def main():
parser = argparse.ArgumentParser(description='Table generator')
parser.add_argument('num', help=('Instance of the script to run; '
'determines input a_b/v_s values. '
'Value between 0-3'))
args = parser.parse_args()
idx = int(args.num)
# vs/ab values to use in this instance
vs_nodamp = VS_VALS_ALL[idx]
abvals = AB_VALS_ALL[idx]
# mu / eta2 / B0 grid settings
mu_vals_nodamp = [0, 1./3, 1./2, 1, 1.5, 2] # Following Sean
n_B0_nodamp = 20
mu_vals_damp = [1.]
n_B0_damp = 50
eta2_vals = [np.logspace(-2, -1, 25, base=10, endpoint=False),
np.logspace(-1, 1, 100, base=10, endpoint=False),
np.logspace(1, 2, 26, base=10, endpoint=True)]
eta2_vals = np.sort(np.concatenate(eta2_vals))
# Tycho settings (yes this is rather silly)
snr_nodamp = snrcat.make_tycho()
snr_nodamp.vs = vs_nodamp
snr_damp = snrcat.make_tycho()
kevs = TYCHO_KEVS
data_min = TYCHO_DATA_MIN / 1.1
data_max = TYCHO_DATA_MAX * 1.1
# First make non-damped table
fname_nodamp = '{}_gen_{}_grid_{}-{}-{}_vs-{:0.2e}.pkl'.format(snr_nodamp.name,
datetime.now().strftime('%Y-%m-%d'), len(mu_vals_nodamp),
len(eta2_vals), n_B0_nodamp, vs_nodamp)
models.maketab(snr_nodamp, kevs, data_min, data_max,
mu_vals_nodamp, eta2_vals, n_B0_nodamp,
fname = fname_nodamp,
f_B0_init = 1.1, f_B0_step = 0.10,
idamp = False)
# Then slew of damped tables
for ab in abvals:
fname_damp = '{}_gen_{}_grid_{}-{}-{}_ab-{:0.2e}.pkl'.format(snr_damp.name,
datetime.now().strftime('%Y-%m-%d'),
len(mu_vals_damp), len(eta2_vals), n_B0_damp, ab)
models.maketab(snr_damp, kevs, data_min, data_max,
mu_vals_damp, eta2_vals, n_B0_damp,
fname = fname_damp,
f_B0_init = 1.1, f_B0_step = 0.10,
idamp = True, damp_ab = ab, damp_bmin = 5e-6)
def main():
# Read shock velocity
parser = argparse.ArgumentParser(description='Table generator')
parser.add_argument('vs', help='Shock velocity (cm/s)')
args = parser.parse_args()
vs = float(args.vs)
# Set SNR parameters
snr = snrcat.make_tycho()
snr.vs = vs
# Set data
kevs = TYCHO_KEVS
data_min = TYCHO_DATA_MIN / 1.25
data_max = TYCHO_DATA_MAX * 1.25
# Set default grid
eta2_vals_orig = np.logspace(-2, 2, 50, base=10)
eta2_vals_orig = np.sort(np.append(eta2_vals_orig, np.linspace(0, 10, 50)))
n_B0 = 20 # In practice, you'll usually get ~1.5 to 2x as many points
# as code tries to achieve good spacing
# Set rminarc for gridding (determined manually) (NEW LARGER VALUES)
rminarc = [18.5, 15., 10.77, 10.77, 10.77]
# approx ~ TYCHO_DATA_MAX * 1.25 * f_rminarc, f_rminarc = 1.25
# ------------------------------------
mu_vals = [1.5]
eta2_vals = eta2_vals_orig[eta2_vals_orig > 15]
fname = '{}_gen_2014-07-30_grid_6-100-20_vs-{:0.2e}_part2_mu-1.50.pkl'.format(
snr.name, vs)
models.maketab(snr, kevs, data_min, data_max, mu_vals, eta2_vals, n_B0,
rminarc = rminarc,
fname = fname,
f_rminarc = float('NaN'), # Irrelevant, just being explicit
f_B0_init = 1.1,
f_B0_step = 0.10)
# ------------------------------------
mu_vals = [2]
eta2_vals = eta2_vals_orig
fname = '{}_gen_2014-07-30_grid_6-100-20_vs-{:0.2e}_part2_mu-2.00.pkl'.format(
snr.name, vs)
models.maketab(snr, kevs, data_min, data_max, mu_vals, eta2_vals, n_B0,
rminarc = rminarc,
fname = fname,
f_rminarc = float('NaN'), # Irrelevant, just being explicit
f_B0_init = 1.1,
f_B0_step = 0.10)
def main():
# Read damping length
parser = argparse.ArgumentParser(description='Table generator')
parser.add_argument('abvals',
help='Damping lengths (%% of shock radius)',
nargs='*')
args = parser.parse_args()
abvals = map(float, args.abvals)
# Set SNR parameters
snr = snrcat.make_tycho()
# Set data
kevs = TYCHO_KEVS
data_min = TYCHO_DATA_MIN / 1.1
data_max = TYCHO_DATA_MAX * 1.1
# Set grid (values should be, preferably, sorted)
mu_vals = [1.]
eta2_vals = [
np.logspace(-2, -1, 25, base=10, endpoint=False),
np.logspace(-1, 1, 100, base=10, endpoint=False),
np.logspace(1, 2, 26, base=10, endpoint=True)
]
eta2_vals = np.sort(np.concatenate(eta2_vals))
n_B0 = 50 # In practice, you'll usually get ~1.5 to 2x as many points
# as code tries to achieve good spacing (esp. for small n_B0)
for ab in abvals:
# Set output filename base (end with .pkl)
# Using custom name with damping length ab appended, for Tycho
fname = '{}_gen_{}_grid_{}-{}-{}_ab-{:0.2e}_Bmin-2e-6.pkl'.format(
snr.name,
datetime.now().strftime('%Y-%m-%d'), len(mu_vals), len(eta2_vals),
n_B0, ab)
# Set a few other twiddle-ables here
models.maketab(snr,
kevs,
data_min,
data_max,
mu_vals,
eta2_vals,
n_B0,
fname=fname,
f_B0_init=1.1,
f_B0_step=0.10,
idamp=True,
damp_ab=ab,
damp_bmin=2e-6)
def main():
# Read shock velocity
parser = argparse.ArgumentParser(description='Table generator')
parser.add_argument('vs', help='Shock velocity (cm/s)')
args = parser.parse_args()
vs = float(args.vs)
# Set SNR parameters
snr = snrcat.make_tycho()
snr.vs = vs
# Set data
kevs = TYCHO_KEVS
data_min = TYCHO_DATA_MIN / 1.25
data_max = TYCHO_DATA_MAX * 1.25
# Set grid (values should be, preferably, sorted)
mu_vals = [0, 1. / 3, 1. / 2, 1, 1.5, 2] # Following Sean
eta2_vals = np.logspace(-2, 3, 60, base=10)
eta2_vals = np.sort(np.append(eta2_vals, np.linspace(0, 10, 50)))
n_B0 = 20 # In practice, you'll usually get ~1.5 to 2x as many points
# as code tries to achieve good spacing
# Set rminarc for gridding (determined manually)
rminarc = np.array([18.5, 15., 10.77, 10.77,
10.77]) # from 20140730 tycho pt. 2
# approx ~ TYCHO_DATA_MAX * 1.25 * f_rminarc, f_rminarc = 1.25
# Set output filename base (end with .pkl)
# Using custom name with shock velocity appended, for Tycho
fname = '{}_gen_{}_grid_{}-{}-{}_vs-{:0.2e}.pkl'.format(
snr.name,
datetime.now().strftime('%Y-%m-%d'), len(mu_vals), len(eta2_vals),
n_B0, vs)
# Set a few other twiddle-ables here
models.maketab(snr,
kevs,
data_min,
data_max,
mu_vals,
eta2_vals,
n_B0,
fname=fname,
f_B0_init=1.1,
f_B0_step=0.10,
rminarc=rminarc)
def main():
# Read shock velocity
parser = argparse.ArgumentParser(description='Table generator')
parser.add_argument('vs', help='Shock velocity (cm/s)')
args = parser.parse_args()
vs = float(args.vs)
# Set SNR parameters
snr = snrcat.make_tycho()
snr.vs = vs
# Set data
kevs = TYCHO_KEVS
data_min = TYCHO_DATA_MIN / 1.25
data_max = TYCHO_DATA_MAX * 1.25
# Set grid (values should be, preferably, sorted)
mu_vals = [0, 1./3, 1./2, 1, 1.5, 2] # Following Sean
eta2_vals = np.logspace(-2, 2, 50, base=10)
eta2_vals = np.sort(np.append(eta2_vals, np.linspace(0, 10, 50)))
n_B0 = 20 # In practice, you'll usually get ~1.5 to 2x as many points
# as code tries to achieve good spacing
# Set rminarc for gridding (determined manually)
rminarc = [18.5, 15., 10.77, 11.73, 9.1]
# approx ~ TYCHO_DATA_MAX * 1.25 * f_rminarc, f_rminarc = 1.25
# Set output filename base (end with .pkl)
fname = '{}_gen_{}_grid_{}-{}-{}_vs-{:0.2e}.pkl'.format(snr.name,
datetime.now().strftime('%Y-%m-%d'), len(mu_vals), len(eta2_vals),
n_B0, vs)
# Set a few other twiddle-ables here
# See the docstring / code of models_all.maketab(...)
models.maketab(snr, kevs, data_min, data_max, mu_vals, eta2_vals, n_B0,
rminarc = rminarc,
fname = fname,
f_rminarc = float('NaN'), # Irrelevant, just being explicit
f_B0_init = 1.1,
f_B0_step = 0.10)
def main():
# Read damping length
parser = argparse.ArgumentParser(description='Table generator')
parser.add_argument('abvals', help='Damping lengths (%% of shock radius)',
nargs='*')
args = parser.parse_args()
abvals = map(float, args.abvals)
# Set SNR parameters
snr = snrcat.make_tycho()
# Set data
kevs = TYCHO_KEVS
data_min = TYCHO_DATA_MIN / 1.1
data_max = TYCHO_DATA_MAX * 1.1
# Set grid (values should be, preferably, sorted)
mu_vals = [1.]
eta2_vals = [np.logspace(-2, -1, 25, base=10, endpoint=False),
np.logspace(-1, 1, 100, base=10, endpoint=False),
np.logspace(1, 2, 26, base=10, endpoint=True)]
eta2_vals = np.sort(np.concatenate(eta2_vals))
n_B0 = 30 # In practice, you'll usually get ~1.5 to 2x as many points
# as code tries to achieve good spacing (esp. for small n_B0)
for ab in abvals:
# Set output filename base (end with .pkl)
# Using custom name with damping length ab appended, for Tycho
fname = '{}_gen_{}_grid_{}-{}-{}_ab-{:0.2e}.pkl'.format(snr.name,
datetime.now().strftime('%Y-%m-%d'),
len(mu_vals), len(eta2_vals), n_B0, ab)
# Set a few other twiddle-ables here
models.maketab(snr, kevs, data_min, data_max,
mu_vals, eta2_vals, n_B0,
fname = fname,
f_B0_init = 1.1, f_B0_step = 0.10,
idamp = True, damp_ab = ab)
def main():
# Read shock velocity
parser = argparse.ArgumentParser(description='Table generator')
parser.add_argument('vs', help='Shock velocity (cm/s)')
args = parser.parse_args()
vs = float(args.vs)
# Set SNR parameters
snr = snrcat.make_tycho()
snr.vs = vs
# Set data
kevs = TYCHO_KEVS
data_min = TYCHO_DATA_MIN / 1.25
data_max = TYCHO_DATA_MAX * 1.25
# Set default grid
eta2_vals_orig = np.logspace(-2, 2, 50, base=10)
eta2_vals_orig = np.sort(np.append(eta2_vals_orig, np.linspace(0, 10, 50)))
n_B0 = 20 # In practice, you'll usually get ~1.5 to 2x as many points
# as code tries to achieve good spacing
# Set rminarc for gridding (determined manually) (NEW LARGER VALUES)
rminarc = [18.5, 15., 10.77, 10.77, 10.77]
# approx ~ TYCHO_DATA_MAX * 1.25 * f_rminarc, f_rminarc = 1.25
# ------------------------------------
mu_vals = [1.5]
eta2_vals = eta2_vals_orig[eta2_vals_orig > 15]
fname = '{}_gen_2014-07-30_grid_6-100-20_vs-{:0.2e}_part2_mu-1.50.pkl'.format(
snr.name, vs)
models.maketab(
snr,
kevs,
data_min,
data_max,
mu_vals,
eta2_vals,
n_B0,
rminarc=rminarc,
fname=fname,
f_rminarc=float('NaN'), # Irrelevant, just being explicit
f_B0_init=1.1,
f_B0_step=0.10)
# ------------------------------------
mu_vals = [2]
eta2_vals = eta2_vals_orig
fname = '{}_gen_2014-07-30_grid_6-100-20_vs-{:0.2e}_part2_mu-2.00.pkl'.format(
snr.name, vs)
models.maketab(
snr,
kevs,
data_min,
data_max,
mu_vals,
eta2_vals,
n_B0,
rminarc=rminarc,
fname=fname,
f_rminarc=float('NaN'), # Irrelevant, just being explicit
f_B0_init=1.1,
f_B0_step=0.10)
def main():
parser = argparse.ArgumentParser(description='Table generator')
parser.add_argument('num',
help=('Instance of the script to run; '
'determines input a_b/v_s values. '
'Value between 0-3'))
args = parser.parse_args()
idx = int(args.num)
# vs/ab values to use in this instance
vs_nodamp = VS_VALS_ALL[idx]
abvals = AB_VALS_ALL[idx]
# mu / eta2 / B0 grid settings
mu_vals_nodamp = [0, 1. / 3, 1. / 2, 1, 1.5, 2] # Following Sean
n_B0_nodamp = 20
mu_vals_damp = [1.]
n_B0_damp = 50
eta2_vals = [
np.logspace(-2, -1, 25, base=10, endpoint=False),
np.logspace(-1, 1, 100, base=10, endpoint=False),
np.logspace(1, 2, 26, base=10, endpoint=True)
]
eta2_vals = np.sort(np.concatenate(eta2_vals))
# Tycho settings (yes this is rather silly)
snr_nodamp = snrcat.make_tycho()
snr_nodamp.vs = vs_nodamp
snr_damp = snrcat.make_tycho()
kevs = TYCHO_KEVS
data_min = TYCHO_DATA_MIN / 1.1
data_max = TYCHO_DATA_MAX * 1.1
# First make non-damped table
fname_nodamp = '{}_gen_{}_grid_{}-{}-{}_vs-{:0.2e}.pkl'.format(
snr_nodamp.name,
datetime.now().strftime('%Y-%m-%d'), len(mu_vals_nodamp),
len(eta2_vals), n_B0_nodamp, vs_nodamp)
models.maketab(snr_nodamp,
kevs,
data_min,
data_max,
mu_vals_nodamp,
eta2_vals,
n_B0_nodamp,
fname=fname_nodamp,
f_B0_init=1.1,
f_B0_step=0.10,
idamp=False)
# Then slew of damped tables
for ab in abvals:
fname_damp = '{}_gen_{}_grid_{}-{}-{}_ab-{:0.2e}.pkl'.format(
snr_damp.name,
datetime.now().strftime('%Y-%m-%d'), len(mu_vals_damp),
len(eta2_vals), n_B0_damp, ab)
models.maketab(snr_damp,
kevs,
data_min,
data_max,
mu_vals_damp,
eta2_vals,
n_B0_damp,
fname=fname_damp,
f_B0_init=1.1,
f_B0_step=0.10,
idamp=True,
damp_ab=ab,
damp_bmin=5e-6)