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import numpy as np
import matplotlib.pyplot as plt
import os
import sys
import shutil
import natsort
import imageio
from .ProcData import ProcData
import copy
class Plotter:
ani_pngs_dir = "plotter_lib_pngs/"
def __init__(self):
self.filename = ""
self.out = ""
self.oname = ""
self.var = ""
self.mval = ""
self.function = ""
self.variable_names = ""
def __check_arg_dim_equiv(self, args):
if args.var != None and args.mval != None:
if len(args.var) != len(args.mval):
print("The count of var assumed to be equal to the count of mval")
sys.exit(-1)
def __get_variable_names(self):
var_names = []
for d in self.data:
names = d.variable_names
var_names.append(np.array(names, dtype=object))
if(len(var_names) > 1):
for i in range(1, len(var_names)):
if np.equal(var_names[0], var_names[i]).any() != True:
print("All files must have the same variable names")
sys.exit(-1)
elif len(var_names) == 0:
print("Undefined variable names")
sys.exit(-1)
self.variable_names = var_names[0]
def set(self, args, **kwargs):
self.__check_arg_dim_equiv(args)
self.filename = args.filename
pData = []
for fname in self.filename:
p = ProcData(fname)
p.get_variable_names()
pData.append(p)
self.data = copy.deepcopy(pData)
self.__get_variable_names()
if args.func != self.dump:
self.out = args.out
self.oname = args.oname
self.var = args.var
self.mval = args.mval
self.function = args.func
self.if_manual_plot = kwargs.get('if_manual_plot', False)
self.if_save_result = kwargs.get('if_save_result', True)
if args.func == self.plot or args.func == self.ani_plot:
ndim = 1
if self.var == None and len(self.variable_names) != 0:
self.var = [self.variable_names[i] for i in range(ndim, len(self.variable_names))]
for p in self.data:
p.process_file(ndim, self.var, self.mval)
elif args.func == self.plot_contour or args.func == self.ani_plot_contour:
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ndim = 2
if self.var == None and len(self.variable_names) != 0:
self.var = [self.variable_names[i] for i in range(ndim, len(self.variable_names))]
for p in self.data:
p.process_file(ndim, self.var, self.mval)
elif args.func == self.avg_plot:
ndim = 3
if self.var == None and len(self.variable_names) != 0:
self.var = [self.variable_names[i] for i in range(ndim, len(self.variable_names))]
for p in self.data:
p.process_file(ndim, self.var, self.mval)
if self.var == None:
self.fig_count = len(self.variable_names) - ndim
else:
self.fig_count = len(self.var)
def __plot_plt(self):
os.system("mkdir -p " + self.out)
x_name = self.variable_names[0]
fig = plt.figure()
for y_name in self.var:
plt.plot(self.data[0].data[x_name], self.data[0].data[y_name], linewidth=4)
plt.legend(self.var)
plt.xlabel(x_name, fontsize=10, fontweight='bold')
if self.if_manual_plot: plt.show()
else: plt.close(fig)
if self.if_save_result: fig.savefig(self.out + self.oname[0])
def __ani_plot(self):
if self.if_save_result:
png_names = []
os.system("mkdir -p " + self.out)
os.system("mkdir -p " + self.ani_pngs_dir)
names = natsort.natsorted(self.filename,reverse=False)
x_name = self.variable_names[0]
data_i = 0
for datafile in names:
fig = plt.figure()
for y_name in self.var:
plt.plot(self.data[data_i].data[x_name], self.data[data_i].data[y_name], linewidth=4)
plt.legend(self.var)
plt.xlabel(x_name, fontsize=10, fontweight='bold')
figname = os.path.basename(datafile)
plt.close(fig)
fig.savefig(self.ani_pngs_dir + figname.split('.')[0] + '.png')
name = self.ani_pngs_dir + figname.split('.')[0] + '.png'
png_names.append(name)
data_i = data_i + 1
images = []
for file_name in png_names:
images.append(imageio.v2.imread(file_name))
imageio.mimsave(self.oname[0], images, fps = 5)
shutil.rmtree(self.ani_pngs_dir)
def __plot_contour(self):
os.system("mkdir -p " + self.out)
x_name = self.variable_names[0]
y_name = self.variable_names[1]
if self.oname == None:
fig_names = self.var
fig_end = ".png"
else:
fig_names = self.oname
fig_end = ""
for i in range(self.fig_count):
fig,ax=plt.subplots(1,1)
title = self.var[i]
X = self.data[0].data[x_name]
Y = self.data[0].data[y_name]
Z = self.data[0].data[self.var[i]]
cp = ax.contourf(X, Y, Z)
fig.colorbar(cp) # Add a colorbar to a plot
ax.set_title(title)
ax.set_xlabel(x_name)
ax.set_ylabel(y_name)
if self.if_manual_plot: plt.show()
else: plt.close(fig)
if self.if_save_result: fig.savefig(self.out + fig_names[i] + fig_end)
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def __get_min_max_bar(self):
self.filename = natsort.natsorted(self.filename,reverse=False)
self.vals = {var : [] for var in self.var}
for var in self.var:
max_val = -1e9
min_val = 1e9
for data in self.data:
maval = np.max(data.data[var])
mival = np.min(data.data[var])
if maval > max_val:
max_val = maval
if mival < min_val:
min_val = mival
self.vals[var] = np.array([min_val, max_val])
def __ani_plot_contour(self):
if self.if_save_result:
# png_names = {var:[] for var in self.var}
os.system("mkdir -p " + self.out)
os.system("mkdir -p " + self.ani_pngs_dir)
x_name = self.variable_names[0]
y_name = self.variable_names[1]
if self.oname == None:
fig_names = self.var
fig_end = ".gif"
else:
fig_names = self.oname
fig_end = ""
X = self.data[0].data[x_name]
Y = self.data[0].data[y_name]
i = 0
for var in self.var:
title = var
counter = 0
png_names = []
for data in self.data:
fig,ax=plt.subplots(1,1)
ax.set_title(title)
ax.set_xlabel(x_name)
ax.set_ylabel(y_name)
Z = data.data[var]
cp = ax.contourf(X, Y, Z, vmin=self.vals[var][0], vmax=self.vals[var][1])
fig.colorbar(cp) # Add a colorbar to a plot
plt.close(fig)
figname = var + str(counter)
fig.savefig(self.ani_pngs_dir + figname + '.png')
name = self.ani_pngs_dir + figname + '.png'
png_names.append(name)
counter += 1
images = []
for file_name in png_names:
images.append(imageio.v2.imread(file_name))
imageio.mimsave(self.out + fig_names[i] + fig_end, images, duration = 5, )
i += 1
shutil.rmtree(self.ani_pngs_dir)
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def __avg(self, data, var_name):
cx = data['cx']
cy = data['cy']
cz = data['cz']
flat_matrix_data = np.zeros((cx * cy * cz))
flat_data = data[var_name].flatten()
for k in range(cz):
for j in range(cy):
for i in range(cx):
flat_matrix_data[k * cy * cx + j * cx + i] = flat_data[k * cy * cx + j * cx + i]
matrix_data = np.reshape(flat_matrix_data, (cx, cy, cz), order='F')
avg_data = np.average(matrix_data, axis=(1, 0))
return avg_data
def __avg_plot(self):
os.system("mkdir -p " + self.out)
fig = plt.figure()
x_name = self.variable_names[2]
x = self.data[0].data[x_name]
for var in self.var:
avg_data = self.__avg(self.data[0].data, var)
plt.plot(x, avg_data, linewidth=4)
plt.legend(self.var)
plt.xlabel(x_name, fontsize=10, fontweight='bold')
if self.if_manual_plot: plt.show()
else: plt.close(fig)
if self.if_save_result: fig.savefig(self.out + self.oname[0])
def __dump(self):
for variable_name in self.variable_names:
print(variable_name, end=' ')
print('\n')
def __plot_diff(self):
if self.data[0].data.shape != self.data[1].data.shape:
print("Data dimensions do not match")
sys.exit(-1)
diff = {}
diff[self.var] = self.data[0][self.var] - self.data[1][self.var]
dim_variables = list(set(self.variable_names) - set(self.var))
def dump(self):
self.__dump()
def plot(self):
self.__plot_plt()
def ani_plot(self):
self.__ani_plot()
def avg_plot(self):
self.__avg_plot()
def plot_contour(self):
self.__plot_contour()
def ani_plot_contour(self):
self.__get_min_max_bar()