def load_qnuc_table(source, grid_version=0):
path = grid_strings.get_source_subdir(source, 'qnuc')
prefix = f'qnuc_v{grid_version}'
filename = grid_strings.get_source_filename(source,
prefix=prefix,
extension='.txt')
filepath = os.path.join(path, filename)
return pd.read_table(filepath, delim_whitespace=True)
def save_qnuc_table(table, source, grid_version=0):
path = grid_strings.get_source_subdir(source, 'qnuc')
prefix = f'qnuc_v{grid_version}'
filename = grid_strings.get_source_filename(source,
prefix=prefix,
extension='.txt')
filepath = os.path.join(path, filename)
table_str = table.to_string(index=False)
with open(filepath, 'w') as f:
f.write(table_str)
def load_lum(run, batch, source, basename='xrb', reload=False, save=True,
silent=True, check_monotonic=True):
"""Attempts to load pre-extracted luminosity data, or load raw binary.
Returns [time (s), luminosity (erg/s)]
"""
def load_save(load_filepath, save_filepath):
lum_loaded = extract_lcdata(filepath=load_filepath, silent=silent)
if save:
try:
save_ascii(lum=lum_loaded, filepath=save_filepath)
except FileNotFoundError:
print("Can't save preloaded luminosity file, path not found")
return lum_loaded
pyprint.print_dashes()
batch_str = grid_strings.get_batch_string(batch, source)
analysis_path = grid_strings.get_source_subdir(source, 'burst_analysis')
input_path = os.path.join(analysis_path, batch_str, 'input')
presaved_filepath = os.path.join(input_path, f'{batch_str}_{run}.txt')
run_str = grid_strings.get_run_string(run, basename)
model_path = grid_strings.get_model_path(run, batch, source, basename)
binary_filepath = os.path.join(model_path, f'{run_str}.lc')
print(binary_filepath)
if reload:
print('Deleting preloaded file, reloading binary file')
subprocess.run(['rm', '-f', presaved_filepath])
try:
lum = load_save(binary_filepath, presaved_filepath)
except FileNotFoundError:
print('XXXXXXX lumfile not found. Skipping XXXXXXXX')
return
else:
try:
lum = load_ascii(presaved_filepath)
except (FileNotFoundError, OSError):
print('No preloaded file found. Reloading binary')
try:
lum = load_save(binary_filepath, presaved_filepath)
except FileNotFoundError:
print('XXXXXXX lumfile not found. Skipping XXXXXXX')
return
if check_monotonic:
dt = np.diff(lum[:, 0])
if True in (dt < 0):
pyprint.print_warning('Lightcurve timesteps are not in order. '
+ 'Something has gone horribly wrong!', n=80)
raise RuntimeError('Lightcurve timesteps are not in order')
pyprint.print_dashes()
return lum
def write_submission_script(source,
version,
n_walkers,
n_steps,
dump_step,
walltime=20,
n_threads=8,
cluster='icer'):
"""Writes a script for submitting a job on a cluster
Parameter:
----------
path : str
target path for slurm script
walltime: int
job time limit (hr)
"""
extensions = {'monarch': '.sh', 'icer': '.qsub'}
job_str = get_jobstring(source=source,
version=version,
n_walkers=n_walkers,
n_threads=n_threads,
n_steps=n_steps)
time_str = f'{walltime:02}:00:00'
print(f'Writing submission script for cluster: {cluster}')
ext = extensions[cluster]
script_str = get_submission_str(source=source,
version=version,
n_walkers=n_walkers,
n_threads=n_threads,
n_steps=n_steps,
time_str=time_str,
job_str=job_str,
cluster=cluster,
dump_step=dump_step)
# prepend_str = {True:'restart_', False:''}[restart]
logs_path = grid_strings.get_source_subdir(source, 'logs')
filename = f'{cluster}_{job_str}{ext}'
filepath = os.path.join(logs_path, filename)
with open(filepath, 'w') as f:
f.write(script_str)
def copy_lightcurve(run, batch, source, basename='xrb'):
"""Copies over full model lightcurve
"""
dashes()
print('Copying model lightcurve')
path = grid_strings.get_source_subdir(source, 'burst_analysis')
batch_str = grid_strings.get_batch_string(batch, source)
run_str = get_run_string(run, basename)
model_string = grid_strings.get_model_string(run=run,
batch=batch,
source=source)
filename = f'{model_string}.txt'
filepath = os.path.join(path, batch_str, 'input', filename)
target_filename = f'model_lightcurve_{model_string}'
target_filepath = os.path.join(PROJECT_PATH, source, batch_str, run_str,
target_filename)
print(f'from: \n{filepath}' + f'to: {target_filepath}')
subprocess.run(['cp', filepath, target_filepath])
def batch_path(batch, source='frank'):
"""Returns string of path to batch dir
"""
path = grid_strings.get_source_subdir(source, 'profiles')
batch_str = grid_strings.get_batch_string(batch=batch, source=source)
return os.path.join(path, batch_str)
# =================================================================
# Script callable from terminal to clean up chain/sampler files
# =================================================================
GRIDS_PATH = os.environ['KEPLER_GRIDS']
n_arg = len(sys.argv)
if n_arg != 4:
print('Must provide 3 parameters: \n\t1. [source]' +
'\n\t2. [version]\n\t3. [keep_step]')
sys.exit()
source = sys.argv[1]
version = sys.argv[2]
keep_step = sys.argv[3]
source_path = grid_strings.get_source_subdir(source, 'mcmc')
file_list = os.listdir(source_path)
discard = []
keep = []
print(source)
print(source_path)
for file_ in file_list:
if (source in file_ and file_ not in ['.keep', '.gitignore']
and f'_V{version}_' in file_ and f'_S{keep_step}.' not in file_):
discard += [file_]
elif (source in file_ and keep_step in file_ and f'_V{version}_' in file_):
keep += [file_]