def LocBeamInt(x, z):
alpha_1 = (x+d/2)*(np.sqrt(2/(lam*10**z)))
alpha_2 = (x-d/2)*(np.sqrt(2/(lam*10**z)))
s1, c1 = fresnel(alpha_1) #Fresnel integrals
s2, c2 = fresnel(alpha_2) #Fresnel integrals
I = 0.5*((c2-c1)**2+(s2-s1)**2)
return I;
def Fres_Diff(write_wavelength, slitwidth, x_pos, screen_pos):
alpha_1 = (x_pos + slitwidth/2)*(np.sqrt(2/(write_wavelength*screen_pos)))
alpha_2 = (x_pos - slitwidth/2)*(np.sqrt(2/(write_wavelength*screen_pos)))
s1, c1 = fresnel(alpha_1) #Fresnel integrals
s2, c2 = fresnel(alpha_2) #Fresnel integrals
Intensity = 0.5*((c2-c1)**2+(s2-s1)**2)
return Intensity
def motion_CSAA(state, dt):
'''
Constant Steering Angle and Acceleration.
States: [x, y, theta, v, a, c]
[0 1 2 3 4 5]
'''
x, y, th, v, a, c = state
gamma1 = (c * v * v) / (4 * a) + th
gamma2 = c * dt * v + c * dt * dt * a - th
eta = np.sqrt(2 * np.pi) * v * c
zeta1 = (2 * a * dt + v) * np.sqrt(c / 2 * a * np.pi)
zeta2 = v * np.sqrt(c / 2 * a * np.pi)
sz1, cz1 = fresnel(zeta1)
sz2, cz2 = fresnel(zeta2)
nx = x + (eta * (np.cos(gamma1) * cz1 + np.sin(gamma1) * sz1 -
np.cos(gamma1) * cz2 - np.sin(gamma1) * sz2) +
2 * np.sin(gamma2) * np.sqrt(a * c) +
2 * np.sin(th) * np.sqrt(a * c)) / 4 * np.sqrt(a * c) * c
ny = y + (eta * (-np.cos(gamma1) * sz1 + np.sin(gamma1) * cz1 -
np.sin(gamma1) * cz2 - np.cos(gamma1) * sz2) +
2 * np.cos(gamma2) * np.sqrt(a * c) -
2 * np.sin(th) * np.sqrt(a * c)) / 4 * np.sqrt(a * c) * c
nth = wrap_angle(th - c * dt * dt * a / 2 - c * dt * v)
nv = v + a * dt
state = np.copy(state)
state[:4] = (nx, ny, nth, nv)
return state
def I2(k, horn_height, eplane_effective_length, theta, phi):
"""
Calculate the integral used for far field calculations.
:param k: The wavenumber (rad/m).
:param horn_height: The height of the horn (m).
:param eplane_effective_length: The horn effective length in the E-plane (m).
:param theta: The theta angle to the field point (rad).
:param phi: The phi angle to the field point (rad).
:return: The integral used for far field calculations.
"""
# Calculate the y-component of the wavenumber
ky = k * sin(theta) * sin(phi)
# Calculate the arguments for the Fresnel integrals
t1 = sqrt(1.0 / (pi * k * eplane_effective_length)) * (
-k * horn_height / 2.0 - ky * eplane_effective_length)
t2 = sqrt(1.0 / (pi * k * eplane_effective_length)) * (
k * horn_height / 2.0 - ky * eplane_effective_length)
# Calculate the Fresnel integrals
s1, c1 = fresnel(t1)
s2, c2 = fresnel(t2)
return sqrt(pi * eplane_effective_length / k) * exp(1j * ky ** 2 * eplane_effective_length / (2.0 * k)) * \
((c2 - c1) + 1j * (s1 - s2))
def elementarykernel_fresnel(t):
#==========================================================================
"""Calculate kernel using Fresnel integrals (fast and accurate)"""
# Calculation using Fresnel integrals
if complex:
ɸ = np.outer(t, ωr)
κ = np.lib.scimath.sqrt(6 * ɸ / π)
S, C = fresnel(κ)
K0 = np.exp(-1j * ɸ) * (C + 1j * S)
else:
ɸ = np.outer(np.abs(t), ωr)
κ = np.lib.scimath.sqrt(6 * ɸ / π)
S, C = fresnel(κ)
K0 = C * np.cos(ɸ) + S * np.sin(ɸ)
# Supress divide by 0 warning
with warnings.catch_warnings():
warnings.simplefilter("ignore")
K0 = K0 / κ
# Limit of K0(t,r) as t->0
K0[t == 0] = 1
return K0
def directivity(horn_width, horn_height, eplane_effective_length, hplane_effective_length, frequency):
"""
Calculate the directivity for a pyramidal horn.
:param horn_width: The width of the horn (m).
:param horn_height: The height of the horn (m).
:param eplane_effective_length: The horn effective length in the E-plane (m).
:param hplane_effective_length: The horn effective length in the H-plane (m).
:param frequency: The operating frequency (Hz).
:return: The directivity of the pyramidal horn.
"""
# Calculate the wavelength
wavelength = c / frequency
# Calculate the arguments for the Fresnel integrals
u = 1.0 / sqrt(2.0) * (sqrt(wavelength * hplane_effective_length) / horn_width +
horn_width / sqrt(wavelength * hplane_effective_length))
v = 1.0 / sqrt(2.0) * (sqrt(wavelength * hplane_effective_length) / horn_width - horn_width /
sqrt(wavelength * hplane_effective_length))
# Calculate the Fresnel sin and cos integrals
Su, Cu = fresnel(u)
Sv, Cv = fresnel(v)
arg = horn_height / sqrt(2.0 * wavelength * eplane_effective_length)
S2, C2 = fresnel(arg)
S2 *= S2
C2 *= C2
return 8.0 * pi * eplane_effective_length * hplane_effective_length / (horn_width * horn_height) * \
((Cu - Cv) ** 2 + (Su - Sv) ** 2) * (C2 + S2)
def fresnel_analytical_rectangle(fresnel_number=None,
propagation_distance=1.140,
aperture_half=1e-3,
wavelength=639e-9,
detector_array=None,
npoints=1000):
if fresnel_number is None:
fresnel_number = aperture_half**2 / (wavelength * propagation_distance)
if detector_array is None:
if fresnel_number > 1.0:
window_aperture_ratio = 2.0
else:
window_aperture_ratio = 1.0 / fresnel_number
x = numpy.linspace(-window_aperture_ratio * aperture_half,
window_aperture_ratio * aperture_half, npoints)
else:
x = detector_array.copy()
s_plus = numpy.sqrt(2.0 * fresnel_number) * (1.0 + x / aperture_half)
s_minus = numpy.sqrt(2.0 * fresnel_number) * (1.0 - x / aperture_half)
fs_plus, fc_plus = fresnel(s_plus)
fs_minus, fc_minus = fresnel(s_minus)
Ux = (fc_minus + fc_plus) + 1j * (fs_minus + fs_plus)
Ux *= 1.0 / numpy.sqrt(2.0)
# TODO note that the global phase (Goldman 4-59) is missing
return x, Ux # note that wavefield is being returned, not intensity!
def motion_CSAA(state: np.ndarray, dt: float) -> np.ndarray:
'''
Constant Steering Angle and Acceleration model.
:param state: original state in format [x, y, theta, v, a, c]
[0 1 2 3 4 5]
:param dt: time difference after last update
:return: updated state
'''
x, y, th, v, a, c = state
gamma1 = (c * v * v) / (4 * a) + th
gamma2 = c * dt * v + c * dt * dt * a - th
eta = np.sqrt(2 * np.pi) * v * c
zeta1 = (2 * a * dt + v) * np.sqrt(c / 2 * a * np.pi)
zeta2 = v * np.sqrt(c / 2 * a * np.pi)
sz1, cz1 = fresnel(zeta1)
sz2, cz2 = fresnel(zeta2)
nx = x + (eta * (np.cos(gamma1) * cz1 + np.sin(gamma1) * sz1 -
np.cos(gamma1) * cz2 - np.sin(gamma1) * sz2) +
2 * np.sin(gamma2) * np.sqrt(a * c) +
2 * np.sin(th) * np.sqrt(a * c)) / 4 * np.sqrt(a * c) * c
ny = y + (eta * (-np.cos(gamma1) * sz1 + np.sin(gamma1) * cz1 -
np.sin(gamma1) * cz2 - np.cos(gamma1) * sz2) +
2 * np.cos(gamma2) * np.sqrt(a * c) -
2 * np.sin(th) * np.sqrt(a * c)) / 4 * np.sqrt(a * c) * c
nth = wrap_angle(th - c * dt * dt * a / 2 - c * dt * v)
nv = v + a * dt
state = np.copy(state)
state[:4] = (nx, ny, nth, nv)
return state
def LocBeamInt(x, z, lam): # function works out beam intensity as a function of distance from slit (z) and position along axis of slit (x)
alpha_1 = (x+slit_width/2)*(np.sqrt(2/(lam*z)))
alpha_2 = (x-slit_width/2)*(np.sqrt(2/(lam*z)))
s1, c1 = fresnel(alpha_1) #Fresnel integrals
s2, c2 = fresnel(alpha_2) #Fresnel integrals
I = 0.5*((c2-c1)**2+(s2-s1)**2)
return I;
def directivity(guide_height, horn_width, horn_effective_length, frequency):
"""
Calculate the directivity for the H-plane horn.
:param guide_height: The height of the waveguide feed (m).
:param horn_width: The width of the horn (m).
:param horn_effective_length: The effective length of the horn (m).
:param frequency: The operating frequency (Hz).
:return: The directivity for the H-plane horn.
"""
# Calculate the wavelength
wavelength = c / frequency
# Calculate the arguments for the Fresnel integrals
u = 1.0 / sqrt(2.0) * (
sqrt(wavelength * horn_effective_length) / horn_width +
horn_width / sqrt(wavelength + horn_effective_length))
v = 1.0 / sqrt(2.0) * (
sqrt(wavelength * horn_effective_length) / horn_width -
horn_width / sqrt(wavelength + horn_effective_length))
# Calculate the Fresnel integrals
Cu, Su = fresnel(u)
Cv, Sv = fresnel(v)
return 4.0 * pi * guide_height * horn_effective_length / (horn_width * wavelength) * \
((Cu - Cv) ** 2 + (Su - Sv) ** 2)
def calc(self, s, x0=0, y0=0, kappa0=0, theta0=0):
# Start
C0 = x0 + 1j * y0
if self._gamma == 0 and kappa0 == 0:
# Straight line
Cs = C0 + s * np.exp(1j * theta0)
elif self._gamma == 0 and kappa0 != 0:
# Arc
Cs = C0 + np.exp(1j * theta0) / kappa0 * (np.sin(kappa0 * s) + 1j *
(1 - np.cos(kappa0 * s)))
else:
# Fresnel integrals
Sa, Ca = fresnel((kappa0 + self._gamma * s) /
np.sqrt(np.pi * np.abs(self._gamma)))
Sb, Cb = fresnel(kappa0 / np.sqrt(np.pi * np.abs(self._gamma)))
# Euler Spiral
Cs1 = np.sqrt(np.pi / np.abs(self._gamma)) * np.exp(
1j * (theta0 - kappa0**2 / 2 / self._gamma))
Cs2 = np.sign(self._gamma) * (Ca - Cb) + 1j * Sa - 1j * Sb
Cs = C0 + Cs1 * Cs2
# Tangent at each point
theta = self._gamma * s**2 / 2 + kappa0 * s + theta0
return (Cs.real, Cs.imag, theta)
def I(k, r, theta, phi, horn_effective_length, horn_height, guide_width):
"""
Calculate the integral used in the far field calculations.
:param k: The wavenumber (rad/m).
:param r: The distance to the field point (m).
:param theta: The theta angle to the field point (rad).
:param phi: The phi angle to the field point (rad).
:param horn_effective_length: The horn effective length (m).
:param horn_height: The horn height (m).
:param guide_width: The width of the waveguide feed (m).
:return: The result of the integral for far field calculations.
"""
# Calculate the x and y components of the wavenumber
kx = k * sin(theta) * cos(phi)
ky = k * sin(theta) * sin(phi)
# Two separate terms for the Fresnel integrals
t1 = sqrt(1.0 /
(pi * k * horn_effective_length)) * (-k * horn_height * 0.5 -
ky * horn_effective_length)
t2 = sqrt(1.0 /
(pi * k * horn_effective_length)) * (k * horn_height * 0.5 -
ky * horn_effective_length)
# Get the Fresnel sin and cos integrals
s1, c1 = fresnel(t1)
s2, c2 = fresnel(t2)
index = (kx * guide_width != pi) & (kx * guide_width != -pi)
term2 = -ones_like(kx) / pi
term2[index] = cos(kx[index] * guide_width * 0.5) / (
(kx[index] * guide_width * 0.5)**2 - (pi * 0.5)**2)
return exp(1j * ky ** 2 * horn_effective_length / (2.0 * k)) * -1j * guide_width * \
sqrt(pi * k * horn_effective_length) / (8.0 * r) * exp(-1j * k * r) * term2 * ((c2 - c1) - 1j * (s2 - s1))
def _xy(s):
if th == 0:
return Coord2(0.0, 0.0)
elif s <= Ltot / 2:
(fsin, fcos) = fresnel(s / (sq2pi * a))
X = sq2pi * a * fcos
Y = sq2pi * a * fsin
else:
(fsin, fcos) = fresnel((Ltot - s) / (sq2pi * a))
X = (
sq2pi
* a
* (
facos
+ np.cos(2 * th) * (facos - fcos)
+ np.sin(2 * th) * (fasin - fsin)
)
)
Y = (
sq2pi
* a
* (
fasin
- np.cos(2 * th) * (fasin - fsin)
+ np.sin(2 * th) * (facos - fcos)
)
)
return Coord2(X, Y)
def fresnel_prop_square_aperture_analitical(x2, y2, aperture_diameter,
wavelength, propagation_distance):
f_n = (aperture_diameter / 2)**2 / (wavelength * propagation_distance
) # Fresnel number
# substitutions
big_x = x2 / numpy.sqrt(wavelength * propagation_distance)
big_y = y2 / numpy.sqrt(wavelength * propagation_distance)
alpha1 = -numpy.sqrt(2) * (numpy.sqrt(f_n) + big_x)
alpha2 = numpy.sqrt(2) * (numpy.sqrt(f_n) - big_x)
beta1 = -numpy.sqrt(2) * (numpy.sqrt(f_n) + big_y)
beta2 = numpy.sqrt(2) * (numpy.sqrt(f_n) - big_y)
# Fresnel sine and cosine integrals
cos_sin_a1 = fresnel(alpha1)
cos_sin_a2 = fresnel(alpha2)
cos_sin_b1 = fresnel(beta1)
cos_sin_b2 = fresnel(beta2)
# observation-plane field
U = 1 / (2 * 1.0j) * ((cos_sin_a2[0] - cos_sin_a1[0]) + 1.0j *
(cos_sin_a2[1] - cos_sin_a1[1])) * (
(cos_sin_b2[0] - cos_sin_b1[0]) + 1.0j *
(cos_sin_b2[1] - cos_sin_b1[1]))
return U
def __euler_function(self, t):
# input (t) goes from 0->1
# Returns an (x,y) tuple
if t > 1.0 or t < 0.0:
raise ValueError(
"Warning! A value was given to __euler_function not between 0 and 1"
)
end_t = self.t # (end-point)
if abs(self.turnby) <= np.pi / 2.0:
# Obtuse bend
if t < 0.5:
y, x = fresnel(2 * t * end_t)
return x * self.scale_factor, self.sign * y * self.scale_factor
else:
y, x = fresnel(2 * (1 - t) * end_t)
x, y = (
x * np.cos(-self.sign * self.turnby)
- y * np.sin(-self.sign * self.turnby),
x * np.sin(-self.sign * self.turnby)
+ y * np.cos(-self.sign * self.turnby),
)
return (
self.output_port[0] - x * self.scale_factor,
self.output_port[1] + self.sign * y * self.scale_factor,
)
else:
# Acute bend
if t < 0.3:
# First section of Euler bend
y, x = fresnel((t / 0.3) * end_t)
return x * self.scale_factor, self.sign * y * self.scale_factor
elif t < 0.7:
t0 = (t - 0.3) / 0.4
return (
self.circle_center[0]
+ self.wgt.bend_radius
* np.cos(
(-self.sign * np.pi / 4) + self.sign * self.circle_angle * t0
),
self.sign * self.circle_center[1]
+ self.wgt.bend_radius
* np.sin(
(-self.sign * np.pi / 4) + self.sign * self.circle_angle * t0
),
)
else:
y, x = fresnel(((1 - t) / 0.3) * end_t)
x, y = (
x * np.cos(-self.sign * self.turnby)
- y * np.sin(-self.sign * self.turnby),
x * np.sin(-self.sign * self.turnby)
+ y * np.cos(-self.sign * self.turnby),
)
return (
self.output_port[0] - x * self.scale_factor,
self.output_port[1] + self.sign * y * self.scale_factor,
)
def transfer_function(s, u):
a = u[0]
b = u[1]
t = u[2]
v = s[3]
w = s[4]
theta = s[2]
s_n = np.array(s, copy=True)
# The easy ones
dz = 0.5*b*t*t + w*t
dv = a*t
dw = b*t
# b = 0 and c = 0 case -> just linear acceleration
if abs(b) < 0.001 and abs(w) < 0.001:
l = 0.5*a*t*t + v*t
dx = math.cos(theta) * l
dy = math.sin(theta) * l
# b = 0 case -> formula singularity covered
elif abs(b) < 0.001:
dx = a * (math.cos(w * t + theta) - math.cos(theta)) / (theta * theta) + ((a * t + v) * math.sin(w * t + theta) - v * math.sin(theta)) / w
dy = a * (math.sin(w * t + theta) - math.sin(theta)) / (theta * theta) - ((a * t + v) * math.cos(w * t + theta) - v * math.cos(theta)) / w
else:
flipped = False
if b < 0:
b = -b
w = -w
flipped = True
sb = math.sqrt(b)
pb15 = math.pow(b, 1.5)
gamma = math.cos(0.5 * w * w / b - theta)
sigma = math.sin(0.5 * w * w / b - theta)
SPI = math.pow(math.pi, 0.5)
s1, c1 = special.fresnel((w + b*t) / (sb*SPI))
s0, c0 = special.fresnel(w / (sb*SPI))
S = s1 - s0
C = c1 - c0
dx = SPI * (b * v - a * w) * (sigma * S + gamma * C) / pb15 + (a / b) * (math.sin(0.5 * b * t * t + w * t + theta) - math.sin(theta))
dy = SPI * (b * v - a * w) * (gamma * S - sigma * C) / pb15 - (a / b) * (math.cos(0.5 * b * t * t + w * t + theta) - math.cos(theta))
if flipped:
c2d = math.cos(2 * theta)
s2d = math.sin(2 * theta)
dxt = c2d * dx + s2d * dy
dy = s2d * dx - c2d * dy
dx = dxt
s_n[0] += dx
s_n[1] += dy
s_n[2] += dz
s_n[3] += dv
s_n[4] += dw
return s_n
def Jacobian(s, u):
a = u[0]
b = u[1]
t = u[2]
x = s[0]
y = s[1]
theta = s[2]
v = s[3]
w = s[4]
# The easy ones
dxdt = (a*t + v) * math.cos(0.5*b*t*t + w*t)
dydt = (a*t + v) * math.sin(0.5*b*t*t + w*t)
dzda = 0.0
dzdb = 0.5*t*t
dzdt = b*t + w
dvda = t
dvdb = 0.0
dvdt = a
dwda = 0.0
dwdb = t
dwdt = b
# b = 0 and w = 0 -> linear acceleration
if abs(b) < 0.00001 and abs(w) < 0.00001:
dxda = 0.5 * t * t
dyda = 0.0
# Singularity at b = 0
dxdb = 0.0
dydb = 1.0
# b = 0
elif abs(b) < 0.00001:
dxda = (w*t*math.sin(w*t) + math.cos(w*t) - 1) / (w*w)
dyda = (math.sin(w*t) - w*t*math.cos(w*t)) / (w*w)
# Singularity at b = 0
dxdb = -math.sin(w*t)
dydb = math.cos(w*t)
else:
sgn = 1.0
if b < 0.0:
b = -b
w = -w
sgn = -1.0
sb = math.sqrt(b)
pb15 = pow(b, 1.5)
pb25 = pow(b, 2.5)
pb35 = pow(b, 3.5)
gamma = math.cos(0.5*w*w/b)
sigma = math.sin(0.5*w*w/b)
kappa = math.cos(0.5*t*t*b + w*t)
zeta = math.sin(0.5*t*t*b + w*t)
SPI = math.pow(math.pi, 0.5)
s1,c1 = special.fresnel((w + b*t)/(sb*SPI))
s0,c0 = special.fresnel(w/(sb*SPI))
c = c1 - c0
s = s1 - s0
dsdb = math.sin((b*t+w)*(b*t+w)/(2.0*b)) * ()
def f(theta):
S_t, C_t = fresnel(arclength(theta))
S_at, C_at = fresnel(arclength(alpha - theta))
result = math.sqrt(theta) * (C_t * math.sin(alpha) - S_t *
(k + math.cos(alpha)))
result += math.sqrt(alpha - theta) * (S_at *
(1 + k * math.cos(alpha)) -
k * C_at * math.sin(alpha))
return result
def compute_fresnel_at_polar(rho, phi, phi0, wavelength):
k = 2 * np.pi / wavelength # wave number
# Eq (3.4) Arguments of Fresnel Integrals are multiplied by sqrt(2 / pi) due to different definition of fresnels / c in matlab, use substitution to change between definitions...
fresnels, fresnelc = fresnel(
sqrt(2.0 / pi) * sqrt(2 * k * rho) * cos((phi - phi0) / 2.0))
phiplus = (1 - 1j) / 2.0 + fresnelc - 1j * fresnels
fresnels, fresnelc = fresnel(
sqrt(2.0 / pi) * sqrt(2 * k * rho) * cos((phi + phi0) / 2.0))
phiminus = (1 - 1j) / 2.0 + fresnelc - 1j * fresnels
return phiplus, phiminus
def _calc_fresnel_integral(self, s, kappa0, theta0, C0):
Sa, Ca = special.fresnel(
(kappa0 + self._gamma * s) / np.sqrt(np.pi * np.abs(self._gamma)))
Sb, Cb = special.fresnel(kappa0 / np.sqrt(np.pi * np.abs(self._gamma)))
# Euler Spiral
Cs1 = np.sqrt(np.pi / np.abs(self._gamma)) * np.exp(
1j * (theta0 - kappa0**2 / 2 / self._gamma))
Cs2 = np.sign(self._gamma) * (Ca - Cb) + 1j * Sa - 1j * Sb
Cs = C0 + Cs1 * Cs2
return Cs
def spiralInterpolation(resolution, s, x, y, hdg, length, curvStart, curvEnd):
points = np.zeros((int(length/resolution), 1))
points = [i*resolution for i in range(len(points))]
xx = np.zeros_like(points)
yy = np.zeros_like(points)
hh = np.zeros_like(points)
if curvStart == 0 and curvEnd > 0:
print("Case 1: curvStart == 0 and curvEnd > 0")
radius = np.abs(1/curvEnd)
A_sq = radius*length
ss, cc = fresnel(np.square(points)/(2*A_sq*np.sqrt(np.pi/2)))
xx = points*cc
yy = points*ss
hh = np.square(points)*2*radius*length
xx, yy, hh = rotate(xx, yy, hh, hdg)
xx, yy = translate(xx, yy, x, y)
xx = np.insert(xx, 0, x, axis=0)
yy = np.insert(yy, 0, y, axis=0)
hh = np.insert(hh, 0, hdg, axis=0)
elif curvStart == 0 and curvEnd < 0:
print("Case 2: curvStart == 0 and curvEnd < 0")
radius = np.abs(1/curvEnd)
A_sq = radius*length
ss, cc = fresnel(np.square(points)/(2*A_sq*np.sqrt(np.pi/2)))
xx = points*cc
yy = points*ss*-1
hh = np.square(points)*2*radius*length
xx, yy, hh = rotate(xx, yy, hh, hdg)
xx, yy = translate(xx, yy, x, y)
xx = np.insert(xx, 0, x, axis=0)
yy = np.insert(yy, 0, y, axis=0)
hh = np.insert(hh, 0, hdg, axis=0)
elif curvEnd == 0 and curvStart > 0:
print("Case 3: curvEnd == 0 and curvStart > 0")
elif curvEnd == 0 and curvStart < 0:
print("Case 4: curvEnd == 0 and curvStart < 0")
else:
print("The curvature parameters differ from the 4 predefined cases. Change curvStart and/or curvEnd")
n_stations = int(length/resolution) + 1
stations = np.zeros((n_stations, 3))
for i in range(len(xx)):
stations[i][0] = xx[i]
stations[i][1] = yy[i]
stations[i][2] = hh[i]
return stations
def XY(s):
if th == 0:
return np.array((0.0, 0.0))
elif s <= Ltot / 2:
(fsin, fcos) = fresnel(s / (sq2pi * a))
X = sq2pi * a * fcos
Y = sq2pi * a * fsin
else:
(fsin, fcos) = fresnel((Ltot - s) / (sq2pi * a))
X = sq2pi * a * (facos + np.cos(2 * th) *
(facos - fcos) + np.sin(2 * th) * (fasin - fsin))
Y = sq2pi * a * (fasin - np.cos(2 * th) *
(fasin - fsin) + np.sin(2 * th) * (facos - fcos))
return np.array((X, Y))
def test_spiral(self):
'''
spiral test compares outcome of wrapped odrSpiral implementation with scipy fresnel calculation
'''
# spiral using scipy
t = np.linspace(-7, 7, 250)
y, x = fresnel(t)
# spiral using odrSpiral
x_odr = []
y_odr = []
for t_i in t:
x_odr.append(fresnel_cos(t_i))
y_odr.append(fresnel_sin(t_i))
#plt.plot(x, y)
#plt.plot(x_odr, y_odr, 'g')
#plt.axes().set_aspect("equal")
#plt.show()
x_odr_np = np.asarray(x_odr)
y_odr_np = np.asarray(y_odr)
assert (np.allclose(x, x_odr_np) == 1)
assert (np.allclose(y, y_odr_np) == 1)
def PELDOR_matrix_kernel(r_usr, Pr_usr, time, moddepth):
""""
in: time: (1xn) time vector in ns units
r_usr: (1xm) user defined distance vector
Pr_usr: (1xm) distance distribution vector
out: signal: (1xn) PELDOR signal, normalized to the modulation depth
The function takes a user defined ditance distribution (Pr_user) to
create a corresponding PELDOR time trace.
"""
time = time / 1000.0
kernel = np.zeros((len(time), len(Pr_usr)))
indext0 = np.argwhere(np.abs(time) < 1e-6)[0][0]
for i in range(0, len(r_usr)):
w = (327.0 / (np.power(r_usr[i], 3)))
z = np.sqrt((6 * w * np.absolute(time)) / np.pi)
tmpfresnel = fresnel(z)
kernel[indext0, :] = 1.0
z[indext0] = 1
kernel[:, i] = ((np.cos(w * np.absolute(time)) / z) * tmpfresnel[1] +
(np.sin(w * np.absolute(time)) / z) * tmpfresnel[0])
kernel[indext0][:] = 1.0
signal = kernel @ Pr_usr
return (moddepth * (signal / max(signal)))
def fresnel_prop_square_ap(x2, y2, D1, wvl, Dz):
N_F = (D1/2)**2/(wvl*Dz)
bigX = x2/np.sqrt(wvl*Dz)
bigY = y2/np.sqrt(wvl*Dz)
alpha1 = -np.sqrt(2)*(np.sqrt(N_F)+bigX)
alpha2 = np.sqrt(2)*(np.sqrt(N_F)-bigX)
beta1 = -np.sqrt(2)*(np.sqrt(N_F)+bigY)
beta2 = np.sqrt(2)*(np.sqrt(N_F)-bigY)
sa1, ca1 = fresnel(alpha1)
sa2, ca2 = fresnel(alpha2)
sb1, cb1 = fresnel(beta1)
sb2, cb2 = fresnel(beta2)
U = 1/(2j)*((ca2-ca1)+1j*(sa2-sa1))*((cb2-cb1)+1j*(sb2-sb1))
return U
def EulerEndPt(start_point=(0.0, 0.0),
radius=10.0,
input_angle=0.0,
clockwise=False,
angle_amount=np.pi / 2.):
"""Gives the end point of a simple Euler bend"""
if clockwise:
eth = (-angle_amount) % (2 * np.pi)
else:
eth = angle_amount % (2 * np.pi)
th = eth / 2.0
R = radius
# clockwise = bool(angle_amount < 0)
(fsin, fcos) = fresnel(np.sqrt(2 * th / np.pi))
a = 2 * np.sqrt(2 * np.pi * th) * (np.cos(th) * fcos + np.sin(th) * fsin)
r = a * R
X = r * np.cos(th)
Y = r * np.sin(th)
if clockwise:
Y *= -1
pt = np.array((X, Y)) + np.array(start_point)
pt = rotate(point=pt, angle=input_angle, origin=start_point)
return pt
def fp(x):
# real, dimension(dimh) :: x
# real, dimension(dimh) :: rx
rx = np.sqrt(x * 2 / np.pi)
s_fresnel, c_fresnel = sp.fresnel(rx)
return - 2 * 1j * np.sqrt(x) * np.exp(-1j * x) * np.sqrt(np.pi / 2.) * \
(.5 - c_fresnel + 1j * (.5 - s_fresnel))
def deer_ft(d, t, lambda_v=1.0, D_dip=2 * np.pi * 52.04 * 10**-3):
"""
F_v/mu = C_F(x) cos(pi/6x^2) + S_F(x) sine(pi/6x^2)
sin_f(x) = int_0^x sin(pi/2 t^2)
cos_f(x) = int_o^x cos(pi/2 t^2)
with x = [6 D_dip t / pi r^3]^0.5 and D_dip= 2pi 52.04 MHz nm^3
Parameters
-----------
d: array
Spin-spin distance [nm] for N structures
t: array
Time points [ns], M time points to be calculated
D_dip: float
2 pi 52.04 MHz nm^3 = 2 pi 52.04/1000 nm^3/ns
lambda_v: float
Modulation depth
Returns
-------
vt: array
DEER/PELDOR time traces for each of the N structures for M time points (NxM)
"""
x = (6 * D_dip * t / (np.pi * d**3))**0.5
# SciPy follows convention from Abramowitz and Stergun.
# https://docs.scipy.org/doc/scipy/reference/generated/scipy.special.fresnel.html#s
sin_f, cos_f = fresnel(x)
F_vmu = (cos_f * np.cos(np.pi / 6. * x**2) +
sin_f * np.sin(np.pi / 6. * x**2)) / x
return (1. - lambda_v) + lambda_v * F_vmu
def FreF2(x):
""" F function using numpy fresnel function
Parameters
----------
Not working for large argument
"""
y = np.zeros(x.shape, dtype=complex)
u1 = np.where(x > 5)[0]
u2 = np.where(x <= 5)[0]
xu1 = x[u1]
xu2 = x[u2]
x2 = xu1 * xu1
x3 = x2 * xu1
x4 = x3 * xu1
w1 = 1 - 0.75 / x2 + 4.6875 / x4 + 1j * (0.5 / xu1 - 1.875 / x3)
cst = np.sqrt(np.pi / 2.)
sF, cF = sps.fresnel(np.sqrt(xu2 / cst))
Fc = (0.5 - cF) * cst
Fs = (0.5 - sF) * cst
modx = np.mod(xu2, 2 * np.pi)
expjx = np.exp(1j * modx)
w2 = 2 * 1j * np.sqrt(xu2) * expjx * (Fc - 1j * Fs)
y[u1] = w1
y[u2] = w2
return (y)
def EffectiveDeformabilityFromDynamicalTides(orbital_freq, omega_fmode,
ell_mode, q):
"""arxiv:1608.01907, eqn 6.51
Inputs:
orbital_freq -- orbital frequency of the binary
omega_fmode -- f-mode dimensionless angular frequency of the ell-polar
mode of the deformed object
ell_mode -- ell-polar deformability (2 = quadrupolar; 3 = octopolar)
q -- mass ratio
Outputs:
The effective amplification of the ell-polar tidal deformability as a
function of the oribital frequency """
if (ell_mode not in [2, 3]):
raise ValueError(
"ERROR: 'ell_mode' only implemented for ell=2 or ell=3!")
# If the input to the universal relations is too small (lambda2<1), then the
# fits can return unphysical negative resonance frequencies, in such cases
# just assume there is no significant resonance
if (omega_fmode <= 0):
return np.ones(len(orbital_freq))
# resonanace => freq_ratio == 1
freq_ratio = omega_fmode / ell_mode / orbital_freq
# Intermediate values
# Because it only matters what the symmetric mass ratio is, XA*XB, it doesn't
# matter whether the input is q or 1/q
X1 = q / (q + 1.)
X2 = 1. - X1
epsilon = 256. / 5. * X1 * X2 * pow(omega_fmode / ell_mode, 5. / 3.)
t_hat = 8. / 5. / np.sqrt(epsilon) * (1 - pow(freq_ratio, 5. / 3.))
omega_prime = 3. / 8.
# Fresnel integral values
ssa, csa = fresnel(t_hat * np.sqrt(2 * omega_prime / np.pi))
betaDTOverA = (
pow(omega_fmode, 2) /
(pow(omega_fmode, 2) - pow(ell_mode * orbital_freq, 2)) +
pow(freq_ratio, 2) / 2. / np.sqrt(epsilon) / t_hat / omega_prime +
pow(freq_ratio, 2) / np.sqrt(epsilon) *
np.sqrt(np.pi / 8. / omega_prime) *
(np.cos(omega_prime * t_hat * t_hat) *
(1 + 2. * ssa) - np.sin(omega_prime * t_hat * t_hat) *
(1 + 2. * csa)))
# When 'orbital_freq' is close enough to 0, this formula seems to be
# numerically unstable though the asympotic limit should be 1. So when small
# enough, just set it to that value
# NOTE: this cutoff value should match value used in
# EffectiveDissipativeDynamicalTides
omega_cutoff = 5.e-5
betaDTOverA[abs(orbital_freq) <= omega_cutoff] = 1.
if ell_mode == 2:
return (1. + 3. * betaDTOverA) / 4.
else:
return (3. + 5. * betaDTOverA) / 8.
def FreF2(x):
""" F function using numpy fresnel function
Parameters
----------
Not working for large argument
"""
y = np.zeros(x.shape,dtype=complex)
u1 = np.where(x>5)[0]
u2 = np.where(x<=5)[0]
xu1 = x[u1]
xu2 = x[u2]
x2 = xu1*xu1
x3 = x2*xu1
x4 = x3*xu1
w1 = 1-0.75/x2+4.6875/x4 + 1j*( 0.5/xu1 -1.875/x3)
cst = np.sqrt(np.pi/2.)
sF,cF = sps.fresnel(np.sqrt(xu2/cst))
Fc = (0.5-cF)*cst
Fs = (0.5-sF)*cst
modx = np.mod(xu2,2*np.pi)
expjx = np.exp(1j*modx)
w2 = 2*1j*np.sqrt(xu2)*expjx*(Fc-1j*Fs)
y[u1] = w1
y[u2] = w2
return(y)
def get_pose(self, length):
# This implements:
# dx = http://www.wolframalpha.com/input/?i=integral+of+cos%28+w+*+0.5+*+t%5E2+%2B+q*t+%2B+theta+%29+dt+from+0+to+x
# dy =
time = length
omega0 = self._start[3]
theta0 = self._start[2]
omega = omega0 + self._w * time
theta = theta0 + self._w * time * time / 2 + omega0 * time
w = self._w
f1 = omega0 / cmath.sqrt(math.pi * w)
S1, C1 = fresnel(f1)
f2 = (omega0 + w * time) / cmath.sqrt(math.pi * w)
S2, C2 = fresnel(f2)
pi_w = cmath.sqrt(math.pi / self._w)
t0 = (omega0 * omega0 / (2 * self._w)) - theta0
dx = pi_w * (math.cos(t0) * (C2 - C1) + math.sin(t0) * (S2 - S1))
dy = pi_w * (math.sin(t0) * (C1 - C2) + math.cos(t0) * (S2 - S1))
imag = False
if dx.imag != 0:
print "WARNING: imaginary result for dx:", dx
imag = True
if dy.imag != 0:
print "WARNING: imaginary result for dy:", dy
imag = True
if imag:
print " With w", w, ", length", self._length, "at", length
dx = dx.real
dy = dy.real
# not quite sure why... but this works
if w < 0:
dx = -dx
dy = -dy
x = self._start[0] + dx
y = self._start[1] + dy
return (x, y, theta, omega)
def get_pose(self, length):
# This implements:
# dx = http://www.wolframalpha.com/input/?i=integral+of+cos%28+w+*+0.5+*+t%5E2+%2B+q*t+%2B+theta+%29+dt+from+0+to+x
# dy =
time = length
omega0 = self._start[3]
theta0 = self._start[2]
omega = omega0 + self._w * time
theta = theta0 + self._w * time * time / 2 + omega0 * time
w = self._w
f1 = omega0 / cmath.sqrt(math.pi * w)
S1, C1 = fresnel(f1)
f2 = (omega0 + w * time) / cmath.sqrt(math.pi * w)
S2, C2 = fresnel(f2)
pi_w = cmath.sqrt(math.pi / self._w)
t0 = (omega0 * omega0 / (2 * self._w)) - theta0
dx = pi_w * (math.cos(t0) * (C2 - C1) + math.sin(t0) * (S2 - S1))
dy = pi_w * (math.sin(t0) * (C1 - C2) + math.cos(t0) * (S2 - S1))
imag = False
if dx.imag != 0:
print "WARNING: imaginary result for dx:", dx
imag = True
if dy.imag != 0:
print "WARNING: imaginary result for dy:", dy
imag = True
if imag:
print " With w", w, ", length", self._length, "at", length
dx = dx.real
dy = dy.real
# not quite sure why... but this works
if w < 0:
dx = -dx
dy = -dy
x = self._start[0] + dx
y = self._start[1] + dy
return (x, y, theta, omega)
def eulerBend(radius, theta, pts):
length = 2 * radius * theta
a = 1 / np.sqrt(2 * radius * length)
s = np.linspace(0, length, pts)
tprime = s * a * np.sqrt(2 / np.pi)
y, x = fresnel(tprime)
return (1 / a) * x, (1 / a) * y
def test_fresnel_sin_small(self, dtype):
x = np.random.uniform(0., 1., size=int(1e4)).astype(dtype)
try:
from scipy import special # pylint: disable=g-import-not-at-top
self.assertAllClose(
special.fresnel(x)[0], self.evaluate(special_math_ops.fresnel_sin(x)))
except ImportError as e:
tf_logging.warn('Cannot test special functions: %s' % str(e))
def fresnelc(x):
return sc.fresnel(x)[1]
def fresnels(x):
return sc.fresnel(x)[0]
def calc_resonant_pitchangle_change(crossing_df, L_target):
# Start timer
tstart = time.time()
# # Generate energy and velocity arrays
# E_tot_arr = pow(10,sc.E_EXP_BOT + sc.DE_EXP*np.arange(0,sc.NUM_E))
# v_tot_arr = sc.C*np.sqrt(1 - pow(sc.E_EL/(sc.E_EL + E_tot_arr),2))
L = L_target
epsm = (1.0/L)*(sc.R_E + sc.H_IONO)/sc.R_E
alpha_eq = np.arcsin(np.sqrt( pow(epsm, 3)/np.sqrt(1 + 3*(1 - epsm)) ))
# Gen EA array (maybe pass this as an arg)
EA_array = gen_EA_array(L_target)
# Initialize alpha array
DA_array_N = np.zeros((sc.NUM_E, sc.NUM_STEPS))
DA_array_S = np.zeros((sc.NUM_E, sc.NUM_STEPS))
tstop = time.time()
# Loop through EA segments:
#for EA_ind, EA_row in EA_array.iterrows():
for EA_ind in np.unique(crossing_df['EA_index']):
# For each EA segment, CALCULATE:
# - wh
# - dwh/ds
# - flight-time constant
# - alpha_lc
lat = EA_array['lam'][EA_ind]
print 'EA segment at latitude = ',lat
slat = np.sin(lat*sc.D2R)
clat = np.cos(lat*sc.D2R)
slat_term = np.sqrt(1 + 3*slat*slat)
# Lower hybrid frequency
wh = (sc.Q_EL*sc.B0/sc.M_EL)*(1.0/pow(L,3))*slat_term/pow(clat,6)
#wh = (2*np.pi*880000) / (pow(L,3)*slat_term/pow(clat,6)) # Jacob used a hard coded value for qB/m
dwh_ds = (3.0*wh/(L*sc.R_E)) *(slat/slat_term) * (1.0/(slat_term*slat_term) + 2.0/(clat*clat))
# flight time constants (divide by velocity to get time to ionosphere, in seconds)
ftc_N, ftc_S = get_flight_time_constant(L, lat, alpha_eq)
# Local loss cone angle
alpha_lc = np.arcsin(np.sqrt(slat_term/pow(clat,6) )*np.sin(alpha_eq))
salph = np.sin(alpha_lc)
calph = np.cos(alpha_lc)
ds = L*sc.R_E*slat_term*clat*sc.EAIncr*np.pi/180.0
dv_para_ds = -0.5*(salph*salph/(calph*wh))*dwh_ds
# # Sometimes Python is pretty and readable, but now is not one of those times
# for cell_ind, cells in crossing_df[crossing_df['EA_index'] == EA_ind].iterrows():
# print np.shape(cell)
# Mask out just the entries which cross the current EA segment:
cells = crossing_df[crossing_df['EA_index'] == EA_ind]
#print cells
for ir, c in cells.iterrows():
#print c
# where you left off: time and frequency (line 1800)
t = c.tg + sc.T_STEP/2.0
f = c.frequency + sc.F_STEP/2.0
# Jacob divides by num_rays too -- since he stores total power in each cell. Average?
# Do we need to do that here? I'm not doing that right now.
pwr = c.power/(sc.T_STEP*EA_array['EA_length'][EA_ind])
# pwr = c.power/sc.T_STEP
psi = c.psi*sc.D2R
# print "EA_length: ",EA_array['EA_length'][EA_ind]
# print "Pwr: ",pwr
# print "DT: ",sc.DT
#print pwr
# Maybe threshold power here?
# Misc. parameters and trig
mu = c.mu
stixP = c.stixP
stixR = c.stixR
stixL = c.stixL
spsi = np.sin(psi)
cpsi = np.cos(psi)
spsi_sq = spsi*spsi
cpsi_sq = cpsi*cpsi
n_x = mu*abs(spsi)
n_z = mu*cpsi
mu_sq = mu*mu
w = 2.0 * np.pi * f
k = w*mu/sc.C
kx = w*n_x/sc.C
kz = w*n_z/sc.C
Y = wh / w
stixS = (stixR + stixL)/2.0
stixD = (stixR - stixL)/2.0
stixA = stixS + (stixP-stixS)*cpsi_sq
stixB = stixP*stixS + stixR*stixL + (stixP*stixS - stixR*stixL)*cpsi_sq
stixX = stixP/(stixP - mu_sq*spsi_sq)
rho1=((mu_sq-stixS)*mu_sq*spsi*cpsi)/(stixD*(mu_sq*spsi_sq-stixP))
rho2 = (mu_sq - stixS) / stixD
#print num
Byw_sq = ( (2.0*sc.MU0/sc.C) * (pwr*stixX*stixX*rho2*rho2*mu*abs(cpsi)) /
np.sqrt( pow((np.tan(psi)-rho1*rho2*stixX),2) + pow((1+rho2*rho2*stixX),2)) )
# print ("t: %g, f: %g, pwr: %g, psi: %g\nmu: %g, stixP: %g, stixR: %g, stixL: %g Byw_sq: %g"%(t,f,pwr,psi,mu, stixP, stixR, stixL, Byw_sq))
# RMS wave components
Byw = np.sqrt(Byw_sq);
Exw = abs(sc.C*Byw * (stixP - n_x*n_x)/(stixP*n_z))
Eyw = abs(Exw * stixD/(stixS-mu_sq))
Ezw = abs(Exw *n_x*n_z / (n_x*n_x - stixP))
Bxw = abs((Exw *stixD*n_z/sc.C)/ (stixS - mu_sq))
Bzw = abs((Exw *stixD *n_x) /(sc.C*(stixX - mu_sq)));
# Oblique integration quantities
R1 = (Exw + Eyw)/(Bxw+Byw)
R2 = (Exw - Eyw)/(Bxw-Byw)
w1 = (sc.Q_EL/(2*sc.M_EL))*(Bxw+Byw)
w2 = (sc.Q_EL/(2*sc.M_EL))*(Bxw-Byw)
alpha1 = w2/w1
# Loop at line 1897 -- MRES loop
# Since we're trying to keep it vectorized:
# target dimensions are num(cell rows) rows x num(mres) columns.
# (Sometimes Python is beautiful, but now is not one of those times)
# --> Note to future editors: the (vec)[:,np.newaxis] command is similar to repmat or tile:
# It will tile the vector along the new axis, with length dictated by whatever operation
# follows it. In Python lingo this is "broadcasting"
# Resonant modes to sum over: Integers, positive and negative
for mres in np.linspace(-5,5,11):
# Parallel resonance velocity V_z^res (pg 5 of Bortnik et al)
t1 = w*w*kz*kz
t2 = pow(mres*wh, 2)-(w*w)
t3 = kz*kz + pow((mres*wh),2)/(pow(sc.C*np.cos(alpha_lc),2))
#print np.diff(t3[0,:])
if mres==0:
direction = -1.0*np.sign(kz)
else:
direction = np.sign(kz)*np.sign(mres)
v_para_res = ( direction*np.sqrt(t1 + t2*t3) - w*kz) / t3
# # Getting some obnoxious numerical stuff in the case of m=0:
# if mres==0:
# v_para_res = (w/kz)
# else:
# v_tot_res = v_para_res / np.cos(alpha_lc)
v_tot_res = v_para_res / np.cos(alpha_lc)
E_res = sc.E_EL*(1.0/np.sqrt( 1-(v_tot_res*v_tot_res/(sc.C*sc.C)) ) - 1 )
# Start and end indices in the energy array (+-20% energy band)
e_starti = np.floor((np.log10(E_res)-sc.E_EXP_BOT-sc.E_BANDWIDTH)/sc.DE_EXP)
e_endi = np.ceil(( np.log10(E_res)-sc.E_EXP_BOT+sc.E_BANDWIDTH)/sc.DE_EXP)
# Threshold to range of actual indexes (some energies may be outside our target range)
e_starti = np.clip(e_starti,0,sc.NUM_E)
e_endi = np.clip(e_endi, 0,sc.NUM_E)
# energy bins to calculate at:
evec_inds = np.arange(e_starti,e_endi,dtype=int)
v_tot = direction*sc.v_tot_arr[evec_inds]
v_para = v_tot*calph
v_perp = abs(v_tot*salph)
# Relativistic factor
gamma = 1.0/np.sqrt(1.0 - pow(v_tot/sc.C, 2))
alpha2 = sc.Q_EL*Ezw /(sc.M_EL*gamma*w1*v_perp)
beta = kx*v_perp/wh
wtau_sq = (pow((-1),(mres-1)) * w1/gamma *
( jn( (mres-1), beta ) -
alpha1*jn( (mres+1) , beta ) +
gamma*alpha2*jn( mres , beta ) ))
T1 = -wtau_sq*(1 + calph*calph/(mres*Y - 1))
# Analytical evaluation! (Line 1938)
if (abs(lat) < 1e-3):
eta_dot = mres*wh/gamma - w - kz*v_para
dalpha_eq = np.zeros_like(eta_dot)
eta_mask = eta_dot < 10
dalpha_eq[eta_mask] = abs(T1[eta_mask] /v_para[eta_mask])*ds/np.sqrt(2)
dalpha_eq[~eta_mask] = abs(T1[~eta_mask]/eta_dot[~eta_mask])*np.sqrt(1-np.cos(ds*eta_dot[~eta_mask]/v_para[~eta_mask]))
else:
v_para_star = v_para - dv_para_ds*ds/2.0
v_para_star_sq = v_para_star*v_para_star
AA =( (mres/(2.0*v_para_star*gamma))*dwh_ds*
(1 + ds/(2.0*v_para_star)*dv_para_ds) -
mres/(2.0*v_para_star_sq*gamma)*wh*dv_para_ds +
w/(2.0*v_para_star_sq)*dv_para_ds )
BB =( mres/(gamma*v_para_star)*wh -
mres/(gamma*v_para_star)*dwh_ds*(ds/2.0) -
w/v_para_star - kz )
Farg = (BB + 2.0*AA*ds) / np.sqrt(2.0*np.pi*abs(AA))
Farg0 = BB / np.sqrt(2*np.pi*abs(AA))
Fs, Fc = fresnel(Farg)
Fs0, Fc0 = fresnel(Farg0)
dFs_sq = pow(Fs - Fs0, 2)
dFc_sq = pow(Fc - Fc0, 2)
dalpha = np.sqrt( (np.pi/4.0)/abs(AA))*abs(T1/v_para)*np.sqrt(dFs_sq + dFc_sq)
alpha_eq_p = np.arcsin( np.sin(alpha_lc+dalpha)*pow(clat,3) / np.sqrt(slat_term) )
dalpha_eq = alpha_eq_p - alpha_eq
#print "dalpha_eq:", dalpha_eq
#print "output vec shape:", np.shape(dalpha_eq)
#print "end - start:", endi - starti
#print "t offset:",t.iloc[index[0]]
# Add net change in alpha to total array:
if direction > 0:
#print "Norf!"
iono_time = t + abs(ftc_N/v_para)
tt = np.round( iono_time/sc.T_STEP ).astype(int)
#print tt
tt = np.clip(tt,0,sc.NUM_STEPS - 1)
#tt.clip(0,sc.NUM_STEPS)
DA_array_N[evec_inds,tt] += dalpha_eq*dalpha_eq
else:
#print "Souf!"
iono_time = t + abs(ftc_S/v_para)
tt = np.round( iono_time/sc.T_STEP ).astype(int)
tt = np.clip(tt,0,sc.NUM_STEPS - 1)
#print tt
DA_array_S[evec_inds,tt] += dalpha_eq*dalpha_eq
# --------------------- Vector-ish version that isn't working ---------------
# if cells.shape[0] > 0:
# print cells.shape
# #print cells.columns
# # where you left off: time and frequency (line 1800)
# t = cells.tg + sc.DT/2.0
# f = cells.frequency + sc.DF/2.0
# pwr = cells.power/sc.DT # Jacob divides by num_rays too, but it looks like it's always 1
# psi = cells.psi*sc.D2R
# #print pwr
# # Maybe threshold power here?
# # Misc. parameters and trig
# mu = cells.mu
# stixP = cells.stixP
# stixR = cells.stixR
# stixL = cells.stixL
# spsi = np.sin(psi)
# cpsi = np.cos(psi)
# spsi_sq = spsi*spsi
# cpsi_sq = cpsi*cpsi
# n_x = mu*abs(spsi)
# n_z = mu*cpsi
# mu_sq = mu*mu
# w = 2.0 * np.pi * f
# k = w*mu/sc.C
# kx = w*n_x/sc.C
# kz = w*n_z/sc.C
# Y = wh / w
# stixS = (stixR + stixL)/2.0
# stixD = (stixR - stixL)/2.0
# stixA = stixS + (stixP-stixS)*cpsi_sq
# stixB = stixP*stixS + stixR*stixL + (stixP*stixS - stixR*stixL)*cpsi_sq
# stixX = stixP/(stixP - mu_sq*spsi_sq)
# rho1=((mu_sq-stixS)*mu_sq*spsi*cpsi)/(stixD*(mu_sq*spsi_sq-stixP))
# rho2 = (mu_sq - stixS) / stixD
# #print num
# Byw_sq = ( (2.0*sc.MU0/sc.C) * (pwr*stixX*stixX*rho2*rho2*mu*abs(cpsi)) /
# np.sqrt( pow((np.tan(psi)-rho1*rho2*stixX),2) + pow((1+rho2*rho2*stixX),2)) )
# #print Byw_sq
# # RMS wave components
# Byw = np.sqrt(Byw_sq);
# Exw = abs(sc.C*Byw * (stixP - n_x*n_x)/(stixP*n_z))
# Eyw = abs(Exw * stixD/(stixS-mu_sq))
# Ezw = abs(Exw *n_x*n_z / (n_x*n_x - stixP))
# Bxw = abs((Exw *stixD*n_z/sc.C)/ (stixS - mu_sq))
# Bzw = abs((Exw *stixD *n_x) /(sc.C*(stixX - mu_sq)));
# # Oblique integration quantities
# R1 = (Exw + Eyw)/(Bxw+Byw)
# R2 = (Exw - Eyw)/(Bxw-Byw)
# w1 = (sc.Q_EL/(2*sc.M_EL))*(Bxw+Byw)
# w2 = (sc.Q_EL/(2*sc.M_EL))*(Bxw-Byw)
# alpha1 = w2/w1
# # Loop at line 1897 -- MRES loop
# # Since we're trying to keep it vectorized:
# # target dimensions are num(cell rows) rows x num(mres) columns.
# # (Sometimes Python is beautiful, but now is not one of those times)
# # --> Note to future editors: the (vec)[:,np.newaxis] command is similar to repmat or tile:
# # It will tile the vector along the new axis, with length dictated by whatever operation
# # follows it. In Python lingo this is "broadcasting"
# # Resonant modes to sum over: Integers, positive and negative
# mres = np.linspace(-5,5,11)
# # Parallel resonance velocity V_z^res (pg 5 of Bortnik et al)
# t1 = w*w*kz*kz
# t2 = (mres*mres*wh*wh)[np.newaxis,:]-(w*w)[:,np.newaxis]
# t3 = (kz*kz)[:,np.newaxis] + ((mres*wh*mres*wh)[np.newaxis,:]/(pow(sc.C*np.cos(alpha_lc),2)))
# #print np.diff(t3[0,:])
# direction = np.outer(np.sign(kz),np.sign(mres))
# direction[:,mres==0] = -1*np.sign(kz)[:,np.newaxis] # Sign
# # v_para_res = (ta - tb)
# v_para_res = ( direction*np.sqrt(abs(t1[:,np.newaxis] + t2*t3)) - (w*kz)[:,np.newaxis] ) / t3
# # Getting some obnoxious numerical stuff in the case of m=0:
# v_para_res[:,mres==0] = (w/kz)[:,np.newaxis]
# v_tot_res = v_para_res / np.cos(alpha_lc)
# E_res = sc.E_EL*(1.0/np.sqrt( 1-(v_tot_res*v_tot_res/(sc.C*sc.C)) ) - 1 )
# # Start and end indices in the energy array (+-20% energy band)
# e_starti = np.floor((np.log10(E_res)-sc.E_EXP_BOT-sc.E_BANDWIDTH)/sc.DE_EXP)
# e_endi = np.ceil(( np.log10(E_res)-sc.E_EXP_BOT+sc.E_BANDWIDTH)/sc.DE_EXP)
# # Threshold to range of actual indexes (some energies may be outside our target range)
# np.clip(e_starti,0,sc.NUM_E, out=e_starti)
# np.clip(e_endi, 0,sc.NUM_E, out=e_endi)
# #print "Start index:",e_starti
# #print "Stop index: ",e_endi
# #inds = zip(e_starti.ravel(), e_endi.ravel())
# #print np.shape(inds)
# #v_tot = direction*v_tot_arr[e_]
# # emask = np.zeros((len(cells), len(mres), sc.NUM_E),dtype=bool)
# # for index, starti in np.ndenumerate(e_starti):
# # emask[index[0], index[1],e_starti[index]:e_endi[index]] = True
# # print "total emask: ",np.sum(emask)
# # emask[:,:,e_starti:e_endi] = True
# #print "emask is: ", np.shape(emask)
# # Where you left off: Adding in the next loop (V_TOT). Need to iterate from estarti to eendi
# # for each cell in the 2d arrays... hmm.... how to vectorize nicely. Hmm.
# #print "e_starti is", np.shape(e_starti)
# for index, starti in np.ndenumerate(e_starti):
# endi = e_endi[index]
# #print starti, endi
# # Energies to do
# #print Ezw.index.values
# #print Ezw[index(0)]
# if endi >= starti:
# # Dimensions of matrices: (num cells) rows x (num energies) columns
# #print "Index is", index
# v_tot = direction[index]*sc.v_tot_arr[starti:endi]
# v_para = v_tot*calph
# v_perp = abs(v_tot*salph)
# # Relativistic factor
# gamma = 1.0/np.sqrt(1.0 - pow(v_tot/sc.C, 2))
# alpha2 = (sc.Q_EL/sc.M_EL)*(Ezw.iloc[index[0]]/w1.iloc[index[0]])/(gamma*v_perp)
# #print "gamma:", gamma
# #print "alpha2:",alpha2
# # beta = np.outer(kx/wh,v_perp)
# beta = (kx.iloc[index[0]]/wh)*v_perp
# #print "beta:", beta
# mr = mres[index[1]]
# # wtau_sq = (pow((-1),(mr-1))*np.outer(w1, 1.0/gamma) *
# # (jn(mr -1, beta) -
# # alpha1[:,np.newaxis]*jn(mr + 1, beta) +
# # gamma[np.newaxis,:]*alpha2*jn(mr, beta)))
# wtau_sq = (pow((-1),(mr-1))*(w1.iloc[index[0]]/gamma)*
# jn(mr - 1, beta) -
# alpha1.iloc[index[0]]*jn(mr + 1, beta) +
# gamma*alpha2*jn(mr,beta))
# #T1 = -wtau_sq*(1 + calph*calph/(mr*Y[:,np.newaxis] - 1))
# T1 = -wtau_sq*(1 + calph*calph/(mr*Y.iloc[index[0]] - 1))
# # Analytical evaluation! (Line 1938)
# if (abs(lat) < 1e-3):
# eta_dot = mr*wh/gamma - w.iloc[index[0]] - kz.iloc[index[0]]*v_para
# dalpha_eq = abs(T1/eta_dot)*np.sqrt(1 - np.cos(ds*eta_dot/v_para))
# else:
# v_para_star = v_para - dv_para_ds*ds/2.0
# v_para_star_sq = v_para_star*v_para_star
# AA = ((mr/(2.0*v_para_star*gamma))*dwh_ds *
# (1 + ds/(2.0*v_para_star)*dv_para_ds) -
# (mr/(2.0*v_para_star_sq*gamma))*wh*dv_para_ds +
# (w.iloc[index[0]]/(2.0*v_para_star_sq))*dv_para_ds)
# BB = ((mr/(gamma*v_para_star))*wh -
# (mr/(gamma*v_para_star))*dwh_ds*(ds/2.0) -
# w.iloc[index[0]]/v_para_star - kz.iloc[index[0]])
# Farg = (BB + 2.0*AA*ds) / np.sqrt(2.0*np.pi*abs(AA))
# Farg0 = BB / np.sqrt(2*np.pi*abs(AA))
# Fs, Fc = fresnel(Farg)
# Fs0, Fc0 = fresnel(Farg0)
# dFs_sq = pow(Fs - Fs0, 2)
# dFc_sq = pow(Fc - Fc0, 2)
# dalpha = np.sqrt( (np.pi/4.0)*abs(AA))*abs(T1/v_para)*np.sqrt(dFs_sq + dFc_sq)
# alpha_eq_p = np.arcsin( np.sin(alpha_lc+dalpha)*pow(clat,3) / np.sqrt(slat_term) )
# dalpha_eq = alpha_eq_p - alpha_eq
# #print dalpha_eq
# #print "output vec shape:", np.shape(dalpha_eq)
# #print "end - start:", endi - starti
# #print "t offset:",t.iloc[index[0]]
# # Add net change in alpha to total array:
# if direction[index] > 0:
# #print "Norf!"
# tt = np.round( (t.iloc[index[0]] + ftc_N/v_para)/sc.T_STEP ).astype(int)
# #print tt
# np.clip(tt,0,sc.NUM_STEPS - 1, out=tt)
# #tt.clip(0,sc.NUM_STEPS)
# DA_array_N[starti:endi,tt] += dalpha_eq*dalpha_eq
# else:
# #print "Souf!"
# tt = np.round( (t.iloc[index[0]] + ftc_S/v_para)/sc.T_STEP ).astype(int)
# np.clip(tt,0,sc.NUM_STEPS - 1, out=tt)
# #print tt
# DA_array_S[starti:endi,tt] += dalpha_eq*dalpha_eq
tstop = time.time()
print "Scattering took %g seconds"%(tstop - tstart)
return DA_array_N, DA_array_S
def euler_spiral_parametric(t):
s, c = fresnel(t)
return numpy.column_stack((t, c, s))
d = 0.75 # slitwidth mm
lam = 2.66e-4 # wavelength mm
x = np.linspace(-1.5*d,1.5*d,5000) # distance in x direction mm
z = np.linspace(0,3,1000) # log10 of the distance to the screen mm
I1 = np.zeros((len(x),len(z))) # set up array to receive the intensity data
# fix slitwidth, vary screen location
for i in range (0,len(z)-1):
alpha_1 = (x+d/2)*(np.sqrt(2/(lam*10**z[i])))
alpha_2 = (x-d/2)*(np.sqrt(2/(lam*10**z[i])))
s1, c1 = fresnel(alpha_1) #Fresnel integrals
s2, c2 = fresnel(alpha_2) #Fresnel integrals
Intensity = 0.5*((c2-c1)**2+(s2-s1)**2)
I1[:,i]= Intensity
zplot = 310 # distance at which you would like to plot the intesity pattern mm
plt.figure(1)
plt.plot(x,I1[:,np.where(10**z>zplot-1)[0][0]])
plt.xlabel("x (mm)")
plt.ylabel("Intensity (au)")
plt.title("Intensity profile " + str(int(10**z[np.where(10**z>zplot-1)[0][0]])) + "mm behind a slit of width " + str(d) + "mm")
# plot limts
def integrand(u, N):
fS, fC = fresnel((self.mu[0] * N * np.pi + self.mu[1] * u) / np.sqrt(self.mu[1] * N * np.pi**2))
term1 = np.cos(np.pi * self.mu[0]**2 * N / (2. * self.mu[1]) + 2. * np.pi * self.nu0 * N)
term2 = np.sin(np.pi * self.mu[0]**2 * N / (2. * self.mu[1]) + 2. * np.pi * self.nu0 * N)
return fC * term1 + fS * term2
def dist(alpha): fresnelS, fresnelC = fresnel(math.sqrt(2 * alpha / math.pi)) return math.cos(alpha) * fresnelC + math.sin(alpha) * fresnelS
def fres(t): s, c = fresnel(math.sqrt(2.0 * t / math.pi)) return math.cos(t) * c + math.sin(t) * s
def fresnel0(s):
im, re = special.fresnel(s);
return complex(re, im);
def LocBeamInt2(x, z):
s3, c3 = fresnel(x*(np.sqrt(2/(lam*10**z))))
I = 0.5*((c3[0:steplen]-c3[steplen:])**2+(s3[0:steplen]-s3[steplen:])**2)
return I;
### ch 1.4 Integration
# p10
###-----------------------------------
### ch 1.4.1 General integration(quad)
from scipy import integrate, special
result = integrate.quad(lambda x:special.jv(2.5,x), 0, 4.5)
print result
I = sqrt(2/pi) * (18.0/27 *sqrt(2) *cos(4.5) - 4.0 /27 *sqrt(2) *sin(4.5) + sqrt(2 *pi) *special.fresnel(3 /sqrt(pi))[0])
print I
print abs(result[0] - I)
###-----------------------------------
### p11
from scipy.integrate import quad
def integrand(t,n,x):
return exp(-x*t) / t**n
def expint(n,x):
return quad(integrand, 1, Inf, args=(n, x))[0]
vec_expint = vectorize(expint)
pointval = 500 #number of points d = 1.0#0.75 #slitwidth mm lam = 2.66e-4 # wavelength mm zposlim = 500 RefSpace = np.empty([pointval, zposlim]) #Array of Reflection values IntSpace = np.empty([pointval, zposlim]) xpos1 = np.linspace(-GratLimP/2,GratLimP/2,GratLenOutside)# distance in x direction mm xpos2 = np.linspace(-GratLimP/2,GratLimP/2,pointval) zpos = np.linspace(0.5,3.5,zposlim) # log10 of the distance to the screen mm lampos = np.linspace(1.498,1.503,pointval) #wavelength range microns steplen = (GratLenOutside+(d/Period)*10**3)/2 xpos3 = np.linspace(-(GratLimP+d)/2, (GratLimP+d)/2, steplen*2) s3, c3 = fresnel(xpos3) #tiamat = LocBeamInt(xpos3, zpos[300]) # plt.plot(s3) plt.plot(c3) plt.show() #dpos = np.linspace(0.5,1.5,zposlim) #for y in range(0,10,1):#zposlim,1): # d = dpos[y] # for x in range(0,pointval,1): # RefSpace[x,y] = CompRef(lampos[x], xpos1, 2.5).real # IntSpace[x,y] = LocBeamInt(xpos2[x], 2.5) #for tep in range(1,9,1):
def fresnel_k0_abg(a, s):
c0 = sqrt(abs(a) / math.pi)
y, x = special.fresnel(c0 * s)
return complex(x / c0, copysign(1, a) * y / c0)
