Source code for wolframclient.serializers.wxfencoder.wxfnumpyencoder

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

from __future__ import absolute_import, print_function, unicode_literals

from wolframclient.serializers.wxfencoder.constants import ARRAY_TYPES
from wolframclient.serializers.wxfencoder.wxfencoder import WXFEncoder
from wolframclient.serializers.wxfencoder.wxfexpr import (
from wolframclient.utils.api import numpy

__all__ = ["NumPyWXFEncoder"]

[docs]class NumPyWXFEncoder(WXFEncoder): """ NumPy array encoder. Encode numpy array as instances of packed array and / or raw array. By default only packed arrays are generated. Unsigned integer data are cast to a type that can fit the maximum value. It's possible to add support for raw arrays only for unsigned data, in which case both `packed_array_support` and `numeric_array_support` must be true. >>> NumPyWXFEncoder(packed_array_support=True, numeric_array_support=True) Finally it's possible to only output raw arrays with: >>> NumPyWXFEncoder(packed_array_support=False, numeric_array_support=True) """ def __init__(self, packed_array_support=True, numeric_array_support=False): if not packed_array_support and not numeric_array_support: raise ValueError( "At least one of the two parameters packed_array_support or numeric_array_support must be True." ) self.packed_array_support = packed_array_support self.numeric_array_support = numeric_array_support
[docs] def encode(self, python_expr): if isinstance(python_expr, numpy.ndarray): if self.packed_array_support: array_class = WXFExprPackedArray else: array_class = WXFExprNumericArray if python_expr.dtype == numpy.int8: value_type = ARRAY_TYPES.Integer8 data = python_expr.astype("<i1") elif python_expr.dtype == numpy.int16: data = python_expr.astype("<i2") value_type = ARRAY_TYPES.Integer16 elif python_expr.dtype == numpy.int32: data = python_expr.astype("<i4") value_type = ARRAY_TYPES.Integer32 elif python_expr.dtype == numpy.int64: data = python_expr.astype("<i8") value_type = ARRAY_TYPES.Integer64 elif python_expr.dtype == numpy.uint8: if self.numeric_array_support: value_type = ARRAY_TYPES.UnsignedInteger8 data = python_expr.astype("<u1") array_class = WXFExprNumericArray else: value_type = ARRAY_TYPES.Integer16 data = python_expr.astype("<i2") elif python_expr.dtype == numpy.uint16: if self.numeric_array_support: value_type = ARRAY_TYPES.UnsignedInteger16 data = python_expr.astype("<u2") array_class = WXFExprNumericArray else: value_type = ARRAY_TYPES.Integer32 data = python_expr.astype("<i4") elif python_expr.dtype == numpy.uint32: if self.numeric_array_support: value_type = ARRAY_TYPES.UnsignedInteger32 data = python_expr.astype("<u4") array_class = WXFExprNumericArray else: value_type = ARRAY_TYPES.Integer64 data = python_expr.astype("<i8") # no one to one mapping to signed values, even if most of the time # the values would fit elif python_expr.dtype == numpy.uint64: if self.numeric_array_support: value_type = ARRAY_TYPES.UnsignedInteger64 data = python_expr.astype("<u8") array_class = WXFExprNumericArray else: TypeError("Cannot represent data of type uint64 as signed int64") elif python_expr.dtype == numpy.float32: value_type = ARRAY_TYPES.Real32 data = python_expr elif python_expr.dtype == numpy.float64: value_type = ARRAY_TYPES.Real64 data = python_expr elif python_expr.dtype == numpy.complex64: value_type = ARRAY_TYPES.ComplexReal32 data = python_expr elif python_expr.dtype == numpy.complex128: value_type = ARRAY_TYPES.ComplexReal64 data = python_expr else: raise NotImplementedError( "NumPy serialization not implemented for %s" % repr(python_expr.dtype) ) if hasattr(data, "tobytes"): # Numpy 1.9+ support array.tobytes, but previous versions don't and use tostring instead. yield array_class(python_expr.shape, value_type, data.tobytes()) else: yield array_class(python_expr.shape, value_type, data.tostring())