def _save_simulation_results(self, save_only_ID_0=False, time_elapsed=None) :
if save_only_ID_0 and self.cfg.network.ID != 0 :
return None
filename_hdf5 = self._get_filename(name="network", filetype="hdf5")
utils.make_sure_folder_exist(filename_hdf5)
with h5py.File(filename_hdf5, "w", **hdf5_kwargs) as f : #
f.create_dataset("my_state", data=self.my_state)
f.create_dataset("my_corona_type", data=self.my.corona_type)
f.create_dataset("my_number_of_contacts", data=self.my.number_of_contacts)
f.create_dataset("day_found_infected", data=self.intervention.day_found_infected)
f.create_dataset("coordinates", data=self.my.coordinates)
# import ast; ast.literal_eval(str(cfg))
f.create_dataset("cfg_str", data=str(self.cfg))
f.create_dataset("R_true", data=self.intervention.R_true_list)
f.create_dataset("freedom_impact", data=self.intervention.freedom_impact_list)
f.create_dataset("R_true_brit", data=self.intervention.R_true_list_brit)
f.create_dataset("df", data=utils.dataframe_to_hdf5_format(self.df))
# f.create_dataset(
# "df_coordinates",
# data=utils.dataframe_to_hdf5_format(self.df_coordinates, cols_to_str="kommune"),
# )
if time_elapsed :
f.create_dataset("time_elapsed", data=time_elapsed)
self._add_cfg_to_hdf5_file(f)
return None
def _save_initialized_network(self, filename) :
if self.verbose :
print(f"Saving initialized network to {filename}", flush=True)
utils.make_sure_folder_exist(filename)
my_hdf5ready = nb_load_jitclass.jitclass_to_hdf5_ready_dict(self.my)
with h5py.File(filename, "w", **hdf5_kwargs) as f :
group_my = f.create_group("my")
nb_load_jitclass.save_jitclass_hdf5ready(group_my, my_hdf5ready)
utils.NestedArray(self.agents_in_age_group).add_to_hdf5_file(f, "agents_in_age_group")
f.create_dataset("N_ages", data=self.N_ages)
self._add_cfg_to_hdf5_file(f)
def get_fit_results(abm_files, force_rerun=False, num_cores=1, y_max=0.01):
all_fits_file = f"Data/fits_ymax_{y_max}.joblib"
if Path(all_fits_file).exists() and not force_rerun:
print("Loading all Imax fits", flush=True)
return joblib.load(all_fits_file)
else:
all_fits = {}
print(
f"Fitting {len(abm_files.all_filenames)} files with {len(abm_files.cfgs)} different simulation parameters, please wait.",
flush=True,
)
reject_counter = Counter()
desc = "Fitting ABM simulations"
for cfg, filenames in tqdm(abm_files.iter_folders(),
total=len(abm_files.cfgs),
desc=desc):
# break
output_filename = Path(
"Data/fits") / f"fits_{cfg.hash}_ymax_{y_max}.joblib"
utils.make_sure_folder_exist(output_filename)
if output_filename.exists():
all_fits[cfg.hash] = joblib.load(output_filename)
else:
with warnings.catch_warnings():
warnings.filterwarnings(
"ignore",
message="covariance is not positive-semidefinite.")
fit_results, reject_counter_tmp = fit_multiple_files(
cfg,
filenames,
num_cores=num_cores,
y_max=y_max,
)
joblib.dump(fit_results, output_filename)
all_fits[cfg.hash] = fit_results
reject_counter += reject_counter_tmp
print(reject_counter)
joblib.dump(all_fits, all_fits_file)
return all_fits
def _save_dataframe(self, save_csv=False, save_hdf5=True) :
# Save CSV
if save_csv :
filename_csv = self._get_filename(name="ABM", filetype="csv")
utils.make_sure_folder_exist(filename_csv)
self.df.to_csv(filename_csv, index=False)
if save_hdf5 :
filename_hdf5 = self._get_filename(name="ABM", filetype="hdf5")
utils.make_sure_folder_exist(filename_hdf5)
with h5py.File(filename_hdf5, "w", **hdf5_kwargs) as f : #
f.create_dataset("df", data=utils.dataframe_to_hdf5_format(self.df))
self._add_cfg_to_hdf5_file(f)
return None
def plot_simulation(I_tot_scaled, f, start_date, axes) :
# Create the plots
tmp_handles_0 = axes[0].plot(pd.date_range(start=start_date, periods = len(I_tot_scaled), freq="D"), I_tot_scaled, lw = 4, c = "k")[0]
tmp_handles_2 = axes[1].plot(pd.date_range(start=start_date, periods = len(f), freq="W-SUN"), f, lw = 4, c = "k")[0]
return [tmp_handles_0, tmp_handles_2]
rc_params.set_rc_params()
reload(plot)
reload(file_loaders)
# Prepare output file
utils.make_sure_folder_exist(fig_name)
logK, logK_sigma, beta, covid_index_offset, t_index = load_covid_index(start_date.date())
fraction, fraction_sigma, fraction_offset, t_fraction = load_b117_fraction()
# Load the ABM simulations
abm_files = file_loaders.ABM_simulations(base_dir="Output/ABM", subset=subset, verbose=True)
if len(abm_files.all_filenames) == 0 :
raise ValueError(f"No files loaded with subset: {subset}")
plot_handles = []
lls = []
return fig, axes, fi_list, pc_list,name_list
rc_params.set_rc_params()
#%%
reload(plot)
reload(file_loaders)
abm_files = file_loaders.ABM_simulations(verbose=True)
network_files = file_loaders.ABM_simulations(base_dir="Data/network", filetype="hdf5")
pdf_name = Path(f"Figures/data_anal.pdf")
utils.make_sure_folder_exist(pdf_name)
with PdfPages(pdf_name) as pdf:
fi_list = []
pc_list = []
name_list = []
# for ABM_parameter in tqdm(abm_files.keys, desc="Plotting individual ABM parameters"):
for cfg in tqdm(
abm_files.iter_cfgs(),
desc="Plotting individual ABM parameters",
total=len(abm_files.cfgs),
):
# break
fig, _, fi_list, pc_list, name_list = analyse_single_ABM_simulation(cfg, abm_files, network_files, fi_list, pc_list, name_list)