Array operations

`friendly_matrix.ndarray` methods

class friendly_matrix.ndarray

moveaxis(dim, new_dim) → friendly_matrix.ndarray

Performs a NumPy-style moveaxis operation on the friendly_matrix.ndarray instance. The ordering of dimensions is changed by moving one dimension to the position of another dimension.

Parameters

dim – the dimension to move
new_dim – the dimension whose place dim will take

Returns

The new friendly_matrix.ndarray instance

moveaxis_A(dim, new_dim) → numpy.ndarray: Same as friendly_matrix.ndarray.moveaxis(), except returns only the NumPy array.

swapaxes(dim1, dim2) → friendly_matrix.ndarray

Performs a NumPy-style swapaxes operation on the friendly_matrix.ndarray instance. The ordering of dimensions is changed by swapping the positions of two dimensions.

Parameters

dim1 – dimension
dim2 – dimension

Returns

The new friendly_matrix.ndarray instance

swapaxes_A(dim1, dim2) → numpy.ndarray: Same as friendly_matrix.ndarray.swapaxis(), except returns only the NumPy array.

transpose() → friendly_matrix.ndarray

Performs a NumPy-style transpose operation on the friendly_matrix.ndarray instance. The ordering of the first two dimensions are swapped.

Returns: The new friendly_matrix.ndarray instance

transpose_A() → numpy.ndarray: Same as friendly_matrix.ndarray.transpose(), except returns only the NumPy array.

friendly_matrix.ndarray.T -> friendly_matrix.ndarray: Same as friendly_matrix.ndarray.transpose().

friendly_matrix.ndarray.T_A -> numpy.ndarray: Same as friendly_matrix.ndarray.transpose_A().

mean(axis) → friendly_matrix.ndarray

Performs a NumPy-style mean computation on the friendly_matrix.ndarray instance. Aggregates over a given dimension by calculating the mean(s) along that dimension.

Parameters: axis – dimension
Returns: The new friendly_matrix.ndarray instance

mean_A(axis) → numpy.ndarray: Same as friendly_matrix.ndarray.mean(), except returns only the NumPy array.

std(axis) → friendly_matrix.ndarray

Performs a NumPy-style std computation on the friendly_matrix.ndarray instance. Aggregates over a given dimension by calculating the standard deviation(s) along that dimension.

Parameters: axis – dimension
Returns: The new friendly_matrix.ndarray instance

std_A(axis) → numpy.ndarray: Same as friendly_matrix.ndarray.std(), except returns only the NumPy array.

var(axis) → friendly_matrix.ndarray

Performs a NumPy-style var computation on the friendly_matrix.ndarray instance. Aggregates over a given dimension by calculating the variance(s) along that dimension.

Parameters: axis – dimension
Returns: The new friendly_matrix.ndarray instance

var_A(axis) → numpy.ndarray: Same as friendly_matrix.ndarray.var(), except returns only the NumPy array.

sum(axis) → friendly_matrix.ndarray

Performs a NumPy-style sum computation on the friendly_matrix.ndarray instance. Aggregates over a given dimension by calculating the sum(s) along that dimension.

Parameters: axis – dimension
Returns: The new friendly_matrix.ndarray instance

sum_A(axis) → numpy.ndarray: Same as friendly_matrix.ndarray.sum(), except returns only the NumPy array.

prod(axis) → friendly_matrix.ndarray

Performs a NumPy-style prod computation on the friendly_matrix.ndarray instance. Aggregates over a given dimension by calculating the product(s) along that dimension.

Parameters: axis – dimension
Returns: The new friendly_matrix.ndarray instance

prod_A(axis) → numpy.ndarray: Same as friendly_matrix.ndarray.prod(), except returns only the NumPy array.

min(axis) → friendly_matrix.ndarray

Performs a NumPy-style min computation on the friendly_matrix.ndarray instance. Aggregates over a given dimension by calculating minimum value(s) along that dimension.

Parameters: axis – dimension
Returns: The new friendly_matrix.ndarray instance

min_A(axis) → numpy.ndarray: Same as friendly_matrix.ndarray.min(), except returns only the NumPy array.

argmin(axis) → friendly_matrix.ndarray

Performs a NumPy-style argmin computation on the friendly_matrix.ndarray instance. Aggregates over a given dimension by calculating the index or indices of the minimum value along that dimension.

Parameters: axis – dimension
Returns: The new friendly_matrix.ndarray instance

argmin_A(axis) → numpy.ndarray: Same as friendly_matrix.ndarray.argmin(), except returns only the NumPy array.

all(axis) → friendly_matrix.ndarray

Performs a NumPy-style all computation on the friendly_matrix.ndarray instance. Aggregates over a given dimension by calculating whether all the values along that dimension are truthy.

Parameters: axis – dimension
Returns: The new friendly_matrix.ndarray instance

all_A(axis) → numpy.ndarray: Same as friendly_matrix.ndarray.all(), except returns only the NumPy array.

any(axis) → friendly_matrix.ndarray

Performs a NumPy-style any computation on the friendly_matrix.ndarray instance. Aggregates over a given dimension by calculating the any of the values along that dimension are truthy.

Parameters: axis – dimension
Returns: The new friendly_matrix.ndarray instance

any_A(axis) → numpy.ndarray: Same as friendly_matrix.ndarray.any(), except returns only the NumPy array.

cumsum(axis) → friendly_matrix.ndarray

Performs a NumPy-style cumsum computation on the friendly_matrix.ndarray instance. Aggregates over a given dimension by calculating the cumulative sum along that dimension.

Parameters: axis – dimension
Returns: The new friendly_matrix.ndarray instance (with the same shape as the original)

cumsum_A(axis) → numpy.ndarray: Same as friendly_matrix.ndarray.cumsum(), except returns only the NumPy array.

cumprod(axis) → friendly_matrix.ndarray

Performs a NumPy-style cumprod computation on the friendly_matrix.ndarray instance. Aggregates over a given dimension by calculating the cumulative product along that dimension.

Parameters: axis – dimension
Returns: The new friendly_matrix.ndarray instance (with the same shape as the original)

cumprod_A(axis) → numpy.ndarray: Same as friendly_matrix.ndarray.cumprod(), except returns only the NumPy array.

squeeze() → friendly_matrix.ndarray

Removes any length 1 dimensions in the friendly_matrix.ndarray instance by aggregating over them.

Returns: The new friendly_matrix.ndarray instance

squeeze_A() → numpy.ndarray: Same as friendly_matrix.ndarray.squeeze(), except returns only the NumPy array.

Module functions

friendly_matrix.concatenate(friendlies, axis=0) → friendly_matrix.ndarray

Performs a NumPy-style concatenate operation on the friendly_matrix.ndarray instance. Concatenates the provided friendly_matrix.ndarray instances along the specified dimension.

Parameters

friendlies – friendly_matrix.ndarray instances
axis – the dimension along which to concatenate friendlies

Returns

The new friendly_matrix.ndarray instance

friendly_matrix.concatenate_A(friendlies, axis=0) numpy.ndarray): Same as friendly_matrix.concatenate(), except returns only the NumPy array.

friendly_matrix.stack(friendlies, axis_name, axis_array, axis=0) → friendly_matrix.ndarray

Performs a NumPy-style stack operation on the friendly_matrix.ndarray instances. Stacks the provided friendly_matrix.ndarray instances along a new dimension.

Parameters

friendlies – friendly_matrix.ndarray instances
axis_name – label for the new dimension
axis_array – index labels for the new dimension
axis – the dimension where the new dimension will be inserted

The axis_array argument should have the same length as friendlies.

friendly_matrix.stack_A(friendlies, axis_name=None, axis_array=None, axis=None) → friendly_matrix.ndarray: Same as friendly_matrix.stack(), except returns only the NumPy array.