Activation foil analysis

from libra_toolbox.neutron_detection.activation_foils import *
from data import foil_data
import pandas as pd
import pint_pandas

# make a pandas dataframe based on the foil data with columns for run, generator, flux and error

irradiations = [
    {"t_on": 0, "t_off": 12 * settings.ureg.h},
    {"t_on": 24 * settings.ureg.h, "t_off": 36 * settings.ureg.h},
]

data = {
    "run": [],
    "generator": [],
    "flux": [],
    "error": [],
}

for name, foil in foil_data.items():
    flux = explicit.get_neutron_flux(foil, irradiations)
    error = explicit.get_neutron_flux_error(foil)
    data["run"].append(foil["run"])
    data["generator"].append(foil["generator"])
    data["flux"].append(flux.to(settings.ureg.s**-1))
    data["error"].append(error)
data["flux"] = pd.Series(data["flux"], dtype="pint[s**-1]")
pd.options.display.float_format = '{:,.2e}'.format
df = pd.DataFrame(data)
df.pint.dequantify()

	run	generator	flux	error
unit	No Unit	No Unit	1 / second	No Unit
0	4	P383	2.61e+08	8.81e-02
1	4	P383	2.67e+08	8.81e-02
2	4	A325	9.84e+07	8.82e-02
3	4	A325	1.06e+08	8.82e-02
4	5	A325	1.15e+08	8.82e-02
5	5	A325	1.17e+08	8.82e-02
6	5	P383	2.68e+08	8.81e-02
7	5	P383	2.74e+08	8.81e-02
8	6	A325	1.06e+08	8.82e-02
9	6	A325	1.07e+08	8.82e-02
10	6	P383	2.49e+08	8.81e-02
11	6	P383	2.46e+08	8.81e-02

#for each run number compute the average per generator
grouped_multiple = df.groupby(['run', 'generator']).agg({'flux': ['mean', 'min', 'max']})
grouped_multiple.columns = ['flux_mean', 'flux_min', 'flux_max']
grouped_multiple = grouped_multiple.reset_index()
grouped_multiple.pint.dequantify()

	run	generator	flux_mean	flux_min	flux_max
unit	No Unit	No Unit	1 / second	1 / second	1 / second
0	4	A325	1.02e+08	9.84e+07	1.06e+08
1	4	P383	2.64e+08	2.61e+08	2.67e+08
2	5	A325	1.16e+08	1.15e+08	1.17e+08
3	5	P383	2.71e+08	2.68e+08	2.74e+08
4	6	A325	1.06e+08	1.06e+08	1.07e+08
5	6	P383	2.48e+08	2.46e+08	2.49e+08