+ # Creating the *from_reference* transforms.
+ cs.from_reference_transforms = []
+
+ return cs
+
+
+# -------------------------------------------------------------------------
+# *Transfer Function + Matrix Transform*
+# -------------------------------------------------------------------------
+def create_matrix_plus_transfer_colorspace(
+ name='matrix_plus_transfer',
+ transfer_function_name='transfer_function',
+ transfer_function=lambda x: x,
+ lut_directory='/tmp',
+ lut_resolution_1d=1024,
+ from_reference_values=None,
+ to_reference_values=None,
+ aliases=None):
+ """
+ Object description.
+
+ Parameters
+ ----------
+ parameter : type
+ Parameter description.
+
+ Returns
+ -------
+ type
+ Return value description.
+ """
+
+ if from_reference_values is None:
+ from_reference_values = []
+
+ if to_reference_values is None:
+ to_reference_values = []
+
+ if aliases is None:
+ aliases = []
+
+ cs = ColorSpace(name)
+ cs.description = 'The %s color space' % name
+ cs.aliases = aliases
+ cs.equality_group = name
+ cs.family = 'Utility'
+ cs.is_data = False
+
+ # A linear space needs allocation variables.
+ cs.allocation_type = ocio.Constants.ALLOCATION_UNIFORM
+ cs.allocation_vars = [0, 1]
+
+ # Sampling the transfer function.
+ data = array.array('f', '\0' * lut_resolution_1d * 4)
+ for c in range(lut_resolution_1d):
+ data[c] = transfer_function(c / (lut_resolution_1d - 1))
+
+ # Writing the sampled data to a *LUT*.
+ lut = '%s_to_linear.spi1d' % transfer_function_name
+ genlut.write_SPI_1d(
+ os.path.join(lut_directory, lut),
+ 0,
+ 1,
+ data,
+ lut_resolution_1d,
+ 1)
+
+ # Creating the *to_reference* transforms.
+ cs.to_reference_transforms = []