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209 changes: 103 additions & 106 deletions colradpy/read_adf11.py
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Original file line number Diff line number Diff line change
@@ -1,106 +1,103 @@
import numpy as np
import re


def read_adf11(fil):
""" Reads data formatted in adf11 format. This format is generally used for GCR coefficients.
The data is stored in arrays of log_10.
Creates a dictionary to hold the data
Args:
:param fil: The file path to the input file
:type fil: string
"""

f = open(fil)
adf11 = {}
adf11['input_file'] = {}

#reading the first line
tmp = re.findall('(\d+)',f.readline())
adf11['input_file']['nuc_charge'] = int(tmp[0])
adf11['input_file']['num_dens'] = int(tmp[1])
adf11['input_file']['num_temp'] = int(tmp[2])
adf11['input_file']['charge_min'] = int(tmp[3])
adf11['input_file']['charge_max'] = int(tmp[4])

f.readline() #reading '-------------'
if( 'r' in re.split('_',re.split('/',fil)[-1])[0]):

adf11['input_file']['metas'] = np.array(list( #metastables
map(int,re.findall('(\d+)',f.readline()))))
f.readline() #reading '---------------'
else:
adf11['input_file']['metas'] = np.ones(adf11['input_file']['charge_max']+1,dtype='int')

#read in the density grid
adf11['input_file']['dens_grid'] = np.array([])
while adf11['input_file']['dens_grid'].size <adf11['input_file']['num_dens']:
adf11['input_file']['dens_grid'] = np.append(adf11['input_file']['dens_grid'],np.array(list(map(float,re.findall('(.\d*\.\d+)',f.readline())))))
#read in the temperature grid
adf11['input_file']['temp_grid'] = np.array([])
while adf11['input_file']['temp_grid'].size <adf11['input_file']['num_temp']:
adf11['input_file']['temp_grid'] = np.append(adf11['input_file']['temp_grid'],np.array(list(map(float,re.findall('(.\d*\.\d+)',f.readline())))))

#setting up the GCR stages
if(adf11['input_file']['nuc_charge'] == len(adf11['input_file']['metas'])-1):
num_stages = adf11['input_file']['nuc_charge']
else:
num_stages = len(adf11['input_file']['metas'])
for i in range(0,num_stages):
adf11['input_file'][str(i)] = {}
if( 'scd' in fil or 'acd' in fil):
adf11['input_file'][str(i)] = np.zeros((adf11['input_file']['metas'][i],
adf11['input_file']['metas'][i+1],
len(adf11['input_file']['temp_grid']),
len(adf11['input_file']['dens_grid'])))
if( 'qcd' in fil ):
adf11['input_file'][str(i)] = np.zeros((adf11['input_file']['metas'][i],
adf11['input_file']['metas'][i],
len(adf11['input_file']['temp_grid']),
len(adf11['input_file']['dens_grid'])))
if('xcd' in fil):
adf11['input_file'][str(i)] = np.zeros((adf11['input_file']['metas'][i+1],
adf11['input_file']['metas'][i+1],
len(adf11['input_file']['temp_grid']),
len(adf11['input_file']['dens_grid'])))
if('plt' in fil):
adf11['input_file'][str(i)] = np.zeros((adf11['input_file']['metas'][i],
adf11['input_file']['metas'][i],
len(adf11['input_file']['temp_grid']),
len(adf11['input_file']['dens_grid'])))
if('prb' in fil):
adf11['input_file'][str(i)] = np.zeros((adf11['input_file']['metas'][i],
adf11['input_file']['metas'][i],
len(adf11['input_file']['temp_grid']),
len(adf11['input_file']['dens_grid'])))

#Reading the GCR value portion
gcr_line = f.readline()
ii = 0

while len(gcr_line.strip()) != 0 and 'C-' not in gcr_line:
#look for the stage identifying line
if('----------' in gcr_line):
dens_count = 0
temp_count = 0
stage_id = np.array(list(map(int,re.findall('(\d+ )',gcr_line))))
if('scd' in fil or 'acd' in fil):
if(len(stage_id) >1):
tmp = stage_id[0]
stage_id[0] = stage_id[1]
stage_id[1] = tmp
else:#this accounts for unresolved files that don't follow the convection of resolved files
tmp = stage_id[0]
stage_id = np.array([1,1,tmp])

ii = ii+1
else:
gcr_vals = np.array(list(map(float,re.findall(r'((?:-\d+|\d).\d+)',gcr_line))))#Si gcr has positive vals maybe other do to?
adf11['input_file'][str(stage_id[2]-1)][stage_id[0]-1,stage_id[1]-1,
temp_count,dens_count:dens_count+len(gcr_vals)] = gcr_vals
dens_count = dens_count + len(gcr_vals)
if(dens_count == len(adf11['input_file']['dens_grid'])):
temp_count = temp_count + 1
dens_count = 0
gcr_line = f.readline()
return adf11
import numpy as np
import re
from pathlib import Path


def read_adf11(fil):
""" Reads data formatted in adf11 format. This format is generally used for GCR coefficients.
The data is stored in arrays of log_10.
Creates a dictionary to hold the data
Args:
:param fil: The file path to the input file
:type fil: string
"""

path = Path(fil)
f = path.open()
adf11 = {}
adf11['input_file'] = {}

is_ascd = 'acd' in path.name or 'scd' in path.name
is_qcd = 'qcd' in path.name
is_xcd = 'xcd' in path.name
is_plt = 'plt' in path.name
is_prb = 'prb' in path.name

#reading the first line
tmp = re.findall('(\d+)',f.readline())
adf11['input_file']['nuc_charge'] = int(tmp[0])
adf11['input_file']['num_dens'] = int(tmp[1])
adf11['input_file']['num_temp'] = int(tmp[2])
adf11['input_file']['charge_min'] = int(tmp[3])
adf11['input_file']['charge_max'] = int(tmp[4])

f.readline() #reading '-------------'
if( 'r' in path.name):

adf11['input_file']['metas'] = np.array(list( #metastables
map(int,re.findall('(\d+)',f.readline()))))
f.readline() #reading '---------------'
else:
adf11['input_file']['metas'] = np.ones(adf11['input_file']['charge_max']+1,dtype='int')

#read in the density grid
adf11['input_file']['dens_grid'] = np.array([])
while adf11['input_file']['dens_grid'].size <adf11['input_file']['num_dens']:
adf11['input_file']['dens_grid'] = np.append(adf11['input_file']['dens_grid'],np.array(list(map(float,re.findall('(.\d*\.\d+)',f.readline())))))
#read in the temperature grid
adf11['input_file']['temp_grid'] = np.array([])
while adf11['input_file']['temp_grid'].size <adf11['input_file']['num_temp']:
adf11['input_file']['temp_grid'] = np.append(adf11['input_file']['temp_grid'],np.array(list(map(float,re.findall('(.\d*\.\d+)',f.readline())))))

#setting up the GCR stages
if(adf11['input_file']['nuc_charge'] == len(adf11['input_file']['metas'])-1):
num_stages = adf11['input_file']['nuc_charge']
else:
num_stages = len(adf11['input_file']['metas'])


for i in range(0,num_stages):
size_1 = size_2 = i
if is_ascd:
size_2 += 1
elif is_xcd:
size_1 += 1
size_2 += 1

adf11['input_file'][str(i)] = np.zeros((
adf11['input_file']['metas'][size_1],
adf11['input_file']['metas'][size_2],
len(adf11['input_file']['temp_grid']),
len(adf11['input_file']['dens_grid'])
))

#Reading the GCR value portion
gcr_line = f.readline()
ii = 0

while len(gcr_line.strip()) != 0 and 'C-' not in gcr_line:
#look for the stage identifying line
if('----------' in gcr_line):
dens_count = 0
temp_count = 0
stage_id = np.array(list(map(int,re.findall('(\d+ )',gcr_line))))
if is_ascd:
if(len(stage_id) >1):
tmp = stage_id[0]
stage_id[0] = stage_id[1]
stage_id[1] = tmp
else:#this accounts for unresolved files that don't follow the convection of resolved files
tmp = stage_id[0]
stage_id = np.array([1,1,tmp])

ii = ii+1
else:
gcr_vals = np.array(list(map(float,re.findall(r'((?:-\d+|\d).\d+)',gcr_line))))#Si gcr has positive vals maybe other do to?
adf11['input_file'][str(stage_id[2]-1)][stage_id[0]-1,stage_id[1]-1,
temp_count,dens_count:dens_count+len(gcr_vals)] = gcr_vals
dens_count = dens_count + len(gcr_vals)
if(dens_count == len(adf11['input_file']['dens_grid'])):
temp_count = temp_count + 1
dens_count = 0
gcr_line = f.readline()
return adf11