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+# coding=utf-8
+#
+# Copyright © 2011 Intel Corporation
+#
+# Permission is hereby granted, free of charge, to any person obtaining a
+# copy of this software and associated documentation files (the "Software"),
+# to deal in the Software without restriction, including without limitation
+# the rights to use, copy, modify, merge, publish, distribute, sublicense,
+# and/or sell copies of the Software, and to permit persons to whom the
+# Software is furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice (including the next
+# paragraph) shall be included in all copies or substantial portions of the
+# Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
+# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
+# DEALINGS IN THE SOFTWARE.
+
+# This source file defines a set of test vectors that can be used to
+# test GLSL's built-in functions. It is intended to be used by
+# Python code that generates Piglit tests.
+#
+# The key export is the dictionary test_suite. It contains an entry
+# for each possible overload of every pure built-in function. By
+# iterating through this dictionary you can find a set of test vectors
+# for testing nearly every built-in GLSL function. Notable exceptions
+# include the fragment shader functions dFdx(), dFdy(), and fwidth(),
+# the texture lookup functions, and the ftransform() function, since
+# they are not pure, so they can't be tested using simple test
+# vectors.
+
+import collections
+import itertools
+import numpy as np
+
+
+
+class GlslBuiltinType(object):
+ """Class representing a GLSL built-in type."""
+ def __init__(self, name, base_type, num_cols, num_rows,
+ version_introduced):
+ self.__name = name
+ if base_type is not None:
+ self.__base_type = base_type
+ else:
+ self.__base_type = self
+ self.__num_cols = num_cols
+ self.__num_rows = num_rows
+ self.__version_introduced = version_introduced
+
+ @property
+ def name(self):
+ """The name of the type, as a string."""
+ return self.__name
+
+ @property
+ def base_type(self):
+ """For vectors and matrices, the type of data stored in each
+ element. For scalars, equal to self.
+ """
+ return self.__base_type
+
+ @property
+ def num_cols(self):
+ """For matrices, the number of columns. For vectors and
+ scalars, 1.
+ """
+ return self.__num_cols
+
+ @property
+ def num_rows(self):
+ """For vectors and matrices, the number of rows. For scalars,
+ 1.
+ """
+ return self.__num_rows
+
+ @property
+ def is_scalar(self):
+ return self.__num_cols == 1 and self.__num_rows == 1
+
+ @property
+ def is_vector(self):
+ return self.__num_cols == 1 and self.__num_rows != 1
+
+ @property
+ def is_matrix(self):
+ return self.__num_cols != 1
+
+ @property
+ def version_introduced(self):
+ """The earliest version of GLSL that this type appears in (as
+ a string, e.g. '1.10').
+ """
+ return self.__version_introduced
+
+ def __str__(self):
+ return self.__name
+
+ def __repr__(self):
+ return 'glsl_{0}'.format(self.__name)
+
+
+
+# Concrete declarations of GlslBuiltinType
+glsl_bool = GlslBuiltinType('bool', None, 1, 1, '1.10')
+glsl_int = GlslBuiltinType('int', None, 1, 1, '1.10')
+glsl_float = GlslBuiltinType('float', None, 1, 1, '1.10')
+glsl_vec2 = GlslBuiltinType('vec2', glsl_float, 1, 2, '1.10')
+glsl_vec3 = GlslBuiltinType('vec3', glsl_float, 1, 3, '1.10')
+glsl_vec4 = GlslBuiltinType('vec4', glsl_float, 1, 4, '1.10')
+glsl_bvec2 = GlslBuiltinType('bvec2', glsl_bool, 1, 2, '1.10')
+glsl_bvec3 = GlslBuiltinType('bvec3', glsl_bool, 1, 3, '1.10')
+glsl_bvec4 = GlslBuiltinType('bvec4', glsl_bool, 1, 4, '1.10')
+glsl_ivec2 = GlslBuiltinType('ivec2', glsl_int, 1, 2, '1.10')
+glsl_ivec3 = GlslBuiltinType('ivec3', glsl_int, 1, 3, '1.10')
+glsl_ivec4 = GlslBuiltinType('ivec4', glsl_int, 1, 4, '1.10')
+glsl_mat2 = GlslBuiltinType('mat2', glsl_float, 2, 2, '1.10')
+glsl_mat3 = GlslBuiltinType('mat3', glsl_float, 3, 3, '1.10')
+glsl_mat4 = GlslBuiltinType('mat4', glsl_float, 4, 4, '1.10')
+glsl_mat2x2 = glsl_mat2
+glsl_mat3x2 = GlslBuiltinType('mat3x2', glsl_float, 3, 2, '1.20')
+glsl_mat4x2 = GlslBuiltinType('mat4x2', glsl_float, 4, 2, '1.20')
+glsl_mat2x3 = GlslBuiltinType('mat2x3', glsl_float, 2, 3, '1.20')
+glsl_mat3x3 = glsl_mat3
+glsl_mat4x3 = GlslBuiltinType('mat4x3', glsl_float, 4, 3, '1.20')
+glsl_mat2x4 = GlslBuiltinType('mat2x4', glsl_float, 2, 4, '1.20')
+glsl_mat3x4 = GlslBuiltinType('mat3x4', glsl_float, 3, 4, '1.20')
+glsl_mat4x4 = glsl_mat4
+
+
+
+# Named tuple representing the signature of a single overload of a
+# built-in GLSL function:
+# - name is the function name.
+# - version_introduced earliest version of GLSL the test applies to
+# (as a string, e.g. '1.10').
+# - rettype is the return type of the function (as a GlslBuiltinType).
+# - argtypes is a tuple containing the types of each function
+# parameter (as GlslBuiltinTypes).
+#
+# For example, the function
+#
+# vec3 step(float edge, vec3 x)
+#
+# has a signature of
+#
+# Signature(name='step', version_introduced='1.10', rettype='vec3',
+# argtypes=('float', 'vec3'))
+Signature = collections.namedtuple(
+ 'Signature', ('name', 'version_introduced', 'rettype', 'argtypes'))
+
+
+
+# Named tuple representing a single piece of test data for testing a
+# built-in GLSL function:
+# - arguments is a tuple containing the arguments to apply to the
+# function. Each argument is of a type native to numpy (e.g.
+# numpy.float64 or numpy.ndarray)
+# - result is the value the function is expected to return. It is
+# also of a type native to numpy.
+TestVector = collections.namedtuple('TestVector', ('arguments', 'result'))
+
+
+
+def glsl_type_of(value):
+ """Return the GLSL type corresponding to the given native numpy
+ value, as a GlslBuiltinType.
+ """
+ if isinstance(value, float):
+ return glsl_float
+ elif isinstance(value, (bool, np.bool_)):
+ return glsl_bool
+ elif isinstance(value, (int, long)):
+ return glsl_int
+ else:
+ assert isinstance(value, np.ndarray)
+ if len(value.shape) == 1:
+ # Vector
+ vector_length = value.shape[0]
+ assert 2 <= vector_length <= 4
+ if value.dtype == float:
+ return (glsl_vec2, glsl_vec3, glsl_vec4)[vector_length - 2]
+ elif value.dtype == bool:
+ return (glsl_bvec2, glsl_bvec3, glsl_bvec4)[vector_length - 2]
+ elif value.dtype == int:
+ return (glsl_ivec2, glsl_ivec3, glsl_ivec4)[vector_length - 2]
+ else:
+ raise Exception(
+ 'Unexpected vector base type {0}'.format(value.dtype))
+ else:
+ # Matrix
+ assert value.dtype == float
+ assert len(value.shape) == 2
+ matrix_rows = value.shape[0]
+ assert 2 <= matrix_rows <= 4
+ matrix_columns = value.shape[1]
+ assert 2 <= matrix_columns <= 4
+ matrix_types = ((glsl_mat2x2, glsl_mat2x3, glsl_mat2x4),
+ (glsl_mat3x2, glsl_mat3x3, glsl_mat3x4),
+ (glsl_mat4x2, glsl_mat4x3, glsl_mat4x4))
+ return matrix_types[matrix_columns - 2][matrix_rows - 2]
+
+
+
+def column_major_values(value):
+ """Given a native numpy value, return a list of the scalar values
+ comprising it, in column-major order."""
+ return np.reshape(np.array(value), -1, 'F').tolist()
+
+
+
+def glsl_constant(value):
+ """Given a native numpy value, return GLSL code that constructs
+ it."""
+ column_major = np.reshape(np.array(value), -1, 'F')
+ if column_major.dtype == bool:
+ values = ['true' if x else 'false' for x in column_major]
+ else:
+ values = [str(x) for x in column_major]
+ if len(column_major) == 1:
+ return values[0]
+ else:
+ return '{0}({1})'.format(glsl_type_of(value), ', '.join(values))
+
+
+
+# Dictionary containing the test vectors. Each entry in the
+# dictionary represents a single overload of a single built-in
+# function. Its key is a Signature tuple, and its value is a list of
+# TestVector tuples.
+#
+# Note: the dictionary is initialized to {} here, but it is filled
+# with test vectors by code later in this file.
+test_suite = {}
+
+
+
+# Implementation
+# ==============
+#
+# The functions below shouldn't be necessary to call from outside this
+# file. They exist solely to populate test_suite with test vectors.
+
+# Functions that simulate GLSL built-in functions (in the cases where
+# the GLSL built-in functions have no python or numpy equivalent, or
+# in cases where there is a behavioral difference). These functions
+# return None if the behavior of the GLSL built-in is undefined for
+# the given set of inputs.
+def _arctan2(y, x):
+ if x == y == 0.0:
+ return None
+ return np.arctan2(y, x)
+def _pow(x, y):
+ if x < 0.0:
+ return None
+ if x == 0.0 and y <= 0.0:
+ return None
+ return np.power(x, y)
+def _clamp(x, minVal, maxVal):
+ if minVal > maxVal:
+ return None
+ return min(max(x, minVal), maxVal)
+def _smoothstep(edge0, edge1, x):
+ if edge0 >= edge1:
+ return None
+ t = _clamp((x-edge0)/(edge1-edge0),0.0,1.0)
+ return t*t*(3.0-2.0*t)
+def _normalize(x):
+ return x/np.linalg.norm(x)
+def _faceforward(N, I, Nref):
+ if np.dot(Nref, I) < 0.0:
+ return N
+ else:
+ return -N
+def _reflect(I, N):
+ return I-2*np.dot(N,I)*N
+def _refract(I, N, eta):
+ k = 1.0-eta*eta*(1.0-np.dot(N,I)*np.dot(N,I))
+ if k < 0.0:
+ return I*0.0
+ else:
+ return eta*I-(eta*np.dot(N,I)+np.sqrt(k))*N
+
+
+
+def _argument_types_match(arguments, argument_indices_to_match):
+ """Return True if all of the arguments indexed by
+ argument_indices_to_match have the same GLSL type.
+ """
+ types = [glsl_type_of(arguments[i]) for i in argument_indices_to_match]
+ return all(x == types[0] for x in types)
+
+
+
+def _simulate_function(test_inputs, python_equivalent):
+ """Construct test vectors by simulating a GLSL function on a list
+ of possible inputs.
+
+ test_inputs is a list of possible input sequences, each of which
+ represents a set of arguments that should be applied to the
+ function.
+
+ python_equivalent is the function to simulate--it should return
+ None if the GLSL function returns undefined results for the given
+ set of inputs, otherwise it should return the expected result.
+ Input sequences for which python_equivalent returns None are
+ ignored."""
+ test_vectors = []
+ for inputs in test_inputs:
+ expected_output = python_equivalent(*inputs)
+ if expected_output is not None:
+ test_vectors.append(TestVector(inputs, expected_output))
+ return test_vectors
+
+
+
+def _vectorize_test_vectors(test_vectors, scalar_arg_indices, vector_length):
+ """Build a new set of test vectors by combining elements of
+ test_vectors into vectors of length vector_length. For example,
+ vectorizing the test vectors
+
+ [TestVector((10, 20), 30), TestVector((11, 20), 31)]
+
+ into vectors of length 2 would produce the result:
+
+ [TestVector((vec2(10, 11), vec2(20, 20)), vec2(30, 31))].
+
+ scalar_arg_indices is a sequence of argument indices which should
+ not be vectorized. So, if scalar_arg_indices is [1] in the above
+ example, the result would be:
+
+ [TestVector((vec2(10, 11), 20), vec2(30, 31))].
+ """
+ def make_groups(test_vectors):
+ """Group test vectors according to the values passed to the
+ arguments that should not be vectorized.
+ """
+ groups = {}
+ for tv in test_vectors:
+ key = tuple(tv.arguments[i] for i in scalar_arg_indices)
+ if key not in groups:
+ groups[key] = []
+ groups[key].append(tv)
+ return groups
+ def partition_vectors(test_vectors, partition_size):
+ """Partition test_vectors into lists of length partition_size.
+ If partition_size does not evenly divide the number of test
+ vectors, wrap around as necessary to ensure that every input
+ test vector is included.
+ """
+ for i in xrange(0, len(test_vectors), partition_size):
+ partition = []
+ for j in xrange(partition_size):
+ partition.append(test_vectors[(i + j) % len(test_vectors)])
+ yield partition
+ def merge_vectors(test_vectors):
+ """Merge the given set of test vectors (whose arguments and
+ result are scalars) into a single test vector whose arguments
+ and result are vectors. For argument indices in
+ scalar_arg_indices, leave the argument as a scalar.
+ """
+ arity = len(test_vectors[0].arguments)
+ arguments = []
+ for j in xrange(arity):
+ if j in scalar_arg_indices:
+ arguments.append(test_vectors[0].arguments[j])
+ else:
+ arguments.append(
+ np.array([tv.arguments[j] for tv in test_vectors]))
+ result = np.array([tv.result for tv in test_vectors])
+ return TestVector(arguments, result)
+ vectorized_test_vectors = []
+ groups = make_groups(test_vectors)
+ for key in sorted(groups.keys()):
+ test_vectors = groups[key]
+ vectorized_test_vectors.extend(
+ merge_vectors(partition)
+ for partition in partition_vectors(test_vectors, vector_length))
+ return vectorized_test_vectors
+
+
+
+def _store_test_vector(test_suite_dict, name, glsl_version, test_vector):
+ """Store a test vector in the appropriate place in
+ test_suite_dict. The dictionary key (which is a Signature tuple)
+ is generated by consulting the argument and return types of the
+ test vector, and combining them with name and glsl_version.
+
+ glsl_version is adjusted if necessary to reflect when the argument
+ and return types were introduced into GLSL.
+ """
+ rettype = glsl_type_of(test_vector.result)
+ argtypes = tuple(glsl_type_of(arg) for arg in test_vector.arguments)
+ adjusted_glsl_version = max(
+ glsl_version, rettype.version_introduced,
+ *[t.version_introduced for t in argtypes])
+ signature = Signature(name, adjusted_glsl_version, rettype, argtypes)
+ if signature not in test_suite_dict:
+ test_suite_dict[signature] = []
+ test_suite_dict[signature].append(test_vector)
+
+
+
+def _store_test_vectors(test_suite_dict, name, glsl_version, test_vectors):
+ """Store multiple test vectors in the appropriate places in
+ test_suite_dict.
+ """
+ for test_vector in test_vectors:
+ _store_test_vector(test_suite_dict, name, glsl_version, test_vector)
+
+
+
+def _make_componentwise_test_vectors(test_suite_dict):
+ """Add test vectors to test_suite_dict for GLSL built-in
+ functions that operate on vectors in componentwise fashion.
+ Examples include sin(), cos(), min(), max(), and clamp().
+ """
+ def f(name, arity, glsl_version, python_equivalent,
+ alternate_scalar_arg_indices, test_inputs):
+ """Create test vectors for the function with the given name
+ and arity, which was introduced in the given glsl_version.
+
+ python_equivalent is a Python function which operates on scalars,
+ and simulates the GLSL function. This function should return None
+ in any case where the output of the GLSL function is undefined.
+
+ If alternate_scalar_arg_indices is not None, also create test
+ vectors for an alternate vectorized version of the function,
+ in which some arguments are scalars.
+ alternate_scalar_arg_indices is a sequence of the indices of
+ the arguments which are scalars.
+
+ test_inputs is a list, the ith element of which is a list of
+ values that are suitable for use as the ith argument of the
+ function.
+ """
+ scalar_test_vectors = _simulate_function(
+ itertools.product(*test_inputs), python_equivalent)
+ _store_test_vectors(
+ test_suite_dict, name, glsl_version, scalar_test_vectors)
+ if alternate_scalar_arg_indices is None:
+ scalar_arg_indices_list = [()]
+ else:
+ scalar_arg_indices_list = [(), alternate_scalar_arg_indices]
+ for scalar_arg_indices in scalar_arg_indices_list:
+ for vector_length in (2, 3, 4):
+ _store_test_vectors(
+ test_suite_dict, name, glsl_version,
+ _vectorize_test_vectors(
+ scalar_test_vectors, scalar_arg_indices,
+ vector_length))
+ f('radians', 1, '1.10', np.radians, None, [np.linspace(-180.0, 180.0, 4)])
+ f('degrees', 1, '1.10', np.degrees, None, [np.linspace(-np.pi, np.pi, 4)])
+ f('sin', 1, '1.10', np.sin, None, [np.linspace(-np.pi, np.pi, 4)])
+ f('cos', 1, '1.10', np.cos, None, [np.linspace(-np.pi, np.pi, 4)])
+ f('tan', 1, '1.10', np.tan, None, [np.linspace(-np.pi, np.pi, 4)])
+ f('asin', 1, '1.10', np.arcsin, None, [np.linspace(-1.0, 1.0, 4)])
+ f('acos', 1, '1.10', np.arccos, None, [np.linspace(-1.0, 1.0, 4)])
+ f('atan', 1, '1.10', np.arctan, None, [np.linspace(-2.0, 2.0, 4)])
+ f('atan', 2, '1.10', _arctan2, None, [np.linspace(-2.0, 2.0, 3), np.linspace(-2.0, 2.0, 3)])
+ f('pow', 2, '1.10', _pow, None, [np.linspace(0.0, 2.0, 4), np.linspace(-2.0, 2.0, 4)])
+ f('exp', 1, '1.10', np.exp, None, [np.linspace(-2.0, 2.0, 4)])
+ f('log', 1, '1.10', np.log, None, [np.linspace(0.01, 2.0, 4)])
+ f('exp2', 1, '1.10', np.exp2, None, [np.linspace(-2.0, 2.0, 4)])
+ f('log2', 1, '1.10', np.log2, None, [np.linspace(0.01, 2.0, 4)])
+ f('sqrt', 1, '1.10', np.sqrt, None, [np.linspace(0.0, 2.0, 4)])
+ f('inversesqrt', 1, '1.10', lambda x: 1.0/np.sqrt(x), None, [np.linspace(0.1, 2.0, 4)])
+ f('abs', 1, '1.10', np.abs, None, [np.linspace(-1.5, 1.5, 5)])
+ f('sign', 1, '1.10', np.sign, None, [np.linspace(-1.5, 1.5, 5)])
+ f('floor', 1, '1.10', np.floor, None, [np.linspace(-2.0, 2.0, 4)])
+ f('ceil', 1, '1.10', np.ceil, None, [np.linspace(-2.0, 2.0, 4)])
+ f('fract', 1, '1.10', lambda x: x-np.floor(x), None, [np.linspace(-2.0, 2.0, 4)])
+ f('mod', 2, '1.10', lambda x, y: x-y*np.floor(x/y), [1], [np.linspace(-1.9, 1.9, 4), np.linspace(-2.0, 2.0, 4)])
+ f('min', 2, '1.10', min, [1], [np.linspace(-2.0, 2.0, 4), np.linspace(-2.0, 2.0, 4)])
+ f('max', 2, '1.10', max, [1], [np.linspace(-2.0, 2.0, 4), np.linspace(-2.0, 2.0, 4)])
+ f('clamp', 3, '1.10', _clamp, [1, 2], [np.linspace(-2.0, 2.0, 4), np.linspace(-1.5, 1.5, 3), np.linspace(-1.5, 1.5, 3)])
+ f('mix', 3, '1.10', lambda x, y, a: x*(1-a)+y*a, [2], [np.linspace(-2.0, 2.0, 2), np.linspace(-3.0, 3.0, 2), np.linspace(0.0, 1.0, 4)])
+ f('step', 2, '1.10', lambda edge, x: 0.0 if x < edge else 1.0, [0], [np.linspace(-2.0, 2.0, 4), np.linspace(-2.0, 2.0, 4)])
+ f('smoothstep', 3, '1.10', _smoothstep, [0, 1], [np.linspace(-1.9, 1.9, 4), np.linspace(-1.9, 1.9, 4), np.linspace(-2.0, 2.0, 4)])
+_make_componentwise_test_vectors(test_suite)
+
+
+
+def _make_vector_relational_test_vectors(test_suite_dict):
+ """Add test vectors to test_suite_dict for GLSL built-in functions
+ that operate on vectors of floats, ints, or bools, but not on
+ single floats, ints, or bools. Examples include lessThan(),
+ equal(), and not().
+ """
+ _default_inputs = {
+ 'v': np.linspace(-1.5, 1.5, 4),
+ 'i': np.array([1, 2, 3, 4]),
+ 'b': np.array([False, True])
+ }
+ def f(name, arity, glsl_version, python_equivalent, arg_types):
+ """Make test vectors for the function with the given name and
+ arity, which was introduced in the given glsl_version.
+
+ python_equivalent is a Python function which operates on scalars,
+ and simulates the GLSL function.
+
+ arg_types is a string containing 'v' if the function supports
+ standard "vec" inputs, 'i' if it supports "ivec" inputs, and 'b'
+ if it supports "bvec" inputs. The output type of the function is
+ assumed to be the same as its input type.
+ """
+ for arg_type in arg_types:
+ test_inputs = [_default_inputs[arg_type]]*arity
+ scalar_test_vectors = _simulate_function(
+ itertools.product(*test_inputs), python_equivalent)
+ for vector_length in (2, 3, 4):
+ _store_test_vectors(
+ test_suite_dict, name, glsl_version,
+ _vectorize_test_vectors(
+ scalar_test_vectors, (), vector_length))
+ f('lessThan', 2, '1.10', lambda x, y: x < y, 'vi')
+ f('lessThanEqual', 2, '1.10', lambda x, y: x <= y, 'vi')
+ f('greaterThan', 2, '1.10', lambda x, y: x > y, 'vi')
+ f('greaterThanEqual', 2, '1.10', lambda x, y: x >= y, 'vi')
+ f('equal', 2, '1.10', lambda x, y: x == y, 'vib')
+ f('not', 1, '1.10', lambda x: not x, 'b')
+_make_vector_relational_test_vectors(test_suite)
+
+
+
+def _make_vector_or_matrix_test_vectors(test_suite_dict):
+ """Add test vectors to test_suite_dict for GLSL built-in functions
+ that operate on vectors/matrices as a whole. Examples include
+ length(), dot(), cross(), normalize(), and refract().
+ """
+ _std_vectors = [
+ -1.33,
+ 0.85,
+ np.array([-0.10, -1.20]),
+ np.array([-0.42, 0.48]),
+ np.array([-0.03, -0.85, -0.94]),
+ np.array([1.67, 0.66, 1.87]),
+ np.array([-1.65, 1.33, 1.93, 0.76]),
+ np.array([0.80, -0.15, -0.51, 0.0])
+ ]
+ _std_vectors3 = [
+ np.array([-0.03, -0.85, -0.94]),
+ np.array([1.67, 0.66, 1.87]),
+ ]
+ _normalized_vectors = [_normalize(x) for x in _std_vectors]
+ _nontrivial_vectors = [x for x in _std_vectors if not isinstance(x, float)]
+ _std_matrices = [
+ np.array([[ 1.60, 0.76],
+ [ 1.53, -1.00]]), # mat2
+ np.array([[-0.13, -0.87],
+ [-1.40, 1.40]]), # mat2
+ np.array([[-1.11, 1.67, -0.41],
+ [ 0.13, 1.09, -0.02],
+ [ 0.56, 0.95, 0.24]]), # mat3
+ np.array([[-1.69, -0.46, -0.18],
+ [-1.09, 1.75, 2.00],
+ [-1.53, -0.70, -1.47]]), # mat3
+ np.array([[-1.00, -0.55, -1.08, 1.79],
+ [ 1.77, 0.62, 0.48, -1.35],
+ [ 0.09, -0.71, -1.39, -1.21],
+ [-0.91, -1.82, -1.43, 0.72]]), # mat4
+ np.array([[ 0.06, 1.31, 1.52, -1.96],
+ [ 1.60, -0.32, 0.51, -1.84],
+ [ 1.25, 0.45, 1.90, -0.72],
+ [-0.16, 0.45, -0.88, 0.39]]), # mat4
+ np.array([[ 0.09, 1.30, 1.25],
+ [-1.19, 0.08, 1.08]]), # mat3x2
+ np.array([[-0.36, -1.08, -0.60],
+ [-0.53, 0.88, -1.79]]), # mat3x2
+ np.array([[-0.46, 1.94],
+ [-0.45, -0.75],
+ [ 1.03, -0.50]]), # mat2x3
+ np.array([[ 1.38, -1.08],
+ [-1.27, 1.83],
+ [ 1.00, -0.74]]), # mat2x3
+ np.array([[ 1.81, -0.87, 0.81, 0.65],
+ [-1.16, -1.52, 0.25, -1.51]]), # mat4x2
+ np.array([[ 1.93, -1.63, 0.29, 1.60],
+ [ 0.49, 0.27, 0.14, 0.94]]), # mat4x2
+ np.array([[ 0.16, -1.69],
+ [-0.80, 0.59],
+ [-1.74, -1.43],
+ [-0.02, -1.21]]), # mat2x4
+ np.array([[-1.02, 0.74],
+ [-1.64, -0.13],
+ [-1.59, 0.47],
+ [ 0.30, 1.13]]), # mat2x4
+ np.array([[-0.27, -1.38, -1.41, -0.12],
+ [-0.17, -0.56, 1.47, 1.86],
+ [-1.85, -1.29, 1.77, 0.01]]), # mat4x3
+ np.array([[-0.47, -0.15, 1.97, -1.05],
+ [-0.20, 0.53, -1.82, -1.41],
+ [-1.39, -0.19, 1.62, 1.58]]), # mat4x3
+ np.array([[ 1.42, -0.86, 0.27],
+ [ 1.80, -1.74, 0.04],
+ [-1.88, -0.37, 0.43],
+ [ 1.37, 1.90, 0.71]]), # mat3x4
+ np.array([[-1.72, 0.09, 0.45],
+ [-0.31, -1.58, 1.92],
+ [ 0.14, 0.18, -0.56],
+ [ 0.40, -0.77, 1.76]]), # mat3x4
+ ]
+ _ft = [False, True]
+ _bvecs = [np.array(bs) for bs in itertools.product(_ft, _ft)] + \
+ [np.array(bs) for bs in itertools.product(_ft, _ft, _ft)] + \
+ [np.array(bs) for bs in itertools.product(_ft, _ft, _ft, _ft)]
+ def f(name, arity, glsl_version, python_equivalent,
+ argument_indices_to_match, test_inputs):
+ """Make test vectors for the function with the given name and
+ arity, which was introduced in the given glsl_version.
+
+ python_equivalent is a Python function which simulates the GLSL
+ function. This function should return None in any case where the
+ output of the GLSL function is undefined. However, it need not
+ check that the lengths of the input vectors are all the same.
+
+ If argument_indices_to_match is not None, it is a sequence of
+ argument indices indicating which arguments of the function
+ need to have matching types.
+
+ test_inputs is a list, the ith element of which is a list of
+ vectors and/or scalars that are suitable for use as the ith
+ argument of the function.
+ """
+ test_inputs = itertools.product(*test_inputs)
+ if argument_indices_to_match is not None:
+ test_inputs = [
+ arguments
+ for arguments in test_inputs
+ if _argument_types_match(arguments, argument_indices_to_match)]
+ _store_test_vectors(
+ test_suite_dict, name, glsl_version,
+ _simulate_function(test_inputs, python_equivalent))
+ f('length', 1, '1.10', np.linalg.norm, None, [_std_vectors])
+ f('distance', 2, '1.10', lambda x, y: np.linalg.norm(x-y), [0, 1], [_std_vectors, _std_vectors])
+ f('dot', 2, '1.10', np.dot, [0, 1], [_std_vectors, _std_vectors])
+ f('cross', 2, '1.10', np.cross, [0, 1], [_std_vectors3, _std_vectors3])
+ f('normalize', 1, '1.10', _normalize, None, [_std_vectors])
+ f('faceforward', 3, '1.10', _faceforward, [0, 1, 2], [_std_vectors, _std_vectors, _std_vectors])
+ f('reflect', 2, '1.10', _reflect, [0, 1], [_std_vectors, _normalized_vectors])
+ f('refract', 3, '1.10', _refract, [0, 1], [_normalized_vectors, _normalized_vectors, [0.5, 2.0]])
+
+ # Note: technically matrixCompMult operates componentwise.
+ # However, since it is the only componentwise function to operate
+ # on matrices, it is easier to generate test cases for it here
+ # than to add matrix support to _make_componentwise_test_vectors.
+ f('matrixCompMult', 2, '1.10', lambda x, y: x*y, [0, 1], [_std_matrices, _std_matrices])
+
+ f('outerProduct', 2, '1.20', np.outer, None, [_nontrivial_vectors, _nontrivial_vectors])
+ f('transpose', 1, '1.20', np.transpose, None, [_std_matrices])
+ f('any', 1, '1.10', any, None, [_bvecs])
+ f('all', 1, '1.10', all, None, [_bvecs])
+_make_vector_or_matrix_test_vectors(test_suite)