In [1]:

    

import os
import sys
root_folder = os.path.dirname(os.getcwd())
sys.path.append(root_folder)
from ResoFit._pulse_shape import NeutronPulse
from ResoFit._pulse_shape import ProtonPulse
from ResoFit.experiment import Experiment
import numpy as np
from ResoFit.simulation import Simulation
overwrite_csv = False
import scipy.signal as ss
import matplotlib.pyplot as plt
# import plotly
# plotly.offline.init_notebook_mode()
# import plotly.graph_objs as go


    

In [2]:

    

%matplotlib notebook


    

In [3]:

    

folder = 'data/IPTS_19558/reso_data_19558'
data_file1 = 'Gd_thick.csv'
spectra_file = 'Image002_Spectra.txt'
experiment1 = Experiment(data_file=data_file1,
                         spectra_file=spectra_file,
                         folder=folder,
                         baseline=False)
# experiment1.slice(slice_start=300, reset_index=False)
# peak_df = experiment1.find_peak()


    

In [4]:

    

experiment1.plot(x_type='time', y_type='transmission', t_unit='us')
plt.ylim(top=1.05, bottom=-0.05)


    

    















    












    
Out[4]:





(-0.05, 1.05)

In [4]:

    

experiment1.plot(x_type='time', y_type='transmission', t_unit='us')
plt.ylim(top=1.05, bottom=-0.05)


    

    















    












    
Out[4]:





(-0.05, 1.05)

In [5]:

    

# folder = 'data/IPTS_19558/reso_data_19558'
# data_file1 = 'Gd_thick.csv'
# spectra_file = 'Image002_Spectra.txt'
experiment2 = Experiment(data_file=data_file1,
                         spectra_file=spectra_file,
                         folder=folder,
                         baseline=True)
# experiment1.slice(slice_start=300, reset_index=False)
# peak_df = experiment1.find_peak()


    

In [6]:

    

experiment2.plot(x_type='time', y_type='transmission', t_unit='us')
plt.ylim(top=1.05, bottom=-0.05)


    

    















    












    
Out[6]:





(-0.05, 1.05)

In [7]:

    

experiment2.plot(x_type='time', y_type='transmission', t_unit='us')
plt.ylim(top=1.05, bottom=-0.05)


    

    















    












    
Out[7]:





(-0.05, 1.05)

In [ ]:

    

experiment2.find_peak()


    

In [3]:

    

source_to_detector_m = 16.45
simulation = Simulation(energy_min=7, energy_max=150, energy_step=0.1, database='ENDF_VII')
simulation.add_layer(layer='Gd', layer_thickness_mm=0.15)
simulation._convolve_neutron_beam_shape(source_to_detector_m=source_to_detector_m)


    

    




'/Users/y9z/Documents/GitHub/ResoFit/ResoFit/result/neutron_pulse/ikeda_carpenter/Neutron_fitted_params_1eV_500eV_ikeda_carpenter.csv' exists...
Fitted parameters file loaded.
'/Users/y9z/Documents/GitHub/ResoFit/ResoFit/result/neutron_pulse/ikeda_carpenter/Loglog_linear_within_1eV_500eV_ikeda_carpenter.csv' exists...
Parameters linear fitted file loaded.
'/Users/y9z/Documents/GitHub/ResoFit/ResoFit/result/neutron_pulse/ikeda_carpenter/TOF_shape_eV_7.0_150.0_0.1_us_0.05_5500000.0_184_for_sum_16.45m_ikeda_carpenter.csv' exists...
TOF neutron beam shape file loaded.

In [61]:

    

tof_us = simulation.neutron_pulse.shape_tof_df_interp['tof_us']


    

In [7]:

    

experiment1.data.plot()
envelope = pku.envelope(arr0)
plt.plot(envelope, label='envelope')
baseline = pku.baseline(arr0)
plt.plot(baseline, label='baseline')
plt.ylim(bottom=-0.05, top=1.05)
plt.legend()


    

    
Out[7]:





<matplotlib.legend.Legend at 0x10e9ae908>






    

In [8]:

    

arr1 = arr0 + (1-envelope)
plt.plot(arr1)
plt.ylim(bottom=-0.05, top=1.05)


    

    
Out[8]:





(-0.05, 1.05)