Ensure that most "Colour" honours float precision change.

colour/adaptation/fairchild1990.py

@@ -22,7 +22,7 @@
 
 from colour.algebra import spow
 from colour.adaptation import VON_KRIES_CAT
-from colour.utilities import (as_float_array, dot_vector, from_range_100,
+from colour.utilities import (as_float_array, dot_vector, from_range_100, ones,
                               row_as_diagonal, to_domain_100, tsplit, tstack)
 
 __author__ = 'Colour Developers'
@@ -231,14 +231,15 @@ def degrees_of_adaptation(LMS, Y_n, v=1 / 3, discount_illuminant=False):
 
     LMS = as_float_array(LMS)
     if discount_illuminant:
-        return np.ones(LMS.shape)
+        return ones(LMS.shape)
 
     Y_n = as_float_array(Y_n)
     v = as_float_array(v)
 
     L, M, S = tsplit(LMS)
 
-    LMS_E = dot_vector(VON_KRIES_CAT, np.ones(LMS.shape))  # E illuminant.
+    # E illuminant.
+    LMS_E = dot_vector(VON_KRIES_CAT, ones(LMS.shape))
     L_E, M_E, S_E = tsplit(LMS_E)
 
     Ye_n = spow(Y_n, v)

colour/algebra/geometry.py

@@ -40,8 +40,8 @@
 import numpy as np
 from collections import namedtuple
 
-from colour.utilities import (CaseInsensitiveMapping, as_float_array, tsplit,
-                              tstack)
+from colour.utilities import (CaseInsensitiveMapping, as_float_array, ones,
+                              tsplit, tstack)
 
 __author__ = 'Colour Developers'
 __copyright__ = 'Copyright (C) 2013-2020 - Colour Developers'
@@ -492,7 +492,7 @@ def ellipse_fitting_Halir1998(a):
     # Quadratic part of the design matrix.
     D1 = tstack([x ** 2, x * y, y ** 2])
     # Linear part of the design matrix.
-    D2 = tstack([x, y, np.ones(x.shape)])
+    D2 = tstack([x, y, ones(x.shape)])
 
     D1_T = np.transpose(D1)
     D2_T = np.transpose(D2)

colour/appearance/cam16.py

@@ -38,7 +38,7 @@
     viewing_condition_dependent_parameters)
 from colour.utilities import (CaseInsensitiveMapping, as_float_array,
                               as_namedtuple, dot_vector, from_range_100,
-                              from_range_degrees, to_domain_100,
+                              from_range_degrees, ones, to_domain_100,
                               to_domain_degrees, tsplit)
 
 __author__ = 'Colour Developers'
@@ -244,7 +244,7 @@ def XYZ_to_CAM16(XYZ,
 
     # Computing degree of adaptation :math:`D`.
     D = (np.clip(degree_of_adaptation(surround.F, L_A), 0, 1)
-         if not discount_illuminant else np.ones(L_A.shape))
+         if not discount_illuminant else ones(L_A.shape))
 
     n, F_L, N_bb, N_cb, z = tsplit(
         viewing_condition_dependent_parameters(Y_b, Y_w, L_A))
@@ -419,7 +419,7 @@ def CAM16_to_XYZ(CAM16_specification,
 
     # Computing degree of adaptation :math:`D`.
     D = (np.clip(degree_of_adaptation(surround.F, L_A), 0, 1)
-         if not discount_illuminant else np.ones(L_A.shape))
+         if not discount_illuminant else ones(L_A.shape))
 
     n, F_L, N_bb, N_cb, z = tsplit(
         viewing_condition_dependent_parameters(Y_b, Y_w, L_A))

colour/appearance/ciecam02.py

@@ -38,8 +38,8 @@
 from colour.constants import EPSILON
 from colour.utilities import (
     CaseInsensitiveMapping, as_float_array, as_int_array, as_namedtuple,
-    as_float, from_range_degrees, dot_matrix, dot_vector, from_range_100,
-    to_domain_100, to_domain_degrees, tsplit, tstack)
+    as_float, from_range_degrees, dot_matrix, dot_vector, from_range_100, ones,
+    to_domain_100, to_domain_degrees, tsplit, tstack, zeros)
 
 __author__ = 'Colour Developers'
 __copyright__ = 'Copyright (C) 2013-2020 - Colour Developers'
@@ -265,7 +265,7 @@ def XYZ_to_CIECAM02(XYZ,
 
     # Computing degree of adaptation :math:`D`.
     D = (degree_of_adaptation(surround.F, L_A)
-         if not discount_illuminant else np.ones(L_A.shape))
+         if not discount_illuminant else ones(L_A.shape))
 
     # Computing full chromatic adaptation.
     RGB_c = full_chromatic_adaptation_forward(RGB, RGB_w, Y_w, D)
@@ -437,7 +437,7 @@ def CIECAM02_to_XYZ(CIECAM02_specification,
 
     # Computing degree of adaptation :math:`D`.
     D = (degree_of_adaptation(surround.F, L_A)
-         if not discount_illuminant else np.ones(L_A.shape))
+         if not discount_illuminant else ones(L_A.shape))
 
     # Computing full chromatic adaptation.
     RGB_wc = full_chromatic_adaptation_forward(RGB_w, RGB_w, Y_w, D)
@@ -900,8 +900,8 @@ def opponent_colour_dimensions_inverse(P_n, h):
     P_5 = P_1 / cos_hr
     n = P_2 * (2 + P_3) * (460 / 1403)
 
-    a = np.zeros(hr.shape)
-    b = np.zeros(hr.shape)
+    a = zeros(hr.shape)
+    b = zeros(hr.shape)
 
     b = np.where(
         np.isfinite(P_1) * np.abs(sin_hr) >= np.abs(cos_hr),
@@ -1456,7 +1456,7 @@ def P(N_c, N_cb, e_t, t, A, N_bb):
 
     P_1 = ((50000 / 13) * N_c * N_cb * e_t) / t
     P_2 = A / N_bb + 0.305
-    P_3 = np.ones(P_1.shape) * (21 / 20)
+    P_3 = ones(P_1.shape) * (21 / 20)
 
     P_n = tstack([P_1, P_2, P_3])
 

colour/appearance/hunt.py

@@ -24,9 +24,9 @@
 from collections import namedtuple
 
 from colour.algebra import spow
-from colour.utilities import (CaseInsensitiveMapping, as_float_array,
-                              dot_vector, from_range_degrees, to_domain_100,
-                              tsplit, tstack, usage_warning)
+from colour.utilities import (
+    CaseInsensitiveMapping, as_float_array, dot_vector, from_range_degrees,
+    ones, to_domain_100, tsplit, tstack, usage_warning, zeros)
 
 __author__ = 'Colour Developers'
 __copyright__ = 'Copyright (C) 2013-2020 - Colour Developers'
@@ -325,7 +325,7 @@ def XYZ_to_Hunt(XYZ,
     >>> XYZ_b = np.array([95.05, 100.00, 108.88])
     >>> L_A = 318.31
     >>> surround = HUNT_VIEWING_CONDITIONS['Normal Scenes']
-    >>> CCT_w = 6504.0
+    >>> CCT_w = 6504
     >>> XYZ_to_Hunt(XYZ, XYZ_w, XYZ_b, L_A, surround, CCT_w=CCT_w)
     ... # doctest: +ELLIPSIS
     Hunt_Specification(J=30.0462678..., C=0.1210508..., h=269.2737594..., \
@@ -662,14 +662,14 @@ def chromatic_adaptation(XYZ,
         L_A_p = spow(L_A, 1 / 3)
         F_rgb = ((1 + L_A_p + h_rgb) / (1 + L_A_p + (1 / h_rgb)))
     else:
-        F_rgb = np.ones(h_rgb.shape)
+        F_rgb = ones(h_rgb.shape)
 
     # Computing Helson-Judd effect parameters.
     if helson_judd_effect:
         D_rgb = (f_n((Y_b / Y_w) * F_L * F_rgb[..., 1]) - f_n(
             (Y_b / Y_w) * F_L * F_rgb))
     else:
-        D_rgb = np.zeros(F_rgb.shape)
+        D_rgb = zeros(F_rgb.shape)
 
     # Computing cone bleach factors.
     B_rgb = (10 ** 7) / ((10 ** 7) + 5 * L_A[..., np.newaxis] * (rgb_w / 100))

colour/characterisation/correction.py

@@ -63,7 +63,7 @@
 
 from colour.algebra import least_square_mapping_MoorePenrose
 from colour.utilities import (CaseInsensitiveMapping, as_float_array, as_int,
-                              closest, filter_kwargs, tsplit, tstack)
+                              closest, filter_kwargs, ones, tsplit, tstack)
 
 __author__ = 'Colour Developers'
 __copyright__ = 'Copyright (C) 2013-2020 - Colour Developers'
@@ -119,7 +119,7 @@ def augmented_matrix_Cheung2004(RGB, terms=3):
     """
 
     R, G, B = tsplit(RGB)
-    ones = np.ones(R.shape)
+    tail = ones(R.shape)
 
     existing_terms = np.array([3, 5, 7, 8, 10, 11, 14, 16, 17, 19, 20, 22])
     closest_terms = as_int(closest(existing_terms, terms))
@@ -132,23 +132,23 @@ def augmented_matrix_Cheung2004(RGB, terms=3):
     if terms == 3:
         return RGB
     elif terms == 5:
-        return tstack([R, G, B, R * G * B, ones])
+        return tstack([R, G, B, R * G * B, tail])
     elif terms == 7:
-        return tstack([R, G, B, R * G, R * B, G * B, ones])
+        return tstack([R, G, B, R * G, R * B, G * B, tail])
     elif terms == 8:
-        return tstack([R, G, B, R * G, R * B, G * B, R * G * B, ones])
+        return tstack([R, G, B, R * G, R * B, G * B, R * G * B, tail])
     elif terms == 10:
         return tstack(
-            [R, G, B, R * G, R * B, G * B, R ** 2, G ** 2, B ** 2, ones])
+            [R, G, B, R * G, R * B, G * B, R ** 2, G ** 2, B ** 2, tail])
     elif terms == 11:
         return tstack([
             R, G, B, R * G, R * B, G * B, R ** 2, G ** 2, B ** 2, R * G * B,
-            ones
+            tail
         ])
     elif terms == 14:
         return tstack([
             R, G, B, R * G, R * B, G * B, R ** 2, G ** 2, B ** 2, R * G * B, R
-            ** 3, G ** 3, B ** 3, ones
+            ** 3, G ** 3, B ** 3, tail
         ])
     elif terms == 16:
         return tstack([
@@ -158,7 +158,7 @@ def augmented_matrix_Cheung2004(RGB, terms=3):
     elif terms == 17:
         return tstack([
             R, G, B, R * G, R * B, G * B, R ** 2, G ** 2, B ** 2, R * G * B,
-            R ** 2 * G, G ** 2 * B, B ** 2 * R, R ** 3, G ** 3, B ** 3, ones
+            R ** 2 * G, G ** 2 * B, B ** 2 * R, R ** 3, G ** 3, B ** 3, tail
         ])
     elif terms == 19:
         return tstack([
@@ -170,7 +170,7 @@ def augmented_matrix_Cheung2004(RGB, terms=3):
         return tstack([
             R, G, B, R * G, R * B, G * B, R ** 2, G ** 2, B ** 2, R * G * B,
             R ** 2 * G, G ** 2 * B, B ** 2 * R, R ** 2 * B, G ** 2 * R,
-            B ** 2 * G, R ** 3, G ** 3, B ** 3, ones
+            B ** 2 * G, R ** 3, G ** 3, B ** 3, tail
         ])
     elif terms == 22:
         return tstack([

colour/colorimetry/generation.py

@@ -36,7 +36,7 @@
 
 from colour.constants import DEFAULT_FLOAT_DTYPE
 from colour.colorimetry import (DEFAULT_SPECTRAL_SHAPE, SpectralDistribution)
-from colour.utilities import CaseInsensitiveMapping, as_float_array
+from colour.utilities import CaseInsensitiveMapping, as_float_array, full, ones
 
 __author__ = 'Colour Developers'
 __copyright__ = 'Copyright (C) 2013-2020 - Colour Developers'
@@ -90,7 +90,7 @@ def sd_constant(k, shape=DEFAULT_SPECTRAL_SHAPE, dtype=None):
         dtype = DEFAULT_FLOAT_DTYPE
 
     wavelengths = shape.range(dtype)
-    values = np.full(len(wavelengths), k, dtype)
+    values = full(len(wavelengths), k, dtype)
 
     name = '{0} Constant'.format(k)
     return SpectralDistribution(values, wavelengths, name=name, dtype=dtype)
@@ -485,7 +485,7 @@ def sd_multi_leds_Ohno2005(peak_wavelengths,
     peak_wavelengths = as_float_array(peak_wavelengths)
     fwhm = np.resize(fwhm, peak_wavelengths.shape)
     if peak_power_ratios is None:
-        peak_power_ratios = np.ones(peak_wavelengths.shape)
+        peak_power_ratios = ones(peak_wavelengths.shape)
     else:
         peak_power_ratios = np.resize(peak_power_ratios,
                                       peak_wavelengths.shape)

colour/colorimetry/photometry.py

@@ -20,6 +20,7 @@
 
 from colour.colorimetry import PHOTOPIC_LEFS
 from colour.constants import K_M
+from colour.utilities import as_float
 
 __author__ = 'Colour Developers'
 __copyright__ = 'Copyright (C) 2013-2020 - Colour Developers'
@@ -75,7 +76,7 @@ def luminous_flux(sd,
 
     flux = K_m * np.trapz(sd.values, sd.wavelengths)
 
-    return flux
+    return as_float(flux)
 
 
 def luminous_efficiency(
@@ -155,4 +156,4 @@ def luminous_efficacy(
 
     efficacy = K_M * luminous_efficiency(sd, lef)
 
-    return efficacy
+    return as_float(efficacy)

colour/colorimetry/tristimulus.py

@@ -498,6 +498,7 @@ def sd_to_XYZ_integration(
     S = illuminant.values
     x_bar, y_bar, z_bar = tsplit(cmfs.values)
     R = sd.values
+
     dw = cmfs.shape.interval
 
     k = 100 / (np.sum(y_bar * S) * dw) if k is None else k

colour/constants/common.py

@@ -8,6 +8,7 @@
 
 from __future__ import division, unicode_literals
 
+import os
 import numpy as np
 
 from colour.utilities.documentation import DocstringFloat
@@ -46,14 +47,16 @@
 EPSILON : numeric
 """
 
-DEFAULT_FLOAT_DTYPE = np.float_
+DEFAULT_FLOAT_DTYPE = np.sctypeDict.get(
+    os.environ.get('COLOUR_SCIENCE__FLOAT_PRECISION', 'float64'), 'float64')
 """
 Default floating point number dtype.
 
 DEFAULT_FLOAT_DTYPE : type
 """
 
-DEFAULT_INT_DTYPE = np.int_
+DEFAULT_INT_DTYPE = np.sctypeDict.get(
+    os.environ.get('COLOUR_SCIENCE__INT_PRECISION', 'int64'), 'int64')
 """
 Default integer number dtype.
 

colour/continuous/multi_signals.py

@@ -1318,10 +1318,6 @@ def multi_signals_unpack_data(data=None,
         if dtype is None:
             dtype = DEFAULT_FLOAT_DTYPE
 
-        assert dtype in np.sctypes['float'], (
-            '"dtype" must be one of the following types: {0}'.format(
-                np.sctypes['float']))
-
         domain_u, range_u, signals = None, None, None
         signals = OrderedDict()
         # TODO: Implement support for Signal class passing.