def diff(v):
"""Calculate approximate derivative.
Calculate approximate derivative from v as d = [v_1-v_0, v2-v_1, ...]
Parameters
----------
v : array(N) | pg.R3Vector(N)
Array of double values or positions
Returns
-------
d : [type(v)](N-1) |
derivative array
Examples
--------
>>> import pygimli as pg
>>> from pygimli.utils import diff
>>> p = pg.R3Vector(4)
>>> p[0] = [0.0, 0.0]
>>> p[1] = [0.0, 1.0]
>>> print(diff(p)[0])
RVector3: (0.0, 1.0, 0.0)
>>> print(diff(p)[1])
RVector3: (0.0, -1.0, 0.0)
>>> print(diff(p)[2])
RVector3: (0.0, 0.0, 0.0)
>>> p = pg.RVector(3)
>>> p[0] = 0.0
>>> p[1] = 1.0
>>> p[2] = 2.0
>>> print(diff(p))
2 [1.0, 1.0]
"""
d = None
if isinstance(v, np.ndarray):
if v.ndim == 2:
if v.shape[1] < 4:
# v = pg.R3Vector(v.T)
vt = v.copy()
v = pg.R3Vector(len(vt))
for i, vi in enumerate(vt):
v.setVal(pg.RVector3(vi), i)
else:
v = pg.R3Vector(v)
else:
v = pg.RVector(v)
elif isinstance(v, list):
v = pg.R3Vector(v)
if isinstance(v, pg.R3Vector) or isinstance(v, pg.stdVectorRVector3):
d = pg.R3Vector(len(v) - 1)
else:
d = pg.RVector(len(v) - 1)
for i, _ in enumerate(d):
d[i] = v[i + 1] - v[i]
return d
def test_ListToR3Vector(self):
""" implemented in custom_rvalue.cpp"""
x = [0.0, 1.0, 0.0]
p = pg.RVector3(x)
pl = [p, p, p]
t = pg.R3Vector(pl)
self.assertEqual(t.size(), len(pl))
def test_NumpyToScalar(self):
"""Implemented through automatic iterator """
x = pg.RVector(2)
x3 = pg.R3Vector(2)
w = pg.RVector()
x += np.float32(1.0)
np.testing.assert_equal(sum(x + 1.0), 4.0)
np.testing.assert_equal(sum(x + np.float32(1)), 4.0)
np.testing.assert_equal(sum(x + np.float64(1)), 4.0)
np.testing.assert_equal(sum(x - 1.0), 0.0)
np.testing.assert_equal(sum(x - np.float32(1)), 0.0)
np.testing.assert_equal(sum(x - np.float64(1)), 0.0)
# HarmonicModelling(size_t nh, const RVector & tvec);
pg.HarmonicModelling(np.int32(1), x)
pg.HarmonicModelling(np.uint32(1), x)
pg.HarmonicModelling(np.int64(1), x)
pg.HarmonicModelling(np.uint64(1), x)
# pg.PolynomialModelling(1, np.int32(1), x3, x);
# pg.PolynomialModelling(1, np.int64(1), x3, x);
# pg.PolynomialModelling(1, np.uint32(1), x3, x);
# pg.PolynomialModelling(1, np.uint64(1), x3, x);
x = pg.Pos(0.0, 0.0, 0.0)
x += np.float32(1)
np.testing.assert_equal(x, pg.Pos(1.0, 1.0, 1.0))
np.testing.assert_equal(x - 1, pg.Pos(0.0, 0.0, 0.0))
np.testing.assert_equal(x - np.float32(1), pg.Pos(0.0, 0.0, 0.0))
np.testing.assert_equal(x - np.float64(1), pg.Pos(0.0, 0.0, 0.0))
def test_ListToR3Vector(self):
'''
custom_rvalue.cpp
'''
x = [0.0, 1.0, 0.0]
p = pg.RVector3(x)
pl = [p, p, p]
t = pg.R3Vector(pl)
self.assertEqual(t.size(), len(pl))
def cellDataToBoundaryData(mesh, data):
""" TODO DOCUMENT_ME """
if len(data) != mesh.cellCount():
raise BaseException(
"Dimension mismatch, expecting cellCount(): " +
str(mesh.cellCount()) + "got: " + str(len(data)),
str(len(data[0])))
CtB = mesh.cellToBoundaryInterpolation()
if isinstance(data, pg.R3Vector()):
return np.array([CtB * pg.x(data), CtB * pg.y(data),
CtB * pg.z(data)]).T
else:
return CtB * data
def test_R3VectorIndex(self):
r3 = pg.R3Vector(10)
self.assertEqual(r3[0], pg.RVector3(0))
np.testing.assert_array_equal(r3[0], pg.RVector3(0))
r3[1] = pg.RVector3(0.0, 1.0, 0.0)
np.testing.assert_array_equal(r3[1], pg.RVector3(0.0, 1.0, 0.0))
r3[2] = (0.0, 2.0, 0.0)
np.testing.assert_array_equal(r3[2], pg.RVector3(0.0, 2.0, 0.0))
r3[3] = (0.0, 3.0, 0.0)
np.testing.assert_array_equal(r3[3], pg.RVector3(0.0, 3.0, 0.0))
d = pg.utils.dist(r3)
self.assertEqual(sum(d), 1 + 2 + 3)
