eta = float(json_variables['eta']) # volume fraction
sigma_r = float(json_variables['sigma_r']) # interface roughness
folder = json_variables['_base_directory'] # output folder dir
N_poly_integral = 9 # number of steps in polydispersity integral
## read checkboxes and related input
# the Json input for checkboxes only exists if boxes are checked
# therefore, I use try-except to import
try:
dummy = json_variables['exclude_overlap']
exclude_overlap = True
except:
exclude_overlap = False
## setup messaging in GUI
message = genapp(json_variables)
## read model parameters
Number_of_models = 5
model, a, b, c, p, x, y, z = [], [], [], [], [], [], [], []
for i in range(Number_of_models):
number = i + 1
model_name = 'model%d' % number
a_name = 'a%d' % number
b_name = 'b%d' % number
c_name = 'c%d' % number
p_name = 'p%d' % number
x_name = 'x%d' % number
y_name = 'y%d' % number
z_name = 'z%d' % number
model.append(json_variables[model_name])
tmp = '%s_pos_%d' % (model, i + 1)
pos = json_variables[tmp]
FIT += 1
except:
pass
except:
pass
# write model non-specific Json input to inputfile
f.write('%f %f %d\n' % (mean, sigma, FIT))
## close input file
f.close()
## messaging
d = genapp(json_variables)
## run bayesfit
d.udpmessage({"_textarea": "run bayesfit\n"})
def execute(command, f):
popen = subprocess.Popen(command, stdout=subprocess.PIPE, bufsize=1)
lines_iterator = iter(popen.stdout.readline, b"")
while popen.poll() is None:
for line in lines_iterator:
nline = line.rstrip()
nline_latin = nline.decode('latin')
out_line = '%s\n' % nline_latin
#print(nline.decode("latin"), end = "\r\n",flush =True) # yield line
d.udpmessage({"_textarea": out_line})
f.write(out_line)
