def addFs(self, sd):
'''
:param sd: dataframe with all necessary variables from which F can be computed
:returns: same dataframe but with F column added
'''
bhdvcs = BHDVCS()
sd['F'] = bhdvcs.TotalUUXS(
np.array(sd[['phi_x', 'k', 'QQ', 'x_b', 't', 'F1', 'F2', 'dvcs']]),
np.array(sd['ReH']), np.array(sd['ReE']), np.array(sd['ReHtilde']))
return sd
class TotalUUXS(tf.keras.layers.Layer):
def __init__(self):
super(TotalUUXS, self).__init__(dtype='float64')
self.F = BHDVCS()
def call(self, inputs):
return self.F.TotalUUXS(inputs[:, :8], inputs[:, 8], inputs[:, 9],
inputs[:, 10])
class TotalUUXSlayer(tf.keras.layers.Layer):
'''
class for incorporating TotalUUXS function into tensorflow layer
'''
def __init__(self):
super(TotalUUXSlayer, self).__init__(dtype='float64')
self.F = BHDVCS()
def call(self, inputs):
return self.F.TotalUUXS(inputs[:, :8], inputs[:, 8], inputs[:, 9],
inputs[:, 10])
def __init__(self):
super(TotalUUXS, self).__init__(dtype='float64')
self.F = BHDVCS()
import matplotlib.pyplot as plt
import scipy.stats as stats
from datetime import datetime
import sys
print(tf.__version__)
print("\n \n I'm running! \n \n")
# In[2]:
import sys
# insert at 1, 0 is the script path (or '' in REPL)
sys.path.insert(1, '/home/cee9hc/ANN_GPD_Calc_Test')
from BHDVCStf import BHDVCS #modified bhdvcs file
bhdvcs = BHDVCS()
# In[37]:
df = pd.read_csv('/home/cee9hc/ANN_GPD_Calc_Test/dvcs_psuedo.csv')
# In[4]:
class DvcsData(object):
def __init__(self, df):
self.X = df.loc[:, [
'phi_x', 'k', 'QQ', 'x_b', 't', 'F1', 'F2', 'ReH', 'ReE',
'ReHtilde', 'dvcs'
]]
self.XnoCFF = df.loc[:, [