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update the subchandra plots to those used in the paper #2543

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Aug 27, 2023
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update the subchandra plots to those used in the paper #2543

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168 changes: 168 additions & 0 deletions Exec/science/subchandra/analysis/subch_res_compare.py
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Original file line number Diff line number Diff line change
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#!/usr/bin/env python3

import argparse
import os
import sys
from functools import reduce

import matplotlib
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.axes_grid1 import ImageGrid

import yt
from yt.fields.derived_field import ValidateSpatial
from yt.frontends.boxlib.api import CastroDataset
from yt.funcs import just_one
# assume that our data is in CGS
from yt.units import amu, cm

matplotlib.use('agg')


clip_val = -35
max_val = -19

# how much to coarsen for the contouring
blocking_factor = 8

def _lap_rho(field, data):
dr = just_one(data["index", "dr"]).d
r = data["index", "r"].d
rl = r - 0.5 * dr
rr = r + 0.5 * dr

dz = just_one(data["index", "dz"]).d
dens = data["gas", "density"].d

_lap = np.zeros_like(dens)

lapl_field = data.ds.arr(np.zeros(dens.shape, dtype=np.float64), None)

# r-component
_lap[1:-1, :] = 1 / (r[1:-1, :] * dr**2) * (
- 2.0 * r[1:-1, :] * dens[1:-1:, :] +
rl[1:-1, :] * dens[:-2, :] + rr[1:-1, :] * dens[2:, :])

_lap[:, 1:-1] += 1 / dz**2 * (dens[:, 2:] + dens[:, :-2] - 2.0 * dens[:, 1:-1])
lapl_field[1:-1, 1:-1] = np.log(np.abs(_lap[1:-1, 1:-1] / dens[1:-1, 1:-1]))
lapl_field[lapl_field < clip_val] = clip_val
return lapl_field

def doit(rows, field):

nrows = len(rows)
ncols = len(rows[0][0])


fig = plt.figure()

grid = ImageGrid(fig, 111, nrows_ncols=(nrows, ncols),
axes_pad=0.25, cbar_pad=0.05, label_mode="L", cbar_mode="single")


i = 0

for row in rows:

plotfiles, label = row

for irow, pf in enumerate(plotfiles):

ds = CastroDataset(pf)

if field == "lap_rho":
ds.force_periodicity()
ds.add_field(name=("gas", "lap_rho"), sampling_type="local",
function=_lap_rho, units="",
validators=[ValidateSpatial(1)])

domain_frac = 0.2

xmin = ds.domain_left_edge[0]
xmax = domain_frac * ds.domain_right_edge[0]
xctr = 0.5 * (xmin + xmax)
L_x = xmax - xmin

ymin = ds.domain_left_edge[1]
ymax = ds.domain_right_edge[1]
yctr = 0.5 * (ymin + ymax)
L_y = ymax - ymin
ymin = yctr - 0.5 * domain_frac * L_y
ymax = yctr + 0.5 * domain_frac * L_y
L_y = ymax - ymin

sp = yt.SlicePlot(ds, "theta", field, center=[xctr, yctr, 0.0*cm], width=[L_x, L_y, 0.0*cm], fontsize="14")
sp.set_buff_size((2400,2400))

if field == "Temp":
text_color = "white"
else:
text_color = "black"

sp.annotate_text((0.05, 0.05), f"time = {float(ds.current_time):8.3f} s", coord_system="axis", text_args={"color": text_color, "fontsize": "12"})
if (irow == 0):
sp.annotate_text((0.05, 0.925), f"{label}", coord_system="axis", text_args={"color": text_color, "fontsize": "14"})

if (irow == 0):
sp.annotate_grids(max_level=10, cmap="tab10")

if field == "Temp":
sp.set_zlim(field, 5.e7, 4e9)
sp.set_cmap(field, "magma")
elif field == "enuc":
sp.set_log(field, True, linthresh=1.e15)
sp.set_zlim(field, -1.e22, 1.e22)
sp.set_cmap(field, "bwr")
elif field == "abar":
sp.set_zlim(field, 4, 28)
sp.set_log(field, False)
sp.set_cmap(field, "plasma_r")
elif field == "lap_rho":
sp.set_zlim(field, clip_val, max_val)
sp.set_log(field, False)
sp.set_cmap(field, "bone_r")

sp.set_axes_unit("km")

plot = sp.plots[field]
plot.figure = fig
plot.axes = grid[i].axes
plot.cax = grid.cbar_axes[i]
if irow < len(plotfiles)-1:
grid[i].axes.xaxis.offsetText.set_visible(False)

sp._setup_plots()

i += 1

fig.set_size_inches(10, 14)
plt.tight_layout()
plt.savefig(f"subch_{field}_res_compare.pdf")

if __name__ == "__main__":


subch_40km = [("subch_sdc_40km/subch_plt02123",
"subch_sdc_40km/subch_plt04184",
"subch_sdc_40km/subch_plt08509",
"subch_sdc_40km/subch_plt17272"), "40 km"]

subch_20km = [("subch_sdc/subch_plt02123",
"subch_sdc/subch_plt04196",
"subch_sdc/subch_plt08614",
"subch_sdc/subch_plt17412"), "20 km"]

subch_10km = [("subch_sdc_10km_3lev/subch_plt02123",
"subch_sdc_10km_3lev/subch_plt04197",
"subch_sdc_10km_3lev/subch_plt08582",
"subch_sdc_10km_3lev/subch_plt17526"), "10 km"]

subch_5km = [("subch_sdc_5km_4lev/subch_plt02123",
"subch_sdc_5km_4lev/subch_plt04197",
"subch_sdc_5km_4lev/subch_plt08581",
"subch_sdc_5km_4lev/subch_plt17472"), "5 km"]

field = "Temp"

doit([subch_40km, subch_20km, subch_10km, subch_5km], field)
45 changes: 27 additions & 18 deletions Exec/science/subchandra/analysis/subch_sequence.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,26 +1,27 @@
#!/usr/bin/env python3

import matplotlib
matplotlib.use('agg')

import argparse
import os
import sys
import yt
import matplotlib.pyplot as plt
import numpy as np
from functools import reduce

import matplotlib
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.axes_grid1 import ImageGrid

# assume that our data is in CGS
from yt.units import cm, amu
import yt
from yt.fields.derived_field import ValidateSpatial
from yt.frontends.boxlib.api import CastroDataset
from yt.funcs import just_one
from yt.fields.derived_field import ValidateSpatial
# assume that our data is in CGS
from yt.units import amu, cm

matplotlib.use('agg')


#times = [0.0, 0.05, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35]
times = [0.0, 0.1, 0.2, 0.4, 0.6, 0.75]
times = [0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.1]
#times = [0.0, 0.15, 0.3, 0.45]

clip_val = -35
Expand Down Expand Up @@ -75,15 +76,18 @@ def doit(field, add_contours, pfiles):

fig = plt.figure()

if len(pfiles) > 4:
if len(pfiles) > 8:
nrows = 3
ncols = (len(pfiles) + 1)//3
elif len(pfiles) > 4:
nrows = 2
ncols = (len(pfiles) + 1)//2
else:
nrows = 1
ncols = len(pfiles)

grid = ImageGrid(fig, 111, nrows_ncols=(nrows, ncols),
axes_pad=0.75, cbar_pad=0.05, label_mode="L", cbar_mode="single")
axes_pad=0.3, cbar_pad=0.05, label_mode="L", cbar_mode="single")


for i in range(nrows * ncols):
Expand All @@ -102,7 +106,7 @@ def doit(field, add_contours, pfiles):
function=_lap_rho, units="",
validators=[ValidateSpatial(1)])

domain_frac = 0.15
domain_frac = 0.2

xmin = ds.domain_left_edge[0]
xmax = domain_frac * ds.domain_right_edge[0]
Expand All @@ -117,13 +121,18 @@ def doit(field, add_contours, pfiles):
ymax = yctr + 0.5 * domain_frac * L_y
L_y = ymax - ymin

sp = yt.SlicePlot(ds, "theta", field, center=[xctr, yctr, 0.0*cm], width=[L_x, L_y, 0.0*cm], fontsize="12")
sp = yt.SlicePlot(ds, "theta", field, center=[xctr, yctr, 0.0*cm], width=[L_x, L_y, 0.0*cm], fontsize="14")
sp.set_buff_size((2400,2400))
sp.annotate_text((0.05, 0.05), f"time = {float(ds.current_time):8.3f} s", coord_system="axis", text_args={"color": "black"})
if field == "Temp":
text_color = "white"
else:
text_color = "black"

sp.annotate_text((0.05, 0.05), f"time = {float(ds.current_time):8.3f} s", coord_system="axis", text_args={"color": text_color})

if field == "Temp":
sp.set_zlim(field, 5.e7, 4e9)
sp.set_cmap(field, "magma_r")
sp.set_cmap(field, "magma")
elif field == "enuc":
sp.set_log(field, True, linthresh=1.e15)
sp.set_zlim(field, -1.e22, 1.e22)
Expand Down Expand Up @@ -151,9 +160,9 @@ def doit(field, add_contours, pfiles):

sp._setup_plots()

fig.set_size_inches(19.2, 10.8)
fig.set_size_inches(11, 14)
plt.tight_layout()
plt.savefig(f"subch_{field}_sequence.png")
plt.savefig(f"subch_{field}_sequence.pdf")

if __name__ == "__main__":

Expand Down
52 changes: 52 additions & 0 deletions Exec/science/subchandra/analysis/subch_zoom.py
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Original file line number Diff line number Diff line change
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#!/usr/bin/env python3

import argparse
import os
import sys
from functools import reduce

import matplotlib
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.axes_grid1 import ImageGrid

import yt
from yt.fields.derived_field import ValidateSpatial
from yt.frontends.boxlib.api import CastroDataset
from yt.funcs import just_one
# assume that our data is in CGS
from yt.units import amu, cm

matplotlib.use('agg')


plotfile = "subch_plt00000"

fig = plt.figure()

ds = CastroDataset(plotfile)

xmin = 0 * cm
xmax = 1.e8 * cm

xctr = 0.5 * (xmin + xmax)
L_x = xmax - xmin

ymin = 5.42e9 * cm
ymax = 5.58e9 * cm
yctr = 0.5 * (ymin + ymax)
L_y = ymax - ymin

field = "Temp"

sp = yt.SlicePlot(ds, "theta", field, center=[xctr, yctr, 0.0*cm], width=[L_x, L_y, 0.0*cm], fontsize="14")
sp.set_buff_size((2400,2400))

sp.set_zlim(field, 5.e7, 4e9)
sp.set_cmap(field, "magma")

sp.annotate_contour(("gas", "density"), take_log=True, ncont=3, clim=(1.e4, 1.e6), plot_args={"colors": "white", "linestyles": ":"})

sp.set_axes_unit("km")

sp.save(f"subch_{field}_zoom.pdf")