Source code for africanus.model.coherency.dask

# -*- coding: utf-8 -*-

from africanus.model.coherency.conversion import (

from africanus.util.requirements import requires_optional

    import dask.array as da
except ImportError as e:
    da_import_error = e
    da_import_error = None

def convert_wrapper(np_input, mapping=None, in_shape=None, out_shape=None, dtype_=None):
    result = convert_impl(np_input, mapping, in_shape, out_shape, dtype_)

    # Introduce extra singleton dimension at the end of our shape
    return result.reshape(result.shape + (1,) * len(in_shape))

[docs] @requires_optional("dask.array", da_import_error) def convert(input, input_schema, output_schema): mapping, in_shape, out_shape, dtype = convert_setup( input, input_schema, output_schema ) n_free_dims = len(input.shape) - len(in_shape) free_dims = tuple("dim-%d" % i for i in range(n_free_dims)) in_corr_dims = tuple("icorr-%d" % i for i in range(len(in_shape))) out_corr_dims = tuple("ocorr-%d" % i for i in range(len(out_shape))) # Output dimension are new dimensions new_axes = {d: s for d, s in zip(out_corr_dims, out_shape)} # Note the dummy in_corr_dims introduced at the end of our output, # We do this to prevent a contraction over the input dimensions # (which can be arbitrary) within the wrapper class res = da.core.blockwise( convert_wrapper, free_dims + out_corr_dims + in_corr_dims, input, free_dims + in_corr_dims, mapping=mapping, in_shape=in_shape, out_shape=out_shape, new_axes=new_axes, dtype_=dtype, dtype=dtype, ) # Now contract over the dummy dimensions start = len(free_dims) + len(out_corr_dims) end = start + len(in_corr_dims) return res.sum(axis=list(range(start, end)))
try: convert.__doc__ = CONVERT_DOCS.substitute(array_type=":class:`dask.array.Array`") except AttributeError: pass