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import numpy as np
import os
import numpy as np
from .binSubfunctions import *
class ProcData:
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self.filename = filename
self.data = {}
self.nse_read_bin_data = {}
self.variable_names = ""
def __get_variable_names_plt(self):
with open(self.filename, "r") as file:
file_data = file.read().split('\n')
file.close()
names = [variable_name.replace(" ", "").replace('"' , "") for variable_name in file_data[1].split('=')[1].split(',')]
self.variable_names = np.array(names, dtype=object)
def __get_variable_names_bin(self):
f = open(self.filename,'rb')
_ = read_int(f)
_ = read_int(f)
ndims = read_int(f)
data_type_size = read_int(f)
if ndims == 1:
self.variable_names = ['I']
elif ndims == 2:
self.variable_names = ['I', 'J']
elif ndims == 3:
self.variable_names = ['I', 'J', 'K']
if data_type_size == 4:
read_float = read_float32
read_floats = read_floats32
float_type = np.float32
elif data_type_size == 8:
read_float = read_float64
read_floats = read_floats64
float_type = np.float64
else:
raise Exception(f"Unknown data_type value: {data_type_size}. Must be either 4 or 8.")
for _ in range(24):
read_float(f)
nx = read_int(f)
ny = read_int(f)
nz = read_int(f)
# skip gap; reserved for future usage
for _ in range(21):
read_int(f)
for _ in range(2):
read_floats(f, num=nx)
read_floats(f, num=ny)
read_floats(f, num=nz)
read_float(f)
field_type = read_int(f)
if field_type == 0:
nvars = 1
elif field_type == 1:
nvars = ndims
else:
raise Exception(f"Unknown field_type value: {field_type}. Must be either 0 or 1")
len_varnames = []
for _ in range(nvars):
len_varnames += [read_int(f)]
varnames = []
for nvar in range(nvars):
varnames += [read_str(f, length=len_varnames[nvar])]
self.variable_names += varnames
self.variable_names = np.array(self.variable_names, dtype=object)
def __read_plt(self, ndim):
with open(self.filename, "r") as file:
file_data = file.read().split('\n')
file.close()
I = int(file_data[2].split(',')[0].split('=')[1])
if ndim == 1:
var_begin = 1
J = 0
K = 0
elif ndim == 2:
var_begin = 2
J = int(file_data[2].split(',')[1].split('=')[1])
K = 0
elif ndim == 3:
var_begin = 3
J = int(file_data[2].split(',')[1].split('=')[1])
K = int(file_data[2].split(',')[2].split('=')[1])
file_data = np.loadtxt(self.filename, dtype = float, delimiter=' ', skiprows=3, unpack=False, ndmin=2, encoding='bytes')
file_data = file_data.T
if self.var == None:
column_names = [self.variable_names[i] for i in range(var_begin, len(self.variable_names))]
else:
column_names = self.var
if self.mval != None:
for col, abs_val in zip(column_names, self.mval):
check_variable_idx = np.where(self.variable_names == col)[0][0]
idx = np.where(np.abs(file_data[check_variable_idx]) > abs_val)[0]
file_data[check_variable_idx][idx] = np.nan
self.data[self.variable_names[0]] = file_data[0][0:I]
if ndim == 2:
self.data[self.variable_names[1]] = file_data[1][: : I]
elif ndim == 3:
self.data[self.variable_names[1]] = file_data[1][: : I]
self.data[self.variable_names[2]] = file_data[2][: : I * J]
i = 0
for name in self.variable_names[ndim : ]:
if ndim == 1:
self.data[name] = file_data[ndim + i]
elif ndim == 2:
self.data[name] = file_data[ndim + i].reshape( J, I )
elif ndim == 3:
self.data[name] = file_data[ndim + i].reshape( K, J, I )
i += 1
self.data['cx'] = I
self.data['cy'] = J
self.data['cz'] = K
def __read_bin(self):
f = open(self.filename,'rb')
fid = read_int(f)
grid_type = read_int(f)
ndims = read_int(f)
data_type_size = read_int(f)
if data_type_size == 4:
read_float = read_float32
read_floats = read_floats32
float_type = np.float32
elif data_type_size == 8:
read_float = read_float64
read_floats = read_floats64
float_type = np.float64
else:
raise Exception(f"Unknown data_type value: {data_type_size}. Must be either 4 or 8.")
x = read_float(f)
y = read_float(f)
z = read_float(f)
xdomainsize = read_float(f)
ydomainsize = read_float(f)
zdomainsize = read_float(f)
# skip gap; reserved for future usage
for _ in range(18):
read_float(f)
nx = read_int(f)
ny = read_int(f)
nz = read_int(f)
if ndims < 3:
nz = 0
if ndims < 2:
ny = 0
dimsizes = ([nx, ny, nz])[0:ndims]
gcx = read_int(f)
gcy = read_int(f)
gcz = read_int(f)
# skip gap; reserved for future usage
for _ in range(18):
read_int(f)
cx = read_floats(f, num=nx)
cy = read_floats(f, num=ny)
cz = read_floats(f, num=nz)
ex = read_floats(f, num=nx)
ey = read_floats(f, num=ny)
ez = read_floats(f, num=nz)
time = read_float(f)
field_type = read_int(f)
if field_type == 0:
nvars = 1
elif field_type == 1:
nvars = ndims
else:
raise Exception(f"Unknown field_type value: {field_type}. Must be either 0 or 1")
len_varnames = []
for _ in range(nvars):
len_varnames += [read_int(f)]
varnames = []
for nvar in range(nvars):
varnames += [read_str(f, length=len_varnames[nvar])]
values = np.fromfile(f, dtype=float_type, count=np.prod(dimsizes)).reshape(dimsizes + [1])
for nvar in range(1,nvars):
vadd = np.fromfile(f, dtype=float_type, count=np.prod(dimsizes)).reshape(dimsizes + [1])
values = np.concatenate((values, vadd), axis=-1)
f.close()
I = nx - 2 * gcx
J = ny - 2 * gcy
K = nz - 2 * gcz
self.data['cx'] = I
self.data['cy'] = J
self.data['cz'] = K
self.variable_names = ['I', 'J', 'K']
for i in range(nvars):
self.variable_names.append(varnames[i][0])
self.data['I'] = cx[gcx:nx - gcx]
self.data['J'] = cy[gcy:ny - gcy]
self.data['K'] = cz[gcz:nz - gcz]
values = values.T
for i in range(ndims, ndims + nvars):
print(values[:, :, :, i - ndims].shape)
self.data[self.variable_names[i]] = values[i - ndims, gcz:nz - gcz, gcy:ny - gcy, gcx:nx - gcx]
if ndims == 1:
var_begin = 1
elif ndims == 2:
var_begin = 2
elif ndims == 3:
var_begin = 3
if self.var == None:
column_names = [self.variable_names[i] for i in range(var_begin, len(self.variable_names))]
else:
column_names = self.var
if self.mval != None:
# print(self.mval)
for col, abs_val in zip(column_names, self.mval):
idx = np.where(np.abs(self.data[col]) > abs_val)
self.data[col][idx] = np.nan
def process_file(self, ndim, column_names, mval):
filename_parts = os.path.splitext(self.filename)
filename_extension = filename_parts[-1]
self.var = column_names
self.mval = mval
if filename_extension == '.plt':
self.__read_plt(ndim)
elif filename_extension == '.nsx':
self.__read_bin()
def get_variable_names(self):
filename_parts = os.path.splitext(self.filename)
filename_extension = filename_parts[-1]
if filename_extension == '.plt':
self.__get_variable_names_plt()
elif filename_extension == '.nsx':
self.__get_variable_names_bin()