ClangFormat: apply to source, most of intern

Apply clang format as proposed in T53211.

For details on usage and instructions for migrating branches
without conflicts, see:

https://wiki.blender.org/wiki/Tools/ClangFormat

1 files changed, 873 insertions, 814 deletions

diff --git a/source/blender/python/mathutils/mathutils_noise.c b/source/blender/python/mathutils/mathutils_noise.c
index 04cadb9b592..b890295d32f 100644
--- a/source/blender/python/mathutils/mathutils_noise.c
+++ b/source/blender/python/mathutils/mathutils_noise.c
@@ -21,7 +21,6 @@
  * blenders noise functions.
  */
 
-
 /************************/
 /* Blender Noise Module */
 /************************/
@@ -88,13 +87,13 @@
 /* Period parameters */
 #define N 624
 #define M 397
-#define MATRIX_A 0x9908b0dfUL   /* constant vector a */
-#define UMASK 0x80000000UL  /* most significant w-r bits */
-#define LMASK 0x7fffffffUL  /* least significant r bits */
-#define MIXBITS(u, v) (((u) & UMASK) | ((v) & LMASK))
-#define TWIST(u, v) ((MIXBITS(u, v) >> 1) ^ ((v) & 1UL ? MATRIX_A : 0UL))
+#define MATRIX_A 0x9908b0dfUL /* constant vector a */
+#define UMASK 0x80000000UL    /* most significant w-r bits */
+#define LMASK 0x7fffffffUL    /* least significant r bits */
+#define MIXBITS(u, v) (((u)&UMASK) | ((v)&LMASK))
+#define TWIST(u, v) ((MIXBITS(u, v) >> 1) ^ ((v)&1UL ? MATRIX_A : 0UL))
 
-static unsigned long state[N];  /* the array for the state vector  */
+static unsigned long state[N]; /* the array for the state vector  */
 static int left = 1;
 static int initf = 0;
 static unsigned long *next;
@@ -103,86 +102,84 @@ static float state_offset_vector[3 * 3];
 /* initializes state[N] with a seed */
 static void init_genrand(unsigned long s)
 {
-	int j;
-	state[0] = s & 0xffffffffUL;
-	for (j = 1; j < N; j++) {
-		state[j] =
-		    (1812433253UL *
-		     (state[j - 1] ^ (state[j - 1] >> 30)) + j);
-		/* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */
-		/* In the previous versions, MSBs of the seed affect   */
-		/* only MSBs of the array state[].                        */
-		/* 2002/01/09 modified by Makoto Matsumoto             */
-		state[j] &= 0xffffffffUL;   /* for >32 bit machines */
-	}
-	left = 1;
-	initf = 1;
-
-	/* update vector offset */
-	{
-		const unsigned long *state_offset = &state[N - ARRAY_SIZE(state_offset_vector)];
-		const float range = 32;  /* range in both pos/neg direction */
-		for (j = 0; j < ARRAY_SIZE(state_offset_vector); j++, state_offset++) {
-			/* overflow is fine here */
-			state_offset_vector[j] = (float)(int)(*state_offset) * (1.0f / (INT_MAX / range));
-		}
-	}
+  int j;
+  state[0] = s & 0xffffffffUL;
+  for (j = 1; j < N; j++) {
+    state[j] = (1812433253UL * (state[j - 1] ^ (state[j - 1] >> 30)) + j);
+    /* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */
+    /* In the previous versions, MSBs of the seed affect   */
+    /* only MSBs of the array state[].                        */
+    /* 2002/01/09 modified by Makoto Matsumoto             */
+    state[j] &= 0xffffffffUL; /* for >32 bit machines */
+  }
+  left = 1;
+  initf = 1;
+
+  /* update vector offset */
+  {
+    const unsigned long *state_offset = &state[N - ARRAY_SIZE(state_offset_vector)];
+    const float range = 32; /* range in both pos/neg direction */
+    for (j = 0; j < ARRAY_SIZE(state_offset_vector); j++, state_offset++) {
+      /* overflow is fine here */
+      state_offset_vector[j] = (float)(int)(*state_offset) * (1.0f / (INT_MAX / range));
+    }
+  }
 }
 
 static void next_state(void)
 {
-	unsigned long *p = state;
-	int j;
+  unsigned long *p = state;
+  int j;
 
-	/* if init_genrand() has not been called, */
-	/* a default initial seed is used         */
-	if (initf == 0) {
-		init_genrand(5489UL);
-	}
+  /* if init_genrand() has not been called, */
+  /* a default initial seed is used         */
+  if (initf == 0) {
+    init_genrand(5489UL);
+  }
 
-	left = N;
-	next = state;
+  left = N;
+  next = state;
 
-	for (j = N - M + 1; --j; p++) {
-		*p = p[M] ^ TWIST(p[0], p[1]);
-	}
+  for (j = N - M + 1; --j; p++) {
+    *p = p[M] ^ TWIST(p[0], p[1]);
+  }
 
-	for (j = M; --j; p++) {
-		*p = p[M - N] ^ TWIST(p[0], p[1]);
-	}
+  for (j = M; --j; p++) {
+    *p = p[M - N] ^ TWIST(p[0], p[1]);
+  }
 
-	*p = p[M - N] ^ TWIST(p[0], state[0]);
+  *p = p[M - N] ^ TWIST(p[0], state[0]);
 }
 
 /*------------------------------------------------------------*/
 
 static void setRndSeed(int seed)
 {
-	if (seed == 0) {
-		init_genrand(time(NULL));
-	}
-	else {
-		init_genrand(seed);
-	}
+  if (seed == 0) {
+    init_genrand(time(NULL));
+  }
+  else {
+    init_genrand(seed);
+  }
 }
 
 /* float number in range [0, 1) using the mersenne twister rng */
 static float frand(void)
 {
-	unsigned long y;
+  unsigned long y;
 
-	if (--left == 0) {
-		next_state();
-	}
-	y = *next++;
+  if (--left == 0) {
+    next_state();
+  }
+  y = *next++;
 
-	/* Tempering */
-	y ^= (y >> 11);
-	y ^= (y << 7) & 0x9d2c5680UL;
-	y ^= (y << 15) & 0xefc60000UL;
-	y ^= (y >> 18);
+  /* Tempering */
+  y ^= (y >> 11);
+  y ^= (y << 7) & 0x9d2c5680UL;
+  y ^= (y << 15) & 0xefc60000UL;
+  y ^= (y >> 18);
 
-	return (float) y / 4294967296.f;
+  return (float)y / 4294967296.f;
 }
 
 /*------------------------------------------------------------*/
@@ -190,898 +187,960 @@ static float frand(void)
 /*------------------------------------------------------------*/
 
 #define BPY_NOISE_BASIS_ENUM_DOC \
-"   :arg noise_basis: Enumerator in ['BLENDER', 'PERLIN_ORIGINAL', 'PERLIN_NEW', 'VORONOI_F1', 'VORONOI_F2', " \
-									"'VORONOI_F3', 'VORONOI_F4', 'VORONOI_F2F1', 'VORONOI_CRACKLE', " \
-									"'CELLNOISE'].\n" \
-"   :type noise_basis: string\n" \
+  "   :arg noise_basis: Enumerator in ['BLENDER', 'PERLIN_ORIGINAL', 'PERLIN_NEW', " \
+  "'VORONOI_F1', 'VORONOI_F2', " \
+  "'VORONOI_F3', 'VORONOI_F4', 'VORONOI_F2F1', 'VORONOI_CRACKLE', " \
+  "'CELLNOISE'].\n" \
+  "   :type noise_basis: string\n"
 
 #define BPY_NOISE_METRIC_ENUM_DOC \
-"   :arg distance_metric: Enumerator in ['DISTANCE', 'DISTANCE_SQUARED', 'MANHATTAN', 'CHEBYCHEV', " \
-										"'MINKOVSKY', 'MINKOVSKY_HALF', 'MINKOVSKY_FOUR'].\n" \
-"   :type distance_metric: string\n" \
+  "   :arg distance_metric: Enumerator in ['DISTANCE', 'DISTANCE_SQUARED', 'MANHATTAN', " \
+  "'CHEBYCHEV', " \
+  "'MINKOVSKY', 'MINKOVSKY_HALF', 'MINKOVSKY_FOUR'].\n" \
+  "   :type distance_metric: string\n"
 
 /* Noise basis enum */
 #define DEFAULT_NOISE_TYPE TEX_STDPERLIN
 
 static PyC_FlagSet bpy_noise_types[] = {
-	{TEX_BLENDER,         "BLENDER"},
-	{TEX_STDPERLIN,       "PERLIN_ORIGINAL"},
-	{TEX_NEWPERLIN,       "PERLIN_NEW"},
-	{TEX_VORONOI_F1,      "VORONOI_F1"},
-	{TEX_VORONOI_F2,      "VORONOI_F2"},
-	{TEX_VORONOI_F3,      "VORONOI_F3"},
-	{TEX_VORONOI_F4,      "VORONOI_F4"},
-	{TEX_VORONOI_F2F1,    "VORONOI_F2F1"},
-	{TEX_VORONOI_CRACKLE, "VORONOI_CRACKLE"},
-	{TEX_CELLNOISE,       "CELLNOISE"},
-	{0, NULL},
+    {TEX_BLENDER, "BLENDER"},
+    {TEX_STDPERLIN, "PERLIN_ORIGINAL"},
+    {TEX_NEWPERLIN, "PERLIN_NEW"},
+    {TEX_VORONOI_F1, "VORONOI_F1"},
+    {TEX_VORONOI_F2, "VORONOI_F2"},
+    {TEX_VORONOI_F3, "VORONOI_F3"},
+    {TEX_VORONOI_F4, "VORONOI_F4"},
+    {TEX_VORONOI_F2F1, "VORONOI_F2F1"},
+    {TEX_VORONOI_CRACKLE, "VORONOI_CRACKLE"},
+    {TEX_CELLNOISE, "CELLNOISE"},
+    {0, NULL},
 };
 
 /* Metric basis enum */
 #define DEFAULT_METRIC_TYPE TEX_DISTANCE
 
 static PyC_FlagSet bpy_noise_metrics[] = {
-	{TEX_DISTANCE,         "DISTANCE"},
-	{TEX_DISTANCE_SQUARED, "DISTANCE_SQUARED"},
-	{TEX_MANHATTAN,        "MANHATTAN"},
-	{TEX_CHEBYCHEV,        "CHEBYCHEV"},
-	{TEX_MINKOVSKY,        "MINKOVSKY"},
-	{TEX_MINKOVSKY_HALF,   "MINKOVSKY_HALF"},
-	{TEX_MINKOVSKY_FOUR,   "MINKOVSKY_FOUR"},
-	{0, NULL},
+    {TEX_DISTANCE, "DISTANCE"},
+    {TEX_DISTANCE_SQUARED, "DISTANCE_SQUARED"},
+    {TEX_MANHATTAN, "MANHATTAN"},
+    {TEX_CHEBYCHEV, "CHEBYCHEV"},
+    {TEX_MINKOVSKY, "MINKOVSKY"},
+    {TEX_MINKOVSKY_HALF, "MINKOVSKY_HALF"},
+    {TEX_MINKOVSKY_FOUR, "MINKOVSKY_FOUR"},
+    {0, NULL},
 };
 
 /* Fills an array of length size with random numbers in the range (-1, 1)*/
 static void rand_vn(float *array_tar, const int size)
 {
-	float *array_pt = array_tar + (size - 1);
-	int i = size;
-	while (i--) { *(array_pt--) = 2.0f * frand() - 1.0f; }
+  float *array_pt = array_tar + (size - 1);
+  int i = size;
+  while (i--) {
+    *(array_pt--) = 2.0f * frand() - 1.0f;
+  }
 }
 
 /* Fills an array of length 3 with noise values */
 static void noise_vector(float x, float y, float z, int nb, float v[3])
 {
-	/* Simply evaluate noise at 3 different positions */
-	const float *ofs = state_offset_vector;
-	for (int j = 0; j < 3; j++) {
-		v[j] = (2.0f * BLI_gNoise(1.0f, x + ofs[0], y + ofs[1], z + ofs[2], 0, nb) - 1.0f);
-		ofs += 3;
-	}
+  /* Simply evaluate noise at 3 different positions */
+  const float *ofs = state_offset_vector;
+  for (int j = 0; j < 3; j++) {
+    v[j] = (2.0f * BLI_gNoise(1.0f, x + ofs[0], y + ofs[1], z + ofs[2], 0, nb) - 1.0f);
+    ofs += 3;
+  }
 }
 
 /* Returns a turbulence value for a given position (x, y, z) */
 static float turb(
-        float x, float y, float z, int oct, int hard, int nb,
-        float ampscale, float freqscale)
+    float x, float y, float z, int oct, int hard, int nb, float ampscale, float freqscale)
 {
-	float amp, out, t;
-	int i;
-	amp = 1.f;
-	out = (float)(2.0f * BLI_gNoise(1.f, x, y, z, 0, nb) - 1.0f);
-	if (hard) {
-		out = fabsf(out);
-	}
-	for (i = 1; i < oct; i++) {
-		amp *= ampscale;
-		x *= freqscale;
-		y *= freqscale;
-		z *= freqscale;
-		t = (float)(amp * (2.0f * BLI_gNoise(1.f, x, y, z, 0, nb) - 1.0f));
-		if (hard) {
-			t = fabsf(t);
-		}
-		out += t;
-	}
-	return out;
+  float amp, out, t;
+  int i;
+  amp = 1.f;
+  out = (float)(2.0f * BLI_gNoise(1.f, x, y, z, 0, nb) - 1.0f);
+  if (hard) {
+    out = fabsf(out);
+  }
+  for (i = 1; i < oct; i++) {
+    amp *= ampscale;
+    x *= freqscale;
+    y *= freqscale;
+    z *= freqscale;
+    t = (float)(amp * (2.0f * BLI_gNoise(1.f, x, y, z, 0, nb) - 1.0f));
+    if (hard) {
+      t = fabsf(t);
+    }
+    out += t;
+  }
+  return out;
 }
 
 /* Fills an array of length 3 with the turbulence vector for a given
  * position (x, y, z) */
-static void vTurb(
-        float x, float y, float z, int oct, int hard, int nb,
-        float ampscale, float freqscale, float v[3])
+static void vTurb(float x,
+                  float y,
+                  float z,
+                  int oct,
+                  int hard,
+                  int nb,
+                  float ampscale,
+                  float freqscale,
+                  float v[3])
 {
-	float amp, t[3];
-	int i;
-	amp = 1.f;
-	noise_vector(x, y, z, nb, v);
-	if (hard) {
-		v[0] = fabsf(v[0]);
-		v[1] = fabsf(v[1]);
-		v[2] = fabsf(v[2]);
-	}
-	for (i = 1; i < oct; i++) {
-		amp *= ampscale;
-		x *= freqscale;
-		y *= freqscale;
-		z *= freqscale;
-		noise_vector(x, y, z, nb, t);
-		if (hard) {
-			t[0] = fabsf(t[0]);
-			t[1] = fabsf(t[1]);
-			t[2] = fabsf(t[2]);
-		}
-		v[0] += amp * t[0];
-		v[1] += amp * t[1];
-		v[2] += amp * t[2];
-	}
+  float amp, t[3];
+  int i;
+  amp = 1.f;
+  noise_vector(x, y, z, nb, v);
+  if (hard) {
+    v[0] = fabsf(v[0]);
+    v[1] = fabsf(v[1]);
+    v[2] = fabsf(v[2]);
+  }
+  for (i = 1; i < oct; i++) {
+    amp *= ampscale;
+    x *= freqscale;
+    y *= freqscale;
+    z *= freqscale;
+    noise_vector(x, y, z, nb, t);
+    if (hard) {
+      t[0] = fabsf(t[0]);
+      t[1] = fabsf(t[1]);
+      t[2] = fabsf(t[2]);
+    }
+    v[0] += amp * t[0];
+    v[1] += amp * t[1];
+    v[2] += amp * t[2];
+  }
 }
 
 /*-------------------------DOC STRINGS ---------------------------*/
-PyDoc_STRVAR(M_Noise_doc,
-"The Blender noise module"
-);
+PyDoc_STRVAR(M_Noise_doc, "The Blender noise module");
 
 /*------------------------------------------------------------*/
 /* Python Functions */
 /*------------------------------------------------------------*/
 
 PyDoc_STRVAR(M_Noise_random_doc,
-".. function:: random()\n"
-"\n"
-"   Returns a random number in the range [0, 1).\n"
-"\n"
-"   :return: The random number.\n"
-"   :rtype: float\n"
-);
+             ".. function:: random()\n"
+             "\n"
+             "   Returns a random number in the range [0, 1).\n"
+             "\n"
+             "   :return: The random number.\n"
+             "   :rtype: float\n");
 static PyObject *M_Noise_random(PyObject *UNUSED(self))
 {
-	return PyFloat_FromDouble(frand());
+  return PyFloat_FromDouble(frand());
 }
 
 PyDoc_STRVAR(M_Noise_random_unit_vector_doc,
-".. function:: random_unit_vector(size=3)\n"
-"\n"
-"   Returns a unit vector with random entries.\n"
-"\n"
-"   :arg size: The size of the vector to be produced, in the range [2, 4].\n"
-"   :type size: int\n"
-"   :return: The random unit vector.\n"
-"   :rtype: :class:`mathutils.Vector`\n"
-);
+             ".. function:: random_unit_vector(size=3)\n"
+             "\n"
+             "   Returns a unit vector with random entries.\n"
+             "\n"
+             "   :arg size: The size of the vector to be produced, in the range [2, 4].\n"
+             "   :type size: int\n"
+             "   :return: The random unit vector.\n"
+             "   :rtype: :class:`mathutils.Vector`\n");
 static PyObject *M_Noise_random_unit_vector(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
 {
-	static const char *kwlist[] = {"size", NULL};
-	float vec[4] = {0.0f, 0.0f, 0.0f, 0.0f};
-	float norm = 2.0f;
-	int size = 3;
-
-	if (!PyArg_ParseTupleAndKeywords(
-	            args, kw, "|$i:random_unit_vector", (char **)kwlist,
-	            &size))
-	{
-		return NULL;
-	}
-
-	if (size > 4 || size < 2) {
-		PyErr_SetString(PyExc_ValueError, "Vector(): invalid size");
-		return NULL;
-	}
-
-	while (norm == 0.0f || norm > 1.0f) {
-		rand_vn(vec, size);
-		norm = normalize_vn(vec, size);
-	}
-
-	return Vector_CreatePyObject(vec, size, NULL);
+  static const char *kwlist[] = {"size", NULL};
+  float vec[4] = {0.0f, 0.0f, 0.0f, 0.0f};
+  float norm = 2.0f;
+  int size = 3;
+
+  if (!PyArg_ParseTupleAndKeywords(args, kw, "|$i:random_unit_vector", (char **)kwlist, &size)) {
+    return NULL;
+  }
+
+  if (size > 4 || size < 2) {
+    PyErr_SetString(PyExc_ValueError, "Vector(): invalid size");
+    return NULL;
+  }
+
+  while (norm == 0.0f || norm > 1.0f) {
+    rand_vn(vec, size);
+    norm = normalize_vn(vec, size);
+  }
+
+  return Vector_CreatePyObject(vec, size, NULL);
 }
 
 PyDoc_STRVAR(M_Noise_random_vector_doc,
-".. function:: random_vector(size=3)\n"
-"\n"
-"   Returns a vector with random entries in the range (-1, 1).\n"
-"\n"
-"   :arg size: The size of the vector to be produced.\n"
-"   :type size: int\n"
-"   :return: The random vector.\n"
-"   :rtype: :class:`mathutils.Vector`\n"
-);
+             ".. function:: random_vector(size=3)\n"
+             "\n"
+             "   Returns a vector with random entries in the range (-1, 1).\n"
+             "\n"
+             "   :arg size: The size of the vector to be produced.\n"
+             "   :type size: int\n"
+             "   :return: The random vector.\n"
+             "   :rtype: :class:`mathutils.Vector`\n");
 static PyObject *M_Noise_random_vector(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
 {
-	static const char *kwlist[] = {"size", NULL};
-	float *vec = NULL;
-	int size = 3;
+  static const char *kwlist[] = {"size", NULL};
+  float *vec = NULL;
+  int size = 3;
 
-	if (!PyArg_ParseTupleAndKeywords(
-	            args, kw, "|$i:random_vector", (char **)kwlist,
-	            &size))
-	{
-		return NULL;
-	}
+  if (!PyArg_ParseTupleAndKeywords(args, kw, "|$i:random_vector", (char **)kwlist, &size)) {
+    return NULL;
+  }
 
-	if (size < 2) {
-		PyErr_SetString(PyExc_ValueError, "Vector(): invalid size");
-		return NULL;
-	}
+  if (size < 2) {
+    PyErr_SetString(PyExc_ValueError, "Vector(): invalid size");
+    return NULL;
+  }
 
-	vec = PyMem_New(float, size);
+  vec = PyMem_New(float, size);
 
-	rand_vn(vec, size);
+  rand_vn(vec, size);
 
-	return Vector_CreatePyObject_alloc(vec, size, NULL);
+  return Vector_CreatePyObject_alloc(vec, size, NULL);
 }
 
 PyDoc_STRVAR(M_Noise_seed_set_doc,
-".. function:: seed_set(seed)\n"
-"\n"
-"   Sets the random seed used for random_unit_vector, and random.\n"
-"\n"
-"   :arg seed: Seed used for the random generator.\n"
-"      When seed is zero, the current time will be used instead.\n"
-"   :type seed: int\n"
-);
+             ".. function:: seed_set(seed)\n"
+             "\n"
+             "   Sets the random seed used for random_unit_vector, and random.\n"
+             "\n"
+             "   :arg seed: Seed used for the random generator.\n"
+             "      When seed is zero, the current time will be used instead.\n"
+             "   :type seed: int\n");
 static PyObject *M_Noise_seed_set(PyObject *UNUSED(self), PyObject *args)
 {
-	int s;
-	if (!PyArg_ParseTuple(args, "i:seed_set", &s)) {
-		return NULL;
-	}
-	setRndSeed(s);
-	Py_RETURN_NONE;
+  int s;
+  if (!PyArg_ParseTuple(args, "i:seed_set", &s)) {
+    return NULL;
+  }
+  setRndSeed(s);
+  Py_RETURN_NONE;
 }
 
 PyDoc_STRVAR(M_Noise_noise_doc,
-".. function:: noise(position, noise_basis='PERLIN_ORIGINAL')\n"
-"\n"
-"   Returns noise value from the noise basis at the position specified.\n"
-"\n"
-"   :arg position: The position to evaluate the selected noise function.\n"
-"   :type position: :class:`mathutils.Vector`\n"
-BPY_NOISE_BASIS_ENUM_DOC
-"   :return: The noise value.\n"
-"   :rtype: float\n"
-);
+             ".. function:: noise(position, noise_basis='PERLIN_ORIGINAL')\n"
+             "\n"
+             "   Returns noise value from the noise basis at the position specified.\n"
+             "\n"
+             "   :arg position: The position to evaluate the selected noise function.\n"
+             "   :type position: :class:`mathutils.Vector`\n" BPY_NOISE_BASIS_ENUM_DOC
+             "   :return: The noise value.\n"
+             "   :rtype: float\n");
 static PyObject *M_Noise_noise(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
 {
-	static const char *kwlist[] = {"", "noise_basis", NULL};
-	PyObject *value;
-	float vec[3];
-	const char *noise_basis_str = NULL;
-	int noise_basis_enum = DEFAULT_NOISE_TYPE;
-
-	if (!PyArg_ParseTupleAndKeywords(
-	            args, kw, "O|$s:noise", (char **)kwlist,
-	            &value, &noise_basis_str))
-	{
-		return NULL;
-	}
-
-	if (!noise_basis_str) {
-		/* pass through */
-	}
-	else if (PyC_FlagSet_ValueFromID(
-	                 bpy_noise_types, noise_basis_str, &noise_basis_enum, "noise") == -1)
-	{
-		return NULL;
-	}
-
-	if (mathutils_array_parse(vec, 3, 3, value, "noise: invalid 'position' arg") == -1) {
-		return NULL;
-	}
-
-	return PyFloat_FromDouble((2.0f * BLI_gNoise(1.0f, vec[0], vec[1], vec[2], 0, noise_basis_enum) - 1.0f));
+  static const char *kwlist[] = {"", "noise_basis", NULL};
+  PyObject *value;
+  float vec[3];
+  const char *noise_basis_str = NULL;
+  int noise_basis_enum = DEFAULT_NOISE_TYPE;
+
+  if (!PyArg_ParseTupleAndKeywords(
+          args, kw, "O|$s:noise", (char **)kwlist, &value, &noise_basis_str)) {
+    return NULL;
+  }
+
+  if (!noise_basis_str) {
+    /* pass through */
+  }
+  else if (PyC_FlagSet_ValueFromID(bpy_noise_types, noise_basis_str, &noise_basis_enum, "noise") ==
+           -1) {
+    return NULL;
+  }
+
+  if (mathutils_array_parse(vec, 3, 3, value, "noise: invalid 'position' arg") == -1) {
+    return NULL;
+  }
+
+  return PyFloat_FromDouble(
+      (2.0f * BLI_gNoise(1.0f, vec[0], vec[1], vec[2], 0, noise_basis_enum) - 1.0f));
 }
 
 PyDoc_STRVAR(M_Noise_noise_vector_doc,
-".. function:: noise_vector(position, noise_basis='PERLIN_ORIGINAL')\n"
-"\n"
-"   Returns the noise vector from the noise basis at the specified position.\n"
-"\n"
-"   :arg position: The position to evaluate the selected noise function.\n"
-"   :type position: :class:`mathutils.Vector`\n"
-BPY_NOISE_BASIS_ENUM_DOC
-"   :return: The noise vector.\n"
-"   :rtype: :class:`mathutils.Vector`\n"
-);
+             ".. function:: noise_vector(position, noise_basis='PERLIN_ORIGINAL')\n"
+             "\n"
+             "   Returns the noise vector from the noise basis at the specified position.\n"
+             "\n"
+             "   :arg position: The position to evaluate the selected noise function.\n"
+             "   :type position: :class:`mathutils.Vector`\n" BPY_NOISE_BASIS_ENUM_DOC
+             "   :return: The noise vector.\n"
+             "   :rtype: :class:`mathutils.Vector`\n");
 static PyObject *M_Noise_noise_vector(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
 {
-	static const char *kwlist[] = {"", "noise_basis", NULL};
-	PyObject *value;
-	float vec[3], r_vec[3];
-	const char *noise_basis_str = NULL;
-	int noise_basis_enum = DEFAULT_NOISE_TYPE;
-
-	if (!PyArg_ParseTupleAndKeywords(
-	            args, kw, "O|$s:noise_vector", (char **)kwlist,
-	            &value, &noise_basis_str))
-	{
-		return NULL;
-	}
-
-	if (!noise_basis_str) {
-		/* pass through */
-	}
-	else if (PyC_FlagSet_ValueFromID(
-	                 bpy_noise_types, noise_basis_str, &noise_basis_enum, "noise_vector") == -1)
-	{
-		return NULL;
-	}
-
-	if (mathutils_array_parse(vec, 3, 3, value, "noise_vector: invalid 'position' arg") == -1) {
-		return NULL;
-	}
-
-	noise_vector(vec[0], vec[1], vec[2], noise_basis_enum, r_vec);
-
-	return Vector_CreatePyObject(r_vec, 3, NULL);
+  static const char *kwlist[] = {"", "noise_basis", NULL};
+  PyObject *value;
+  float vec[3], r_vec[3];
+  const char *noise_basis_str = NULL;
+  int noise_basis_enum = DEFAULT_NOISE_TYPE;
+
+  if (!PyArg_ParseTupleAndKeywords(
+          args, kw, "O|$s:noise_vector", (char **)kwlist, &value, &noise_basis_str)) {
+    return NULL;
+  }
+
+  if (!noise_basis_str) {
+    /* pass through */
+  }
+  else if (PyC_FlagSet_ValueFromID(
+               bpy_noise_types, noise_basis_str, &noise_basis_enum, "noise_vector") == -1) {
+    return NULL;
+  }
+
+  if (mathutils_array_parse(vec, 3, 3, value, "noise_vector: invalid 'position' arg") == -1) {
+    return NULL;
+  }
+
+  noise_vector(vec[0], vec[1], vec[2], noise_basis_enum, r_vec);
+
+  return Vector_CreatePyObject(r_vec, 3, NULL);
 }
 
 PyDoc_STRVAR(M_Noise_turbulence_doc,
-".. function:: turbulence(position, octaves, hard, noise_basis='PERLIN_ORIGINAL', amplitude_scale=0.5, frequency_scale=2.0)\n"
-"\n"
-"   Returns the turbulence value from the noise basis at the specified position.\n"
-"\n"
-"   :arg position: The position to evaluate the selected noise function.\n"
-"   :type position: :class:`mathutils.Vector`\n"
-"   :arg octaves: The number of different noise frequencies used.\n"
-"   :type octaves: int\n"
-"   :arg hard: Specifies whether returned turbulence is hard (sharp transitions) or soft (smooth transitions).\n"
-"   :type hard: boolean\n"
-BPY_NOISE_BASIS_ENUM_DOC
-"   :arg amplitude_scale: The amplitude scaling factor.\n"
-"   :type amplitude_scale: float\n"
-"   :arg frequency_scale: The frequency scaling factor\n"
-"   :type frequency_scale: float\n"
-"   :return: The turbulence value.\n"
-"   :rtype: float\n"
-);
+             ".. function:: turbulence(position, octaves, hard, noise_basis='PERLIN_ORIGINAL', "
+             "amplitude_scale=0.5, frequency_scale=2.0)\n"
+             "\n"
+             "   Returns the turbulence value from the noise basis at the specified position.\n"
+             "\n"
+             "   :arg position: The position to evaluate the selected noise function.\n"
+             "   :type position: :class:`mathutils.Vector`\n"
+             "   :arg octaves: The number of different noise frequencies used.\n"
+             "   :type octaves: int\n"
+             "   :arg hard: Specifies whether returned turbulence is hard (sharp transitions) or "
+             "soft (smooth transitions).\n"
+             "   :type hard: boolean\n" BPY_NOISE_BASIS_ENUM_DOC
+             "   :arg amplitude_scale: The amplitude scaling factor.\n"
+             "   :type amplitude_scale: float\n"
+             "   :arg frequency_scale: The frequency scaling factor\n"
+             "   :type frequency_scale: float\n"
+             "   :return: The turbulence value.\n"
+             "   :rtype: float\n");
 static PyObject *M_Noise_turbulence(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
 {
-	static const char *kwlist[] = {"", "", "", "noise_basis", "amplitude_scale", "frequency_scale", NULL};
-	PyObject *value;
-	float vec[3];
-	const char *noise_basis_str = NULL;
-	int oct, hd, noise_basis_enum = DEFAULT_NOISE_TYPE;
-	float as = 0.5f, fs = 2.0f;
-
-	if (!PyArg_ParseTupleAndKeywords(
-	            args, kw, "Oii|$sff:turbulence", (char **)kwlist,
-	            &value, &oct, &hd, &noise_basis_str, &as, &fs))
-	{
-		return NULL;
-	}
-
-	if (!noise_basis_str) {
-		/* pass through */
-	}
-	else if (PyC_FlagSet_ValueFromID(
-	                 bpy_noise_types, noise_basis_str, &noise_basis_enum, "turbulence") == -1)
-	{
-		return NULL;
-	}
-
-	if (mathutils_array_parse(vec, 3, 3, value, "turbulence: invalid 'position' arg") == -1) {
-		return NULL;
-	}
-
-	return PyFloat_FromDouble(turb(vec[0], vec[1], vec[2], oct, hd, noise_basis_enum, as, fs));
+  static const char *kwlist[] = {
+      "", "", "", "noise_basis", "amplitude_scale", "frequency_scale", NULL};
+  PyObject *value;
+  float vec[3];
+  const char *noise_basis_str = NULL;
+  int oct, hd, noise_basis_enum = DEFAULT_NOISE_TYPE;
+  float as = 0.5f, fs = 2.0f;
+
+  if (!PyArg_ParseTupleAndKeywords(args,
+                                   kw,
+                                   "Oii|$sff:turbulence",
+                                   (char **)kwlist,
+                                   &value,
+                                   &oct,
+                                   &hd,
+                                   &noise_basis_str,
+                                   &as,
+                                   &fs)) {
+    return NULL;
+  }
+
+  if (!noise_basis_str) {
+    /* pass through */
+  }
+  else if (PyC_FlagSet_ValueFromID(
+               bpy_noise_types, noise_basis_str, &noise_basis_enum, "turbulence") == -1) {
+    return NULL;
+  }
+
+  if (mathutils_array_parse(vec, 3, 3, value, "turbulence: invalid 'position' arg") == -1) {
+    return NULL;
+  }
+
+  return PyFloat_FromDouble(turb(vec[0], vec[1], vec[2], oct, hd, noise_basis_enum, as, fs));
 }
 
 PyDoc_STRVAR(M_Noise_turbulence_vector_doc,
-".. function:: turbulence_vector(position, octaves, hard, noise_basis='PERLIN_ORIGINAL', amplitude_scale=0.5, frequency_scale=2.0)\n"
-"\n"
-"   Returns the turbulence vector from the noise basis at the specified position.\n"
-"\n"
-"   :arg position: The position to evaluate the selected noise function.\n"
-"   :type position: :class:`mathutils.Vector`\n"
-"   :arg octaves: The number of different noise frequencies used.\n"
-"   :type octaves: int\n"
-"   :arg hard: Specifies whether returned turbulence is hard (sharp transitions) or soft (smooth transitions).\n"
-"   :type hard: :boolean\n"
-BPY_NOISE_BASIS_ENUM_DOC
-"   :arg amplitude_scale: The amplitude scaling factor.\n"
-"   :type amplitude_scale: float\n"
-"   :arg frequency_scale: The frequency scaling factor\n"
-"   :type frequency_scale: float\n"
-"   :return: The turbulence vector.\n"
-"   :rtype: :class:`mathutils.Vector`\n"
-);
+             ".. function:: turbulence_vector(position, octaves, hard, "
+             "noise_basis='PERLIN_ORIGINAL', amplitude_scale=0.5, frequency_scale=2.0)\n"
+             "\n"
+             "   Returns the turbulence vector from the noise basis at the specified position.\n"
+             "\n"
+             "   :arg position: The position to evaluate the selected noise function.\n"
+             "   :type position: :class:`mathutils.Vector`\n"
+             "   :arg octaves: The number of different noise frequencies used.\n"
+             "   :type octaves: int\n"
+             "   :arg hard: Specifies whether returned turbulence is hard (sharp transitions) or "
+             "soft (smooth transitions).\n"
+             "   :type hard: :boolean\n" BPY_NOISE_BASIS_ENUM_DOC
+             "   :arg amplitude_scale: The amplitude scaling factor.\n"
+             "   :type amplitude_scale: float\n"
+             "   :arg frequency_scale: The frequency scaling factor\n"
+             "   :type frequency_scale: float\n"
+             "   :return: The turbulence vector.\n"
+             "   :rtype: :class:`mathutils.Vector`\n");
 static PyObject *M_Noise_turbulence_vector(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
 {
-	static const char *kwlist[] = {"", "", "", "noise_basis", "amplitude_scale", "frequency_scale", NULL};
-	PyObject *value;
-	float vec[3], r_vec[3];
-	const char *noise_basis_str = NULL;
-	int oct, hd, noise_basis_enum = DEFAULT_NOISE_TYPE;
-	float as = 0.5f, fs = 2.0f;
-
-	if (!PyArg_ParseTupleAndKeywords(
-	            args, kw, "Oii|$sff:turbulence_vector", (char **)kwlist,
-	            &value, &oct, &hd, &noise_basis_str, &as, &fs))
-	{
-		return NULL;
-	}
-
-	if (!noise_basis_str) {
-		/* pass through */
-	}
-	else if (PyC_FlagSet_ValueFromID(
-	                 bpy_noise_types, noise_basis_str, &noise_basis_enum, "turbulence_vector") == -1)
-	{
-		return NULL;
-	}
-
-	if (mathutils_array_parse(vec, 3, 3, value, "turbulence_vector: invalid 'position' arg") == -1) {
-		return NULL;
-	}
-
-	vTurb(vec[0], vec[1], vec[2], oct, hd, noise_basis_enum, as, fs, r_vec);
-
-	return Vector_CreatePyObject(r_vec, 3, NULL);
+  static const char *kwlist[] = {
+      "", "", "", "noise_basis", "amplitude_scale", "frequency_scale", NULL};
+  PyObject *value;
+  float vec[3], r_vec[3];
+  const char *noise_basis_str = NULL;
+  int oct, hd, noise_basis_enum = DEFAULT_NOISE_TYPE;
+  float as = 0.5f, fs = 2.0f;
+
+  if (!PyArg_ParseTupleAndKeywords(args,
+                                   kw,
+                                   "Oii|$sff:turbulence_vector",
+                                   (char **)kwlist,
+                                   &value,
+                                   &oct,
+                                   &hd,
+                                   &noise_basis_str,
+                                   &as,
+                                   &fs)) {
+    return NULL;
+  }
+
+  if (!noise_basis_str) {
+    /* pass through */
+  }
+  else if (PyC_FlagSet_ValueFromID(
+               bpy_noise_types, noise_basis_str, &noise_basis_enum, "turbulence_vector") == -1) {
+    return NULL;
+  }
+
+  if (mathutils_array_parse(vec, 3, 3, value, "turbulence_vector: invalid 'position' arg") == -1) {
+    return NULL;
+  }
+
+  vTurb(vec[0], vec[1], vec[2], oct, hd, noise_basis_enum, as, fs, r_vec);
+
+  return Vector_CreatePyObject(r_vec, 3, NULL);
 }
 
 /* F. Kenton Musgrave's fractal functions */
-PyDoc_STRVAR(M_Noise_fractal_doc,
-".. function:: fractal(position, H, lacunarity, octaves, noise_basis='PERLIN_ORIGINAL')\n"
-"\n"
-"   Returns the fractal Brownian motion (fBm) noise value from the noise basis at the specified position.\n"
-"\n"
-"   :arg position: The position to evaluate the selected noise function.\n"
-"   :type position: :class:`mathutils.Vector`\n"
-"   :arg H: The fractal increment factor.\n"
-"   :type H: float\n"
-"   :arg lacunarity: The gap between successive frequencies.\n"
-"   :type lacunarity: float\n"
-"   :arg octaves: The number of different noise frequencies used.\n"
-"   :type octaves: int\n"
-BPY_NOISE_BASIS_ENUM_DOC
-"   :return: The fractal Brownian motion noise value.\n"
-"   :rtype: float\n"
-);
+PyDoc_STRVAR(
+    M_Noise_fractal_doc,
+    ".. function:: fractal(position, H, lacunarity, octaves, noise_basis='PERLIN_ORIGINAL')\n"
+    "\n"
+    "   Returns the fractal Brownian motion (fBm) noise value from the noise basis at the "
+    "specified position.\n"
+    "\n"
+    "   :arg position: The position to evaluate the selected noise function.\n"
+    "   :type position: :class:`mathutils.Vector`\n"
+    "   :arg H: The fractal increment factor.\n"
+    "   :type H: float\n"
+    "   :arg lacunarity: The gap between successive frequencies.\n"
+    "   :type lacunarity: float\n"
+    "   :arg octaves: The number of different noise frequencies used.\n"
+    "   :type octaves: int\n" BPY_NOISE_BASIS_ENUM_DOC
+    "   :return: The fractal Brownian motion noise value.\n"
+    "   :rtype: float\n");
 static PyObject *M_Noise_fractal(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
 {
-	static const char *kwlist[] = {"", "", "", "", "noise_basis", NULL};
-	PyObject *value;
-	float vec[3];
-	const char *noise_basis_str = NULL;
-	float H, lac, oct;
-	int noise_basis_enum = DEFAULT_NOISE_TYPE;
-
-	if (!PyArg_ParseTupleAndKeywords(
-	            args, kw, "Offf|$s:fractal", (char **)kwlist,
-	            &value, &H, &lac, &oct, &noise_basis_str))
-	{
-		return NULL;
-	}
-
-	if (!noise_basis_str) {
-		/* pass through */
-	}
-	else if (PyC_FlagSet_ValueFromID(
-	                 bpy_noise_types, noise_basis_str, &noise_basis_enum, "fractal") == -1)
-	{
-		return NULL;
-	}
-
-	if (mathutils_array_parse(vec, 3, 3, value, "fractal: invalid 'position' arg") == -1) {
-		return NULL;
-	}
-
-	return PyFloat_FromDouble(mg_fBm(vec[0], vec[1], vec[2], H, lac, oct, noise_basis_enum));
+  static const char *kwlist[] = {"", "", "", "", "noise_basis", NULL};
+  PyObject *value;
+  float vec[3];
+  const char *noise_basis_str = NULL;
+  float H, lac, oct;
+  int noise_basis_enum = DEFAULT_NOISE_TYPE;
+
+  if (!PyArg_ParseTupleAndKeywords(args,
+                                   kw,
+                                   "Offf|$s:fractal",
+                                   (char **)kwlist,
+                                   &value,
+                                   &H,
+                                   &lac,
+                                   &oct,
+                                   &noise_basis_str)) {
+    return NULL;
+  }
+
+  if (!noise_basis_str) {
+    /* pass through */
+  }
+  else if (PyC_FlagSet_ValueFromID(
+               bpy_noise_types, noise_basis_str, &noise_basis_enum, "fractal") == -1) {
+    return NULL;
+  }
+
+  if (mathutils_array_parse(vec, 3, 3, value, "fractal: invalid 'position' arg") == -1) {
+    return NULL;
+  }
+
+  return PyFloat_FromDouble(mg_fBm(vec[0], vec[1], vec[2], H, lac, oct, noise_basis_enum));
 }
 
-PyDoc_STRVAR(M_Noise_multi_fractal_doc,
-".. function:: multi_fractal(position, H, lacunarity, octaves, noise_basis='PERLIN_ORIGINAL')\n"
-"\n"
-"   Returns multifractal noise value from the noise basis at the specified position.\n"
-"\n"
-"   :arg position: The position to evaluate the selected noise function.\n"
-"   :type position: :class:`mathutils.Vector`\n"
-"   :arg H: The fractal increment factor.\n"
-"   :type H: float\n"
-"   :arg lacunarity: The gap between successive frequencies.\n"
-"   :type lacunarity: float\n"
-"   :arg octaves: The number of different noise frequencies used.\n"
-"   :type octaves: int\n"
-BPY_NOISE_BASIS_ENUM_DOC
-"   :return: The multifractal noise value.\n"
-"   :rtype: float\n"
-);
+PyDoc_STRVAR(
+    M_Noise_multi_fractal_doc,
+    ".. function:: multi_fractal(position, H, lacunarity, octaves, "
+    "noise_basis='PERLIN_ORIGINAL')\n"
+    "\n"
+    "   Returns multifractal noise value from the noise basis at the specified position.\n"
+    "\n"
+    "   :arg position: The position to evaluate the selected noise function.\n"
+    "   :type position: :class:`mathutils.Vector`\n"
+    "   :arg H: The fractal increment factor.\n"
+    "   :type H: float\n"
+    "   :arg lacunarity: The gap between successive frequencies.\n"
+    "   :type lacunarity: float\n"
+    "   :arg octaves: The number of different noise frequencies used.\n"
+    "   :type octaves: int\n" BPY_NOISE_BASIS_ENUM_DOC
+    "   :return: The multifractal noise value.\n"
+    "   :rtype: float\n");
 static PyObject *M_Noise_multi_fractal(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
 {
-	static const char *kwlist[] = {"", "", "", "", "noise_basis", NULL};
-	PyObject *value;
-	float vec[3];
-	const char *noise_basis_str = NULL;
-	float H, lac, oct;
-	int noise_basis_enum = DEFAULT_NOISE_TYPE;
-
-	if (!PyArg_ParseTupleAndKeywords(
-	            args, kw, "Offf|$s:multi_fractal", (char **)kwlist,
-	            &value, &H, &lac, &oct, &noise_basis_str))
-	{
-		return NULL;
-	}
-
-	if (!noise_basis_str) {
-		/* pass through */
-	}
-	else if (PyC_FlagSet_ValueFromID(
-	                 bpy_noise_types, noise_basis_str, &noise_basis_enum, "multi_fractal") == -1)
-	{
-		return NULL;
-	}
-
-	if (mathutils_array_parse(vec, 3, 3, value, "multi_fractal: invalid 'position' arg") == -1) {
-		return NULL;
-	}
-
-	return PyFloat_FromDouble(mg_MultiFractal(vec[0], vec[1], vec[2], H, lac, oct, noise_basis_enum));
+  static const char *kwlist[] = {"", "", "", "", "noise_basis", NULL};
+  PyObject *value;
+  float vec[3];
+  const char *noise_basis_str = NULL;
+  float H, lac, oct;
+  int noise_basis_enum = DEFAULT_NOISE_TYPE;
+
+  if (!PyArg_ParseTupleAndKeywords(args,
+                                   kw,
+                                   "Offf|$s:multi_fractal",
+                                   (char **)kwlist,
+                                   &value,
+                                   &H,
+                                   &lac,
+                                   &oct,
+                                   &noise_basis_str)) {
+    return NULL;
+  }
+
+  if (!noise_basis_str) {
+    /* pass through */
+  }
+  else if (PyC_FlagSet_ValueFromID(
+               bpy_noise_types, noise_basis_str, &noise_basis_enum, "multi_fractal") == -1) {
+    return NULL;
+  }
+
+  if (mathutils_array_parse(vec, 3, 3, value, "multi_fractal: invalid 'position' arg") == -1) {
+    return NULL;
+  }
+
+  return PyFloat_FromDouble(
+      mg_MultiFractal(vec[0], vec[1], vec[2], H, lac, oct, noise_basis_enum));
 }
 
 PyDoc_STRVAR(M_Noise_variable_lacunarity_doc,
-".. function:: variable_lacunarity(position, distortion, noise_type1='PERLIN_ORIGINAL', noise_type2='PERLIN_ORIGINAL')\n"
-"\n"
-"   Returns variable lacunarity noise value, a distorted variety of noise, from noise type 1 distorted by noise type 2 at the specified position.\n"
-"\n"
-"   :arg position: The position to evaluate the selected noise function.\n"
-"   :type position: :class:`mathutils.Vector`\n"
-"   :arg distortion: The amount of distortion.\n"
-"   :type distortion: float\n"
-"   :arg noise_type1: Enumerator in ['BLENDER', 'PERLIN_ORIGINAL', 'PERLIN_NEW', 'VORONOI_F1', 'VORONOI_F2', " \
-									"'VORONOI_F3', 'VORONOI_F4', 'VORONOI_F2F1', 'VORONOI_CRACKLE', " \
-									"'CELLNOISE'].\n"
-"   :type noise_type1: string\n"
-"   :arg noise_type2: Enumerator in ['BLENDER', 'PERLIN_ORIGINAL', 'PERLIN_NEW', 'VORONOI_F1', 'VORONOI_F2', " \
-									"'VORONOI_F3', 'VORONOI_F4', 'VORONOI_F2F1', 'VORONOI_CRACKLE', " \
-									"'CELLNOISE'].\n"
-"   :type noise_type2: string\n"
-"   :return: The variable lacunarity noise value.\n"
-"   :rtype: float\n"
-);
+             ".. function:: variable_lacunarity(position, distortion, "
+             "noise_type1='PERLIN_ORIGINAL', noise_type2='PERLIN_ORIGINAL')\n"
+             "\n"
+             "   Returns variable lacunarity noise value, a distorted variety of noise, from "
+             "noise type 1 distorted by noise type 2 at the specified position.\n"
+             "\n"
+             "   :arg position: The position to evaluate the selected noise function.\n"
+             "   :type position: :class:`mathutils.Vector`\n"
+             "   :arg distortion: The amount of distortion.\n"
+             "   :type distortion: float\n"
+             "   :arg noise_type1: Enumerator in ['BLENDER', 'PERLIN_ORIGINAL', 'PERLIN_NEW', "
+             "'VORONOI_F1', 'VORONOI_F2', "
+             "'VORONOI_F3', 'VORONOI_F4', 'VORONOI_F2F1', 'VORONOI_CRACKLE', "
+             "'CELLNOISE'].\n"
+             "   :type noise_type1: string\n"
+             "   :arg noise_type2: Enumerator in ['BLENDER', 'PERLIN_ORIGINAL', 'PERLIN_NEW', "
+             "'VORONOI_F1', 'VORONOI_F2', "
+             "'VORONOI_F3', 'VORONOI_F4', 'VORONOI_F2F1', 'VORONOI_CRACKLE', "
+             "'CELLNOISE'].\n"
+             "   :type noise_type2: string\n"
+             "   :return: The variable lacunarity noise value.\n"
+             "   :rtype: float\n");
 static PyObject *M_Noise_variable_lacunarity(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
 {
-	static const char *kwlist[] = {"", "", "noise_type1", "noise_type2", NULL};
-	PyObject *value;
-	float vec[3];
-	const char *noise_type1_str = NULL, *noise_type2_str = NULL;
-	float d;
-	int noise_type1_enum = DEFAULT_NOISE_TYPE, noise_type2_enum = DEFAULT_NOISE_TYPE;
-
-	if (!PyArg_ParseTupleAndKeywords(
-	            args, kw, "Of|$ss:variable_lacunarity", (char **)kwlist,
-	            &value, &d, &noise_type1_str, &noise_type2_str))
-	{
-		return NULL;
-	}
-
-	if (!noise_type1_str) {
-		/* pass through */
-	}
-	else if (PyC_FlagSet_ValueFromID(
-	                 bpy_noise_types, noise_type1_str, &noise_type1_enum, "variable_lacunarity") == -1)
-	{
-		return NULL;
-	}
-
-	if (!noise_type2_str) {
-		/* pass through */
-	}
-	else if (PyC_FlagSet_ValueFromID(
-	                 bpy_noise_types, noise_type2_str, &noise_type2_enum, "variable_lacunarity") == -1)
-	{
-		return NULL;
-	}
-
-	if (mathutils_array_parse(vec, 3, 3, value, "variable_lacunarity: invalid 'position' arg") == -1) {
-		return NULL;
-	}
-
-	return PyFloat_FromDouble(mg_VLNoise(vec[0], vec[1], vec[2], d, noise_type1_enum, noise_type2_enum));
+  static const char *kwlist[] = {"", "", "noise_type1", "noise_type2", NULL};
+  PyObject *value;
+  float vec[3];
+  const char *noise_type1_str = NULL, *noise_type2_str = NULL;
+  float d;
+  int noise_type1_enum = DEFAULT_NOISE_TYPE, noise_type2_enum = DEFAULT_NOISE_TYPE;
+
+  if (!PyArg_ParseTupleAndKeywords(args,
+                                   kw,
+                                   "Of|$ss:variable_lacunarity",
+                                   (char **)kwlist,
+                                   &value,
+                                   &d,
+                                   &noise_type1_str,
+                                   &noise_type2_str)) {
+    return NULL;
+  }
+
+  if (!noise_type1_str) {
+    /* pass through */
+  }
+  else if (PyC_FlagSet_ValueFromID(
+               bpy_noise_types, noise_type1_str, &noise_type1_enum, "variable_lacunarity") == -1) {
+    return NULL;
+  }
+
+  if (!noise_type2_str) {
+    /* pass through */
+  }
+  else if (PyC_FlagSet_ValueFromID(
+               bpy_noise_types, noise_type2_str, &noise_type2_enum, "variable_lacunarity") == -1) {
+    return NULL;
+  }
+
+  if (mathutils_array_parse(vec, 3, 3, value, "variable_lacunarity: invalid 'position' arg") ==
+      -1) {
+    return NULL;
+  }
+
+  return PyFloat_FromDouble(
+      mg_VLNoise(vec[0], vec[1], vec[2], d, noise_type1_enum, noise_type2_enum));
 }
 
-PyDoc_STRVAR(M_Noise_hetero_terrain_doc,
-".. function:: hetero_terrain(position, H, lacunarity, octaves, offset, noise_basis='PERLIN_ORIGINAL')\n"
-"\n"
-"   Returns the heterogeneous terrain value from the noise basis at the specified position.\n"
-"\n"
-"   :arg position: The position to evaluate the selected noise function.\n"
-"   :type position: :class:`mathutils.Vector`\n"
-"   :arg H: The fractal dimension of the roughest areas.\n"
-"   :type H: float\n"
-"   :arg lacunarity: The gap between successive frequencies.\n"
-"   :type lacunarity: float\n"
-"   :arg octaves: The number of different noise frequencies used.\n"
-"   :type octaves: int\n"
-"   :arg offset: The height of the terrain above 'sea level'.\n"
-"   :type offset: float\n"
-BPY_NOISE_BASIS_ENUM_DOC
-"   :return: The heterogeneous terrain value.\n"
-"   :rtype: float\n"
-);
+PyDoc_STRVAR(
+    M_Noise_hetero_terrain_doc,
+    ".. function:: hetero_terrain(position, H, lacunarity, octaves, offset, "
+    "noise_basis='PERLIN_ORIGINAL')\n"
+    "\n"
+    "   Returns the heterogeneous terrain value from the noise basis at the specified position.\n"
+    "\n"
+    "   :arg position: The position to evaluate the selected noise function.\n"
+    "   :type position: :class:`mathutils.Vector`\n"
+    "   :arg H: The fractal dimension of the roughest areas.\n"
+    "   :type H: float\n"
+    "   :arg lacunarity: The gap between successive frequencies.\n"
+    "   :type lacunarity: float\n"
+    "   :arg octaves: The number of different noise frequencies used.\n"
+    "   :type octaves: int\n"
+    "   :arg offset: The height of the terrain above 'sea level'.\n"
+    "   :type offset: float\n" BPY_NOISE_BASIS_ENUM_DOC
+    "   :return: The heterogeneous terrain value.\n"
+    "   :rtype: float\n");
 static PyObject *M_Noise_hetero_terrain(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
 {
-	static const char *kwlist[] = {"", "", "", "", "", "noise_basis", NULL};
-	PyObject *value;
-	float vec[3];
-	const char *noise_basis_str = NULL;
-	float H, lac, oct, ofs;
-	int noise_basis_enum = DEFAULT_NOISE_TYPE;
-
-	if (!PyArg_ParseTupleAndKeywords(
-	            args, kw, "Offff|$s:hetero_terrain", (char **)kwlist,
-	            &value, &H, &lac, &oct, &ofs, &noise_basis_str))
-	{
-		return NULL;
-	}
-
-	if (!noise_basis_str) {
-		/* pass through */
-	}
-	else if (PyC_FlagSet_ValueFromID(
-	                 bpy_noise_types, noise_basis_str, &noise_basis_enum, "hetero_terrain") == -1)
-	{
-		return NULL;
-	}
-
-	if (mathutils_array_parse(vec, 3, 3, value, "hetero_terrain: invalid 'position' arg") == -1) {
-		return NULL;
-	}
-
-	return PyFloat_FromDouble(mg_HeteroTerrain(vec[0], vec[1], vec[2], H, lac, oct, ofs, noise_basis_enum));
+  static const char *kwlist[] = {"", "", "", "", "", "noise_basis", NULL};
+  PyObject *value;
+  float vec[3];
+  const char *noise_basis_str = NULL;
+  float H, lac, oct, ofs;
+  int noise_basis_enum = DEFAULT_NOISE_TYPE;
+
+  if (!PyArg_ParseTupleAndKeywords(args,
+                                   kw,
+                                   "Offff|$s:hetero_terrain",
+                                   (char **)kwlist,
+                                   &value,
+                                   &H,
+                                   &lac,
+                                   &oct,
+                                   &ofs,
+                                   &noise_basis_str)) {
+    return NULL;
+  }
+
+  if (!noise_basis_str) {
+    /* pass through */
+  }
+  else if (PyC_FlagSet_ValueFromID(
+               bpy_noise_types, noise_basis_str, &noise_basis_enum, "hetero_terrain") == -1) {
+    return NULL;
+  }
+
+  if (mathutils_array_parse(vec, 3, 3, value, "hetero_terrain: invalid 'position' arg") == -1) {
+    return NULL;
+  }
+
+  return PyFloat_FromDouble(
+      mg_HeteroTerrain(vec[0], vec[1], vec[2], H, lac, oct, ofs, noise_basis_enum));
 }
 
-PyDoc_STRVAR(M_Noise_hybrid_multi_fractal_doc,
-".. function:: hybrid_multi_fractal(position, H, lacunarity, octaves, offset, gain, noise_basis='PERLIN_ORIGINAL')\n"
-"\n"
-"   Returns hybrid multifractal value from the noise basis at the specified position.\n"
-"\n"
-"   :arg position: The position to evaluate the selected noise function.\n"
-"   :type position: :class:`mathutils.Vector`\n"
-"   :arg H: The fractal dimension of the roughest areas.\n"
-"   :type H: float\n"
-"   :arg lacunarity: The gap between successive frequencies.\n"
-"   :type lacunarity: float\n"
-"   :arg octaves: The number of different noise frequencies used.\n"
-"   :type octaves: int\n"
-"   :arg offset: The height of the terrain above 'sea level'.\n"
-"   :type offset: float\n"
-"   :arg gain: Scaling applied to the values.\n"
-"   :type gain: float\n"
-BPY_NOISE_BASIS_ENUM_DOC
-"   :return: The hybrid multifractal value.\n"
-"   :rtype: float\n"
-);
+PyDoc_STRVAR(
+    M_Noise_hybrid_multi_fractal_doc,
+    ".. function:: hybrid_multi_fractal(position, H, lacunarity, octaves, offset, gain, "
+    "noise_basis='PERLIN_ORIGINAL')\n"
+    "\n"
+    "   Returns hybrid multifractal value from the noise basis at the specified position.\n"
+    "\n"
+    "   :arg position: The position to evaluate the selected noise function.\n"
+    "   :type position: :class:`mathutils.Vector`\n"
+    "   :arg H: The fractal dimension of the roughest areas.\n"
+    "   :type H: float\n"
+    "   :arg lacunarity: The gap between successive frequencies.\n"
+    "   :type lacunarity: float\n"
+    "   :arg octaves: The number of different noise frequencies used.\n"
+    "   :type octaves: int\n"
+    "   :arg offset: The height of the terrain above 'sea level'.\n"
+    "   :type offset: float\n"
+    "   :arg gain: Scaling applied to the values.\n"
+    "   :type gain: float\n" BPY_NOISE_BASIS_ENUM_DOC
+    "   :return: The hybrid multifractal value.\n"
+    "   :rtype: float\n");
 static PyObject *M_Noise_hybrid_multi_fractal(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
 {
-	static const char *kwlist[] = {"", "", "", "", "", "", "noise_basis", NULL};
-	PyObject *value;
-	float vec[3];
-	const char *noise_basis_str = NULL;
-	float H, lac, oct, ofs, gn;
-	int noise_basis_enum = DEFAULT_NOISE_TYPE;
-
-	if (!PyArg_ParseTupleAndKeywords(
-	            args, kw, "Offfff|$s:hybrid_multi_fractal", (char **)kwlist,
-	            &value, &H, &lac, &oct, &ofs, &gn, &noise_basis_str))
-	{
-		return NULL;
-	}
-
-	if (!noise_basis_str) {
-		/* pass through */
-	}
-	else if (PyC_FlagSet_ValueFromID(
-	                 bpy_noise_types, noise_basis_str, &noise_basis_enum, "hybrid_multi_fractal") == -1)
-	{
-		return NULL;
-	}
-
-	if (mathutils_array_parse(vec, 3, 3, value, "hybrid_multi_fractal: invalid 'position' arg") == -1) {
-		return NULL;
-	}
-
-	return PyFloat_FromDouble(mg_HybridMultiFractal(vec[0], vec[1], vec[2], H, lac, oct, ofs, gn, noise_basis_enum));
+  static const char *kwlist[] = {"", "", "", "", "", "", "noise_basis", NULL};
+  PyObject *value;
+  float vec[3];
+  const char *noise_basis_str = NULL;
+  float H, lac, oct, ofs, gn;
+  int noise_basis_enum = DEFAULT_NOISE_TYPE;
+
+  if (!PyArg_ParseTupleAndKeywords(args,
+                                   kw,
+                                   "Offfff|$s:hybrid_multi_fractal",
+                                   (char **)kwlist,
+                                   &value,
+                                   &H,
+                                   &lac,
+                                   &oct,
+                                   &ofs,
+                                   &gn,
+                                   &noise_basis_str)) {
+    return NULL;
+  }
+
+  if (!noise_basis_str) {
+    /* pass through */
+  }
+  else if (PyC_FlagSet_ValueFromID(
+               bpy_noise_types, noise_basis_str, &noise_basis_enum, "hybrid_multi_fractal") ==
+           -1) {
+    return NULL;
+  }
+
+  if (mathutils_array_parse(vec, 3, 3, value, "hybrid_multi_fractal: invalid 'position' arg") ==
+      -1) {
+    return NULL;
+  }
+
+  return PyFloat_FromDouble(
+      mg_HybridMultiFractal(vec[0], vec[1], vec[2], H, lac, oct, ofs, gn, noise_basis_enum));
 }
 
-PyDoc_STRVAR(M_Noise_ridged_multi_fractal_doc,
-".. function:: ridged_multi_fractal(position, H, lacunarity, octaves, offset, gain, noise_basis='PERLIN_ORIGINAL')\n"
-"\n"
-"   Returns ridged multifractal value from the noise basis at the specified position.\n"
-"\n"
-"   :arg position: The position to evaluate the selected noise function.\n"
-"   :type position: :class:`mathutils.Vector`\n"
-"   :arg H: The fractal dimension of the roughest areas.\n"
-"   :type H: float\n"
-"   :arg lacunarity: The gap between successive frequencies.\n"
-"   :type lacunarity: float\n"
-"   :arg octaves: The number of different noise frequencies used.\n"
-"   :type octaves: int\n"
-"   :arg offset: The height of the terrain above 'sea level'.\n"
-"   :type offset: float\n"
-"   :arg gain: Scaling applied to the values.\n"
-"   :type gain: float\n"
-BPY_NOISE_BASIS_ENUM_DOC
-"   :return: The ridged multifractal value.\n"
-"   :rtype: float\n"
-);
+PyDoc_STRVAR(
+    M_Noise_ridged_multi_fractal_doc,
+    ".. function:: ridged_multi_fractal(position, H, lacunarity, octaves, offset, gain, "
+    "noise_basis='PERLIN_ORIGINAL')\n"
+    "\n"
+    "   Returns ridged multifractal value from the noise basis at the specified position.\n"
+    "\n"
+    "   :arg position: The position to evaluate the selected noise function.\n"
+    "   :type position: :class:`mathutils.Vector`\n"
+    "   :arg H: The fractal dimension of the roughest areas.\n"
+    "   :type H: float\n"
+    "   :arg lacunarity: The gap between successive frequencies.\n"
+    "   :type lacunarity: float\n"
+    "   :arg octaves: The number of different noise frequencies used.\n"
+    "   :type octaves: int\n"
+    "   :arg offset: The height of the terrain above 'sea level'.\n"
+    "   :type offset: float\n"
+    "   :arg gain: Scaling applied to the values.\n"
+    "   :type gain: float\n" BPY_NOISE_BASIS_ENUM_DOC
+    "   :return: The ridged multifractal value.\n"
+    "   :rtype: float\n");
 static PyObject *M_Noise_ridged_multi_fractal(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
 {
-	static const char *kwlist[] = {"", "", "", "", "", "", "noise_basis", NULL};
-	PyObject *value;
-	float vec[3];
-	const char *noise_basis_str = NULL;
-	float H, lac, oct, ofs, gn;
-	int noise_basis_enum = DEFAULT_NOISE_TYPE;
-
-	if (!PyArg_ParseTupleAndKeywords(
-	            args, kw, "Offfff|$s:ridged_multi_fractal", (char **)kwlist,
-	            &value, &H, &lac, &oct, &ofs, &gn, &noise_basis_str))
-	{
-		return NULL;
-	}
-
-	if (!noise_basis_str) {
-		/* pass through */
-	}
-	else if (PyC_FlagSet_ValueFromID(
-	                 bpy_noise_types, noise_basis_str, &noise_basis_enum, "ridged_multi_fractal") == -1)
-	{
-		return NULL;
-	}
-
-	if (mathutils_array_parse(vec, 3, 3, value, "ridged_multi_fractal: invalid 'position' arg") == -1) {
-		return NULL;
-	}
-
-	return PyFloat_FromDouble(mg_RidgedMultiFractal(vec[0], vec[1], vec[2], H, lac, oct, ofs, gn, noise_basis_enum));
+  static const char *kwlist[] = {"", "", "", "", "", "", "noise_basis", NULL};
+  PyObject *value;
+  float vec[3];
+  const char *noise_basis_str = NULL;
+  float H, lac, oct, ofs, gn;
+  int noise_basis_enum = DEFAULT_NOISE_TYPE;
+
+  if (!PyArg_ParseTupleAndKeywords(args,
+                                   kw,
+                                   "Offfff|$s:ridged_multi_fractal",
+                                   (char **)kwlist,
+                                   &value,
+                                   &H,
+                                   &lac,
+                                   &oct,
+                                   &ofs,
+                                   &gn,
+                                   &noise_basis_str)) {
+    return NULL;
+  }
+
+  if (!noise_basis_str) {
+    /* pass through */
+  }
+  else if (PyC_FlagSet_ValueFromID(
+               bpy_noise_types, noise_basis_str, &noise_basis_enum, "ridged_multi_fractal") ==
+           -1) {
+    return NULL;
+  }
+
+  if (mathutils_array_parse(vec, 3, 3, value, "ridged_multi_fractal: invalid 'position' arg") ==
+      -1) {
+    return NULL;
+  }
+
+  return PyFloat_FromDouble(
+      mg_RidgedMultiFractal(vec[0], vec[1], vec[2], H, lac, oct, ofs, gn, noise_basis_enum));
 }
 
 PyDoc_STRVAR(M_Noise_voronoi_doc,
-".. function:: voronoi(position, distance_metric='DISTANCE', exponent=2.5)\n"
-"\n"
-"   Returns a list of distances to the four closest features and their locations.\n"
-"\n"
-"   :arg position: The position to evaluate the selected noise function.\n"
-"   :type position: :class:`mathutils.Vector`\n"
-BPY_NOISE_METRIC_ENUM_DOC
-"   :arg exponent: The exponent for Minkowski distance metric.\n"
-"   :type exponent: float\n"
-"   :return: A list of distances to the four closest features and their locations.\n"
-"   :rtype: list of four floats, list of four :class:`mathutils.Vector` types\n"
-);
+             ".. function:: voronoi(position, distance_metric='DISTANCE', exponent=2.5)\n"
+             "\n"
+             "   Returns a list of distances to the four closest features and their locations.\n"
+             "\n"
+             "   :arg position: The position to evaluate the selected noise function.\n"
+             "   :type position: :class:`mathutils.Vector`\n" BPY_NOISE_METRIC_ENUM_DOC
+             "   :arg exponent: The exponent for Minkowski distance metric.\n"
+             "   :type exponent: float\n"
+             "   :return: A list of distances to the four closest features and their locations.\n"
+             "   :rtype: list of four floats, list of four :class:`mathutils.Vector` types\n");
 static PyObject *M_Noise_voronoi(PyObject *UNUSED(self), PyObject *args, PyObject *kw)
 {
-	static const char *kwlist[] = {"", "distance_metric", "exponent", NULL};
-	PyObject *value;
-	PyObject *list;
-	PyObject *ret;
-	float vec[3];
-	const char *metric_str = NULL;
-	float da[4], pa[12];
-	int metric_enum = DEFAULT_METRIC_TYPE;
-	float me = 2.5f;  /* default minkowski exponent */
-
-	int i;
-
-	if (!PyArg_ParseTupleAndKeywords(
-	            args, kw, "O|$sf:voronoi", (char **)kwlist,
-	            &value, &metric_str, &me))
-	{
-		return NULL;
-	}
-
-	if (!metric_str) {
-		/* pass through */
-	}
-	else if (PyC_FlagSet_ValueFromID(
-	                 bpy_noise_metrics, metric_str, &metric_enum, "voronoi") == -1)
-	{
-		return NULL;
-	}
-
-	if (mathutils_array_parse(vec, 3, 3, value, "voronoi: invalid 'position' arg") == -1) {
-		return NULL;
-	}
-
-	list = PyList_New(4);
-
-	voronoi(vec[0], vec[1], vec[2], da, pa, me, metric_enum);
-
-	for (i = 0; i < 4; i++) {
-		PyObject *v = Vector_CreatePyObject(pa + 3 * i, 3, NULL);
-		PyList_SET_ITEM(list, i, v);
-	}
-
-	ret = Py_BuildValue("[[ffff]O]", da[0], da[1], da[2], da[3], list);
-	Py_DECREF(list);
-	return ret;
+  static const char *kwlist[] = {"", "distance_metric", "exponent", NULL};
+  PyObject *value;
+  PyObject *list;
+  PyObject *ret;
+  float vec[3];
+  const char *metric_str = NULL;
+  float da[4], pa[12];
+  int metric_enum = DEFAULT_METRIC_TYPE;
+  float me = 2.5f; /* default minkowski exponent */
+
+  int i;
+
+  if (!PyArg_ParseTupleAndKeywords(
+          args, kw, "O|$sf:voronoi", (char **)kwlist, &value, &metric_str, &me)) {
+    return NULL;
+  }
+
+  if (!metric_str) {
+    /* pass through */
+  }
+  else if (PyC_FlagSet_ValueFromID(bpy_noise_metrics, metric_str, &metric_enum, "voronoi") == -1) {
+    return NULL;
+  }
+
+  if (mathutils_array_parse(vec, 3, 3, value, "voronoi: invalid 'position' arg") == -1) {
+    return NULL;
+  }
+
+  list = PyList_New(4);
+
+  voronoi(vec[0], vec[1], vec[2], da, pa, me, metric_enum);
+
+  for (i = 0; i < 4; i++) {
+    PyObject *v = Vector_CreatePyObject(pa + 3 * i, 3, NULL);
+    PyList_SET_ITEM(list, i, v);
+  }
+
+  ret = Py_BuildValue("[[ffff]O]", da[0], da[1], da[2], da[3], list);
+  Py_DECREF(list);
+  return ret;
 }
 
 PyDoc_STRVAR(M_Noise_cell_doc,
-".. function:: cell(position)\n"
-"\n"
-"   Returns cell noise value at the specified position.\n"
-"\n"
-"   :arg position: The position to evaluate the selected noise function.\n"
-"   :type position: :class:`mathutils.Vector`\n"
-"   :return: The cell noise value.\n"
-"   :rtype: float\n"
-);
+             ".. function:: cell(position)\n"
+             "\n"
+             "   Returns cell noise value at the specified position.\n"
+             "\n"
+             "   :arg position: The position to evaluate the selected noise function.\n"
+             "   :type position: :class:`mathutils.Vector`\n"
+             "   :return: The cell noise value.\n"
+             "   :rtype: float\n");
 static PyObject *M_Noise_cell(PyObject *UNUSED(self), PyObject *args)
 {
-	PyObject *value;
-	float vec[3];
+  PyObject *value;
+  float vec[3];
 
-	if (!PyArg_ParseTuple(args, "O:cell", &value)) {
-		return NULL;
-	}
+  if (!PyArg_ParseTuple(args, "O:cell", &value)) {
+    return NULL;
+  }
 
-	if (mathutils_array_parse(vec, 3, 3, value, "cell: invalid 'position' arg") == -1) {
-		return NULL;
-	}
+  if (mathutils_array_parse(vec, 3, 3, value, "cell: invalid 'position' arg") == -1) {
+    return NULL;
+  }
 
-	return PyFloat_FromDouble(cellNoise(vec[0], vec[1], vec[2]));
+  return PyFloat_FromDouble(cellNoise(vec[0], vec[1], vec[2]));
 }
 
 PyDoc_STRVAR(M_Noise_cell_vector_doc,
-".. function:: cell_vector(position)\n"
-"\n"
-"   Returns cell noise vector at the specified position.\n"
-"\n"
-"   :arg position: The position to evaluate the selected noise function.\n"
-"   :type position: :class:`mathutils.Vector`\n"
-"   :return: The cell noise vector.\n"
-"   :rtype: :class:`mathutils.Vector`\n"
-);
+             ".. function:: cell_vector(position)\n"
+             "\n"
+             "   Returns cell noise vector at the specified position.\n"
+             "\n"
+             "   :arg position: The position to evaluate the selected noise function.\n"
+             "   :type position: :class:`mathutils.Vector`\n"
+             "   :return: The cell noise vector.\n"
+             "   :rtype: :class:`mathutils.Vector`\n");
 static PyObject *M_Noise_cell_vector(PyObject *UNUSED(self), PyObject *args)
 {
-	PyObject *value;
-	float vec[3], r_vec[3];
+  PyObject *value;
+  float vec[3], r_vec[3];
 
-	if (!PyArg_ParseTuple(args, "O:cell_vector", &value)) {
-		return NULL;
-	}
+  if (!PyArg_ParseTuple(args, "O:cell_vector", &value)) {
+    return NULL;
+  }
 
-	if (mathutils_array_parse(vec, 3, 3, value, "cell_vector: invalid 'position' arg") == -1) {
-		return NULL;
-	}
+  if (mathutils_array_parse(vec, 3, 3, value, "cell_vector: invalid 'position' arg") == -1) {
+    return NULL;
+  }
 
-	cellNoiseV(vec[0], vec[1], vec[2], r_vec);
-	return Vector_CreatePyObject(r_vec, 3, NULL);
+  cellNoiseV(vec[0], vec[1], vec[2], r_vec);
+  return Vector_CreatePyObject(r_vec, 3, NULL);
 }
 
 static PyMethodDef M_Noise_methods[] = {
-	{"seed_set", (PyCFunction) M_Noise_seed_set, METH_VARARGS, M_Noise_seed_set_doc},
-	{"random", (PyCFunction) M_Noise_random, METH_NOARGS, M_Noise_random_doc},
-	{"random_unit_vector", (PyCFunction) M_Noise_random_unit_vector, METH_VARARGS | METH_KEYWORDS, M_Noise_random_unit_vector_doc},
-	{"random_vector", (PyCFunction) M_Noise_random_vector, METH_VARARGS | METH_KEYWORDS, M_Noise_random_vector_doc},
-	{"noise", (PyCFunction) M_Noise_noise, METH_VARARGS | METH_KEYWORDS, M_Noise_noise_doc},
-	{"noise_vector", (PyCFunction) M_Noise_noise_vector, METH_VARARGS | METH_KEYWORDS, M_Noise_noise_vector_doc},
-	{"turbulence", (PyCFunction) M_Noise_turbulence, METH_VARARGS | METH_KEYWORDS, M_Noise_turbulence_doc},
-	{"turbulence_vector", (PyCFunction) M_Noise_turbulence_vector, METH_VARARGS | METH_KEYWORDS, M_Noise_turbulence_vector_doc},
-	{"fractal", (PyCFunction) M_Noise_fractal, METH_VARARGS | METH_KEYWORDS, M_Noise_fractal_doc},
-	{"multi_fractal", (PyCFunction) M_Noise_multi_fractal, METH_VARARGS | METH_KEYWORDS, M_Noise_multi_fractal_doc},
-	{"variable_lacunarity", (PyCFunction) M_Noise_variable_lacunarity, METH_VARARGS | METH_KEYWORDS, M_Noise_variable_lacunarity_doc},
-	{"hetero_terrain", (PyCFunction) M_Noise_hetero_terrain, METH_VARARGS | METH_KEYWORDS, M_Noise_hetero_terrain_doc},
-	{"hybrid_multi_fractal", (PyCFunction) M_Noise_hybrid_multi_fractal, METH_VARARGS | METH_KEYWORDS, M_Noise_hybrid_multi_fractal_doc},
-	{"ridged_multi_fractal", (PyCFunction) M_Noise_ridged_multi_fractal, METH_VARARGS | METH_KEYWORDS, M_Noise_ridged_multi_fractal_doc},
-	{"voronoi", (PyCFunction) M_Noise_voronoi, METH_VARARGS | METH_KEYWORDS, M_Noise_voronoi_doc},
-	{"cell", (PyCFunction) M_Noise_cell, METH_VARARGS, M_Noise_cell_doc},
-	{"cell_vector", (PyCFunction) M_Noise_cell_vector, METH_VARARGS, M_Noise_cell_vector_doc},
-	{NULL, NULL, 0, NULL},
+    {"seed_set", (PyCFunction)M_Noise_seed_set, METH_VARARGS, M_Noise_seed_set_doc},
+    {"random", (PyCFunction)M_Noise_random, METH_NOARGS, M_Noise_random_doc},
+    {"random_unit_vector",
+     (PyCFunction)M_Noise_random_unit_vector,
+     METH_VARARGS | METH_KEYWORDS,
+     M_Noise_random_unit_vector_doc},
+    {"random_vector",
+     (PyCFunction)M_Noise_random_vector,
+     METH_VARARGS | METH_KEYWORDS,
+     M_Noise_random_vector_doc},
+    {"noise", (PyCFunction)M_Noise_noise, METH_VARARGS | METH_KEYWORDS, M_Noise_noise_doc},
+    {"noise_vector",
+     (PyCFunction)M_Noise_noise_vector,
+     METH_VARARGS | METH_KEYWORDS,
+     M_Noise_noise_vector_doc},
+    {"turbulence",
+     (PyCFunction)M_Noise_turbulence,
+     METH_VARARGS | METH_KEYWORDS,
+     M_Noise_turbulence_doc},
+    {"turbulence_vector",
+     (PyCFunction)M_Noise_turbulence_vector,
+     METH_VARARGS | METH_KEYWORDS,
+     M_Noise_turbulence_vector_doc},
+    {"fractal", (PyCFunction)M_Noise_fractal, METH_VARARGS | METH_KEYWORDS, M_Noise_fractal_doc},
+    {"multi_fractal",
+     (PyCFunction)M_Noise_multi_fractal,
+     METH_VARARGS | METH_KEYWORDS,
+     M_Noise_multi_fractal_doc},
+    {"variable_lacunarity",
+     (PyCFunction)M_Noise_variable_lacunarity,
+     METH_VARARGS | METH_KEYWORDS,
+     M_Noise_variable_lacunarity_doc},
+    {"hetero_terrain",
+     (PyCFunction)M_Noise_hetero_terrain,
+     METH_VARARGS | METH_KEYWORDS,
+     M_Noise_hetero_terrain_doc},
+    {"hybrid_multi_fractal",
+     (PyCFunction)M_Noise_hybrid_multi_fractal,
+     METH_VARARGS | METH_KEYWORDS,
+     M_Noise_hybrid_multi_fractal_doc},
+    {"ridged_multi_fractal",
+     (PyCFunction)M_Noise_ridged_multi_fractal,
+     METH_VARARGS | METH_KEYWORDS,
+     M_Noise_ridged_multi_fractal_doc},
+    {"voronoi", (PyCFunction)M_Noise_voronoi, METH_VARARGS | METH_KEYWORDS, M_Noise_voronoi_doc},
+    {"cell", (PyCFunction)M_Noise_cell, METH_VARARGS, M_Noise_cell_doc},
+    {"cell_vector", (PyCFunction)M_Noise_cell_vector, METH_VARARGS, M_Noise_cell_vector_doc},
+    {NULL, NULL, 0, NULL},
 };
 
 static struct PyModuleDef M_Noise_module_def = {
-	PyModuleDef_HEAD_INIT,
-	"mathutils.noise",  /* m_name */
-	M_Noise_doc,  /* m_doc */
-	0,     /* m_size */
-	M_Noise_methods,  /* m_methods */
-	NULL,  /* m_reload */
-	NULL,  /* m_traverse */
-	NULL,  /* m_clear */
-	NULL,  /* m_free */
+    PyModuleDef_HEAD_INIT,
+    "mathutils.noise", /* m_name */
+    M_Noise_doc,       /* m_doc */
+    0,                 /* m_size */
+    M_Noise_methods,   /* m_methods */
+    NULL,              /* m_reload */
+    NULL,              /* m_traverse */
+    NULL,              /* m_clear */
+    NULL,              /* m_free */
 };
 
 /*----------------------------MODULE INIT-------------------------*/
 PyMODINIT_FUNC PyInit_mathutils_noise(void)
 {
-	PyObject *submodule = PyModule_Create(&M_Noise_module_def);
+  PyObject *submodule = PyModule_Create(&M_Noise_module_def);
 
-	/* use current time as seed for random number generator by default */
-	setRndSeed(0);
+  /* use current time as seed for random number generator by default */
+  setRndSeed(0);
 
-	return submodule;
+  return submodule;
 }