plot_results Namespace Reference

Variables
string	generator_type = 'random'
	list_of_files = glob.glob(sys.argv[1] + '*npy')
	latest_file = max(list_of_files, key=os.path.getctime)
	results = np.load(latest_file)
	pickle_data = pickle.load(f)
	nbatches = len(pickle_data[1]['run_order'])
	names = results.dtype.names
dictionary	results_dict = {}
list	plot_output = ['f', 'emittance', 'charge', 'energy_avg', 'energy_std']
list	plot_input = ['ramp_down_1', 'zlens_1', 'adjust_factor', 'ramp_down_2']
dictionary	d_ylim
dictionary	d_yunits
	ind_best = np.nanargmin(results_dict['f'])
	figsize
	my_sims
	s
	c
	cmap
	cbar = plt.colorbar()
	bbox_inches

Detailed Description

Plotting script for LibEnsemble run on WarpX simulations.
input: A directory which which the script will read the
latest .npy and .pickle files generated by LibEnsemble

Variable Documentation

bbox_inches

plot_results.bbox_inches

c

plot_results.c

cbar

plot_results.cbar = plt.colorbar()

cmap

plot_results.cmap

d_ylim

dictionary plot_results.d_ylim

Initial value:

=  {
    'f': (3.e-7, 5.e-3),
    'emittance': (3.e-7, 5.e-3),
    'charge': (1.e-7, 1.e-5),
    'energy_avg': (5.e1, 5.e2),
    'energy_std': (1.e-2, 1.e-1)
}

d_yunits

dictionary plot_results.d_yunits

Initial value:

=  {
    'f': " (a.u.)",
    'emittance': " (m rad)",
    'charge': " (pC/m)",
    'energy_avg': " (MeV)",
    'energy_std': " (%)"
}

figsize

plot_results.figsize

generator_type

string plot_results.generator_type = 'random'

ind_best

plot_results.ind_best = np.nanargmin(results_dict['f'])

latest_file

plot_results.latest_file = max(list_of_files, key=os.path.getctime)

list_of_files

plot_results.list_of_files = glob.glob(sys.argv[1] + '*npy')

my_sims

plot_results.my_sims

Initial value:

=  np.isin(results_dict['sim_id'],
                                  pickle_data[1]['run_order'][batch])

names

plot_results.names = results.dtype.names

nbatches

plot_results.nbatches = len(pickle_data[1]['run_order'])

pickle_data

plot_results.pickle_data = pickle.load(f)

plot_input

list plot_results.plot_input = ['ramp_down_1', 'zlens_1', 'adjust_factor', 'ramp_down_2']

plot_output

list plot_results.plot_output = ['f', 'emittance', 'charge', 'energy_avg', 'energy_std']

results

plot_results.results = np.load(latest_file)

results_dict

dictionary plot_results.results_dict = {}

s

plot_results.s