param int|null $axis If $a is an array, this specifies the axis along which to perform the operation. If NULL, the operation is applied across all elements.
* @return float|int
*/
public static function variance(NDArray|array|float|int $array): float|int {}
public static function variance(NDArray|array|float|int $array, ?int $axis = null): float|int {}

/**
* Convert inputs to arrays with at least one dimension.
Expand All @@ -615,24 +621,25 @@ public static function atleast_2d(NDArray|array|float|int $array): NDArray {}
* Convert inputs to arrays with at least three dimensions.
*
* @param NDArray|array|float|int $array
* @param int|null $axis If $a is an array, this specifies the axis along which to perform the operation. If NULL, the operation is applied across all elements.
* @return NDArray
*/
public static function atleast_3d(NDArray|array|float|int $array): NDArray {}
public static function atleast_3d(NDArray|array|float|int $array, ?int $axis = null): NDArray {}

/**
* Create a copy of array `$a`.
*
* #### $device options
* Default = NULL, copy on the same device as `$a`
* Default = null, copy on the same device as `$a`
*
* - **0** - CPU copy (same as `$a->cpu()`);
* - **1** - GPU copy (same as `$a->gpu()`);
*
* @param NDArray|array|float|int $a
* @param int|null $device NULL = Same device, 0 - copy to CPU, 1 - copy to GPU
* @param int|null $device null = Same device, 0 - copy to CPU, 1 - copy to GPU
* @return NDArray copy of $a
*/
public static function copy(NDArray|array|float|int $a, int $device = NULL): NDArray {}
public static function copy(NDArray|array|float|int $a, int $device = null): NDArray {}

/**
* Adds a new axis to the array at the specified position, thereby expanding its shape.
Expand All @@ -641,7 +648,7 @@ public static function copy(NDArray|array|float|int $a, int $device = NULL): NDA
* @param int|int[]|null $axis This parameter specifies the position where the new axis (or axes) will be inserted within the expanded array.
* @return NDArray
*/
public static function expand_dims(NDArray|array|float|int $target, int|array $axis = NULL): NDArray {}
public static function expand_dims(NDArray|array|float|int $target, int|array $axis = null): NDArray {}

/**
* Return a **copy** of the array `$a` into one dimension.
Expand Down Expand Up @@ -823,9 +830,10 @@ public static function dumpDevices(): void {}

/**
* @param NDArray|array|float|int $a
* @param int|null $axis If $a is an array, this specifies the axis along which to perform the operation. If NULL, the operation is applied across all elements.
* @return bool
*/
public static function all(NDArray|array|float|int $a): bool {}
public static function all(NDArray|array|float|int $a, ?int $axis = null): bool {}

/**
* Checks if all elements in two arrays are approximately equal within a specified tolerance element-wise.
Expand Down Expand Up @@ -1124,7 +1132,7 @@ public function fill(float|int $fill_value): NDArray {}
* Returns the indices of the minimum values along an axis.
*
* @param NDArray|array $a Target array
* @param int|null $axis If NULL, the index is into the flattened array, otherwise along the specified axis.
* @param int|null $axis If null, the index is into the flattened array, otherwise along the specified axis.
* @param bool $keepdims
* @return NDArray Array of indices into the array. It has the same shape as $a with the dimension along $axis removed.
*/
Expand All @@ -1134,7 +1142,7 @@ public static function argmin(NDArray|array $a, ?int $axis, bool $keepdims = fal
* Returns the indices of the maximum values along an axis.
*
* @param NDArray|array $a Target array
* @param int|null $axis If NULL, the index is into the flattened array, otherwise along the specified axis.
* @param int|null $axis If null, the index is into the flattened array, otherwise along the specified axis.
* @param bool $keepdims
* @return NDArray Array of indices into the array. It has the same shape as $a with the dimension along axis removed.
*/
Expand Down Expand Up @@ -1162,5 +1170,136 @@ public static function argmax(NDArray|array $a, ?int $axis, bool $keepdims = fal
* @param array ...$indices
* @return NDArray|float
*/
public function slice(...$indices): NDArray|float {};
public function slice(...$indices): NDArray|float {}

/**
* Calculates the element-wise reciprocal square root (1/√x) of an array,
* returning a new NDArray with the result for each element.
*
* @param NDArray|array $array Input array
* @return NDArray
*/
public static function rsqrt(NDArray|array $array): NDArray {}

/**
* Returns the element-wise maximum of array elements.
*
* @param NDArray|array|float|int $a The first input array.
* @param NDArray|array|float|int $b The second input array.
* @return NDArray
*/
public static function maximum(NDArray|array|float|int $a, NDArray|array|float|int $b): NDArray {}

/**
* Returns the element-wise minimum of array elements.
*
* @param NDArray|array|float|int $a The first input array.
* @param NDArray|array|float|int $b The second input array.
* @return NDArray
*/
public static function minimum(NDArray|array|float|int $a, NDArray|array|float|int $b): NDArray {}


/**
* Element-wise arctangent of x/y choosing the quadrant correctly.
*
* @param NDArray|array|float|int $x The x-coordinates.
* @param NDArray|array|float|int $y The y-coordinates.
* @return NDArray
*/
public static function arctan2(NDArray|array|float|int $x, NDArray|array|float|int $y): NDArray {}

/**
* Converts the NDArray to a GD image resource.
*
* @param NDArray|null $alpha Optional alpha channel NDArray.
* @return \GdImage|null
*/
public function toImage(?NDArray $alpha = null): ?\GdImage {}

/**
* Reverses the order of elements in an array along the given axis.
*
* @param NDArray|array $a Input array.
* @param NDArray|array|int|null $axis Axis or axes along which to flip.
* If axis is None, flips all the elements in the input array.
* @return NDArray
*/
public static function flip(NDArray|array $a, NDArray|array|int|null $axis = null): NDArray {}

/**
* Extracts a diagonal or constructs a diagonal array.
*
* @param NDArray|array $target Input array. If the target is a 2-D array,
* return a 1-D array of its diagonals.
* If the target is a 1-D array, return a 2-D
* array with the 1-D array as a diagonal.
* @return NDArray
*/
public static function diagonal(NDArray|array $target): NDArray {}

/**
* Creates an NDArray from a GD image resource.
*
* @param \GdImage $image The GD image resource.
* @param bool $channelLast Whether the output array should have channels
* as the last dimension (default: true). If false,
* channels will be the first dimension.
* @return NDArray
*/
public static function fromImage(\GdImage $image, bool $channelLast = true): NDArray {}

/**
* Draws samples from a binomial distribution.
*
* @param NDArray|array $shape Shape of the output array.
* @param float $n Number of trials.
* @param float $p Probability of success of each trial.
* @return NDArray
*/
public static function random_binomial(NDArray|array $shape, float $n, float $p): NDArray {}

/**
* Cross-correlation of two 2-dimensional arrays.
*
* @param NDArray|array $a First input array.
* @param NDArray|array $b Second input array.
* @param string $mode A string indicating the size of the output:
* 'valid' (default), 'same', or 'full'.
* @param string $boundary A string indicating the boundary handling:
* 'fill' (default), 'wrap', or 'symm'.
* @param float $fill_value Value to fill pad boundaries with (default: 0).
* @return NDArray
*/
public static function correlate2d(NDArray|array $a, NDArray|array $b, string $mode, string $boundary, float $fill_value = 0.0): NDArray {}

/**
* Performs a 2D forward convolution operation for deep neural networks.
*
* @param NDArray|array $input Input tensor (e.g., [batch, channels, height, width]).
* @param NDArray|array $filters Filter kernel tensor (e.g., [num_filters, channels, kernel_height, kernel_width]).
* @return NDArray Output tensor of the convolution operation.
*/
public static function dnn_conv2d_forward(NDArray|array $input, NDArray|array $filters): NDArray {}

/**
* Performs a 2D backward convolution operation for deep neural networks.
*
* @param NDArray|array $x Input tensor.
* @param NDArray|array $y Output gradient tensor.
* @param NDArray|array $filters Filter kernel tensor.
* @return array{NDArray, NDArray} An array containing the gradient with
* respect to the input and the gradient
* with respect to the filters.
*/
public static function dnn_conv2d_backward(NDArray|array $x, NDArray|array $y, NDArray|array $filters): array {}

/**
* Performs a 1D convolution operation for deep neural networks.
*
* @param NDArray|array $input Input tensor (e.g., [batch, channels, width]).
* @param NDArray|array $filters Filter kernel tensor (e.g., [num_filters, channels, kernel_width]).
* @return NDArray Output tensor of the convolution operation.
*/
public static function dnn_conv1d_forward(NDArray|array $input, NDArray|array $filters): NDArray {}
}