def LoadSimFile( data_file, gal_num):
print(data_file)
gal_file = open(data_file, "r")
temp_var = np.zeros(SIZE_GAL_FILE)
for index, line in enumerate(gal_file):
values = line.split(' ')
if local_gal_wl[-1] == 0:
local_gal_wl[index] = float(values[0])
temp_var[index] = float(values[FILE_SECOND_COLUMN])
localgalaxy_numbers[gal_num] = int(B.get_number(data_file))
gal_file.close()
temp_var = temp_var * (local_gal_wl*local_gal_wl)/speed_of_light
#Luminosity per frequency
temp_var = temp_var/(4*math.pi*dist_base_2)
#Luminosity to Flux
#print(new_value)
temp_var = temp_var * 1e32
#Flux in microJanksys
#print(new_value)
#print localgalaxy_file_data.shape
#print temp_var.shape
#print localgalaxy_file_data[gal_num].shape
#print localgalaxy_file_data[gal_num,:].shape
localgalaxy_file_data[gal_num,:]= 23.9 - 2.5 * np.log10(temp_var[:])
def LoadSimFiles():
print("Loading Simulation Files")
data_files = glob.glob(data_folder+"/"+ "*.txt")
for i in range(len(data_files)):
print(data_files[i])
gal_file = open(data_files[i], "r")
index = 0
for line in gal_file:
values = line.split(' ')
if i == 0:
gal_wl[index] = float(values[0])
galaxy_file_data[i][index] = float(values[1])
index+=1
galaxy_numbers[i] = B.get_number(data_files[i])
gal_file.close()
def LoadFiles():
print("Loading Input Files")
doNotAdd = False #For files with problems in the values
for i in range(len(input_file_names)):
print(input_file_names[i])
data = {"red": -1 }
#data dictionary redshift - red
#wavelengths -wl ; flux - fl; error - err
input_file = open(input_file_names[i], "r")
redshift = -1
temp_wl = []
temp_fl = []
temp_err = []
for line in input_file:
values = line.split(' ')
if data['red'] ==-1:
data['red'] = float(values[0])
#Redshift is the first value of the file
else:
if (len(values) ==3 and float(values[1]) >0 and float(values[2]) > 0):
temp_wl.append( float(values[0])/(1+data['red']))
temp_fl.append( float(values[1]))
temp_err.append( float(values[2]))
elif len(temp_fl)>1 and temp_fl[-1] <= 0:
print(values)
doNotAdd = True
if doNotAdd == False:
data['wl'] = np.array(temp_wl)
data['fl'] = np.array(temp_fl)
data['err'] = np.array(temp_err)
data['num'] = B.get_number(input_file_names[i])
input_files_data.append(data)
input_file.close()
def Comp(file_name, have_wl):
data_comp_file = open(file_name, "r")
data_comp = []
for line in data_comp_file:
values = line.split(' ')
if not have_wl:
data_comp_wl.append( float( values[0]))
#print("FILE WL Added: " +str(data_comp_wl[-1]) )
data_comp.append( float(values[1]))
if have_wl == False:
size_comp_wl = len(data_comp_wl)
have_wl = True
#STAR COMPARISON
for k in range(len(input_files_data)):
#For each file do a comparison
#print(k, " ", input_file_names[k])
chi_2 = 0
index = 0
int_comp = 0
#VECTORIZATION OF DATA # NEEDS WORK (A LOT)
file_data_fl = np.zeros(np.shape(input_files_data[k]['wl'])[0])
for i in range(np.shape(input_files_data[k]['wl'])[0]):
while input_files_data[k]['wl'][i] < data_comp_wl[0]:
i+=1
print("DATA WL TOO SMALL")
#we do not have information to calculate these so we skip
if input_files_data[k]['wl'][i] > data_comp_wl[-1]:
i = np.shape(input_files_data[k]['wl'])[0]
print("DATA WL TOO BIG")
break
# we can stop the loop here since the data points cannot be compared
while (index + 1) < size_comp_wl and data_comp_wl[index +1] <= input_files_data[k]['wl'][i]:
index+=1
#choose the correct index to make the comparison
file_data_fl[i] = (data_comp[index+1]-data_comp[index])/(data_comp_wl[index+1] - data_comp_wl[index])*(input_files_data[k]['wl'][i] - data_comp_wl[index]) + data_comp[index]
int_comp +=1
#print(input_files_data[k]['wl'][i], " " , input_files_data[k]['fl'][i], " " , file_data_fl[i])
chi_2 = np.sum( (input_files_data[k]['fl'] - file_data_fl)**2/input_files_data[k]['err'])
try:
chi_2 /= int_comp #normalizes the chi_2 by the number of comparisons
except:
print(int_comp)
if int_comp != np.shape(input_files_data[k]['fl'])[0]:
print("ERRROR NOT ALL COMPARED")
factor = np.exp(-chi_2)
cumu[k] += factor
#print(str(B.get_number(file_name)))
#print( "MASS: ",prop[str(B.get_number(file_name))][0])
cumu_mass[k] += factor * prop[str(B.get_number(file_name))][0]
#print( "MET: ",prop[str(B.get_number(file_name))][1])
cumu_met[k] += factor * prop[str(B.get_number(file_name))][1]
data_comp_file.close()
for i in np.arange(nGal): #range(len(global_prop)):
# print i
# print 'this string is '+str(int(global_prop[0][i]))
prop[str(int(global_prop[0][i]))] = [global_prop[1][i], global_prop[2][i]]
print("BEGIN COMPARISON")
for i in range(len(input_file_names)):
if (i%n_tasks) == rank:
res = Comp(input_file_names[i])
if res == -1: ## Error in running
continue
else:
numb = int(B.get_number(input_file_names[i]))
local_results[0][i] = numb
local_results[1][i] = res[0]
local_results[2][i] = res[1]
#comm.Barrier()
global_results = local_results #comm.Allreduce(local_results, global_results, op=MPI.SUM)
if rank == 0:
result = open(result_folder + "results.out", "w")
for i in np.arange(len(global_results[0])):
result.write(str(int(global_results[0][i])) + " " + str(global_results[1][i]) + " " + str(global_results[2][i]) + "\n")
print("SUCCESS")
#print( "MASS: ",prop[str(B.get_number(file_name))][0])
cumu_mass += factor * prop[str(int(galaxy_numbers[k]))][0]
#print( "MET: ",prop[str(B.get_number(file_name))][1])
cumu_met += factor * prop[str(int(galaxy_numbers[k]))][1]
return (cumu_mass/cumu, cumu_met/cumu)
###################################################################
#
# Run Code
#
###################################################################
loadProperties()
LoadSimFiles()
results = open(result_folder + "results.out", 'w')
for i in range(len(input_file_names)):
p = Comp(input_file_names[i])
if p == -1:
continue
else:
name = B.get_number(input_file_names[i])
results.write(str(name) + " " +str(p[0]) + " " + str(p[1]) + "\n")
results.close()
#Redshift is the first value of the file
else:
if (len(values) ==3 and float(values[1]) >0 and float(values[2]) > 0):
temp_wl.append( float(values[0])/(1+data['red']))
temp_fl.append( float(values[1]))
temp_err.append( float(values[2]))
elif len(temp_fl)>1 and temp_fl[-1] <= 0:
print(values)
doNotAdd = True
if doNotAdd == False:
data['wl'] = np.array(temp_wl)
data['fl'] = np.array(temp_fl)
data['err'] = np.array(temp_err)
data['num'] = B.get_number(input_file_names[i])
input_files_data.append(data)
input_file.close()
###################################################################
#
# TRANSFORM INTO ABSOLUTE MAGNITUDES
#
###################################################################
print("Formating input data to correct units")
for k in range(len(input_files_data)):
dist = (cosmocalc.cosmocalc( input_files_data[k]['red'], H0=70.4, WM=0.2726, WV=0.7274))['DL_Mpc']
