def calculate_corner_periods(periods, ground_motion, magnitude):
"""
periods - 1D array, dimension # of periods
ground_motion - XD array, with last dimension periods.
magnitude - 1D array, dimension # of events
from Newmark and Hall 1982
returns TAV,TVD - the acceleration and velocity dependent
corner periods
TAV and TVD have the same dimensions as ground_motion, except
the last axis (periods) is dropped.
"""
#reference_periods = 0.3,1.0
S03=interp(array(0.3),ground_motion,periods,axis=-1)
S10=interp(array(1.0),ground_motion,periods,axis=-1)
#print 'S03',S03[:,0:5]
#print 'S10',S10[:,0:5]
# interpolate the ground motion at reference periods
acceleration_dependent=(S10/S03)
acceleration_dependent[where(S03<0.00000000000001)]=0.0
acceleration_dependent=acceleration_dependent[...,0] # and collapse
# This assumes ground_motion.shape = (1, events)
velocity_dependent=(10**((magnitude-5.0)/2))[newaxis,:]
assert len(acceleration_dependent.shape)==2
assert len(velocity_dependent.shape)==2
# removed this assert so test_cadell_damage passes.
# This test passes 4660 sites, instead of the usual 1.
# Fixing/ getting rid of the test is another option...
#assert velocity_dependent.shape == acceleration_dependent.shape
return acceleration_dependent, velocity_dependent
def get_dragon_type_for_potion(item):
rand = random.randint(1, 20)
item['xplo'] = interp(item['xplo'], item['xphi'], rand, 20)
item['gplo'] = interp(item['gplo'], item['gphi'], rand, 20)
if rand <= 2:
item['name'] = item['name'] + " (white)"
elif rand <= 4:
item['name'] = item['name'] + " (black)"
elif rand <= 7:
item['name'] = item['name'] + " (green)"
elif rand <= 9:
item['name'] = item['name'] + " (blue)"
elif rand <= 10:
item['name'] = item['name'] + " (red)"
elif rand <= 12:
item['name'] = item['name'] + " (brass)"
elif rand <= 14:
item['name'] = item['name'] + " (copper)"
elif rand <= 15:
item['name'] = item['name'] + " (bronze)"
elif rand <= 16:
item['name'] = item['name'] + " (silver)"
elif rand <= 17:
item['xplo'] = item['xphi']
item['gplo'] = item['gphi']
item['name'] = item['name'] + " (gold)"
elif rand <= 19:
item['xplo'] = item['xphi']
item['gplo'] = item['gphi']
item['name'] = item['name'] + " (evil)"
elif rand <= 20:
item['xplo'] = item['xphi']
item['gplo'] = item['gphi']
item['name'] = item['name'] + " (good)"
def undamped_response(SA,periods,atten_override_RSA_shape=None,
atten_cutoff_max_spectral_displacement=False,
loss_min_pga=0.0,
magnitude=None):
"""
Calculate SD from SA
"""
if atten_override_RSA_shape is None:
pass
elif atten_override_RSA_shape == 'Aust_standard_Sa':
from eqrm_code.ground_motion_misc import Australian_standard_model
SA=SA[:,:,0:1]*Australian_standard_model(periods[newaxis,newaxis,:])
elif atten_override_RSA_shape == 'HAZUS_Sa':
#reference_periods = 0.3,1.0
S03=interp(array(0.3),SA,periods,axis=-1)
S10=interp(array(1.0),SA,periods,axis=-1)
# interpolate the ground motion at reference periods
acceleration_dependent=(S10/S03)
acceleration_dependent[where(S03<0.00000000000001)]=0.0
acceleration_dependent=acceleration_dependent[:,:,0] # and collapse
velocity_dependent=(10**((magnitude-5.0)/2))[newaxis,:]
Tm = periods[newaxis,newaxis,:]
S03M = S03
S10M = S10
TavM = acceleration_dependent[:,:,newaxis]
TvdM = velocity_dependent[:,:,newaxis]
# set up Boolean arrays for the three regions
# (accel, vel, disp, sensitive)
bA = (Tm < TavM)
bV = (Tm >= TavM) & (Tm <= TvdM)
bD = (Tm > TvdM)
SA=(S03M*bA)
SA[where(bV)]=(S10M/Tm)[where(bV)]
SA[where(bD)]=((S10M*TvdM)/(Tm**2))[where(bD)]
#SA = (S03M*bA) + (S10M/Tm)*bV + ((S10M*TvdM)/(Tm**2))*bD
else:
print 'atten_override_RSA_shape = ',atten_override_RSA_shape
raise NotImplementedError('atten_override_RSA_shape = '+str(atten_override_RSA_shape))
too_low=SA[:,:,0:1]<loss_min_pga
scaling_factor=where(too_low,0,1)
SA=SA*scaling_factor
# calculate surface displacement:
#surface_displacement~=(250*(periods**2))*SA
#dimension=1e3*9.8 # convert from g forces to m/s^2, and m to mm
# dimension/(4*pi**2) = 248.236899924
surface_displacement=((248.236899924)*(periods**2))*SA
if atten_cutoff_max_spectral_displacement is True:
surface_displacement=cutoff_after_max(surface_displacement,periods)
return SA,surface_displacement
def _forward(self, input):
if self.shift is not None:
coord = self.coord + self.shift
else:
coord = self.coord
real = interp.interp(self.table, coord, tf.real(input))
with tf.control_dependencies([real]):
imag = interp.interp(self.table, coord, tf.imag(input))
return tf.reshape(tf.complex(real, imag), self.oshape)
def get_medallion_type(item):
rand = random.randint(1, 20)
item['xplo'] = interp(item['xplo'], item['xphi'], rand, 100)
item['gplo'] = interp(item['gplo'], item['gphi'], rand, 100)
if rand <= 15:
item['name'] = item['name'] + " (30')"
elif rand <= 18:
item['name'] = item['name'] + " (30'+ empathy)"
elif rand <= 19:
item['name'] = item['name'] + " (60')"
elif rand <= 20:
item['name'] = item['name'] + " (90')"
def test_interp_no_extrapolate_low(self):
functx = asarray([1,2])
functy = asarray([10,20])
x = asarray([1.3,1.5,1.7])
y = interp(x, functy, functx, extrapolate_low=False)
y_ans = x * 10.0
self.assert_(allclose(y, y_ans, rtol=0.05))
x = asarray([0.5,1.5,2.5])
y = interp(x, functy, functx, extrapolate_low=False)
y_ans = x * 10.0
self.assert_(allclose(y, [10.,15.,25.], rtol=0.05))
def test_interp_no_extrapolate_low_bad_ordering(self):
functx = asarray([2, 1, 0.8])
functy = asarray([20, 10, 8])
x = asarray([1.3,1.5,1.7])
y = interp(x, functy, functx, extrapolate_low=False)
y_ans = x * 10.0
self.assert_(allclose(y, y_ans, rtol=0.05))
x = asarray([0.5,1.5,2.5])
y = interp(x, functy, functx, extrapolate_low=False)
y_ans = x * 10.0
self.assert_(allclose(y, [8.,15.,25.], rtol=0.05))
def test_interp(self):
functx = asarray([1,2])
functy = asarray([10,20])
x = asarray([0.5,1.5,2.5])
y = interp(x, functy, functx)
y_ans = x * 10.0
self.assert_(allclose(y, y_ans, rtol=0.05))
def get_misc_girdle_type(item):
rand = random.randint(1, 100)
item['xplo'] = interp(item['xplo'], item['xphi'], rand, 100)
item['gplo'] = interp(item['gplo'], item['gphi'], rand, 100)
if rand <= 30:
item['name'] = item['name'] + ", hill"
elif rand <= 50:
item['name'] = item['name'] + ", stone"
elif rand <= 70:
item['name'] = item['name'] + ", frost"
elif rand <= 85:
item['name'] = item['name'] + ", fire"
elif rand <= 95:
item['name'] = item['name'] + ", cloud"
elif rand <= 100:
item['name'] = item['name'] + ", storm"
def get_token_type(item):
rand = random.randint(1, 20)
if rand <= 4:
item['name'] = item['name'] + ", anchor"
elif rand <= 7:
item['name'] = item['name'] + ", bird"
elif rand <= 10:
item['name'] = item['name'] + ", fan"
elif rand <= 13:
item['name'] = item['name'] + ", swan boat"
elif rand <= 18:
item['name'] = item['name'] + ", tree"
elif rand <= 20:
item['name'] = item['name'] + ", whip"
item['xplo'] = interp(item['xplo'], item['xphi'], rand, 20)
item['gplo'] = interp(item['gplo'], item['gphi'], rand, 20)
def get_giant_strength_for_potion(item):
rand = random.randint(1, 20)
item['xplo'] = interp(item['xplo'], item['xphi'], rand, 20)
item['gplo'] = interp(item['gplo'], item['gphi'], rand, 20)
if rand <= 6:
item['name'] = item['name'] + " (hill)"
elif rand <= 10:
item['name'] = item['name'] + " (stone)"
elif rand <= 14:
item['name'] = item['name'] + " (frost)"
elif rand <= 17:
item['name'] = item['name'] + " (fire)"
elif rand <= 19:
item['name'] = item['name'] + " (cloud)"
elif rand == 20:
item['name'] = item['name'] + " (storm)"
def test_interp_no_extrapolate_high_local_max(self):
functx = asarray([2, 1, 3])
functy = asarray([30, 10, 20])
x = asarray([0.5, 1.5, 2.5, 3.0, 4.0])
y = interp(x, functy, functx, extrapolate_high=False)
#print "y", y
self.assert_(allclose(y, [0., 20., 25., 20., 20.], rtol=0.05))
def set_ring_subtype(item, rand=None):
if not rand:
rand = random.randint(1, 100)
item['xplo'] = interp(item['xplo'], item['xphi'], rand, 100)
item['gplo'] = interp(item['gplo'], item['gphi'], rand, 100)
if rand <= 70:
item['name'] = item['name'] + " +1"
elif rand <= 82:
item['name'] = item['name'] + " +2"
elif rand <= 83:
item['name'] = item['name'] + " +2 (5' radius)"
elif rand <= 90:
item['name'] = item['name'] + " +3"
elif rand <= 91:
item['name'] = item['name'] + " +3 (5' radius)"
elif rand <= 97:
item['name'] = item['name'] + " +4 AC, +2 saves"
else:
item['name'] = item['name'] + " +6 AC, +1 saves"
def main( argv ):
"""
Script execution entry point
@param argv Arguments passed to the script
@return Exit code (0 = success)
"""
# imports when using this as a script
import argparse
# create and configure an argument parser
parser = argparse.ArgumentParser(
description = 'Lester',
add_help = False
)
parser.add_argument(
'-h',
'--help',
default = False,
help = 'Display this help message and exit.',
action = 'help'
)
parser.add_argument(
'-v',
'--version',
default = False,
help = 'Display script version and exit.',
action = 'version',
version = __version__
)
# parse the arguments
args = parser.parse_args( argv[ 1 : ] )
# check args.* for script execution here
print 'Lester ' + __version__
print ' type "exit" to return to shell'
lirp = interp.interp()
lirp.run( sys.stdin, sys.stdout, interactive = True )
# return success
return 0
def main(argv):
"""
Script execution entry point
@param argv Arguments passed to the script
@return Exit code (0 = success)
"""
# imports when using this as a script
import argparse
# create and configure an argument parser
parser = argparse.ArgumentParser(description='Lester', add_help=False)
parser.add_argument('-h',
'--help',
default=False,
help='Display this help message and exit.',
action='help')
parser.add_argument('-v',
'--version',
default=False,
help='Display script version and exit.',
action='version',
version=__version__)
# parse the arguments
args = parser.parse_args(argv[1:])
# check args.* for script execution here
print 'Lester ' + __version__
print ' type "exit" to return to shell'
lirp = interp.interp()
lirp.run(sys.stdin, sys.stdout, interactive=True)
# return success
return 0
from Environment import default_environment
from Tokenize import read_tokens, create_tokens
from interp import interp, return_quoted_text
if __name__=='__main__':
env = default_environment()
while True:
lisp = raw_input("PyLisp>> ")
if (lisp.lower() == 'exit' or lisp.lower() == 'exit()'):
break
elif lisp.replace(" ","") == '':
continue
lisp_tokens = read_tokens(create_tokens(lisp))
lisp_interpreted = interp(lisp_tokens,env)
if lisp_interpreted:
print lisp_interpreted
self.extIds = {}
# Since we call getExpr with no left, must start with a noLeft op, presumably !!SOF
def compiler(toks):
doMCTcmd('operator "A.AstTuple" ["!!defaultOperand"]', None)
doMCTcmd('operator "None" ["!!SOF"] ["!!EOF"]', None)
doMCTcmd('operator "None" ["!!SOF"] () ["!!EOF"]', None)
#opCtx = OpCtx(upOpCtx=None,indx=0,altOpInfos=[])
e, toks = getExpr(toks=toks,
left=None,
prio=None,
opCtx=None,
noneOK=False)
c = A.AstClosure(e)
c.fixUp(parent=None, closure=FakeAstClosure(I.builtins),
upChain=()) # will fixup e as well
return c
import sys
if __name__ == "__main__":
import lexer
global ast
global debug
debug = len(sys.argv) > 2
ast = compiler(L.lexer(sys.argv[1]))
#for l in ast.pp(1): print(l)
print(I.interp(ast, debug).pp())
import numpy as np
from interp import interpolation as interp
# Define start and end point and the number of points in the function (n) and in the interpolation (N)
n = 50
N = 100
start = 0
end = 4 * np.pi
# Make input -- as an example, the cosine function is used.
x = np.linspace(start, end, n)
y = np.cos(x)
z = np.linspace(start, end, N)
y_dev = -np.sin(x)
y_int = np.sin(x)
# Initialize the class
i_cos = interp(x, y)
# Interpolate
s_qspl, s_qsplint, s_qspldev = i_cos.qspline(z)
# Print the values in order to save the stdout
for i in range(N):
if i < n:
print('%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s' %
(z[i], s_qspl[i], s_qsplint[i], s_qspldev[i], x[i], y[i],
y_int[i], y_dev[i]))
else:
print('%s\t%s\t%s\t%s' % (z[i], s_qspl[i], s_qsplint[i], s_qspldev[i]))
def main(dem, mesh_f, mesh_i):
f = interp(dem)
interp_mesh(mesh_f, mesh_i, f)
def Parameter_reader(profile_name, geomfile, q_scale, manual_ped, mid_ped0,
plot, output_csv):
n0 = 1.
mref = 2. # mass of ion in proton mass
if profile_type == "ITERDB":
rhot0, rhop0, te0, ti0, ne0, ni0, nz0, vrot0 = read_profile_file(
profile_type, profile_name, geomfile_name, suffix)
else:
rhot0, rhop0, te0, ti0, ne0, ni0, vrot0 = read_profile_file(
profile_type, profile_name, geomfile_name, suffix)
if geomfile_type == "gfile":
xgrid, q = read_geom_file(geomfile_type, geomfile_name, suffix)
elif geomfile_type == "GENE_tracor":
xgrid, q, Lref, Bref, x0_from_para = read_geom_file(
geomfile_type, geomfile_name, suffix)
q = q * q_scale
if geomfile_type == "GENE_tracor" and profile_type != "profile":
rhot0_range_min = np.argmin(abs(rhot0 - xgrid[0]))
rhot0_range_max = np.argmin(abs(rhot0 - xgrid[-1]))
rhot0 = rhot0[rhot0_range_min:rhot0_range_max]
rhop0 = rhop0[rhot0_range_min:rhot0_range_max]
te0 = te0[rhot0_range_min:rhot0_range_max]
ti0 = ti0[rhot0_range_min:rhot0_range_max]
ne0 = ne0[rhot0_range_min:rhot0_range_max]
ni0 = ni0[rhot0_range_min:rhot0_range_max]
vrot0 = vrot0[rhot0_range_min:rhot0_range_max]
uni_rhot = np.linspace(min(rhot0), max(rhot0), len(rhot0) * 10.)
te_u = interp(rhot0, te0, uni_rhot)
ne_u = interp(rhot0, ne0, uni_rhot)
ni_u = interp(rhot0, ni0, uni_rhot)
#nz_u = interp(rhot0,nz0,uni_rhot)
vrot_u = interp(rhot0, vrot0, uni_rhot)
q = interp(xgrid, q, uni_rhot)
tprime_e = -fd_d1_o4(te_u, uni_rhot) / te_u
nprime_e = -fd_d1_o4(ne_u, uni_rhot) / ne_u
qprime = fd_d1_o4(q, uni_rhot) / q
#center_index = np.argmax((tprime_e*te_u+nprime_e*ne_u)[0:int(len(tprime_e)*0.99)])
if manual_ped == 1:
x0_center = mid_ped0
else:
if geomfile_type == "gfile":
midped, topped = find_pedestal(file_name=geomfile_name,
path_name='',
plot=False)
elif geomfile_type == "GENE_tracor":
midped = x0_from_para
x0_center = midped
print('mid pedestal is at r/a = ' + str(x0_center))
if geomfile_type == "gfile":
Lref, Bref, R_major, q0, shat0 = get_geom_pars(geomfile_name,
x0_center)
print("Lref=" + str(Lref))
print("x0_center=" + str(x0_center))
index_begin = np.argmin(abs(uni_rhot - x0_center + 2 * (1. - x0_center)))
te_u = te_u[index_begin:len(uni_rhot) - 1]
ne_u = ne_u[index_begin:len(uni_rhot) - 1]
ni_u = ni_u[index_begin:len(uni_rhot) - 1]
vrot_u = vrot_u[index_begin:len(uni_rhot) - 1]
q = q[index_begin:len(uni_rhot) - 1]
tprime_e = tprime_e[index_begin:len(uni_rhot) - 1]
nprime_e = nprime_e[index_begin:len(uni_rhot) - 1]
qprime = qprime[index_begin:len(uni_rhot) - 1]
uni_rhot = uni_rhot[index_begin:len(uni_rhot) - 1]
Lt = 1. / tprime_e
Ln = 1. / nprime_e
Lq = 1. / qprime
center_index = np.argmin(abs(uni_rhot - x0_center))
q0 = q[center_index]
ne = ne_u / (10.**19.) # in 10^19 /m^3
ni = ni_u / (10.**19.) # in 10^19 /m^3
te = te_u / 1000. #in keV
m_SI = mref * 1.6726 * 10**(-27)
me_SI = 9.11 * 10**(-31)
c = 1.
qref = 1.6 * 10**(-19)
#refes to GENE manual
coll_c = 2.3031 * 10**(-5) * Lref * ne / (te)**2 * (
24 - np.log(np.sqrt(ne * 10**13) / (te * 1000)))
coll_ei = 4 * (ni / ne) * coll_c * np.sqrt(
te * 1000. * qref / me_SI) / Lref
nuei = coll_ei
beta = 403. * 10**(-5) * ne * te / Bref**2.
nref = ne_u[center_index]
te_mid = te_u[center_index]
Tref = te_u[center_index] * qref
cref = np.sqrt(Tref / m_SI)
Omegaref = qref * Bref / m_SI / c
rhoref = cref / Omegaref
kymin = n0 * q0 * rhoref / (Lref * x0_center)
kyGENE = kymin * (q / q0) * np.sqrt(te_u / te_mid) * (
x0_center / uni_rhot) #Add the effect of the q varying
#from mtm_doppler
omMTM = kyGENE * (tprime_e + nprime_e)
gyroFreq = 9.79E3 / np.sqrt(mref) * np.sqrt(te_u) / Lref
mtmFreq = omMTM * gyroFreq / (2. * np.pi * 1000.)
omegaDoppler = abs(vrot_u * n0 / (2. * np.pi * 1000.))
omega = mtmFreq + omegaDoppler
omega_n_GENE = kyGENE * (nprime_e) #in cs/a
omega_n = omega_n_GENE * gyroFreq / (2. * np.pi * 1000.) #in kHz
zeff = (ni + nz * Z**2.) * (1. / ni)
coll_ei = coll_ei / (1000.) #in kHz
shat = Ln / Lq
eta = Ln / Lt
ky = kyGENE
nu = (coll_ei) / (omega_n)
nuei = nu * omega_n_GENE / omega_n
mean_rho, xstar = omega_gaussian_fit(uni_rhot, mtmFreq, rhoref, Lref, plot)
if plot == True:
plt.clf()
plt.plot(uni_rhot, nuei, label='nuei(cs/a)')
plt.plot(uni_rhot, nuei * 2. * np.pi, label='nuei(cs/a)*2 pi')
plt.plot(uni_rhot, nuei * zeff, label='nuei(cs/a)*2 pi')
plt.legend()
plt.title('nuei')
plt.axvline(0.96, color='red', alpha=1.)
plt.show()
plt.clf()
plt.xlabel('r/a')
plt.ylabel('eta')
plt.plot(uni_rhot, eta, label='eta')
plt.show()
plt.clf()
#plt.title('mode number finder')
plt.xlabel('r/a')
plt.ylabel('omega*(Lab), kHz')
plt.plot(uni_rhot, omega, label='omega*(Lab)')
plt.show()
plt.clf()
plt.xlabel('r/a')
plt.ylabel('eta')
plt.plot(uni_rhot, eta, label='eta')
plt.show()
plt.clf()
plt.xlabel('r/a')
plt.ylabel('shat')
plt.plot(uni_rhot, shat, label='shat')
plt.show()
plt.clf()
plt.xlabel('r/a')
plt.ylabel('beta')
plt.plot(uni_rhot, beta, label='beta')
plt.show()
plt.clf()
plt.xlabel('r/a')
plt.ylabel('ky rhoi')
plt.plot(uni_rhot, ky, label='ky')
plt.show()
if output_csv == True:
with open('profile_output.csv', 'w') as csvfile:
data = csv.writer(csvfile, delimiter=',')
data.writerow([
'x/a', 'nu_ei(kHz)', 'omega*n(kHz)', 'omega* plasma(kHz)',
'Doppler shift(kHz)', 'nu/omega*n', 'eta', 'shat', 'beta',
'ky rhoi(for n=1)'
])
for i in range(len(uni_rhot)):
data.writerow([
uni_rhot[i], coll_ei[i], omega_n[i], mtmFreq[i],
omegaDoppler[i], nu[i], eta[i], shat[i], beta[i], ky[i]
])
csvfile.close()
return uni_rhot, nu, eta, shat, beta, ky, q, mtmFreq, omegaDoppler, omega_n, omega_n_GENE, xstar, Lref, rhoref
from parser import token_list, get_env, parse
from interp import interp
if __name__ == "__main__":
#take in input as string
input_str = "[hello,there]\nCOND\nCASE 0 > 1\nPRINT yes\nCASE 0 < 1\nPRINT no\nCONDEND"
#seperate program into individual lines
splt_line_lst = token_list(input_str)
#get env from first line
env = get_env(splt_line_lst)
#fill_env(env)
#parse program
ast = parse(splt_line_lst)
#interp ast with given env
interp(ast, env)
def Parameter_reader(path, profile_name, geomfile, q_scale, manual_ped,
mid_ped0, plot, output_csv):
n0 = 1.
mref = 2. # mass of ion in proton mass
if profile_type == "ITERDB":
rhot0, rhop0, te0, ti0, ne0, ni0, nz0, vrot0 = read_profile_file(
profile_type, path + '/' + profile_name,
path + '/' + geomfile_name, suffix)
elif profile_type == "pfile":
rhot0, rhop0, te0, ti0, ne0, ni0, nz0, vrot0 = read_profile_file(
profile_type, path + '/' + profile_name,
path + '/' + geomfile_name, suffix)
if geomfile_type == "gfile":
xgrid, q, R_ref = read_geom_file(geomfile_type,
path + '/' + geomfile_name, suffix)
elif geomfile_type == "GENE_tracor":
xgrid, q, Lref, R_ref, Bref, x0_from_para = read_geom_file(
geomfile_type, path + '/' + geomfile_name, suffix)
q = q * q_scale
if geomfile_type == "GENE_tracor" and profile_type != "profile":
rhot0_range_min = np.argmin(abs(rhot0 - xgrid[0]))
rhot0_range_max = np.argmin(abs(rhot0 - xgrid[-1]))
rhot0 = rhot0[rhot0_range_min:rhot0_range_max]
rhop0 = rhop0[rhot0_range_min:rhot0_range_max]
te0 = te0[rhot0_range_min:rhot0_range_max]
ti0 = ti0[rhot0_range_min:rhot0_range_max]
ne0 = ne0[rhot0_range_min:rhot0_range_max]
ni0 = ni0[rhot0_range_min:rhot0_range_max]
nz0 = nz0[rhot0_range_min:rhot0_range_max]
vrot0 = vrot0[rhot0_range_min:rhot0_range_max]
uni_rhot = np.linspace(min(rhot0), max(rhot0), len(rhot0) * 10)
te_u = interp(rhot0, te0, uni_rhot)
ne_u = interp(rhot0, ne0, uni_rhot)
ni_u = interp(rhot0, ni0, uni_rhot)
print(str((len(rhot0), len(nz0), len(uni_rhot))))
nz_u = interp(rhot0, nz0, uni_rhot)
vrot_u = interp(rhot0, vrot0, uni_rhot)
q = interp(xgrid, q, uni_rhot)
tprime_e = -fd_d1_o4(te_u, uni_rhot) / te_u
nprime_e = -fd_d1_o4(ne_u, uni_rhot) / ne_u
qprime = fd_d1_o4(q, uni_rhot) / q
#center_index = np.argmax((tprime_e*te_u+nprime_e*ne_u)[0:int(len(tprime_e)*0.99)])
if manual_ped == 1:
x0_center = mid_ped0
else:
if geomfile_type == "gfile":
midped, topped = find_pedestal(file_name=path + '/' +
geomfile_name,
path_name='',
plot=False)
elif geomfile_type == "GENE_tracor":
midped = x0_from_para
x0_center = midped
print('mid pedestal is at r/a = ' + str(x0_center))
if geomfile_type == "gfile":
Lref, Bref, R_major, q0, shat0 = get_geom_pars(
path + '/' + geomfile_name, x0_center)
print("Lref=" + str(Lref))
print("x0_center=" + str(x0_center))
index_begin = np.argmin(abs(uni_rhot - x0_center + 2 * (1. - x0_center)))
te_u = te_u[index_begin:len(uni_rhot) - 1]
ne_u = ne_u[index_begin:len(uni_rhot) - 1]
ni_u = ni_u[index_begin:len(uni_rhot) - 1]
nz_u = nz_u[index_begin:len(uni_rhot) - 1]
vrot_u = vrot_u[index_begin:len(uni_rhot) - 1]
q = q[index_begin:len(uni_rhot) - 1]
tprime_e = tprime_e[index_begin:len(uni_rhot) - 1]
nprime_e = nprime_e[index_begin:len(uni_rhot) - 1]
qprime = qprime[index_begin:len(uni_rhot) - 1]
uni_rhot = uni_rhot[index_begin:len(uni_rhot) - 1]
Lt = 1. / tprime_e
Ln = 1. / nprime_e
center_index = np.argmin(abs(uni_rhot - x0_center))
q0 = q[center_index]
ne = ne_u / (10.**19.) # in 10^19 /m^3
ni = ni_u / (10.**19.) # in 10^19 /m^3
nz = nz_u / (10.**19.) # in 10^19 /m^3
te = te_u / 1000. #in keV
m_SI = mref * 1.6726 * 10**(-27)
me_SI = 9.11 * 10**(-31)
c = 1.
qref = 1.6 * 10**(-19)
#refes to GENE manual
coll_c = 2.3031 * 10**(-5) * Lref * ne / (te)**2 * (
24 - np.log(np.sqrt(ne * 10**13) / (te * 1000)))
coll_ei = 4. * coll_c * np.sqrt(te * 1000. * qref / me_SI) / Lref
nuei = coll_ei
beta = 403. * 10**(-5) * ne * te / Bref**2.
nref = ne_u[center_index]
te_mid = te_u[center_index]
Tref = te_u[center_index] * qref
cref = np.sqrt(Tref / m_SI)
Omegaref = qref * Bref / m_SI / c
rhoref = cref / Omegaref
rhoref_temp = rhoref * np.sqrt(te_u / te_mid)
kymin = n0 * q0 * rhoref / (Lref * x0_center)
kyGENE = kymin * (q / q0) * np.sqrt(te_u / te_mid) * (
x0_center / uni_rhot) #Add the effect of the q varying
#from mtm_doppler
omMTM = kyGENE * (tprime_e + nprime_e)
gyroFreq = 9.79E3 / np.sqrt(mref) * np.sqrt(te_u) / Lref
mtmFreq = omMTM * gyroFreq / (2. * np.pi * 1000.)
omegaDoppler = abs(vrot_u * n0 / (2. * np.pi * 1000.))
omega = mtmFreq + omegaDoppler
global zeff
zeff = ((ni + Z**2 * nz) / ne)[center_index]
if zeff_manual != False:
zeff = zeff_manual
print('********zeff*********')
print('zeff=' + str(zeff))
print('********zeff*********')
omega_n_GENE = kyGENE * (nprime_e) #in cs/a
print("*******************")
print("*******************")
print(np.max(omega_n_GENE))
print("*******************")
print("*******************")
omega_n = omega_n_GENE * gyroFreq / (2. * np.pi * 1000.) #in kHz
#coll_ei=coll_ei/(1000.) #in kHz
coll_ei = coll_ei / (2. * np.pi * 1000.) #in kHz
Lq = 1. / (Lref / (R_ref * q) * qprime)
shat = Ln / Lq
eta = Ln / Lt
ky = kyGENE * np.sqrt(2.)
nu = (coll_ei) / (np.max(omega_n))
nuei = nu * omega_n_GENE / omega_n
if plot == True:
if profile_type == "ITERDB0":
plt.clf()
plt.plot(uni_rhot, nuei, label='nuei(cs/a)')
plt.plot(uni_rhot, nuei * 2. * np.pi, label='nuei(cs/a)*2 pi')
plt.plot(uni_rhot, nuei * zeff, label='nuei*zeff')
plt.legend()
plt.title('nuei')
plt.axvline(0.96, color='red', alpha=1.)
plt.show()
index = np.argmin(
abs(float(input("Enter location of interest:\n")) - uni_rhot))
print('zeff(x/r=' + str(uni_rhot[index]) + ')=' + str(zeff[index]))
#print('id(x/r='+str(rho)+')='+str(id[index]))
print('nuei*zeff(x/r=' + str(uni_rhot[index]) + ')=' +
str((nuei * zeff)[index]))
print('nuei*2 pi(x/r=' + str(uni_rhot[index]) + ')=' +
str((nuei * 2. * np.pi)[index]))
plt.clf()
plt.xlabel('r/a')
plt.ylabel('nuei(kHZ)')
plt.plot(uni_rhot, nu * np.max(omega_n), label='coll')
plt.show()
d = {'uni_rhot': uni_rhot, 'nu*np.max(omega_n)': nu * np.max(omega_n)}
df = pd.DataFrame(d, columns=['uni_rhot', 'nu*np.max(omega_n)'])
df.to_csv('0nu_ei_smooth.csv', index=False)
plt.clf()
#plt.title('mode number finder')
plt.xlabel('r/a')
plt.ylabel('omega*, kHz')
plt.plot(uni_rhot, mtmFreq, label='omega*p')
plt.plot(uni_rhot, omega_n, label='omega*n')
plt.axvline(uni_rhot[np.argmax(mtmFreq)],
color='red',
alpha=1.,
label='peak of omega*p')
plt.axvline(uni_rhot[np.argmax(omega_n)],
color='green',
alpha=1.,
label='peak of omega*n')
plt.plot(uni_rhot, rhoref_temp, color='purple', label='rhoref')
plt.legend()
plt.show()
print("rho i for peak of omega*p: " +
str(rhoref_temp[np.argmax(mtmFreq)]))
print("rho i for peak of omega*n: " +
str(rhoref_temp[np.argmax(omega_n)]))
plt.clf()
plt.xlabel('r/a')
plt.ylabel('eta')
plt.plot(uni_rhot, eta, label='eta')
plt.show()
plt.clf()
#plt.title('mode number finder')
plt.xlabel('r/a')
plt.ylabel('omega*(Lab), kHz')
plt.plot(uni_rhot, omega, label='omega*(Lab)')
plt.show()
plt.clf()
plt.xlabel('r/a')
plt.ylabel('eta')
plt.plot(uni_rhot, eta, label='eta')
plt.show()
plt.clf()
plt.xlabel('r/a')
plt.ylabel('shat')
plt.plot(uni_rhot, shat, label='shat')
plt.show()
plt.clf()
plt.xlabel('r/a')
plt.ylabel('beta')
plt.plot(uni_rhot, beta, label='beta')
plt.show()
plt.clf()
plt.xlabel('r/a')
plt.ylabel('ky rhoi')
plt.plot(uni_rhot, ky, label='ky')
plt.show()
mean_rho, xstar = omega_gaussian_fit(uni_rhot, mtmFreq,
rhoref * np.sqrt(2.), Lref, path,
profile_name, plot)
if abs(mean_rho) + abs(xstar) < 0.0001:
quit()
if output_csv == True:
with open('profile_output.csv', 'w') as csvfile:
data = csv.writer(csvfile, delimiter=',')
data.writerow([
'x/a', 'nu_ei(kHz)', 'omega*n(kHz)', 'omega* plasma(kHz)',
'Doppler shift(kHz)', 'nu/omega*n', 'eta', 'shat', 'beta',
'ky rhoi(for n=1)'
])
for i in range(len(uni_rhot)):
data.writerow([
uni_rhot[i], coll_ei[i], omega_n[i], mtmFreq[i],
omegaDoppler[i], nu[i], eta[i], shat[i], beta[i], ky[i]
])
csvfile.close()
return uni_rhot, nu, eta, shat, beta, ky, q, mtmFreq, omegaDoppler, omega_n, omega_n_GENE, xstar, Lref, R_ref, rhoref
# uncomment if running on SageMaker
#sys.path[0] = '/home/ec2-user/SageMaker/asteroid/code'
#sys.path[0] = '/Users/lutz/Dropbox/URI/Projects/Asteroid/asteroid-git/code'
# Get the path of this run-tests.py file
file_path = os.path.dirname(os.path.abspath(__file__))
# Temporarly change the working directory to that path
os.chdir(file_path)
# Set the path to two levels above (the code directory)
sys.path[0] = "../../"
from interp import interp
programs = os.listdir("programs")
programs.sort()
for pname in programs:
f = open("programs/" + pname, "r")
p = f.read()
print("**********" + pname + "*************")
#print(p)
#print("********************output*********************")
try:
interp(p, exceptions=True)
except:
pass
f.close()
def main():
# fetch_many()
interp()
label_and_rename()
make_gif()
import factor_filter as ff
import interp as intp
from datetime import datetime
if __name__ == '__main__':
# ----user's input-------
t1 = datetime.strptime('2017/08/03', '%Y/%m/%d')
stock_list = [
'600725.SZ', '600306.SZ', '600000.SH', '600004.SH', '600006.SH',
'600007.SH', '600008.SH', '600009.SH', '600010.SH', '600011.SH',
'600012.SH', '600015.SH', '600016.SH'
]
factor_txt = 'MA5 = MA(trade_closeprice,5)\nMA10 = MA(trade_closeprice, 10)'
filter_txt = 'gx = CROSS(MA5, MA10)\nasc5 = SORT(MA5, asc, 5)'
# ----interp user's input----
d1, d2 = intp.interp(factor_txt, filter_txt)
# ----get daily stock list on day t1-----
for key in d2.keys():
# print key, d2[key].factor_list, d2[key].method
stocks = d2[key].filter(stock_list, t1)
print 'Stock list by applying filter', key, ':', stocks
def test_diffenv():
"""
Individual env
"""
unittest(lambda: None, lambda _, y: interp(parse(y)[0]), test_suite)
#!/usr/bin/env python3
# coding: utf-8
# # Regression Tests
import sys
import os
# Get the path of this run-tests.py file
file_path = os.path.dirname(os.path.abspath(__file__))
# Temporarly change the working directory to that path
os.chdir(file_path)
# Set the path to two levels above (the code directory)
sys.path[0] = "../../"
from interp import interp
programs = os.listdir("programs")
programs.sort()
for pname in programs:
f = open("programs/" + pname, "r")
p = f.read()
print("**********" + pname + "************")
print(p)
print("**********output***********")
interp(p)
f.close()
def read_profile_file(profile_type,profile_name,geomfile_name,suffix):
if profile_type=="ITERDB":
rhot0, te0, ti0, ne0, ni0, nz0, vrot0 = read_iterdb_file(profile_name)
psi0 = np.linspace(0.,1.,len(rhot0))
rhop0 = np.sqrt(np.array(psi0))
return rhot0, rhop0, te0, ti0, ne0, ni0, nz0, vrot0
elif profile_type=="pfile":
rhot0, rhop0, te0, ti0, ne0, ni0, nz0, vrot0 = p_to_iterdb_format(profile_name,geomfile_name)
return rhot0, rhop0, te0, ti0, ne0, ni0, nz0, vrot0
elif profile_type=="profile_e":
if suffix=="dat":
suffix=".dat"
else:
suffix="_"+suffix
rhot0, te0, ti0, ne0, ni0, nz0, vrot0 = read_iterdb_file(profile_name)
psi0 = np.linspace(0.,1.,len(rhot0))
rhop0 = np.sqrt(np.array(psi0))
x_a,x_rho_ref,T,n0,omt,omn = profile_e_info(suffix)
if 1==0:
plt.clf()
plt.plot(x_a,n0*1.0e19,label='profile')
plt.plot(rhot0,ne0,label='ITERDB')
#plt.plot(x_rho_ref,T,label='x_rho_ref')
plt.legend()
plt.show()
plt.clf()
plt.plot(x_a,T*1000.,label='profile')
plt.plot(rhot0,te0,label='ITERDB')
#plt.plot(x_rho_ref,T,label='x_rho_ref')
plt.legend()
plt.show()
#x_a,x_rho_ref,T,n0,omt,omn = profile_i_info(suffix)
rhot0_range_min=np.argmin(abs(rhot0-x_a[0]))
rhot0_range_max=np.argmin(abs(rhot0-x_a[-1]))
rhot=rhot0[rhot0_range_min:rhot0_range_max]
rhop=rhop0[rhot0_range_min:rhot0_range_max]
ti=ti0[rhot0_range_min:rhot0_range_max]
ni=ni0[rhot0_range_min:rhot0_range_max]
vrot=vrot0[rhot0_range_min:rhot0_range_max]
rhot0 = np.linspace(min(rhot),max(rhot),len(rhot)*3.)
rhop0=interp(rhot,rhop,rhot0)
te0 = interp(x_a,T*1000.,rhot0)
ti0=interp(rhot,ti,rhot0)
ni0=interp(rhot,ni,rhot0)
nz0 = interp(rhot,nz,rhot0)
ne0 = interp(x_a,n0*1.0e19,rhot0)
vrot0=interp(rhot,vrot,rhot0)
print("**************************")
print("**************************")
print("x_a min max: "+str(np.min(x_a))+", "+str(np.max(x_a)))
print("**************************")
print("**************************")
print("**************************")
return rhot0, rhop0, te0, ti0, ne0, ni0, vrot0
def pic(electron, ion, nx, dx, nt, dt, L, B0, save_res=[],
n_pairs=2, L_source=1.0, max_scale=2):
N = 0
for s in [electron, ion]: N += s.N
N_max = N*max_scale
q, qm, wc, xp, vx, vy = [np.zeros(N_max) for _ in range(6)]
el = np.ndarray((N_max,), dtype=np.bool)
do_move = np.ndarray((N_max,), dtype=np.bool)
do_move[:] = False
count = 0 # Trailing count
for s,t in [(electron,True), (ion,False)]:
q[count:count+s.N] = s.q
qm[count:count+s.N] = s.q/s.m
wc[count:count+s.N] = (s.q/s.m)*B0
xp[count:count+s.N] = s.x0
vx[count:count+s.N] = s.vx0
vy[count:count+s.N] = s.vy0
el[count:count+s.N] = t
do_move[count:count+s.N] = s.m>0
count += s.N
# store the results at each time step
save_xp = 'xp' in save_res
save_vx = 'vx' in save_res
save_vy = 'vy' in save_res
save_E = 'E' in save_res
save_phi = 'phi' in save_res
save_rho = 'rho' in save_res
save_sig = 'sig' in save_res
save_N = 'N' in save_res
save_el = 'el' in save_res
save_pw = 'phi_wall' in save_res
if save_xp or save_vx or save_vy:
save_N = save_el = True
if save_xp: xpa = np.zeros((nt+1, N_max))
if save_vx: vxa = np.zeros((nt+1, N_max))
if save_vy: vya = np.zeros((nt+1, N_max))
if save_E: Ea = np.zeros((nt+1, nx))
if save_phi: phia = np.zeros((nt+1, nx))
if save_pw: pwa = np.zeros(nt+1)
if save_rho: rhoa = np.zeros((nt+1, nx))
if save_sig: siga = np.zeros(nt+1)
if save_N: Na = np.zeros(nt+1)
if save_el: ela = np.zeros((nt+1,N_max), dtype=np.bool)
# Main solution loop
# Init half step back
sigma = 0.
rho = weight(xp[:N], q[:N], nx, L)/dx
phi = poisson_solve(rho, dx, sigma)
E0 = calc_E(phi, dx, sigma)
E = interp(E0, xp[:N], nx, L)
#rotate(vx[:N], vy[:N], -wc[:N], dt)
accel(vx[:N], vy[:N], E, -qm[:N], dt)
if save_xp: xpa[0] = xp
if save_vx: vxa[0] = vx
if save_vy: vya[0] = vy
if save_E: Ea[0] = E0
if save_phi: phia[0] = phi
if save_pw: pwa[0] = phi[-1]
if save_rho: rhoa[0] = rho
if save_sig: siga[0] = sigma
if save_N: Na[0] = N
if save_el: ela[0] = el
for i in range(1, nt+1):
# Update velocity
accel(vx[:N], vy[:N], E[:N], qm[:N], dt)
#rotate(vx[:N], vy[:N], wc, dt)
accel(vx[:N], vy[:N], E[:N], qm[:N], dt)
# Update position
move(xp[:N], vx[:N], vy[:N], dt, L)
# Reflect particles
reflect = xp[:N] < 0.
n_reflect = np.sum(reflect)
ne_reflect = np.sum(el[:N][reflect])
ni_reflect = n_reflect-ne_reflect
xp[:N][reflect] = 0.0
vx[:N][ el[:N] &reflect] = np.abs(electron.sample(ne_reflect))
vx[:N][(~el[:N])&reflect] = np.abs(ion.sample(ni_reflect))
vy[:N][reflect] = 0.0
# Update wall charge density
hit = xp[:N] >= L
n_hit = np.sum(hit)
sigma += np.sum(q[:N][hit])
# Remove particles that hit the wall
xp[:N-n_hit] = xp[:N][~hit].copy()
vx[:N-n_hit] = vx[:N][~hit].copy()
vy[:N-n_hit] = vy[:N][~hit].copy()
q[:N-n_hit] = q[:N][~hit].copy()
qm[:N-n_hit] = qm[:N][~hit].copy()
el[:N-n_hit] = el[:N][~hit].copy()
N -= n_hit
# Add particles from source term
vxe = electron.source(n_pairs)
vxi = ion.source(n_pairs)
xe_new = np.random.rand(n_pairs)*L_source
xi_new = np.random.rand(n_pairs)*L_source
xp[N:N+n_pairs] = xe_new
vx[N:N+n_pairs] = vxe
vy[N:N+n_pairs] = 0.0
q[N:N+n_pairs] = electron.q
qm[N:N+n_pairs] = electron.q/electron.m
el[N:N+n_pairs] = True
N += n_pairs
xp[N:N+n_pairs] = xi_new
vx[N:N+n_pairs] = vxi
vy[N:N+n_pairs] = 0.0
q[N:N+n_pairs] = ion.q
qm[N:N+n_pairs] = ion.q/ion.m
el[N:N+n_pairs] = False
N += n_pairs
# Calc fields
rho = weight(xp[:N], q[:N], nx, L)/dx
phi = poisson_solve(rho, dx, sigma)
E0 = calc_E(phi, dx, sigma)
E = interp(E0, xp[:N], nx, L)
if save_xp: xpa[i] = xp
if save_vx: vxa[i] = vx
if save_vy: vya[i] = vy
if save_E: Ea[i] = E0
if save_phi: phia[i] = phi
if save_pw: pwa[i] = phi[-1]
if save_rho: rhoa[i] = rho
if save_sig: siga[i] = sigma
if save_N: Na[i] = N
if save_el: ela[i] = el
results = {}
if save_xp: results['xp_all'] = xpa
if save_vx: results['vx_all'] = vxa
if save_vy: results['vy_all'] = vya
if save_E: results['E_all'] = Ea
if save_phi: results['phi_all'] = phia
if save_pw: results['phi_wall'] = pwa
if save_rho: results['rho_all'] = rhoa
if save_sig: results['sig_all'] = siga
if save_N: results['N_all'] = Na
if save_el: results['el_all'] = ela
# Save the last value for each variable
results['N'] = N
results['xp'] = xp[:N]
results['vx'] = vx[:N]
results['vy'] = vy[:N]
results['el'] = el[:N]
results['E'] = E0
results['phi'] = phi
results['rho'] = rho
results['sig'] = sigma
return results
