pyunitwizard.utils.numpy package

Submodules

pyunitwizard.utils.numpy.column_stack module

pyunitwizard.utils.numpy.column_stack.column_stack(sequence, to_unit=None, to_form=None, value_type='tuple', standardized=False)

pyunitwizard.utils.numpy.hstack module

pyunitwizard.utils.numpy.hstack.hstack(sequence, to_unit=None, to_form=None, value_type='tuple', standardized=False)

pyunitwizard.utils.numpy.ops module

pyunitwizard.utils.numpy.ops.dot(quantity_like_a, quantity_like_b, to_unit=None, to_form=None, value_type=None, standardized=False, **kwargs)

pyunitwizard.utils.numpy.ops.linalg_norm(quantity_like, ord=None, axis=None, keepdims=False, to_unit=None, to_form=None, value_type=None, standardized=False)

pyunitwizard.utils.numpy.ops.mean(quantity_like, axis=None, to_unit=None, to_form=None, value_type=None, standardized=False, **kwargs)

pyunitwizard.utils.numpy.ops.std(quantity_like, axis=None, to_unit=None, to_form=None, value_type=None, standardized=False, **kwargs)

pyunitwizard.utils.numpy.ops.sum(quantity_like, axis=None, to_unit=None, to_form=None, value_type=None, standardized=False, **kwargs)

pyunitwizard.utils.numpy.ops.trapz(y, x=None, dx=1.0, axis=-1, to_unit=None, to_form=None, value_type=None, standardized=False)

pyunitwizard.utils.numpy.ops.var(quantity_like, axis=None, to_unit=None, to_form=None, value_type=None, standardized=False, **kwargs)

pyunitwizard.utils.numpy.repeat module

pyunitwizard.utils.numpy.repeat.repeat(sequence, repeats, axis=None, to_unit=None, to_form=None, value_type=None, standardized=False)

pyunitwizard.utils.numpy.stack module

pyunitwizard.utils.numpy.stack.stack(sequence, axis=0, to_unit=None, to_form=None, value_type='tuple', standardized=False)

pyunitwizard.utils.numpy.vstack module

pyunitwizard.utils.numpy.vstack.vstack(sequence, to_unit=None, to_form=None, value_type='tuple', standardized=False)

Module contents

pyunitwizard.utils.numpy.column_stack(sequence, to_unit=None, to_form=None, value_type='tuple', standardized=False)

pyunitwizard.utils.numpy.dot(quantity_like_a, quantity_like_b, to_unit=None, to_form=None, value_type=None, standardized=False, **kwargs)

pyunitwizard.utils.numpy.hstack(sequence, to_unit=None, to_form=None, value_type='tuple', standardized=False)

pyunitwizard.utils.numpy.linalg_norm(quantity_like, ord=None, axis=None, keepdims=False, to_unit=None, to_form=None, value_type=None, standardized=False)

pyunitwizard.utils.numpy.mean(quantity_like, axis=None, to_unit=None, to_form=None, value_type=None, standardized=False, **kwargs)

pyunitwizard.utils.numpy.numpy_context()

Temporarily enable transparent NumPy quantity dispatch.

pyunitwizard.utils.numpy.repeat(sequence, repeats, axis=None, to_unit=None, to_form=None, value_type=None, standardized=False)

pyunitwizard.utils.numpy.setup_numpy(enable=True)

Enable or disable transparent NumPy quantity dispatch for common ops.

Parameters:

enable (bool)

Return type:

None

pyunitwizard.utils.numpy.stack(sequence, axis=0, to_unit=None, to_form=None, value_type='tuple', standardized=False)

pyunitwizard.utils.numpy.std(quantity_like, axis=None, to_unit=None, to_form=None, value_type=None, standardized=False, **kwargs)

pyunitwizard.utils.numpy.sum(quantity_like, axis=None, to_unit=None, to_form=None, value_type=None, standardized=False, **kwargs)

pyunitwizard.utils.numpy.trapz(y, x=None, dx=1.0, axis=-1, to_unit=None, to_form=None, value_type=None, standardized=False)

pyunitwizard.utils.numpy.var(quantity_like, axis=None, to_unit=None, to_form=None, value_type=None, standardized=False, **kwargs)

pyunitwizard.utils.numpy.vstack(sequence, to_unit=None, to_form=None, value_type='tuple', standardized=False)