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fulltest.py
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import sys
import os
import glob
import shutil
from abc import ABC, abstractmethod
from datetime import datetime
import argparse
def dir_path(string):
if os.path.isdir(string):
return string
else:
raise NotADirectoryError(string)
def clustername(string):
if string in ["perseus", "stellar", "ginsburg"]:
return string
else:
raise ValueError(string)
parser = argparse.ArgumentParser()
parser.add_argument("--path", required=True, type=dir_path)
parser.add_argument("--cluster", type=clustername)
parser.add_argument("--dry", action="store_true", default=False, help="dry run.")
parser.add_argument(
"-c", action="store_true", default=False, help="only test compilation."
)
parser.add_argument(
"-r", action="store_true", default=False, help="only run simulations."
)
parser.add_argument(
"-v", action="store_true", default=False, help="verbose mode (full output)."
)
parser.add_argument(
"-d", "--diag", type=int, default=None, help="diagnostic mode [choose test #]."
)
parser.add_argument(
"-t",
"--test",
type=str,
default=",".join(map(str, list(range(15)))),
help="tests to run.",
)
options = parser.parse_args()
tests = [int(t) for t in options.test.split(",")]
suffix = "" if options.v else " >/dev/null 2>&1"
def callCommand(command):
if options.dry:
print(f"$ {command}")
else:
os.system(command)
# modules for compilation
if options.cluster == "perseus":
modules = [
"intel-mkl/2017.4/5/64",
"intel/17.0/64/17.0.5.239",
"intel-mpi/intel/2017.5/64",
"hdf5/intel-17.0/intel-mpi/1.10.0",
]
elif options.cluster == "stellar":
modules = [
"intel/2021.1.2",
"intel-mpi/intel/2021.1.1",
"hdf5/intel-2021.1/intel-mpi/1.10.6",
]
elif options.cluster == "ginsburg":
modules = ["intel-parallel-studio/2020", "hdf5p/1.10.7", "openmpi/gcc/64/4.1.5a1"]
# global variables
outdir = options.path
codedir = os.getcwd()
testdir = "test_0"
testdir_full = outdir + "/" + testdir
# simulation environment (tristan & slurm)
class Simulation(ABC):
path = None
exe = None
exe_full = None
submit = None
submit_full = None
input = None
input_full = None
def __init__(self, flags, walltime="00:30:00", nproc=28, params={}):
self.walltime = walltime
self.flags = flags
self.params = params
self.nproc = nproc
@abstractmethod
def diag(self, ax):
pass
class TwoStream(Simulation):
jobid = "twostream"
userfile = "user_twostream"
dimension = 1
def diag(self):
import matplotlib.pyplot as plt
fig, ax = plt.subplots(figsize=(8, 6))
hist = isolde.parseHistory(self.path + "/output/history")
omegap0 = self.params["algorithm"]["c"] / self.params["plasma"]["c_omp"]
rate = 0.5 * (0.5) ** 0.5 / (self.params["problem"]["shift_gamma"]) ** (1.5)
time = hist["time"] * omegap0
E2 = hist["Ex^2"] / hist["Etot"][0]
ax.plot(time, E2, label="sim")
xs = np.linspace(10, 40, 10)
ys = np.exp(2 * rate * xs)
ys = (E2[time > 10][0]) * (ys / ys[0])
ax.plot(xs, ys, label=r"$\omega/\omega_{b}^p=\gamma_b^{-3/2}$")
ax.set_ylim(1e-4, 1e-1)
ax.set_xlim(0, 200)
ax.set_yscale("log")
ax.set_xlabel(r"$t\omega_{\rm p0}$")
ax.set_ylabel(r"$U_E / E_{\rm tot}$")
ax.axvline(ax.get_xlim()[0], color="black")
ax.axhline(ax.get_ylim()[0], color="black")
ax.text(
110,
0.6e-3,
r"""
energy conservation
by $t\omega_{{\rm p 0}}={{{}}}: \Delta E/E={{{}}}\%$
""".format(
int(hist["time"][-1] * omegap0),
int(hist["% dEtot"][-1] * 10000) / 10000,
),
)
ax.set_title(self.jobid)
plt.legend()
plt.tight_layout()
plt.show()
class PlasmaOsc(Simulation):
jobid = "plasmaosc"
userfile = "user_langmuir"
dimension = 1
def diag(self):
import matplotlib.pyplot as plt
fig, ax = plt.subplots(figsize=(8, 6))
exs = []
steps = np.arange(50)
for step in steps:
flds = isolde.getFields(self.path + "/output/flds/flds.tot.%05d" % step)
exs.append(flds["ex"][0, 0, int(self.params["grid"]["mx0"] / 4)] / 1e-4)
ax.plot(
steps
* self.params["output"]["interval"]
/ (2 * np.pi * self.params["plasma"]["c_omp"] / 0.45),
exs,
)
ax.set_xlabel(r"$t\omega_{\rm p0}$")
ax.set_ylabel(r"$E_x$")
ax.set_title(self.jobid)
for i in range(4):
ax.axvline(i, c="gray", lw=1, ls="--")
hist = isolde.parseHistory(self.path + "/output/history")
ax.text(
2,
-1,
r"""
energy conservation
by $t\omega_{{\rm p 0}}={{{}}}: \Delta E/E={{{}}}%$
""".format(
int(hist["time"][-1] * 0.45 / self.params["plasma"]["c_omp"]),
int(hist["% dEtot"][-1] * 10000) / 10000,
),
)
plt.tight_layout()
plt.show()
class Weibel(Simulation):
jobid = "weibel"
userfile = "user_weibel"
dimension = 2
def diag(self):
import matplotlib.pyplot as plt
fig, ax = plt.subplots(figsize=(6, 6))
ax.set_title(self.jobid)
ax.grid(False)
from matplotlib.animation import FuncAnimation
flds = isolde.getFields(self.path + "/output/flds/flds.tot.%05d" % 0)
xmin = flds["xx"][0].min() / self.params["plasma"]["c_omp"]
xmax = flds["xx"][0].max() / self.params["plasma"]["c_omp"]
ymin = flds["yy"][0].min() / self.params["plasma"]["c_omp"]
ymax = flds["yy"][0].max() / self.params["plasma"]["c_omp"]
im = ax.imshow(
flds["bz"][0],
origin="lower",
cmap="RdBu",
vmin=-0.01,
vmax=0.01,
extent=(xmin, xmax, ymin, ymax),
)
ax.set_xlabel(r"$x/d_{e0}$")
ax.set_ylabel(r"$y/d_{e0}$")
txt1 = ax.text(10, 120, r"$B_z$", color="k")
txt2 = ax.text(90, 120, r"", color="k", zorder=100)
def init():
im.set_data(flds["bz"][0])
txt2.set_text(r"$t\omega_{{\rm p0}}=0$")
return (
im,
txt1,
txt2,
)
def animate(i):
flds = isolde.getFields(self.path + "/output/flds/flds.tot.%05d" % i)
im.set_data(flds["bz"][0])
txt2.set_text(
r"$t\omega_{{\rm p0}}={{{}}}$".format(
i
* self.params["output"]["interval"]
* 0.45
/ self.params["plasma"]["c_omp"]
)
)
return (
im,
txt1,
txt2,
)
anim = FuncAnimation(
fig,
animate,
init_func=init,
frames=50,
interval=500,
blit=True,
repeat=True,
)
# anim.save('animation.mp4', fps=10)
plt.tight_layout()
plt.show()
class Merging(Simulation):
jobid = "merging"
userfile = "unit_chargedmerging"
dimension = 2
def diag(self):
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
import matplotlib.collections as mcoll
from mpl_toolkits.axes_grid1 import make_axes_locatable
divE_max = 1e-11
fig, ax = plt.subplots(figsize=(6, 6))
def getMomenta(prtls):
en = np.sum(
np.sqrt(
1.0
+ prtls["1"]["u"] ** 2
+ prtls["1"]["v"] ** 2
+ prtls["1"]["w"] ** 2
)
* prtls["1"]["wei"]
) + np.sum(
np.sqrt(
1.0
+ prtls["2"]["u"] ** 2
+ prtls["2"]["v"] ** 2
+ prtls["2"]["w"] ** 2
)
* prtls["2"]["wei"]
)
mx = np.sum(prtls["1"]["u"] * prtls["1"]["wei"]) + np.sum(
prtls["2"]["u"] * prtls["2"]["wei"]
)
my = np.sum(prtls["1"]["v"] * prtls["1"]["wei"]) + np.sum(
prtls["2"]["v"] * prtls["2"]["wei"]
)
mz = np.sum(prtls["1"]["w"] * prtls["1"]["wei"]) + np.sum(
prtls["2"]["w"] * prtls["2"]["wei"]
)
return (en, mx, my, mz)
energy0, momx0, momy0, momz0 = getMomenta(
isolde.getParticles(self.path + "/output/prtl/prtl.tot.%05d" % 0)
)
def template(prtls):
energy1, momx1, momy1, momz1 = getMomenta(prtls)
return (
r"npart: {} ($\times$2)".format(len(prtls["1"]["x"]))
+ "\ntotal energy [err%]: {:.3f} [{:.4f}%]".format(
energy1, np.abs((energy1 - energy0) * 100 / energy0)
)
+ "\nmomX [err%]: {:.3f} [{:.4f}%]".format(
momx1, np.abs((momx1 - momx0) * 100 / momx0)
)
+ "\nmomY [err%]: {:.3f} [{:.4f}%]".format(
momy1, np.abs((momy1 - momy0) * 100 / momy0)
)
+ "\nmomZ [err%]: {:.3f} [{:.4f}%]".format(
momz1, np.abs((momz1 - momz0) * 100 / (momz0 + 1e-10))
)
)
sc1 = ax.scatter([-100], [-100], fc="blue", label="lecs", zorder=2)
sc2 = ax.scatter([-100], [-100], fc="red", label="ions", zorder=2)
lgd = ax.legend(loc="lower right")
major_ticks = np.arange(
0, self.params["grid"]["mx0"], self.params["grid"]["tileX"]
)
minor_ticks = np.arange(0, self.params["grid"]["my0"], 1)
ax.set_xticks(major_ticks)
ax.set_xticks(minor_ticks, minor=True)
ax.set_yticks(major_ticks)
ax.set_yticks(minor_ticks, minor=True)
ax.grid(False)
lines1 = [
[(x, y) for y in (0, self.params["grid"]["mx0"])] for x in major_ticks
] + [[(x, y) for x in (0, self.params["grid"]["mx0"])] for y in major_ticks]
grid1 = mcoll.LineCollection(
lines1, linestyles="solid", linewidths=1, color="k", zorder=1, alpha=0.5
)
ax.add_collection(grid1)
lines2 = [
[(x, y) for y in (0, self.params["grid"]["mx0"])] for x in minor_ticks
] + [[(x, y) for x in (0, self.params["grid"]["mx0"])] for y in minor_ticks]
grid2 = mcoll.LineCollection(
lines2, linestyles="solid", linewidths=0.2, color="k", zorder=1, alpha=0.3
)
ax.add_collection(grid2)
im = ax.imshow(
np.zeros((self.params["grid"]["mx0"], self.params["grid"]["my0"])),
origin="lower",
extent=(0, self.params["grid"]["mx0"], 0, self.params["grid"]["my0"]),
cmap="seismic",
vmin=-divE_max,
vmax=divE_max,
zorder=0,
)
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="2%", pad=0.02)
plt.colorbar(im, cax=cax, label=r"$\nabla\cdot \bf{E}$")
ttl = ax.text(0.1, 0.1, "", transform=ax.transAxes, va="center")
diag = ax.text(
2,
47,
"",
multialignment="left",
va="top",
bbox=dict(facecolor="white", edgecolor="gray", boxstyle="round,pad=0.2"),
)
def init():
ax.set_xlim(0, self.params["grid"]["mx0"])
ax.set_ylim(0, self.params["grid"]["my0"])
ax.set_xlabel(r"$x$")
ax.set_ylabel(r"$y$")
ax.set_title(self.jobid)
prtls = isolde.getParticles(self.path + "/output/prtl/prtl.tot.%05d" % 0)
flds = isolde.getFields(self.path + "/output/flds/flds.tot.%05d" % 0)
sc1.set_offsets(np.array([prtls["1"]["x"], prtls["1"]["y"]]).T)
sc2.set_offsets(np.array([prtls["2"]["x"], prtls["2"]["y"]]).T)
im.set_data(flds["divE"][0])
ttl.set_text("t=0")
diag.set_text(template(prtls))
return (
sc1,
sc2,
im,
ttl,
diag,
lgd,
grid1,
grid2,
)
def animate(i):
prtls = isolde.getParticles(self.path + "/output/prtl/prtl.tot.%05d" % i)
flds = isolde.getFields(self.path + "/output/flds/flds.tot.%05d" % i)
sc1.set_offsets(np.array([prtls["1"]["x"], prtls["1"]["y"]]).T)
sc2.set_offsets(np.array([prtls["2"]["x"], prtls["2"]["y"]]).T)
im.set_data(flds["divE"][0])
ttl.set_text("t=" + str(i))
diag.set_text(template(prtls))
return (
sc1,
sc2,
im,
ttl,
diag,
lgd,
grid1,
grid2,
)
anim = FuncAnimation(
fig,
animate,
init_func=init,
frames=40,
interval=250,
blit=True,
repeat=True,
)
plt.tight_layout()
plt.show()
class AdaptiveLB(Simulation):
jobid = "alb"
userfile = "unit_alb"
dimension = 3
def diag(self):
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
fig = plt.figure(figsize=(8, 8))
sx = self.params["grid"]["mx0"]
sy = self.params["grid"]["my0"]
sz = self.params["grid"]["mz0"]
sizes = {"x": sx, "y": sy, "z": sz}
ax1 = plt.subplot(221)
ax2 = plt.subplot(222)
ax3 = plt.subplot(223)
ax4 = plt.subplot(224, projection="3d")
sc4_1 = ax4.scatter([-100], [-100], fc="C0")
sc4_2 = ax4.scatter([-100], [-100], fc="C0")
ax4.set_xlim(0, sx)
ax4.set_ylim(0, sy)
ax4.set_zlim(0, sz)
ax4.set_xlabel("x")
ax4.set_ylabel("y")
ax4.set_zlabel("z")
def draw(i):
prtls = isolde.getParticles(self.path + "/output/prtl/prtl.tot.%05d" % i)
flds = isolde.getFields(self.path + "/output/flds/flds.tot.%05d" % i)
dom = isolde.getDomains(self.path + "/output/domain.%05d" % i)
# xz
ims = []
for ax, coords, avr in zip([ax1, ax2, ax3], ["xz", "xy", "yz"], [1, 0, 2]):
ax.cla()
ax.grid(False)
s1 = coords[0]
s2 = coords[1]
ax.set_xlim(0, sizes[s1])
ax.set_ylim(0, sizes[s2])
ax.set_xlabel(s1)
ax.set_ylabel(s2)
im = ax.imshow(
np.zeros((sizes[s1], sizes[s2])),
vmin=0,
vmax=300,
origin="lower",
extent=(0, sizes[s1], 0, sizes[s2]),
cmap="hot",
)
for si in np.unique(dom[s1 + "0"]):
ax.axvline(si, c="C0", lw=0.5)
for si in np.unique(dom[s2 + "0"]):
ax.axhline(si, c="C0", lw=0.5)
dens = np.sum(flds["dens1"] + flds["dens2"], axis=avr)
im.set_data(dens)
ims.append(im)
# scatter
sc4_1._offsets3d = (prtls["1"]["x"], prtls["1"]["y"], prtls["1"]["z"])
sc4_2._offsets3d = (prtls["2"]["x"], prtls["2"]["y"], prtls["2"]["z"])
return (
ax1,
ax2,
ax3,
ax4,
ims,
sc4_1,
sc4_2,
)
def init():
return draw(0)
def animate(i):
return draw(i)
anim = FuncAnimation(
fig,
animate,
init_func=init,
frames=40,
interval=250,
blit=False,
repeat=True,
)
# anim.save('animation.mp4', fps=10)
plt.tight_layout()
plt.show()
# Here specify the test simulations and give additional specs of the environment
if options.cluster:
common_flags = " --cluster={} -hdf5 --debug=1".format(options.cluster)
else:
common_flags = " -hdf5"
simulations = [
TwoStream(
common_flags,
params={
"node_configuration": {"sizex": 28},
"time": {"last": 50000},
"grid": {"mx0": 5600, "tileX": 100},
"algorithm": {"c": 0.35, "nfilter": 8},
"output": {"enable": 0, "hst_enable": 1, "hst_interval": 5},
"plasma": {"ppc0": 64, "sigma": 10, "c_omp": 40},
"particles": {
"nspec": 2,
"maxptl1": 1e5,
"m1": 1,
"ch1": -1,
"maxptl2": 1e5,
"m2": 1,
"ch2": -1,
},
"problem": {"shift_gamma": 2.5},
},
),
PlasmaOsc(
common_flags,
nproc=4,
params={
"node_configuration": {"sizex": 4},
"time": {"last": 1000},
"grid": {"mx0": 1120, "tileX": 10},
"algorithm": {"nfilter": 8},
"output": {
"enable": 1,
"prtl_enable": 0,
"spec_enable": 0,
"interval": 10,
"hst_enable": 1,
"hst_interval": 5,
},
"plasma": {"ppc0": 500, "sigma": 1, "c_omp": 10},
"particles": {
"nspec": 2,
"maxptl1": 1e8,
"m1": 1,
"ch1": -1,
"maxptl2": 1e8,
"m2": 1,
"ch2": 1,
},
"problem": {"upstream_T": 1e-5, "amplitude": 0.01, "nwaves": 1},
},
),
Weibel(
common_flags,
nproc=28,
params={
"node_configuration": {"sizex": 7, "sizey": 4},
"time": {"last": 500},
"grid": {"mx0": 1400, "my0": 1400, "tileX": 20, "tileY": 20},
"algorithm": {"nfilter": 8},
"output": {
"enable": 1,
"prtl_enable": 0,
"spec_enable": 0,
"interval": 10,
"hst_enable": 1,
"hst_interval": 10,
},
"plasma": {"ppc0": 16, "sigma": 10, "c_omp": 10},
"particles": {
"nspec": 2,
"maxptl1": 1e8,
"m1": 1,
"ch1": -1,
"maxptl2": 1e8,
"m2": 1,
"ch2": 1,
},
"problem": {"backgr_T": 1e-5, "shift_beta": 0.5},
},
),
Merging(
common_flags + " -dwn",
nproc=1,
params={
"node_configuration": {"sizex": 1, "sizey": 1},
"time": {"last": 500},
"grid": {"mx0": 50, "my0": 50, "tileX": 10, "tileY": 10},
"algorithm": {"nfilter": 0},
"output": {
"interval": 10,
"stride": 1,
"smooth_window": 0,
"write_nablas": 1,
},
"plasma": {"ppc0": 50, "sigma": 5, "c_omp": 50},
"particles": {
"nspec": 2,
"maxptl1": 1e8,
"m1": 1,
"ch1": -1,
"dwn1": 1,
"maxptl2": 1e8,
"m2": 1,
"ch2": 1,
"dwn2": 1,
},
"downsampling": {
"interval": 1,
"start": 1,
"max_weight": 1e5,
"cartesian_bins": 1,
"energy_min": 0,
"energy_max": 1e5,
"int_weights": 0,
"dynamic_bins": 1,
"mom_bins": 1,
"mom_spread": 1e5,
},
},
),
AdaptiveLB(
common_flags + " -alb",
nproc=192,
params={
"node_configuration": {"sizex": 8, "sizey": 8, "sizez": 3},
"time": {"last": 400},
"grid": {
"mx0": 112,
"my0": 112,
"mz0": 114,
"resize_tiles": 1,
"tileX": 5,
"tileY": 5,
"tileZ": 5,
},
"algorithm": {"nfilter": 0, "fieldsolver": 0, "currdeposit": 0},
"output": {
"enable": 1,
"interval": 10,
"stride": 10,
"istep": 1,
"diag_enable": 1,
},
"adaptive_load_balancing": {
"in_x": 1,
"in_y": 1,
"in_z": 1,
"sx_min": 8,
"sy_min": 8,
"sz_min": 8,
"interval_x": 5,
"interval_y": 5,
"interval_z": 5,
"slab_x": 2,
"slab_y": 2,
"slab_z": 2,
},
"plasma": {"ppc0": 16, "sigma": 5, "c_omp": 10},
"particles": {
"nspec": 2,
"maxptl1": 1e6,
"m1": 1,
"ch1": 1,
"maxptl2": 1e6,
"m2": 1,
"ch2": -1,
},
"problem": {"radius": 5},
},
),
]
if options.diag:
# diagnostic mode where you analize the test results
import matplotlib.pyplot as plt
import numpy as np
import tristanVis.isolde as isolde
plt.style.use("fivethirtyeight")
for ii, simulation in enumerate(simulations):
if ii + 1 == options.diag:
if options.dry:
print(f"Plotting for `{simulation.jobid}`")
else:
simulation.path = f"{testdir_full}/{ii + 1:02}_{simulation.jobid}"
simulation.diag()
break
else:
# regular mode where you compile and run tests
if not os.path.exists(testdir_full):
os.makedirs(testdir_full)
with open(testdir_full + "/test.log", "w+") as testlog:
# load modules
for ii, simulation in enumerate(simulations):
if not (ii + 1 in tests):
continue
# create directory for simulation
simulation.path = f"{testdir_full}/{ii + 1:02}_{simulation.jobid}"
if os.path.exists(simulation.path) and not options.r:
callCommand(f"rm -r {simulation.path}")
if not options.r and not options.dry:
os.makedirs(simulation.path)
testlog.write(
("TEST_#{}_".format(ii + 1) + simulation.jobid).ljust(50, ".") + "\n"
)
# configure
config_command = "python3 configure.py"
config_command += simulation.flags
config_command += " -{}d".format(simulation.dimension)
config_command += (
" --{}=".format(simulation.userfile[:4]) + simulation.userfile
)
if not options.r:
# compile everything if not in `r` mode
callCommand(config_command + suffix)
# clean
callCommand("make clean" + suffix)
# compile
callCommand("make all -j " + suffix)
# check if compilation successfull
simulation.exe = f"tristan-mp{simulation.dimension}d"
simulation.exe_full = f"{simulation.path}/{simulation.exe}"
if (
not os.path.isfile(codedir + "/bin/" + simulation.exe)
) and not options.dry:
raise RuntimeError("Something went wrong")
testlog.write("compilation".ljust(46, ".") + "[OK]\n")
print("Compilation of `{}` done.".format(simulation.jobid))
# move executable
callCommand(f"mv {codedir}/bin/{simulation.exe} {simulation.path}")
# clean
callCommand("make clean" + suffix)
# write input
simulation.input = "input." + simulation.jobid
simulation.input_full = simulation.path + "/" + simulation.input
if not options.dry:
with open(simulation.input_full, "w+") as inp:
for block in simulation.params.keys():
inp.write("\n<{}>\n\n".format(block))
for var in simulation.params[block].keys():
inp.write(
" {} = {}\n".format(
var, simulation.params[block][var]
)
)
testlog.write("input file".ljust(46, ".") + "[OK]\n")
# write submit
simulation.submit = "submit_" + simulation.jobid
simulation.submit_full = simulation.path + "/" + simulation.submit
if (not options.r) and (not options.dry) and (options.cluster):
with open(simulation.submit_full, "w+") as sub:
sub.write("#!/bin/bash\n")
sub.write("#SBATCH -t {}\n".format(simulation.walltime))
sub.write("#SBATCH -n {}\n".format(simulation.nproc))
sub.write("#SBATCH -J {}\n".format(simulation.jobid))
sub.write(
"#SBATCH --output={}/tristan-v2.out\n".format(simulation.path)
)
sub.write(
"#SBATCH --error={}/tristan-v2.err\n\n".format(simulation.path)
)
sub.write("DIR={}\n".format(simulation.path))
sub.write("EXECUTABLE=$DIR/{}\n".format(simulation.exe))
sub.write("INPUT=$DIR/{}\n".format(simulation.input))
sub.write("OUTPUT_DIR=output\n".format(simulation.path))
sub.write("SLICE_DIR=slices\n".format(simulation.path))
sub.write("REPORT_FILE=$DIR/report\n".format(simulation.path))
sub.write("ERROR_FILE=$DIR/error\n\n".format(simulation.path))
for module in modules:
sub.write("module load {}\n".format(module))
sub.write("\nmkdir $OUTPUT_DIR\n\n")
sub.write(
"srun $EXECUTABLE -i $INPUT -o $OUTPUT_DIR -s $SLICE_DIR -r $RESTART_DIR -R $RESTART > $REPORT_FILE 2> $ERROR_FILE"
)
testlog.write("submit file".ljust(46, ".") + "[OK]\n")
testlog.write("\n\n")
if (not options.c) or (options.r):
for ii, simulation in enumerate(simulations):
if not (ii + 1 in tests):
continue
callCommand(f"cd {simulation.path} && sbatch {simulation.submit_full}")
testlog.write(
("`{}`".format(simulation.jobid)).ljust(41, ".") + "submitted\n"
)