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"""
Make X and Z Cuts:
- Density
- Velocity
- Pressure
- Temperature (Sound Speed)
"""
import matplotlib as mpl
from pymses import RamsesOutput
from pymses.filters import CellsToPoints
from pymses.utils import constants as C
from pymses.analysis.visualization import Camera, ScalarOperator, SliceMap, \
FractionOperator
import matplotlib.pyplot as plt
import numpy as np
import sys
import argparse
"""
Main Routine. Define Cameras. Take Slices. Plot.
"""
def main():
# Parse Arguments
parser = argparse.ArgumentParser()
parser.add_argument("ilo", type=int, help='First Output', default=1)
parser.add_argument("ihi", type=int, help='Last Output', default=1)
parser.add_argument("-d", action="store_true", help='Show Density Cuts')
parser.add_argument("-v", action="store_true", help='Show Velocity Cuts')
parser.add_argument("-p", action="store_true", help='Show Pressure Cuts')
parser.add_argument("-T", action="store_true", help='Show Temperature Cuts')
parser.add_argument("--save", action="store_true", help='Save Figures')
parser.add_argument("--show", action="store_true", help='Show Figures')
parser.add_argument("--px", type=int, \
default=512, choices=[256, 512, 1024, 2048], \
help='Maximum Map Size')
args = parser.parse_args()
# Sanity Check
if not args.save and not args.show:
print "At least one of --save or --show is required."
sys.exit(0)
if args.ilo != args.ihi and args.show:
print "Can only show single output."
sys.exit(0)
# Build Output List
iouts = range(args.ilo, args.ihi + 1)
# Define Cameras
camZ = Camera(center=[0.5, 0.5, 0.5], line_of_sight_axis='z',
region_size=[1., 1.], up_vector='y', map_max_size=args.px, log_sensitive=True)
camX = Camera(center=[0.5, 0.5, 0.5], line_of_sight_axis='x',
region_size=[1., 1.], up_vector='y', map_max_size=args.px, log_sensitive=True)
# Functions to Get Data
func_rho = lambda dset: dset["rho"]
func_vel = lambda dset: np.sqrt(np.sum(dset["vel"]**2, axis=1))
# func_vel = lambda dset: dset["vel"][:,0]
func_pre = lambda dset: dset["P"]
# Operator to Get Data
op_rho = ScalarOperator(func_rho)
op_vel = ScalarOperator(func_vel)
op_pre = ScalarOperator(func_pre)
op_cs2 = FractionOperator(func_pre, func_rho)
# The Master Loop
for iout in iouts:
# Give Feedback
print ""
print "**********************************"
print "// Creating Cuts for Output %05d." % iout
print "**********************************"
print ""
# Link AMR Data
output = RamsesOutput(".", iout)
source = output.amr_source(["rho", "vel", "P"])
# Compute Slice Maps
rhoZ = SliceMap(source, camZ, op_rho, z=0.0)
rhoX = SliceMap(source, camX, op_rho, z=0.0)
velZ = SliceMap(source, camZ, op_vel, z=0.0)
velX = SliceMap(source, camX, op_vel, z=0.0)
preZ = SliceMap(source, camZ, op_pre, z=0.0)
preX = SliceMap(source, camX, op_pre, z=0.0)
cs2Z = SliceMap(source, camZ, op_cs2, z=0.0)
cs2X = SliceMap(source, camX, op_cs2, z=0.0)
# Convert Human Mind Parsable Units Pt 1 - (CGS)
rhoZ *= output.info["unit_density"].express(C.g_cc)
rhoX *= output.info["unit_density"].express(C.g_cc)
velZ *= output.info["unit_velocity"].express(C.cm / C.s)
velX *= output.info["unit_velocity"].express(C.cm / C.s)
preZ *= output.info["unit_pressure"].express(C.barye)
preX *= output.info["unit_pressure"].express(C.barye)
# Convert Human Mind Parsable Units Pt 2 - (km/s)
# Sound Speed
factor = output.info["unit_pressure"].express(C.barye) / \
output.info["unit_density"].express(C.g_cc)
cs2Z *= factor / 100.**2. / 1000.**2.
cs2X *= factor / 100.**2. / 1000.**2.
# Total Flow Speed
velZ *= 1.0 / 100. / 1000.
velX *= 1.0 / 100. / 1000.
# Compute Temperature
gamma = 1.4
TX = (cs2X * 100.**2. * 1000.**2.) * 2. * C.mH.express(C.kg) / \
gamma / C.kB.express(C.cm**2 * C.kg / C.s**2 / C.K)
TZ = (cs2Z * 100.**2. * 1000.**2.) * 2. * C.mH.express(C.kg) / \
gamma / C.kB.express(C.cm**2 * C.kg / C.s**2 / C.K)
# Log10?
rhoZ = np.log10(rhoZ)
rhoX = np.log10(rhoX)
preZ = np.log10(preZ)
preX = np.log10(preX)
# Mark Arrays vs. NaN
rhoZ = np.ma.masked_array(rhoZ, mask=np.isnan(rhoZ))
rhoX = np.ma.masked_array(rhoX, mask=np.isnan(rhoX))
velZ = np.ma.masked_array(velZ, mask=np.isnan(velZ))
velX = np.ma.masked_array(velX, mask=np.isnan(velX))
preZ = np.ma.masked_array(preZ, mask=np.isnan(preZ))
preX = np.ma.masked_array(preX, mask=np.isnan(preX))
# Set Masked Colormap
# cmap = mpl.cm.hot
cmap = mpl.cm.jet
cmap.set_bad([0.5, 0.5, 0.5])
# Colormaps:
# http://matplotlib.org/examples/pylab_examples/show_colormaps.html
# rho_cm = 'hot'
# vel_cm = 'hot'
# pre_cm = 'hot'
rho_cm = cmap
vel_cm = cmap
pre_cm = cmap
tmp_cm = cmap
# Compute Image Extent
ext = output.info["boxlen"] * np.array([-0.5, 0.5, -0.5, 0.5])
# Plot Density
if args.d:
f1 = plt.figure(1)
plt.imshow(rhoZ, cmap=rho_cm, extent=ext, interpolation='none')
plt.colorbar()
plt.grid()
plt.title('Log10 Density Cut [g/cc], t=%.2f' % output.info["time"])
plt.xlabel('X [AU]')
plt.ylabel('Y [AU]')
f2 = plt.figure(2)
plt.imshow(rhoX, cmap=rho_cm, extent=ext, interpolation='none')
plt.colorbar()
plt.grid()
plt.title('Log10 Density Cut [g/cc], t=%.2f' % output.info["time"])
plt.xlabel('Y [AU]')
plt.ylabel('Z [AU]')
# Plot Velocity
if args.v:
f3 = plt.figure(3)
plt.imshow(velZ, cmap=vel_cm, extent=ext)
plt.colorbar()
plt.grid()
plt.title('Total Flow Speed Cut [km/s], t=%.2f' % output.info["time"])
plt.xlabel('X [AU]')
plt.ylabel('Y [AU]')
f4 = plt.figure(4)
plt.imshow(velX, cmap=vel_cm, extent=ext)
plt.colorbar()
plt.grid()
plt.title('Total Flow Speed Cut [km/s], t=%.2f' % output.info["time"])
plt.xlabel('Y [AU]')
plt.ylabel('Z [AU]')
# Plot Pressure
if args.p:
f5 = plt.figure(5)
plt.imshow(preZ, cmap=pre_cm, extent=ext, interpolation='none')
plt.colorbar()
plt.grid()
plt.title('Log10 Pressure Cut [debye], t=%.2f' % output.info["time"])
plt.xlabel('X [AU]')
plt.ylabel('Y [AU]')
f6 = plt.figure(6)
plt.imshow(preX, cmap=pre_cm, extent=ext, interpolation='none')
plt.colorbar()
plt.grid()
plt.title('Log10 Pressure Cut [debye], t=%.2f' % output.info["time"])
plt.xlabel('Y [AU]')
plt.ylabel('Z [AU]')
# Plot Temperature
if args.T:
f7 = plt.figure(7)
plt.imshow(TZ, cmap=tmp_cm, extent=ext, interpolation='none')
plt.colorbar()
plt.grid()
plt.title('Temperature Cut [K], t=%.2f' % output.info["time"])
plt.xlabel('X [AU]')
plt.ylabel('Y [AU]')
f8 = plt.figure(8)
plt.imshow(TX, cmap=tmp_cm, extent=ext, interpolation='none')
plt.colorbar()
plt.grid()
plt.title('Temperature Cut [K], t=%.2f' % output.info["time"])
plt.xlabel('Y [AU]')
plt.ylabel('Z [AU]')
# Save Figures
if args.save:
if args.d:
f1.savefig('cut_dxy_%05d.png' % iout)
f2.savefig('cut_dzy_%05d.png' % iout)
if args.v:
f3.savefig('cut_vxy_%05d.png' % iout)
f4.savefig('cut_vzy_%05d.png' % iout)
if args.p:
f5.savefig('cut_pxy_%05d.png' % iout)
f6.savefig('cut_pzy_%05d.png' % iout)
if args.T:
f7.savefig('cut_Txy_%05d.png' % iout)
f8.savefig('cut_Tzy_%05d.png' % iout)
# Show Figures?
if args.show:
plt.show()
"""
Jump into Main().
"""
if __name__ == "__main__":
main()
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