import numpy as np
import matplotlib.pyplot as plt

def get_data(filename):
    file = open(filename)
    title = file.readline()
    lines = file.readlines()
    x = []
    y = []
    x_shift = []
    y_shift = []
    for line in lines:
        line.strip()
        data = line.split()
        if float(data[0])<=180:  
            x.append(float(data[0]))
            y.append(float(data[1]))
        else:
            x_shift.append(float(data[0])-360)
            y_shift.append(float(data[1]))
        
    return x_shift+x, y_shift+y

x_meas, y_meas = get_data('Python/Plotting/Base/Measured_P.txt')
x_sim, y_sim = get_data("Python/Plotting/Base/Simulated_P.txt")

for i in x_meas:
    print(i)
################################# BASIC PLOT CODE #################################

# Basic Styling
plt.rcParams.update({
    'font.family': 'Courier New',       # monospace font
    'font.size': 20,                    # Fonts
    'axes.titlesize': 20,               # |
    'axes.labelsize': 20,               # V
    'xtick.labelsize': 15,
    'ytick.labelsize': 15,
    'legend.fontsize': 15,
    'figure.titlesize': 20,
    'figure.figsize': [10,5]           # Figure Size
    })

# Figure Setup
fig, ax = plt.subplots()
title = 'Cylinder Pressure Trace'                              # Title
xlab = ''                               # X Label
ylab = 'Pressure [Bar]'                               # Y Label
ax.set_xlabel(xlab)
ax.set_ylabel(ylab)
ax.set_title(title, pad = 20) #pad controls distance to plot
ax.spines['top'].set_visible(False) # Controls non axis borders
ax.spines['right'].set_visible(False)

x_min = -180                               # Axis Limits and Ticks
x_max = 180
x_step_maj = 1  #steps not division
x_step_min = 1

y_min = 0
y_max = 36
y_step_maj = 5
y_step_min = 1

ax.set_xlim(x_min,x_max)                                        # X limits
ax.set_xticks([-180,-90,0,90,180],['BDC','Intake/Compression','TDC','Exhaust/Expansion','BDC'])                # X Major Ticks
ax.set_xticks([-180,-90,0,90,180], minor=True)    # X Minor Ticks

ax.set_ylim(y_min,y_max)                                        # Y limits
ax.set_yticks(np.arange(y_min,y_max,y_step_maj))                # Y Major Ticks
# ax.set_yticks(np.arange(y_min,y_max,y_step_min),minor=True)     # Y Minor Ticks


ax.grid(True, which='major',alpha=0.5)                      # Turn On Major Grid
ax.grid(True, which='minor',alpha=0.2)                      # Turn on Minor Grid
# alpha controls transparency

###################### Single Line ######################
# x = []
# y = []

# ax.plot(x,y,color='black',linestyle='-',linewidth='1')
# # Basic Line Styles: -, --, :, -.
# # Basic Colors: red, blue, green, purple, cyan, magenta, black, brown, etc
# # Can Specify Hex code for colors

# ax.scatter(x,y,color='black',marker='o',size=20)
# # Many Markers: circle-'o', square-'s', triangle-'^',star-'*', x-'x'

# plt.show()

###################### Multi Line ######################
x = [x_sim,x_meas]                             # List of Lists
y = [y_sim,y_meas]                             # List of Lists

    #### Lists must be equal length ###

dl = ['Simulated','Measured']                                 # Data Labels (list)
lc = ['black','black']                                 # Line Color    |
ls = ['-','--']                                 # Line Style    |
lw = [2,2]                                 # Line Width    V
a = [1,1]                                  # Transparency
s = []                                  # Marker Size, 20 is default
m = []                                  # Marker Type, 'o' is default
# Use color-hex.com for color pallets
# Common ones: Shades of Teal, Ocean Breezes By,Ppt Cv



for i in range(len(x)):
    ax.plot(x[i],y[i],label=dl[i],color=lc[i],linestyle=ls[i],linewidth=lw[i], alpha=a[i])
    #ax.scatter(x[i],y[i],label=dl[i],color=lc[i],marker=m[i],size=s[i])

ax.legend(loc='center', bbox_to_anchor=(0.8,0.8), ncol=1, frameon=True,edgecolor='white',framealpha=1, labelspacing=0.2, 
          columnspacing=0.75,handlelength=0.75, handletextpad=0.3)
# anchor loc is based on the plot area, 0.5 is half the width, 1.01 is just above the top
# labelspacing is for vertical spacing, column is for horizontal, handel is for line length, textpad is for handl eto text


plt.tight_layout()
plt.show()