# -*- coding: Latin-1 -*-

## Modules <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<#

import numpy as np

from numpy import pi, sqrt

np.set_printoptions(6,suppress=True,sign="+",floatmode="fixed")

import matplotlib.pyplot as plt

import matplotlib as mpl

from matplotlib.ticker import MultipleLocator, FormatStrFormatter

from package_kxy.bands_functions import *

import time

##>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>#

## Parameters :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::#

J = 1

B = 0.01 * J

D = 0.01 * J

resolution_k = 100

T_array = np.arange(0.02, 1.3, 0.01)[::-1]

# Initial parameters for root algorithm :::::::::::::::::::::::::::::::::::::::#

chi_up_ini = -0.38

chi_dn_ini = -0.37

## ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::#

# Contains the hexago volume in a rectangle of side pi x (2*pi/sqrt(3))

kx = np.linspace(-pi / 3, 2 * pi / 3, resolution_k)

ky = np.linspace(-pi / sqrt(3), pi / sqrt(3), resolution_k)

kxx, kyy = np.meshgrid(kx, ky, indexing = 'ij')

## ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::#

## Initialize guessed values for root function ##

ts_up_ini = compute_ts(chi_up_ini, chi_dn_ini, J, D, 1)

ts_dn_ini = compute_ts(chi_up_ini, chi_dn_ini, J, D, -1)

la_min_up = diag_func(kxx, kyy, la = 0, s = 1, B = B, ts = ts_up_ini)[-1]

la_min_dn = diag_func(kxx, kyy, la = 0, s = -1, B = B, ts = ts_dn_ini)[-1]

la_min = np.max([la_min_up, la_min_dn]) # prevent from having negative eigen values in the root algorithm

## ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::#

## Compute Kxy ##

kxy_array = np.empty(T_array.shape)

la_array = np.empty(T_array.shape)

chi_up_array = np.empty(T_array.shape)

chi_dn_array = np.empty(T_array.shape)

B_array = np.ones(T_array.shape) * B

J_array = np.ones(T_array.shape) * J

D_array = np.ones(T_array.shape) * D

res_array = np.ones(T_array.shape) * resolution_k

for i, t in enumerate(T_array):

start_time_kxy = time.time()

kxy, la, chi_up, chi_dn = kxy_algorithm(kxx, kyy, B, D, J, t, la_min, chi_up_ini, chi_dn_ini)[:-2]

(la_min, chi_up_ini, chi_dn_ini) = (la, chi_up, chi_dn) # change the initial values for next T

kxy_array[i] = kxy

la_array[i] = la

chi_up_array[i] = chi_up

chi_dn_array[i] = chi_dn

print("One value kxy time : %.6s seconds" % (time.time() - start_time_kxy))

## Save Data >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>#

Data = np.vstack((T_array/J, B_array, kxy_array, la_array, chi_up_array, chi_dn_array, J_array, D_array, res_array))

Data = Data.transpose()

folder = "../data_sim/"

file_name = "TS-kxy" + "_B_" + str(B) + "_J_" + str(J) + "_D_" + str(D) + "_res_" + str(resolution_k) + ".dat"

np.savetxt(folder + file_name, Data, fmt='%.7e', header = "T/J\tB\tkxy\tla\tchi_up\tchi_dn\tJ\tD\tresolution_k", comments = "#")

#<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<#

# Figures PRINT ///////////////////////////////////////////////////////////////#

#>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>#

#///// RC Parameters //////#

mpl.rcdefaults()

mpl.rcParams['font.size'] = 24. # change the size of the font in every figure

mpl.rcParams['font.family'] = 'Arial' # font Arial in every figure

mpl.rcParams['axes.labelsize'] = 24.

mpl.rcParams['xtick.labelsize'] = 24

mpl.rcParams['ytick.labelsize'] = 24

mpl.rcParams['xtick.direction'] = "in"

mpl.rcParams['ytick.direction'] = "in"

mpl.rcParams['xtick.top'] = True

mpl.rcParams['ytick.right'] = True

mpl.rcParams['xtick.major.width'] = 0.6

mpl.rcParams['ytick.major.width'] = 0.6

mpl.rcParams['axes.linewidth'] = 0.6 # thickness of the axes lines

mpl.rcParams['pdf.fonttype'] = 3 # Output Type 3 (Type3) or Type 42 (TrueType), TrueType allows

# editing the text in illustrator

#>>>> Kxy vs T >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>#

fig, axes = plt.subplots(1, 1, figsize = (9.2, 5.6)) # (1,1) means one plot, and figsize is w x h in inch of figure

fig.subplots_adjust(left = 0.18, right = 0.82, bottom = 0.18, top = 0.95) # adjust the box of axes regarding the figure size

axes.axhline(y = 0, ls ="--", c ="k", linewidth = 0.6)

#///// Allow to shift the label ticks up or down with set_pad /////#

for tick in axes.xaxis.get_major_ticks():

tick.set_pad(7)

for tick in axes.yaxis.get_major_ticks():

tick.set_pad(8)

#///// Labels //////#

fig.text(0.84, 0.86, r"$B$ = " + str(B))

fig.text(0.84, 0.79, r"$J$ = " + str(J))

fig.text(0.84, 0.72, r"$D$ = " + str(D))

color = '#29FB87'

line = axes.plot(T_array / J, kxy_array / T_array)

plt.setp(line, ls ="-", c = color, lw = 3, marker = "", mfc = 'k', ms = 8, mec = "#7E2320", mew= 2) # set properties

axes.set_xlim(0, None) # limit for xaxis

axes.set_ylim(None, 0) # leave the ymax auto, but fix ymin

axes.set_xlabel(r"$k_{\rm B}T$ / $J$", labelpad = 8)

axes.set_ylabel(r"$\kappa_{\rm xy}$ / $T$", labelpad = 8)

##///Set ticks space and minor ticks space ///#

xtics = 0.3 # space between two ticks

mxtics = xtics / 2. # space between two minor ticks

majorFormatter = FormatStrFormatter('%g') # put the format of the number of ticks

axes.xaxis.set_major_locator(MultipleLocator(xtics))

axes.xaxis.set_major_formatter(majorFormatter)

axes.xaxis.set_minor_locator(MultipleLocator(mxtics))

axes.yaxis.set_major_formatter(FormatStrFormatter('%.3f'))

axes.locator_params(axis = 'y', nbins = 6)

plt.show()

folder = "../figures_sim/"

figure_name = "TS-kxy" + "_B_" + str(B) + "_J_" + str(J) + "_D_" + str(D) + "_res_" + str(resolution_k) + ".pdf"

fig.savefig(folder + figure_name, bbox_inches = "tight")

#//////////////////////////////////////////////////////////////////////////////#