The following are code examples for showing how to use . They are extracted from open source Python projects. You can vote up the examples you like or vote down the exmaples you don’t like. You can also save this page to your account.
Example 1
def get_polar_t(self):
mag = self.get_magnitude()
sizeimg = np.real(self.imgfft).shape
pol = np.zeros(sizeimg)
for x in range(sizeimg[0]):
for y in range(sizeimg[1]):
my = y - sizeimg[1] / 2
mx = x - sizeimg[0] / 2
if mx != 0:
phi = np.arctan(my / float(mx))
else:
phi = 0
r = np.sqrt(mx**2 + my **2)
ix = map_range(phi, -np.pi, np.pi, sizeimg[0], 0)
iy = map_range(r, 0, sizeimg[0], 0, sizeimg[1])
if ix >= 0 and ix < sizeimg[0] and iy >= 0 and iy < sizeimg[1]:
pol[x][y] = mag.data[int(ix)][int(iy)]
pol = MyImage(pol)
pol.limit(1)
return pol Example 2
def calc_IndCurrent_cos_range(self,f,t):
"""Induced current over a range of times"""
Bpx = self.Bpx
Bpz = self.Bpz
a2 = self.a2
azm = np.pi*self.azm/180.
R = self.R
L = self.L
w = 2*np.pi*f
Ax = np.pi*a2**2*np.sin(azm)
Az = np.pi*a2**2*np.cos(azm)
Phi = (Ax*Bpx + Az*Bpz)
phi = np.arctan(R/(w*L))-np.pi # This is the phase and not phase lag
Is = -(w*Phi/(R*np.sin(phi) + w*L*np.cos(phi)))*np.cos(w*t + phi)
Ire = -(w*Phi/(R*np.sin(phi) + w*L*np.cos(phi)))*np.cos(w*t)*np.cos(phi)
Iim = (w*Phi/(R*np.sin(phi) + w*L*np.cos(phi)))*np.sin(w*t)*np.sin(phi)
return Ire,Iim,Is,phi Example 3
def test_branch_cuts_complex64(self):
# check branch cuts and continuity on them
yield _check_branch_cut, np.log, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.log2, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.log10, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.log1p, -1.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.sqrt, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.arcsin, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64
yield _check_branch_cut, np.arccos, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64
yield _check_branch_cut, np.arctan, [0-2j, 2j], [1, 1], -1, 1, True, np.complex64
yield _check_branch_cut, np.arcsinh, [0-2j, 2j], [1, 1], -1, 1, True, np.complex64
yield _check_branch_cut, np.arccosh, [ -1, 0.5], [1j, 1j], 1, -1, True, np.complex64
yield _check_branch_cut, np.arctanh, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64
# check against bogus branch cuts: assert continuity between quadrants
yield _check_branch_cut, np.arcsin, [0-2j, 2j], [ 1, 1], 1, 1, False, np.complex64
yield _check_branch_cut, np.arccos, [0-2j, 2j], [ 1, 1], 1, 1, False, np.complex64
yield _check_branch_cut, np.arctan, [ -2, 2], [1j, 1j], 1, 1, False, np.complex64
yield _check_branch_cut, np.arcsinh, [ -2, 2, 0], [1j, 1j, 1], 1, 1, False, np.complex64
yield _check_branch_cut, np.arccosh, [0-2j, 2j, 2], [1, 1, 1j], 1, 1, False, np.complex64
yield _check_branch_cut, np.arctanh, [0-2j, 2j, 0], [1, 1, 1j], 1, 1, False, np.complex64 Example 4
def test_against_cmath(self):
import cmath
points = [-1-1j, -1+1j, +1-1j, +1+1j]
name_map = {'arcsin': 'asin', 'arccos': 'acos', 'arctan': 'atan',
'arcsinh': 'asinh', 'arccosh': 'acosh', 'arctanh': 'atanh'}
atol = 4*np.finfo(np.complex).eps
for func in self.funcs:
fname = func.__name__.split('.')[-1]
cname = name_map.get(fname, fname)
try:
cfunc = getattr(cmath, cname)
except AttributeError:
continue
for p in points:
a = complex(func(np.complex_(p)))
b = cfunc(p)
assert_(abs(a - b) < atol, "%s %s: %s; cmath: %s" % (fname, p, a, b)) Example 5
def effect(self, point):
res = []
# print(self.centers)
for center in self.centers:
center_x, center_y = center
src_x, src_y = point.pos
# Check angle
angle = np.arctan((center_x - src_x) / (center_y - src_y))
if np.abs(angle) > self.angle / 2:
continue
angle = np.deg2rad(90) + angle
u_len = np.sqrt((center_x - src_x) ** 2 + (center_y - src_y) ** 2)
reverse_v = (self.r_index - 1) / self.radius - self.r_index / u_len
v_len = 1 / reverse_v
if v_len > 0:
p_type = 'real'
else:
p_type = 'fake'
target = line_end(point.pos, angle, u_len + v_len)
p = Point(target, p_type, 1)
# point.passed.append(self)
res.append(p)
return tuple(res) Example 6
def _radian_direction(dy,dx):
'''
function:
- based on given dy and dx it calculates direction in radian.
- used in feature_eng_pt3
input:
dy = change in y
dx = change in x
output:
returns radian value (0 to 6.28)
'''
if dy < 0.0 and dx > 0.0:
return (2*np.pi + np.arctan(dy/dx))
elif dy >=0.0 and dx > 0.0:
return (np.arctan(dy/dx))
else:
return np.pi + np.arctan(dy/dx) Example 7
def flow(self, Kc, Ks, Kz, Ka, numexpr):
zeros = np.zeros
where = np.where
min = np.minimum
max = np.maximum
abs = np.absolute
arctan = np.arctan
sin = np.sin
center = (slice( 1, -1,None),slice( 1, -1,None))
rock = self.center
ds = self.scour[center]
rcc = rock[center]
rock[center] = rcc - ds * Kz
# there isn't really a bottom to the rock but negative values look ugly
rock[center] = where(rcc<0,0,rcc) Example 8
def fixOffset(self, offset, img):
size = img.shape
finalImg = np.ndarray(size)
indices = np.indices((self.videoSize[0],self.videoSize[1])).swapaxes(0,2).swapaxes(0,1)
indices = np.around(indices, decimals=1)
indices.shape = (self.videoSize[1] * self.videoSize[0], 2)
phi = 2 * np.arctan(np.exp(indices[:, 1] / self.videoSize[1])) - 1/2 * np.pi - offset[0]
lamb = indices[:, 0] - offset[1]
x = lamb
y = np.log(np.tan(np.pi / 4 + 1/2 * phi)) * self.videoSize[1]
finalIdx = np.ndarray((self.videoSize[1] * self.videoSize[0], 2))
finalIdx = np.around(finalIdx, decimals=1).astype(int)
finalIdx[:, 1] = y % self.videoSize[1]
finalIdx[:, 0] = x % self.videoSize[0]
finalImg[indices[:,1], indices[:,0]] = img[finalIdx[:,1], finalIdx[:,0]]
return finalImg Example 9
def _dip_slip_y(self, y1, y2, ang_dip, q):
"""
Based on Okada's paper (1985)
y = down-dip direction
"""
sn = numpy.sin(ang_dip)
cs = numpy.cos(ang_dip)
d_bar = y2*sn - q*cs;
r = numpy.sqrt(y1**2 + y2**2 + q**2)
xx = numpy.sqrt(y1**2 + q**2)
y_bar = y2*cs + q*sn
a5 = 4.*poisson/cs*numpy.arctan((y2*(xx+q*cs)+xx*(r+xx)*sn)/y1/(r+xx)/cs)
a1 = 2.0*poisson*(-y1/(cs*(r+d_bar))) - sn/cs * a5
f = -(y_bar*q/r/(r+y1) + cs*numpy.arctan(y1*y2/q/r) - a1*sn*cs)/(2.0*3.14159)
return f Example 10
def _dip_slip_x(self, y1, y2, ang_dip, q):
"""
Based on Okada's paper (1985)
Added by Xiaoming Wang
"""
sn = numpy.sin(ang_dip)
cs = numpy.cos(ang_dip)
d_bar = y2*sn - q*cs;
r = numpy.sqrt(y1**2 + y2**2 + q**2)
xx = numpy.sqrt(y1**2 + q**2)
#a5 = 4.*poisson/cs*numpy.arctan((y2*(xx+q*cs)+xx*(r+xx)*sn)/y1/(r+xx)/cs)
a4 = 2.0*poisson/cs*(numpy.log(r+d_bar) - sn*numpy.log(r+y2))
ytilde = y2*cs + q*sn
a3 = 2.0*poisson*(ytilde/(cs*(r+d_bar)) - numpy.log(r+y2)) + a4*sn/cs
f = -(q/r - a3*sn*cs)/(2.0*3.14159)
return f Example 11
def _dip_slip_x(self, y1, y2, ang_dip, q):
"""
Based on Okada's paper (1985)
Added by Xiaoming Wang
"""
sn = numpy.sin(ang_dip)
cs = numpy.cos(ang_dip)
d_bar = y2*sn - q*cs;
r = numpy.sqrt(y1**2 + y2**2 + q**2)
xx = numpy.sqrt(y1**2 + q**2)
#a5 = 4.*poisson/cs*numpy.arctan((y2*(xx+q*cs)+xx*(r+xx)*sn)/y1/(r+xx)/cs)
a4 = 2.0*poisson/cs*(numpy.log(r+d_bar) - sn*numpy.log(r+y2))
ytilde = y2*cs + q*sn
a3 = 2.0*poisson*(ytilde/(cs*(r+d_bar)) - numpy.log(r+y2)) + a4*sn/cs
f = -(q/r - a3*sn*cs)/(2.0*3.14159)
return f Example 12
def get_q_per_pixel(self):
'''Gets the delta-q associated with a single pixel. This is computed in
the small-angle limit, so it should only be considered approximate.
For instance, wide-angle detectors will have different delta-q across
the detector face.'''
if self.q_per_pixel is not None:
return self.q_per_pixel
c = (self.pixel_size_um/1e6)/self.distance_m
twotheta = np.arctan(c) # radians
self.q_per_pixel = 2.0*self.get_k()*np.sin(twotheta/2.0)
return self.q_per_pixel
# Maps
######################################## Example 13
def reset_model(self):
self._min_strike_dist = np.inf
self._striked = False
self._strike_pos = None
qpos = self.init_qpos
self.ball = np.array([0.5, -0.175])
while True:
self.goal = np.concatenate([
self.np_random.uniform(low=0.15, high=0.7, size=1),
self.np_random.uniform(low=0.1, high=1.0, size=1)])
if np.linalg.norm(self.ball - self.goal) > 0.17:
break
qpos[-9:-7] = [self.ball[1], self.ball[0]]
qpos[-7:-5] = self.goal
diff = self.ball - self.goal
angle = -np.arctan(diff[0] / (diff[1] + 1e-8))
qpos[-1] = angle / 3.14
qvel = self.init_qvel + self.np_random.uniform(low=-.1, high=.1,
size=self.model.nv)
qvel[7:] = 0
self.set_state(qpos, qvel)
return self._get_obs() Example 14
def test_branch_cuts_complex64(self):
# check branch cuts and continuity on them
yield _check_branch_cut, np.log, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.log2, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.log10, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.log1p, -1.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.sqrt, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.arcsin, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64
yield _check_branch_cut, np.arccos, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64
yield _check_branch_cut, np.arctan, [0-2j, 2j], [1, 1], -1, 1, True, np.complex64
yield _check_branch_cut, np.arcsinh, [0-2j, 2j], [1, 1], -1, 1, True, np.complex64
yield _check_branch_cut, np.arccosh, [ -1, 0.5], [1j, 1j], 1, -1, True, np.complex64
yield _check_branch_cut, np.arctanh, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64
# check against bogus branch cuts: assert continuity between quadrants
yield _check_branch_cut, np.arcsin, [0-2j, 2j], [ 1, 1], 1, 1, False, np.complex64
yield _check_branch_cut, np.arccos, [0-2j, 2j], [ 1, 1], 1, 1, False, np.complex64
yield _check_branch_cut, np.arctan, [ -2, 2], [1j, 1j], 1, 1, False, np.complex64
yield _check_branch_cut, np.arcsinh, [ -2, 2, 0], [1j, 1j, 1], 1, 1, False, np.complex64
yield _check_branch_cut, np.arccosh, [0-2j, 2j, 2], [1, 1, 1j], 1, 1, False, np.complex64
yield _check_branch_cut, np.arctanh, [0-2j, 2j, 0], [1, 1, 1j], 1, 1, False, np.complex64 Example 15
def test_against_cmath(self):
import cmath
points = [-1-1j, -1+1j, +1-1j, +1+1j]
name_map = {'arcsin': 'asin', 'arccos': 'acos', 'arctan': 'atan',
'arcsinh': 'asinh', 'arccosh': 'acosh', 'arctanh': 'atanh'}
atol = 4*np.finfo(np.complex).eps
for func in self.funcs:
fname = func.__name__.split('.')[-1]
cname = name_map.get(fname, fname)
try:
cfunc = getattr(cmath, cname)
except AttributeError:
continue
for p in points:
a = complex(func(np.complex_(p)))
b = cfunc(p)
assert_(abs(a - b) < atol, "%s %s: %s; cmath: %s" % (fname, p, a, b)) Example 16
def angularpixelarea(self):
# get the first instrument element
instruments = self.tree.xpath("//instruments/*[1]")
if len(instruments) != 1: raise ValueError("No instruments in ski file")
instrument = instruments[0]
# get the distance in m
d = self.units().convert(instrument.get("distance"), to_unit='m', quantity='distance')
# get the field of view in m
fovx = self.units().convert(instrument.get("fieldOfViewX"), to_unit='m', quantity='length')
fovy = self.units().convert(instrument.get("fieldOfViewY"), to_unit='m', quantity='length')
# get the number of pixels
nx = int(instrument.get("pixelsX"))
ny = int(instrument.get("pixelsY"))
# calculate the angular pixel area
sx = 2 * arctan(fovx / nx / d / 2)
sy = 2 * arctan(fovy / ny / d / 2)
return sx * sy
## This function returns a list of instrument names, in order of occurrence in the ski file. Example 17
def orientation_angle(self):
"""
This function ...
:return:
"""
diag_a = self.pixel_scale_matrix[0,1]
diag_b = self.pixel_scale_matrix[1,0]
if not np.isclose(diag_a, diag_b, rtol=0.05):
warnings.warn("The diagonal elements of the pixel scale matrix are not equal: " + repr(diag_a) + " and " + repr(diag_b))
first = self.pixel_scale_matrix[0,0]
radians = np.arctan(diag_a / first)
degrees = radians / math.pi * 180.
return Angle(degrees, "deg")
# ----------------------------------------------------------------- Example 18
def angularpixelarea(self):
# get the first instrument element
instruments = self.tree.xpath("//instruments/*[1]")
if len(instruments) != 1: raise ValueError("No instruments in ski file")
instrument = instruments[0]
# get the distance in m
d = self.units().convert(instrument.get("distance"), to_unit='m', quantity='distance')
# get the field of view in m
fovx = self.units().convert(instrument.get("fieldOfViewX"), to_unit='m', quantity='length')
fovy = self.units().convert(instrument.get("fieldOfViewY"), to_unit='m', quantity='length')
# get the number of pixels
nx = int(instrument.get("pixelsX"))
ny = int(instrument.get("pixelsY"))
# calculate the angular pixel area
sx = 2 * arctan(fovx / nx / d / 2)
sy = 2 * arctan(fovy / ny / d / 2)
return sx * sy
## This function returns a list of instrument names, in order of occurrence in the ski file. Example 19
def orientation_angle(self):
"""
This function ...
:return:
"""
diag_a = self.pixel_scale_matrix[0,1]
diag_b = self.pixel_scale_matrix[1,0]
if not np.isclose(diag_a, diag_b, rtol=0.05):
warnings.warn("The diagonal elements of the pixel scale matrix are not equal: " + repr(diag_a) + " and " + repr(diag_b))
first = self.pixel_scale_matrix[0,0]
radians = np.arctan(diag_a / first)
degrees = radians / math.pi * 180.
return Angle(degrees, "deg")
# ----------------------------------------------------------------- Example 20
def conferenceWakeOverlap(X, Y, R):
n = np.size(X)
# theta = np.zeros((n, n), dtype=np.float) # angle of wake from fulcrum
f_theta = np.zeros((n, n), dtype=np.float) # smoothing values for smoothing
for i in range(0, n):
for j in range(0, n):
if X[i] < X[j]:
z = R/np.tan(0.34906585)
# print z
theta = np.arctan((Y[j] - Y[i]) / (X[j] - X[i] + z))
# print 'theta =', theta
if -0.34906585 < theta < 0.34906585:
f_theta[i][j] = (1 + np.cos(9*theta))/2
# print f_theta
# print z
# print f_theta
return f_theta Example 21
def conferenceWakeOverlap_tune(X, Y, R, boundAngle):
n = np.size(X)
boundAngle = boundAngle*np.pi/180.0
# theta = np.zeros((n, n), dtype=np.float) # angle of wake from fulcrum
f_theta = np.zeros((n, n), dtype=np.float) # smoothing values for smoothing
q = np.pi/boundAngle # factor inside the cos term of the smooth Jensen (see Jensen1983 eq.(3))
# print 'boundAngle = %s' %boundAngle, 'q = %s' %q
for i in range(0, n):
for j in range(0, n):
if X[i] < X[j]:
# z = R/tan(0.34906585)
z = R/np.tan(boundAngle) # distance from fulcrum to wake producing turbine
# print z
theta = np.arctan((Y[j] - Y[i]) / (X[j] - X[i] + z))
# print 'theta =', theta
if -boundAngle < theta < boundAngle:
f_theta[i][j] = (1. + np.cos(q*theta))/2.
# print f_theta
# print z
# print f_theta
return f_theta Example 22
def get_cosine_factor_original(X, Y, R0, bound_angle=20.0):
n = np.size(X)
bound_angle = bound_angle*np.pi/180.0
# theta = np.zeros((n, n), dtype=np.float) # angle of wake from fulcrum
f_theta = np.zeros((n, n), dtype=np.float) # smoothing values for smoothing
q = np.pi/bound_angle # factor inside the cos term of the smooth Jensen (see Jensen1983 eq.(3))
for i in range(0, n):
for j in range(0, n):
if X[i] < X[j]:
z = R0/np.tan(bound_angle) # distance from fulcrum to wake producing turbine
theta = np.arctan((Y[j] - Y[i]) / (X[j] - X[i] + z))
if -bound_angle < theta < bound_angle:
f_theta[i][j] = (1. + np.cos(q*theta))/2.
return f_theta Example 23
def rotate(self,rotation_method='RTZ'):
####################################################################################
#rotate-------------------------------------------------------------------------
for i in range(0,len(self.rf_st)):
self.rf_st[i].stats.back_azimuth = self.tr_e.stats.sac['baz']
self.rf_st.rotate(method='NE->RT')
if rotation_method == 'LQT':
r_amp = np.amax(np.amax(self.rf_st[1].data))
z_amp = np.amax(np.amax(self.rf_st[2].data))
incidence_angle = np.arctan(r_amp/z_amp) * (180.0/np.pi)
for i in range(0,len(self.rf_st)):
self.rf_st[i].stats.inclination = incidence_angle
self.rf_st.rotate(method='RT->NE')
self.rf_st.rotate(method='ZNE->LQT')
#################################################################################### Example 24
def test_branch_cuts(self):
# check branch cuts and continuity on them
yield _check_branch_cut, np.log, -0.5, 1j, 1, -1, True
yield _check_branch_cut, np.log2, -0.5, 1j, 1, -1, True
yield _check_branch_cut, np.log10, -0.5, 1j, 1, -1, True
yield _check_branch_cut, np.log1p, -1.5, 1j, 1, -1, True
yield _check_branch_cut, np.sqrt, -0.5, 1j, 1, -1, True
yield _check_branch_cut, np.arcsin, [ -2, 2], [1j, 1j], 1, -1, True
yield _check_branch_cut, np.arccos, [ -2, 2], [1j, 1j], 1, -1, True
yield _check_branch_cut, np.arctan, [0-2j, 2j], [1, 1], -1, 1, True
yield _check_branch_cut, np.arcsinh, [0-2j, 2j], [1, 1], -1, 1, True
yield _check_branch_cut, np.arccosh, [ -1, 0.5], [1j, 1j], 1, -1, True
yield _check_branch_cut, np.arctanh, [ -2, 2], [1j, 1j], 1, -1, True
# check against bogus branch cuts: assert continuity between quadrants
yield _check_branch_cut, np.arcsin, [0-2j, 2j], [ 1, 1], 1, 1
yield _check_branch_cut, np.arccos, [0-2j, 2j], [ 1, 1], 1, 1
yield _check_branch_cut, np.arctan, [ -2, 2], [1j, 1j], 1, 1
yield _check_branch_cut, np.arcsinh, [ -2, 2, 0], [1j, 1j, 1], 1, 1
yield _check_branch_cut, np.arccosh, [0-2j, 2j, 2], [1, 1, 1j], 1, 1
yield _check_branch_cut, np.arctanh, [0-2j, 2j, 0], [1, 1, 1j], 1, 1 Example 25
def test_branch_cuts_complex64(self):
# check branch cuts and continuity on them
yield _check_branch_cut, np.log, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.log2, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.log10, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.log1p, -1.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.sqrt, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.arcsin, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64
yield _check_branch_cut, np.arccos, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64
yield _check_branch_cut, np.arctan, [0-2j, 2j], [1, 1], -1, 1, True, np.complex64
yield _check_branch_cut, np.arcsinh, [0-2j, 2j], [1, 1], -1, 1, True, np.complex64
yield _check_branch_cut, np.arccosh, [ -1, 0.5], [1j, 1j], 1, -1, True, np.complex64
yield _check_branch_cut, np.arctanh, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64
# check against bogus branch cuts: assert continuity between quadrants
yield _check_branch_cut, np.arcsin, [0-2j, 2j], [ 1, 1], 1, 1, False, np.complex64
yield _check_branch_cut, np.arccos, [0-2j, 2j], [ 1, 1], 1, 1, False, np.complex64
yield _check_branch_cut, np.arctan, [ -2, 2], [1j, 1j], 1, 1, False, np.complex64
yield _check_branch_cut, np.arcsinh, [ -2, 2, 0], [1j, 1j, 1], 1, 1, False, np.complex64
yield _check_branch_cut, np.arccosh, [0-2j, 2j, 2], [1, 1, 1j], 1, 1, False, np.complex64
yield _check_branch_cut, np.arctanh, [0-2j, 2j, 0], [1, 1, 1j], 1, 1, False, np.complex64 Example 26
def test_against_cmath(self):
import cmath
points = [-1-1j, -1+1j, +1-1j, +1+1j]
name_map = {'arcsin': 'asin', 'arccos': 'acos', 'arctan': 'atan',
'arcsinh': 'asinh', 'arccosh': 'acosh', 'arctanh': 'atanh'}
atol = 4*np.finfo(np.complex).eps
for func in self.funcs:
fname = func.__name__.split('.')[-1]
cname = name_map.get(fname, fname)
try:
cfunc = getattr(cmath, cname)
except AttributeError:
continue
for p in points:
a = complex(func(np.complex_(p)))
b = cfunc(p)
assert_(abs(a - b) < atol, "%s %s: %s; cmath: %s" % (fname, p, a, b)) Example 27
def test_branch_cuts_complex64(self):
# check branch cuts and continuity on them
yield _check_branch_cut, np.log, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.log2, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.log10, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.log1p, -1.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.sqrt, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.arcsin, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64
yield _check_branch_cut, np.arccos, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64
yield _check_branch_cut, np.arctan, [0-2j, 2j], [1, 1], -1, 1, True, np.complex64
yield _check_branch_cut, np.arcsinh, [0-2j, 2j], [1, 1], -1, 1, True, np.complex64
yield _check_branch_cut, np.arccosh, [ -1, 0.5], [1j, 1j], 1, -1, True, np.complex64
yield _check_branch_cut, np.arctanh, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64
# check against bogus branch cuts: assert continuity between quadrants
yield _check_branch_cut, np.arcsin, [0-2j, 2j], [ 1, 1], 1, 1, False, np.complex64
yield _check_branch_cut, np.arccos, [0-2j, 2j], [ 1, 1], 1, 1, False, np.complex64
yield _check_branch_cut, np.arctan, [ -2, 2], [1j, 1j], 1, 1, False, np.complex64
yield _check_branch_cut, np.arcsinh, [ -2, 2, 0], [1j, 1j, 1], 1, 1, False, np.complex64
yield _check_branch_cut, np.arccosh, [0-2j, 2j, 2], [1, 1, 1j], 1, 1, False, np.complex64
yield _check_branch_cut, np.arctanh, [0-2j, 2j, 0], [1, 1, 1j], 1, 1, False, np.complex64 Example 28
def test_against_cmath(self):
import cmath
points = [-1-1j, -1+1j, +1-1j, +1+1j]
name_map = {'arcsin': 'asin', 'arccos': 'acos', 'arctan': 'atan',
'arcsinh': 'asinh', 'arccosh': 'acosh', 'arctanh': 'atanh'}
atol = 4*np.finfo(np.complex).eps
for func in self.funcs:
fname = func.__name__.split('.')[-1]
cname = name_map.get(fname, fname)
try:
cfunc = getattr(cmath, cname)
except AttributeError:
continue
for p in points:
a = complex(func(np.complex_(p)))
b = cfunc(p)
assert_(abs(a - b) < atol, "%s %s: %s; cmath: %s" % (fname, p, a, b)) Example 29
def arrow(img,p1,p2):
cv2.line(s1,p1,p2,(100,255,100),thickness=2)
cv2.line(s2,p1,p2,(100,255,100),thickness=2)
dy,dx= np.array(p2)-np.array(p1)
theta= np.arctan(dy/dx) + (0 if dx>0 else np.pi) if dx!=0 else (1 if dy>0 else -1) * np.pi/2
phy1=theta+ np.pi*7/6
phy2=theta+ np.pi*5/6
R=0.4*np.linalg.norm([dx,dy])
dx1,dx2= (R*np.cos([phy1,phy2])).astype(np.int)
dy1,dy2= (R*np.sin([phy1,phy2])).astype(np.int)
if R<=2:return
Y1,X1=p1
Y2,X2=p2
cv2.line(s1,(dy1+Y2,dx1+X2),p2,(100,255,100),thickness=1)
cv2.line(s1,(dy2+Y2,dx2+X2),p2,(100,255,100),thickness=1)
cv2.line(s2,(dy1+Y2,dx1+X2),p2,(100,255,100),thickness=1)
cv2.line(s2,(dy2+Y2,dx2+X2),p2,(100,255,100),thickness=1)
#???????????????? Example 30
def convertToOpenGLCameraMatrix(K, framebufferSize, near, far):
""" Convert a camera calibration matrix into OpenGL format. """
width, height = framebufferSize
# print 'framebufferSize:', framebufferSize
fx = K[0,0]
fy = K[1,1]
fovy = 2*np.arctan(0.5*height/fy)#*180/np.pi
aspect = (width*fy)/(height*fx)
# define the near and far clipping planes
# near = 0.1
# far = 100.0
# fx = 10.0
# fy = 10.0
# fovy = 90*(np.pi/180.0)
# aspect = (width*fy)/(height*fx)
proj = openGLPerspectiveMatrix(fovy,aspect,near,far)
return proj Example 31
def test_auto_size_bits_list():
pytest.skip()
a = [0.5, 1.2, 3.2]
b = Sfix.auto_size(a, 18)
for x, y in zip(a, b):
np.isclose(y.val, x)
assert y.left == 2
assert y.right == -15
a = [np.arctan(2 ** -i) for i in range(8)]
b = Sfix.auto_size(a, 18)
for x, y in zip(a, b):
np.isclose(y.val, x)
assert y.left == 0
assert y.right == -17
a = [np.arctan(2 ** -i) for i in range(8, 12)]
b = Sfix.auto_size(a, 18)
for x, y in zip(a, b):
np.isclose(y.val, x)
assert y.left == -8
assert y.right == -25 Example 32
def load(self, ips):
if ips.imgtype in ('8-bit', 'rgb'):
self.para = {'bright':0, 'contrast':45}
self.view = [('slide', (-100,100), 'Brightness', 'bright', ''),
('slide', (1,89), 'Contrast', 'contrast', '')]
if 'not_slice' in self.note:
self.note.remove('not_slice')
else :
self.arange = minv, maxv = ips.img.min(), ips.img.max()
self.para = {'bright':np.mean(ips.range) - np.mean(self.arange),
'contrast':round(np.arctan((maxv-minv)/(ips.range[1]-ips.range[0]))/np.pi*180)}
self.view = [('slide', (-(maxv-minv)/2, (maxv-minv)/2), 'Brightness', 'bright', ''),
('slide', (1,89), 'Contrast', 'contrast', '')]
if not 'not_slice' in self.note:
self.note.append('not_slice')
return True Example 33
def reset_model(self):
self._min_strike_dist = np.inf
self._striked = False
self._strike_pos = None
qpos = self.init_qpos
self.ball = np.array([0.5, -0.175])
while True:
self.goal = np.concatenate([
self.np_random.uniform(low=0.15, high=0.7, size=1),
self.np_random.uniform(low=0.1, high=1.0, size=1)])
if np.linalg.norm(self.ball - self.goal) > 0.17:
break
qpos[-9:-7] = [self.ball[1], self.ball[0]]
qpos[-7:-5] = self.goal
diff = self.ball - self.goal
angle = -np.arctan(diff[0] / (diff[1] + 1e-8))
qpos[-1] = angle / 3.14
qvel = self.init_qvel + self.np_random.uniform(low=-.1, high=.1,
size=self.model.nv)
qvel[7:] = 0
self.set_state(qpos, qvel)
return self._get_obs() Example 34
def FitPCA(self, hPCA_Proj):
'''
Determine the timing of the inflation event.
Uses the first component of the pca projection and
fits A * arctan( (t - t0) / c ) + B to the first pca projection.
@param hPCA_Proj: The sklearn PCA projection
@return [t0, c]
'''
fitfunc = lambda p,t: p[0]*np.arctan((t-p[1])/p[2])+p[3]
errfunc = lambda p,x,y: fitfunc(p,x) - y
dLen = len(hPCA_Proj[:,0])
pA, success = optimize.leastsq(errfunc,[1.,dLen/2.,1.,0.],args=(np.arange(dLen),hPCA_Proj[:,0]))
ct = pA[1:3]
return ct, pA[0] Example 35
def FitPCA(self, hPCA_Proj):
'''
Determine the timing of the inflation event from the first component of the pca projection
fits A * arctan( (t - t0) / c ) + B to the first pca projection, in order to estimate
source amplitude parameters
@param hPCA_Proj: The sklearn PCA
@return ct: the t0, c, and B parameters from the fit
@return pA[0]: the fitted amplitude parameter
'''
fitfunc = lambda p,t: p[0]*np.arctan((t-p[1])/p[2])+p[3]
errfunc = lambda p,x,y: fitfunc(p,x) - y
dLen = len(hPCA_Proj[:,0])
pA, success = optimize.leastsq(errfunc,[1.,dLen/2.,1.,0.],args=(np.arange(dLen),hPCA_Proj[:,0]))
ct = pA[1:3]
return ct, pA[0] Example 36
def test_branch_cuts_complex64(self):
# check branch cuts and continuity on them
yield _check_branch_cut, np.log, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.log2, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.log10, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.log1p, -1.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.sqrt, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.arcsin, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64
yield _check_branch_cut, np.arccos, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64
yield _check_branch_cut, np.arctan, [0-2j, 2j], [1, 1], -1, 1, True, np.complex64
yield _check_branch_cut, np.arcsinh, [0-2j, 2j], [1, 1], -1, 1, True, np.complex64
yield _check_branch_cut, np.arccosh, [ -1, 0.5], [1j, 1j], 1, -1, True, np.complex64
yield _check_branch_cut, np.arctanh, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64
# check against bogus branch cuts: assert continuity between quadrants
yield _check_branch_cut, np.arcsin, [0-2j, 2j], [ 1, 1], 1, 1, False, np.complex64
yield _check_branch_cut, np.arccos, [0-2j, 2j], [ 1, 1], 1, 1, False, np.complex64
yield _check_branch_cut, np.arctan, [ -2, 2], [1j, 1j], 1, 1, False, np.complex64
yield _check_branch_cut, np.arcsinh, [ -2, 2, 0], [1j, 1j, 1], 1, 1, False, np.complex64
yield _check_branch_cut, np.arccosh, [0-2j, 2j, 2], [1, 1, 1j], 1, 1, False, np.complex64
yield _check_branch_cut, np.arctanh, [0-2j, 2j, 0], [1, 1, 1j], 1, 1, False, np.complex64 Example 37
def test_against_cmath(self):
import cmath
points = [-1-1j, -1+1j, +1-1j, +1+1j]
name_map = {'arcsin': 'asin', 'arccos': 'acos', 'arctan': 'atan',
'arcsinh': 'asinh', 'arccosh': 'acosh', 'arctanh': 'atanh'}
atol = 4*np.finfo(np.complex).eps
for func in self.funcs:
fname = func.__name__.split('.')[-1]
cname = name_map.get(fname, fname)
try:
cfunc = getattr(cmath, cname)
except AttributeError:
continue
for p in points:
a = complex(func(np.complex_(p)))
b = cfunc(p)
assert_(abs(a - b) < atol, "%s %s: %s; cmath: %s" % (fname, p, a, b)) Example 38
def compute_pd_control(self):
if self.received_data:
# given the computed wall slope, compute theta, avoid divide by zero error
if np.abs(self.m) < EPSILON:
theta = np.pi / 2.0
x_intercept = 0
else:
theta = np.arctan(1.0/self.m)
# solve for y=0 in y=mx+c
x_intercept = self.c / self.m
# x axis is perp. to robot but not perpindicular to wall
# cosine term solves for minimum distance to wall
wall_dist = np.abs(np.cos(theta)*x_intercept)
# control proportional to angular error and distance from wall
distance_term = self.direction_muliplier * KP * (wall_dist - TARGET_DISTANCE)
angle_term = KD * theta
control = angle_term + distance_term
# avoid turning too sharply
self.control = (np.clip(control, -0.3, 0.3), SPEED) Example 39
def rotate_image(img_src, angle,scale ,crop=True):
img_src,size_dest= pad_image(img_src,scale)
size = tuple(np.array([img_src.shape[1], img_src.shape[0]]))
org_h=size[1]
org_w=size[0]
src_r = np.sqrt((size[0]/2.0)**2+(size[1]/2.0)**2)
org_angle =np.arctan(float(org_h)/org_w)
dest_h = size_dest[0]
dest_w = size_dest[1]
center = tuple(np.array([img_src.shape[1] * 0.5, img_src.shape[0] * 0.5]))
dsize= (dest_w,dest_h)
rotation_matrix = cv2.getRotationMatrix2D(center, angle, scale)
img_rot = cv2.warpAffine(img_src, rotation_matrix, size, flags=cv2.INTER_CUBIC)
if crop:
x,y,w,h = cv2.boundingRect(img_rot[:,:,3])
return img_rot[y:y+h, x:x+w,:]
else:
return img_rot Example 40
def rotate_image(img_src, angle,scale ):
img_src,size_dest= pad_image(img_src,scale)
size = tuple(np.array([img_src.shape[1], img_src.shape[0]]))
org_h=size[1]
org_w=size[0]
src_r = np.sqrt((size[0]/2.0)**2+(size[1]/2.0)**2)
org_angle =np.arctan(float(org_h)/org_w)
dest_h = size_dest[0]
dest_w = size_dest[1]
center = tuple(np.array([img_src.shape[1] * 0.5, img_src.shape[0] * 0.5]))
dsize= (dest_w,dest_h)
rotation_matrix = cv2.getRotationMatrix2D(center, angle, scale)
img_rot = cv2.warpAffine(img_src, rotation_matrix, size, flags=cv2.INTER_CUBIC)
x,y,w,h = cv2.boundingRect(img_rot[:,:,3])
return img_rot[y:y+h, x:x+w,:] Example 41
def test_branch_cuts_complex64(self):
# check branch cuts and continuity on them
yield _check_branch_cut, np.log, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.log2, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.log10, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.log1p, -1.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.sqrt, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.arcsin, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64
yield _check_branch_cut, np.arccos, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64
yield _check_branch_cut, np.arctan, [0-2j, 2j], [1, 1], -1, 1, True, np.complex64
yield _check_branch_cut, np.arcsinh, [0-2j, 2j], [1, 1], -1, 1, True, np.complex64
yield _check_branch_cut, np.arccosh, [ -1, 0.5], [1j, 1j], 1, -1, True, np.complex64
yield _check_branch_cut, np.arctanh, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64
# check against bogus branch cuts: assert continuity between quadrants
yield _check_branch_cut, np.arcsin, [0-2j, 2j], [ 1, 1], 1, 1, False, np.complex64
yield _check_branch_cut, np.arccos, [0-2j, 2j], [ 1, 1], 1, 1, False, np.complex64
yield _check_branch_cut, np.arctan, [ -2, 2], [1j, 1j], 1, 1, False, np.complex64
yield _check_branch_cut, np.arcsinh, [ -2, 2, 0], [1j, 1j, 1], 1, 1, False, np.complex64
yield _check_branch_cut, np.arccosh, [0-2j, 2j, 2], [1, 1, 1j], 1, 1, False, np.complex64
yield _check_branch_cut, np.arctanh, [0-2j, 2j, 0], [1, 1, 1j], 1, 1, False, np.complex64 Example 42
def test_against_cmath(self):
import cmath
points = [-1-1j, -1+1j, +1-1j, +1+1j]
name_map = {'arcsin': 'asin', 'arccos': 'acos', 'arctan': 'atan',
'arcsinh': 'asinh', 'arccosh': 'acosh', 'arctanh': 'atanh'}
atol = 4*np.finfo(np.complex).eps
for func in self.funcs:
fname = func.__name__.split('.')[-1]
cname = name_map.get(fname, fname)
try:
cfunc = getattr(cmath, cname)
except AttributeError:
continue
for p in points:
a = complex(func(np.complex_(p)))
b = cfunc(p)
assert_(abs(a - b) < atol, "%s %s: %s; cmath: %s" % (fname, p, a, b)) Example 43
def arctan_func(xvals, a, b, c):
'''
--------------------------------------------------------------------
This function generates predicted ability levels given data (xvals)
and parameters a, b, and c, from the following arctan function:
y = (-a / pi) * arctan(b * x + c) + (a / 2)
--------------------------------------------------------------------
INPUTS:
xvals = (N,) vector, data inputs to arctan function
a = scalar, scale parameter for arctan function
b = scalar, curvature parameter for arctan function
c = scalar, shift parameter for arctan function
OTHER FUNCTIONS AND FILES CALLED BY THIS FUNCTION: None
OBJECTS CREATED WITHIN FUNCTION:
yvals = (N,) vector, predicted values (output) of arctan function
RETURNS: yvals
--------------------------------------------------------------------
'''
yvals = (-a / np.pi) * np.arctan(b * xvals + c) + (a / 2)
return yvals Example 44
def arctan_func(xvals, a, b, c):
'''
--------------------------------------------------------------------
This function generates predicted ability levels given data (xvals)
and parameters a, b, and c, from the following arctan function:
y = (-a / pi) * arctan(b * x + c) + (a / 2)
--------------------------------------------------------------------
INPUTS:
xvals = (N,) vector, data inputs to arctan function
a = scalar, scale parameter for arctan function
b = scalar, curvature parameter for arctan function
c = scalar, shift parameter for arctan function
OTHER FUNCTIONS AND FILES CALLED BY THIS FUNCTION: None
OBJECTS CREATED WITHIN FUNCTION:
yvals = (N,) vector, predicted values (output) of arctan function
RETURNS: yvals
--------------------------------------------------------------------
'''
yvals = (-a / np.pi) * np.arctan(b * xvals + c) + (a / 2)
return yvals Example 45
def fov(self):
"""
Returns the field of view for each axis
"""
return np.float32([np.arctan(self.shape[1] * 0.5 / self.fx),
np.arctan(self.shape[0] * 0.5 / self.fy)]) * 2.0 Example 46
def dynamics(q, u, p):
"""
Returns state derivative qdot.
Takes current state q, motor input torque u, and disturbance torque p.
See <http://renaissance.ucsd.edu/courses/mae143c/MIPdynamics.pdf> (rederived with incline).
"""
# Angle of pendulum in incline frame
ang = q[2] - incline
# Mass matrix
M = np.array([
[(mass_wheel + mass_pend)*radius**2 + inertia_wheel, mass_pend*radius*cw_to_cm[1]*np.cos(ang)],
[mass_pend*radius*cw_to_cm[1]*np.cos(ang), inertia_pend + mass_pend*cw_to_cm[1]**2]
])
# Gravity effect
g = np.array([
-mass_pend*radius*cw_to_cm[1]*q[3]**2*np.sin(ang) + mass_wheel*radius*gravity[1]*np.sin(incline),
mass_pend*gravity[1]*cw_to_cm[1]*np.sin(q[2])
])
# Friction force
d = np.array([
-friction_wheel * (q[1] + np.arctan(q[1])),
friction_pend * q[3]
])
# Dynamics
accel_wheel_neg, accel_pend = npl.inv(M).dot(np.array([-u, p+u]) - g - d)
return np.array([q[1], -accel_wheel_neg*radius, q[3], accel_pend])
################################################# SIMULATION
# Define time domain Example 47
def cart2sph(x, y, z):
""" Convert cartesian to spherical coordinates.
Attributes
----------
x : float
x-coordinate
y : float
y-coordinate
z : float
z-coordinate
Returns
-------
float
radius
float
aziumth
float
elevation
"""
r = np.sqrt(x**2 + y**2 + z**2)
if x > 0 and y > 0:
az = np.arctan(y / x)
elif x > 0 and y < 0:
az = 2*np.pi - np.arctan(-y / x)
elif x < 0 and y > 0:
az = np.pi - np.arctan(-y / x)
elif x < 0 and y < 0:
az = np.pi + np.arctan(y / x)
elif x == 0 and y > 0:
az = np.pi / 2
elif x == 0 and y < 0:
az = 3 * np.pi / 2
elif y == 0 and x > 0:
az = 0
elif y == 0 and x < 0:
az = np.pi
elev = np.arccos(z / r)
return r, az, elev Example 48
def ellipse_angle_of_rotation( a ):
b,c,d,f,g,a = a[1]/2, a[2], a[3]/2, a[4]/2, a[5], a[0]
return 0.5*NP.arctan(2*b/(a-c)) Example 49
def ellipse_angle_of_rotation2( a ):
b,c,d,f,g,a = a[1]/2, a[2], a[3]/2, a[4]/2, a[5], a[0]
if b == 0:
if a > c:
return 0
else:
return NP.pi/2
else:
if a > c:
return NP.arctan(2*b/(a-c))/2
else:
return NP.pi/2 + NP.arctan(2*b/(a-c))/2 Example 50
def radial_filter(order, freq, array_configuration, amp_maxdB=40):
"""Generate modal radial filter of specified order and frequency
Parameters
----------
order : array_like
order of filter
freq : array_like
Frequency of modal filter
array_configuration : ArrayConfiguration
List/Tuple/ArrayConfiguration, see io.ArrayConfiguration
amp_maxdB : int, optional
Maximum modal amplification limit in dB [Default: 40]
Returns
-------
dn : array_like
Vector of modal frequency domain filter of shape [nOrders x nFreq]
"""
array_configuration = ArrayConfiguration(*array_configuration)
extrapolation_coeffs = array_extrapolation(order, freq, array_configuration)
extrapolation_coeffs[extrapolation_coeffs == 0] = 1e-12
a_max = 10 ** (amp_maxdB / 20)
limiting_factor = 2 * a_max / _np.pi * _np.abs(extrapolation_coeffs) * _np.arctan(_np.pi / (2 * a_max * _np.abs(extrapolation_coeffs)))
return limiting_factor / extrapolation_coeffs 