# Prepare Python environment

import scipy.io as sio
from pathlib import Path

data_dir = Path("../../../data/06-MT-03-MTsat")
data_file = "fig0.mat"

#Load either archived or generated plot variables
mat_contents = sio.loadmat(data_dir / data_file)

## Plot

# Module imports
# PYTHON CODE
# Module imports

import matplotlib.pyplot as plt
import plotly.graph_objs as go
import numpy as np
from plotly import __version__
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
config={'showLink': False, 'displayModeBar': False}

init_notebook_mode(connected=True)


# Prepare Python environment

tissues = [
    "Healthy Cortical GM",
    "Healthy WM",
    "NAWM",
    "Early WM MS Lesion",
    "Late WM MS Lesion",
    ]
    
protocols = [
    "Helms 2008",
    "Weiskopf 2013",
    "Campbell 2018",
    "Karakuzu 2022 Siemens 1",
    "Karakuzu 2022 GE 1",
    "York 2022",
    ]
    
signal_Helms = mat_contents["MTsats"][0]
signal_Weiskopf = mat_contents["MTsats"][1]
signal_Campbell = mat_contents["MTsats"][2]
signal_KarakuzuSiemens = mat_contents["MTsats"][3]
signal_KarakuzuGE = mat_contents["MTsats"][4]
signal_York = mat_contents["MTsats"][5]


# Plot Figure 1

# Module imports

import matplotlib.pyplot as plt
import plotly.graph_objs as go
import numpy as np
from plotly import __version__
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
config={'showLink': False, 'displayModeBar': False}

init_notebook_mode(connected=True)

# PYTHON CODE

init_notebook_mode(connected=True)
# The polling here is to ensure that plotly.js has already been loaded before
# setting display alignment in order to avoid a race condition.


data_Helms = go.Scatter(
    x = tissues,
    y = signal_Helms,
    name = protocols[0],
    text = 'N/A',
    hoverinfo = 'y'
)


data_Weiskopf = go.Scatter(
    x = tissues,
    y = signal_Weiskopf,
    name = protocols[1],
    hoverinfo = 'y'
)


data_Campbell = go.Scatter(
    x = tissues,
    y = signal_Campbell,
    name = protocols[2],
    hoverinfo = 'y'
)


data_KarakuzuSiemens = go.Scatter(
    x = tissues,
    y = signal_KarakuzuSiemens,
    name = protocols[3],
    hoverinfo = 'y'
)

data_KarakuzuGE = go.Scatter(
    x = tissues,
    y = signal_KarakuzuGE,
    name = protocols[4],
    hoverinfo = 'y'
)

data_York = go.Scatter(
    x = tissues,
    y = signal_York,
    name = protocols[5],
    hoverinfo = 'y'
)


data = [data_Helms, data_Weiskopf, data_Campbell, data_KarakuzuSiemens, data_KarakuzuGE, data_York]

layout = go.Layout(
    width=750,
    height=750,
    margin=go.layout.Margin(
        l=100,
        r=80,
        b=100,
        t=130,
    ),
    annotations=[
        dict(
            x=-0.15,
            y=0.50,
            showarrow=False,
            text='MTsat (%)',
            font=dict(
                family='Times New Roman',
                size=22
            ),
            textangle=-90,
            xref='paper',
            yref='paper'
        ),
    ],
    xaxis=dict(
        showgrid=True,
        gridcolor='rgb(169,169,169)',
        linecolor='black',
        linewidth=2
    ),
    yaxis=dict(
        showgrid=True,
        gridcolor='rgb(169,169,169)',
        linecolor='black',
        linewidth=2
    ),
    legend=dict(
        x=0.25,
        y=1.3,
        traceorder='normal',
        font=dict(
            family='Times New Roman',
            size=12,
            color='#000'
        ),
        bordercolor='#000000',
        borderwidth=2
    )
)

fig = dict(data=data, layout=layout)

iplot(fig, filename = 'fig1.html', config = config)