# Source code for toyplot.broadcast

```
# Copyright 2014, Sandia Corporation. Under the terms of Contract
# DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains certain
# rights in this software.
"""Functions for broadcasting values into 1D or 2D arrays.
The functions in this module are used by Toyplot to handle the conversion from
`constant`, `per-series`, and `per-datum` values into their canonical 1D and 2D
array representations.
"""
import numpy
[docs]def scalar(value, shape):
"""Return a 1D or 2D array of floats with the given shape.
Parameters
----------
shape: (tuple)
Shape of the desired output array. A 1-tuple will produce a 1D output
vector containing :math:`N` per-series values. A 2-tuple will produce an :math:`M \\times N`
output matrix of per-datum values grouped into :math:`N` series.
Returns
-------
array: :class:`numpy.ndarray`
"""
array = numpy.array(value).astype("float64")
# As a special-case, allow a vector with shape M to be matched-up with an
# M x 1 matrix.
if array.ndim == 1 and isinstance(shape, tuple) and len(
shape) == 2 and array.shape[0] == shape[0] and shape[1] == 1:
return numpy.reshape(array, shape)
return numpy.broadcast_arrays(array, numpy.empty(shape))[0]
#def string(value, shape):
# array = numpy.array(value).astype("unicode")
# # As a special-case, allow a vector with shape M to be matched-up with an
# # M x 1 matrix.
# if array.ndim == 1 and isinstance(shape, tuple) and len(
# shape) == 2 and array.shape[0] == shape[0] and shape[1] == 1:
# return numpy.reshape(array, shape)
# return numpy.broadcast_arrays(array, numpy.empty(shape))[0]
[docs]def pyobject(value, shape):
"""Return a 1D or 2D array of objects with the given shape.
Parameters
----------
shape: (tuple)
Shape of the desired output array. A 1-tuple will produce a 1D output
vector containing :math:`N` per-series values. A 2-tuple will produce an :math:`M \\times N`
output matrix of per-datum values grouped into :math:`N` series.
Returns
-------
array: :class:`numpy.ndarray`
"""
array = numpy.array(value)
# As a special-case, allow a vector with shape M to be matched-up with an
# M x 1 matrix.
if array.ndim == 1 and isinstance(shape, tuple) and len(
shape) == 2 and array.shape[0] == shape[0] and shape[1] == 1:
return numpy.reshape(array, shape)
result = numpy.empty(shape, dtype="object")
result.flat = [u for u, _ in numpy.broadcast(array, result)]
return result
```