import numpy as np
import matplotlib.pyplot as plt

'''
This file gives the PV Diagram for 2 traces (Nominally measured and simulated)
but can be modified to do 1 or more if needed.

It needs .txt files copied from the data of GT-Power with the format of:

(no headers)
pressure    volume fraction
pressure    volume fraction
.           .
.           .  
.           .

Other needed info: Max y value for the y axis

**Will need to adjust how far out min/max lines go, as well as
colors, line type, etc.** 
'''


def get_data(filename):
    file = open(filename)
    title = file.readline()
    lines = file.readlines()
    x = []
    y = []
    for line in lines:
        line.strip()
        data = line.split()
        x.append(float(data[0]))
        y.append(float(data[1]))

    return x, y, round(min(x),3), round(max(y),2)

x_meas, y_meas, x_meas_min, y_meas_max = get_data('Python/Plotting/Base/Measured.txt')  #Files here
x_sim, y_sim, x_sim_min, y_sim_max = get_data("Python/Plotting/Base/Simulated.txt")

x_min_data = min(x_meas_min, x_meas_min)

#print(min(x_meas),min(x_sim))

################################# BASIC PLOT CODE #################################

# Basic Styling
plt.rcParams.update({
    'font.family': 'Courier New',       # monospace font
    'font.size': 20,                    # Fonts
    'axes.titlesize': 30,               # |
    'axes.labelsize': 20,               # V
    'xtick.labelsize': 15,
    'ytick.labelsize': 15,
    'legend.fontsize': 20,
    'figure.titlesize': 20,
    'figure.figsize': [10,10]           # Figure Size
    })

# Figure Setup
fig, ax = plt.subplots()
title = 'PV Diagram'                              # Title
xlab = '% of Volume'                               # X Label
ylab = 'Cyinder Pressure [Bar]'                               # Y Label
ax.set_xlabel(xlab)
ax.set_ylabel(ylab, labelpad=0)
ax.set_title(title, pad = 0) #pad controls distance to plot
ax.spines['top'].set_visible(False) # Controls non axis borders
ax.spines['right'].set_visible(False)
# ax.set_xscale('log')
# ax.set_yscale('log')

x_min = 0                               # Axis Limits and Ticks
x_max = 1.1
x_step_maj = 1  #steps not division
x_step_min = 1

y_min = 0
y_max = 25
y_step_maj = 25
y_step_min = 1

ax.set_xlim(x_min,x_max)                                        # X limits
ax.set_xticks([x_min_data,1])                # X Major Ticks
# ax.set_xticks(np.arange(x_min,x_max,x_step_min), minor=True)    # X Minor Ticks

ax.set_ylim(y_min,y_max)                                        # Y limits
ax.set_yticks([y_meas_max,y_sim_max])                # 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=1, lw=1, ls='--', color='black')                      # 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_meas,x_sim,[1,1],[x_min_data,x_min_data],[0,.125],[0,.125]]                             # List of Lists
y = [y_meas,y_sim,[0,1.1],[0,12.5],[y_meas_max,y_meas_max],[y_sim_max,y_sim_max]]                             # List of Lists

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

dl = ['Measured', 'Simulated','','','','']                                 # Data Labels (list)
lc = ['black', 'black','black','black','black','black']                                 # Line Color    |
ls = ['-','--','--','--', '--','--']                                 # Line Style    |
lw = [1.5,2,1,1,1,1]                                 # Line Width    V
a = [1,1,1,1,1,1]
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='upper right', bbox_to_anchor=(0.85, 0.85), ncol=1, frameon=False, labelspacing=0.2, columnspacing=0.75,
          handlelength=1, 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()