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import numpy as np
import matplotlib.pyplot as plt
import sympy as sym
import math
import os
import subprocess
import fileinput
import re
import matlab.engine
from HelperFunctions import *
from ClassifyMin import *
import matplotlib.ticker as tickers
import matplotlib as mpl
from matplotlib.ticker import MultipleLocator,FormatStrFormatter,MaxNLocator
import pandas as pd
def format_func(value, tick_number):
# # find number of multiples of pi/2
# N = int(np.round(2 * value / np.pi))
# if N == 0:
# return "0"
# elif N == 1:
# return r"$\pi/2$"
# elif N == 2:
# return r"$\pi$"
# elif N % 2 > 0:
# return r"${0}\pi/2$".format(N)
# else:
# return r"${0}\pi$".format(N // 2)
# find number of multiples of pi/2
N = int(np.round(4 * value / np.pi))
if N == 0:
return "0"
elif N == 1:
return r"$\pi/4$"
elif N == 2:
return r"$\pi/2$"
elif N % 2 > 0:
return r"${0}\pi/2$".format(N)
else:
return r"${0}\pi$".format(N // 2)
def find_nearest(array, value):
array = np.asarray(array)
idx = (np.abs(array - value)).argmin()
return array[idx]
def find_nearestIdx(array, value):
array = np.asarray(array)
idx = (np.abs(array - value)).argmin()
return idx
# ----- Setup Paths -----
# InputFile = "/inputs/cellsolver.parset"
# OutputFile = "/outputs/output.txt"
InputFile = "/inputs/computeMuGamma.parset"
OutputFile = "/outputs/outputMuGamma.txt"
# --------- Run from src folder:
path_parent = os.path.dirname(os.getcwd())
os.chdir(path_parent)
path = os.getcwd()
print(path)
InputFilePath = os.getcwd()+InputFile
OutputFilePath = os.getcwd()+OutputFile
print("InputFilepath: ", InputFilePath)
print("OutputFilepath: ", OutputFilePath)
print("Path: ", path)
#---------------------------------------------------------------
print('---- Input parameters: -----')
mu1 = 1.0 #10.0
rho1 = 1.0
lambda1 = 0.0
# # INTERESTING!:
# alpha = 3
beta = 2.0
# theta= 1/8
# alpha = 2.0
theta = 0.5
beta = 10.0
#TEST
# beta=2
plot_curvature = True
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gamma = 'infinity' #Elliptic Setting
gamma = '0' #Hyperbolic Setting
Gamma_Values = [0.5, 0.75, 1.5, 3.0]
Gamma_Values = [3.0]
Gamma_Values = ['0', 'infinity','infinity','infinity','infinity','infinity']
Gamma_Values = ['0', 0.5, 0.75, 1.5,3.0, 'infinity']
Gamma_Values = ['0', 0.5, 0.75, 1.0, 1.5, 'infinity']
# Gamma_Values = ['0',0.25, 0.5, 0.75, 1.5, 'infinity']
print('(Input) Gamma_Values:', Gamma_Values)
# --- define Interval of x-va1ues:
xmin = -2.0
# xmax = 0.41
xmax = 3.0
# xmin = -1.5
# xmax = 2.0
# xmin = -1.0
# xmax = -0.5
# xmin = -2.0
# xmin = -1.0
# xmax = 1.0
#
# xmin = -1.25
xmin = -1.5
xmax = 1.0
xmin = -1.25
xmax = 1.25
numPoints = 2000
numPoints = 300
numPoints = 500
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X_Values = np.linspace(xmin, xmax, num=numPoints)
X_Values = np.array(X_Values)
print(X_Values)
Angle_Container = []
for gamma in Gamma_Values: # COMPUTE DATA
print('mu1: ', mu1)
print('rho1: ', rho1)
# print('alpha: ', alpha)
print('beta: ', beta)
print('theta: ', theta)
print('gamma:', gamma)
print('----------------------------')
tmp_Container = []
for alpha in X_Values:
print('Situation of Lemma1.4')
q12 = 0.0
q3 = GetMuGamma(beta,theta,gamma,mu1,rho1,InputFilePath ,OutputFilePath)
G, angle, Type, curvature = classifyMin_ana(alpha,beta,theta, q3, mu1, rho1)
if plot_curvature:
tmp_Container.append(curvature)
else:
tmp_Container.append(angle)
tmp_Container = np.array(tmp_Container) #convert the np array
Angle_Container.append(tmp_Container)
##########################################################
# ---------------- CREATE PLOT -------------------
# Styling
plt.style.use("seaborn-darkgrid")
# plt.style.use("seaborn-whitegrid")
plt.style.use("seaborn")
# plt.style.use("seaborn-darkgrid")
mpl.rcParams['text.usetex'] = True
mpl.rcParams["font.family"] = "serif"
mpl.rcParams["font.size"] = "10"
# mpl.rcParams['xtick.labelsize'] = 16mpl.rcParams['xtick.major.size'] = 2.5
# mpl.rcParams['xtick.bottom'] = True
# mpl.rcParams['ticks'] = True
mpl.rcParams['xtick.bottom'] = True
mpl.rcParams['xtick.major.size'] = 3
mpl.rcParams['xtick.minor.size'] = 1.5
mpl.rcParams['xtick.major.width'] = 0.75
mpl.rcParams['ytick.left'] = True
mpl.rcParams['ytick.major.size'] = 3
mpl.rcParams['ytick.minor.size'] = 0
mpl.rcParams['ytick.major.width'] = 0.75
mpl.rcParams.update({'font.size': 10})
mpl.rcParams['axes.labelpad'] = 0
#---- Scale Figure apropriately to fit tex-File Width
# width = 452.9679
# width as measured in inkscape
# width = 6.28 *0.5
# width = 6.28 *0.333
width = 6.28
height = width / 1.618
#setup canvas first
fig = plt.figure()
# ax = plt.axes((0.25,0.28,0.6,0.6))
#
# ax.tick_params(axis='x',which='major', direction='out',pad=3)
# ax.tick_params(axis='y',which='major', length=3, width=1, direction='out',pad=3)
gs = fig.add_gridspec(nrows=2,ncols=3, hspace=0.25, wspace=0.25)
ax4 = fig.add_subplot(gs[1, 0])
ax5 = fig.add_subplot(gs[1, 1],sharey=ax4)
ax6 = fig.add_subplot(gs[1, 2],sharey=ax4)
plt.setp(ax5.get_yticklabels(), visible=False)
plt.setp(ax6.get_yticklabels(), visible=False)
ax1 = fig.add_subplot(gs[0, 0],sharex=ax4)
ax2 = fig.add_subplot(gs[0, 1],sharey=ax1)
ax3 = fig.add_subplot(gs[0, 2],sharey=ax1)
plt.setp(ax1.get_xticklabels(), visible=False)
plt.setp(ax2.get_xticklabels(), visible=False)
plt.setp(ax3.get_xticklabels(), visible=False)
plt.setp(ax2.get_yticklabels(), visible=False)
plt.setp(ax3.get_yticklabels(), visible=False)
ax = [ax1, ax2,ax3,ax4,ax5,ax6]
print('ax:', ax)
print('ax[0]:', ax[0])
for i in range(len(ax)):
print('i=',i)
gamma = Gamma_Values[i]
# TITLE
if gamma == '0':
Title = r'$0< \gamma \ll 1$'
# ax.set_title(Title)
elif gamma == 'infinity':
# print('THIS CASE')
Title = r'$\gamma \gg 1$'
# ax.set_title(Title)
else:
Title = r'$ \gamma =$' + str(gamma)
ax[i].set_title(Title,pad=5)
# ax[i].xaxis.set_major_locator(MultipleLocator(0.25))
# ax[i].xaxis.set_minor_locator(MultipleLocator(0.125))
ax[i].xaxis.set_major_locator(MultipleLocator(1.0))
ax[i].xaxis.set_minor_locator(MultipleLocator(0.5))
# ax[i].xaxis.set_major_locator(MultipleLocator(0.5))
# ax[i].xaxis.set_minor_locator(MultipleLocator(0.25))
#---- print data-types
print(ax[i].xaxis.get_major_locator())
print(ax[i].xaxis.get_minor_locator())
print(ax[i].xaxis.get_major_formatter())
print(ax[i].xaxis.get_minor_formatter())
#----- Fancy Tick Formats
if plot_curvature == False:
ax[i].yaxis.set_major_locator(plt.MultipleLocator(np.pi / 4))
ax[i].yaxis.set_minor_locator(plt.MultipleLocator(np.pi / 12))
ax[i].yaxis.set_major_formatter(plt.FuncFormatter(format_func))
a=ax[i].yaxis.get_major_locator()
b=ax[i].yaxis.get_major_formatter()
c = ax[i].get_xticks()
d = ax[i].get_xticklabels()
# ax[i].set_xticks([0, np.pi/8, np.pi/4, 3*np.pi/8 , np.pi/2])
# print('xticks:',c)
# print('xticklabels:',d)
ax[i].grid(True,which='major',axis='both',alpha=0.3)
# ax[i].set_xlabel(r"$\theta_\rho$",labelpad=0)
# ax[i].set_ylabel(r"$\alpha$")
# ax.set_ylabel(r"angle $\alpha$")
if plot_curvature:
line= ax[i].scatter(X_Values,Angle_Container[i], color='forestgreen', s=0.15 ,zorder=3, label=r"$\theta = 0.5$")
else:
line= ax[i].scatter(X_Values,Angle_Container[i], color='royalblue', s=0.15 ,zorder=3, label=r"$\theta = 0.5$")
if plot_curvature == False:
# ax[i].set_yticks([0, np.pi/8, np.pi/4, 3*np.pi/8 , np.pi/2, 5*np.pi/8 ])
ax[i].set_yticks([0, np.pi/8, np.pi/4, 3*np.pi/8 , np.pi/2])
labels = ['$0$',r'$\pi/8$', r'$\pi/4$' ,r'$3\pi/8$' , r'$\pi/2$',r'$5\pi/8$']
labels = ['$0$',r'$\pi/8$', r'$\pi/4$' ,r'$3\pi/8$' , r'$\pi/2$']
ax[i].set_ylim(0-0.1,np.pi/2+0.1)
ax[i].set_yticklabels(labels)
plt.subplots_adjust(wspace=1, hspace=1)
fig.subplots_adjust(bottom=0.15)
# fig.tight_layout()
fig.text(0.5, 0.04, r"$\theta_\rho$", ha='center')
if plot_curvature:
fig.text(0.03, 0.5, r"curvature $\kappa$", va='center', rotation='vertical')
pdf_outputName = 'Plot-Curv-Alpha_Gamma'+ str(gamma)+ '_transition'+'.pdf'
else:
fig.text(0.03, 0.5, r"angle $\alpha$", va='center', rotation='vertical')
pdf_outputName = 'Plot-Angle-Alpha_Gamma'+ str(gamma)+ '_transition'+'.pdf'
fig.set_size_inches(width, height)
fig.savefig(pdf_outputName)
plt.show()