"""gun.py: Class for gun experiment. Goals are: to develop, analyze
and understand a procedure for estimating an isentrope on the basis of
data and simulations.
"""
import numpy as np
from eos import Go
import fit
magic = Go(
x_i=0.4, # Initial position of projectile / cm'
x_f=4.0, # Final/muzzle position of projectile /cm'
m=100.0, # Mass of projectile / g
area=1e-4, # Projectile cross section in m^2
newton2dyne=1e5, # dynes per newton
var=1.0e-0, # Variance attributed to v measurements
n_t=500, # Number of ts for t2v spline
t_min=-5.0e-6, # Range of times for t2v spline
t_max=110.0e-6, # Range of times for t2v spline
cm2km=1.0e5, # For conversion from cm/sec to km/sec
n_t_sim=1000, # len(vt), simulated velocity time pairs
)
magic.add(D_frac=fit.magic.D_frac) # Fractional finite difference for dv/df
class Gun:
'''Represents an imagined experiment and actual simulations.
Section 2 of the document ../juq.tex describes the imagined
experiment.
"""fit.py: Coordinates optimization for fitting a model eos to experiments.
"""
import numpy as np
from eos import Go
magic = Go(
D_frac=2.0e-2, # Fractional finte difference for esimating dv/df
fit_dim=50, # Number of x points for EOS fit
max_iter=5, # Bound for iterations maximizing likelihood
converge=1.0e-5, # Fractional tolerance for cost
)
class Opt:
def __init__(
self, # Opt instance
eos, # eos.Spline_eos instance
experiment, # Dict of experimental simulation objects
data, # Dict of experimental data
):
'''
'''
self.eos = eos
self.original_eos = eos
self.experiment = experiment
self.data = data
assert set(experiment.keys()) == set(data.keys())
return
def step(self, constrain=True, debug=False):
"""stick.py: Class for rate stick experiment.
"""
import numpy as np
from eos import Go
# From description of Shot1 in Pemberton's document
pemberton = Go(
densities=np.array( # g/cc, page4
[1.835, 1.8358, 1.8353, 1.8356, 1.8356, 1.8345]),
positions=np.array( # mm, page 8
[25.9, 50.74, 75.98, 101.8, 125.91, 152.04, 177.61]),
x_dev=0.02, # mm, position measurement uncertainty (my guess)
t_dev=1.0e-9, # sec, time measurement uncertainty (my guess)
velocity=8.8132, # Km/sec, page 9
)
import fit
class Stick:
'''Represents an imagined experiment and simulation that creates data,
t, the "measured" times.
See the subsection "A Rate Stick" in the section "Experiments" of
notes.pdf.
Methods:
fit_v() Return detonation velocity
def main(argv=None):
import argparse
import os
import os.path
if argv is None: # Usual case
argv = sys.argv[1:]
parser = argparse.ArgumentParser(description='Make plots for notes.pdf')
parser.add_argument('--show', action='store_true')
parser.add_argument('--fig_dir', type=str, default='figs', help=
'Directory of figures')
# Plot requests
h_format = lambda s:'File for figure of {0}'.format(s)
parser.add_argument('--tx_stick', type=str, help=h_format('t(x)'))
parser.add_argument('--C_gun', type=str, help=h_format('d c_v/ d c_p'))
parser.add_argument('--vt_gun', type=str, help=h_format('v(t)'))
parser.add_argument('--BC_gun', type=str, help=h_format('d v(t)/ d c_p'))
parser.add_argument('--opt_result', type=str, help=h_format(
'one optimization step'))
parser.add_argument('--big_d', type=str, help=h_format(
'finite difference derivative with 9 subplots'))
parser.add_argument('--fve_gun', type=str, help=h_format(
'force, velocity and sequence of errors'))
args = parser.parse_args(argv)
params = {'axes.labelsize': 18, # Plotting parameters for latex
'font.size': 15,
'legend.fontsize': 15,
'text.usetex': True,
'font.family':'serif',
'font.serif':'Computer Modern Roman',
'xtick.labelsize': 15,
'ytick.labelsize': 15}
mpl.rcParams.update(params)
if args.show:
mpl.rcParams['text.usetex'] = False
else:
mpl.use('PDF')
import matplotlib.pyplot as plt # must be after mpl.use
if not os.path.exists(args.fig_dir):
os.mkdir(args.fig_dir)
# Do quick calculations to create exp and nom
import eos
import gun
import stick
t=np.linspace(0, gun.magic.t_max, gun.magic.n_t_sim)
exp = Go(eos=eos.Experiment())
nom = Go(eos=eos.Spline_eos(eos.Nominal(), precondition=True))
for go in (exp, nom):
go.add(t=t, gun=gun.Gun(go.eos), stick=stick.Stick(go.eos))
go.add(x=np.linspace(go.gun.x_i, go.gun.x_f, 500))
go.add(t2v=go.gun.fit_t2v())
go.add(v=go.t2v(t))
go.add(vt=(go.v, go.t))
go.add(stick_data=stick.data(go.eos))
C=nom.gun.fit_C()
B,ep = nom.gun.fit_B_ep(exp.vt)
nom.add(C=C, B=B, ep=ep, BC=np.dot(B,C))
# Make requested plots
do_show = args.show
for key in args.__dict__:
if key not in plot_dict:
continue
if args.__dict__[key] == None:
continue
print('work on %s'%(key,))
fig = plot_dict[key](exp, nom, plt)
file_name = getattr(args, key)
if file_name == 'show':
do_show = True
else:
fig.savefig(os.path.join(args.fig_dir, file_name), format='pdf')
if do_show:
plt.show()
return 0