import scipy
import scipy.io as sio
from pathlib import Path
import numpy as np

data_dir = Path("../../../data/06-MT-01-qMT")

# Simulations have been performed and the results have been saved in the folder results.
dataSim_model_mat = scipy.io.loadmat(data_dir / 'qMT_tutorial-ISMRM2022-main' / 'results/dataSim_model.mat')
dataRaw_model_mat = scipy.io.loadmat(data_dir / 'qMT_tutorial-ISMRM2022-main' / 'results/dataRaw_model.mat')
dataSim_model = np.array(dataSim_model_mat["dataSim_modelFit"])
dataRaw_model = np.array(dataRaw_model_mat["dataRaw_modelFit"])

import matplotlib.pyplot as plt
from PIL import Image
from matplotlib.image import imread
import scipy.io
import plotly
from plotly.subplots import make_subplots
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}

# PYTHON CODE

# PYTHON CODE

init_notebook_mode(connected=True)

fitModel = ["Sled Pike RP", "Sled Pike CW", "Yarnykh", "Ramani"]

fig = go.Figure()

#Add traces (three traces per fitting model)
for ii in range(len(fitModel)):
    if ii==0:
        vis = True
    else:
        vis = False
    fig.add_trace(go.Scatter(x=dataSim_model[:,0,0], y=dataSim_model[:,1,ii],
                             name="Fitted curve (angle = 142)", mode='lines', line=dict(color="firebrick"), visible = vis,
                             hovertemplate="Fitted curve (angle = 142)<br>M<sub>z</sub> = %{y}<br>Offset = %{x} Hz<extra></extra>"))
    
    fig.add_trace(go.Scatter(x=dataSim_model[:,0,0], y=dataSim_model[:,2,ii],
                             name="Fitted curve (angle = 426)", mode='lines', line=dict(color="royalblue"), visible = vis,
                             hovertemplate="Fitted curve (angle = 426)<br>M<sub>z</sub> = %{y}<br>Offset = %{x} Hz<extra></extra>"))
    
    fig.add_trace(go.Scatter(x=dataRaw_model[:,0,0], y=dataRaw_model[:,1,ii],
                             name="Raw data", mode='markers', line=dict(color="darkslategray"), visible = vis,
                             hovertemplate="Raw data<br>M<sub>z</sub> = %{y}<br>Offset = %{x} Hz<extra></extra>"))


buttons = []
for i, label in enumerate(fitModel):
    visibility = [False] * 12
    for j in range(3):
        visibility[3*i+j] = True
    button = dict(
                label =  label,
                method = 'update',
                args = [{'visible': visibility}])
    buttons.append(button)
        
updatemenus = list([
    dict(active=0,
         x=0.88,
         y=1.1,
         buttons=buttons
    )
])

fig['layout']['updatemenus'] = updatemenus

fig.update_layout(height=450, width=580, plot_bgcolor='rgba(0,0,0,0)')
fig.update_layout(legend=dict(
        x=0.55,
        y=0.1,
        traceorder='normal',
        font=dict(
            family='Times New Roman',
            size=12,
            color='#000'
        ),
        bordercolor='#000000',
        borderwidth=2),
    annotations=[
        dict(
            x=0.35,
            y=1.1,
            showarrow=False,
            text='Fitting method: ',
            font=dict(
                family='Times New Roman',
                size=22
            ),
            xref='paper',
            yref='paper'
        ),
        dict(
            x=0.5004254919715793,
            y=-0.2,
            showarrow=False,
            text='Frequency offset \u0394 (Hz)',
            font=dict(
                family='Times New Roman',
                size=22
            ),
            xref='paper',
            yref='paper'
        ),
        dict(
            x=-0.14,
            y=0.5,
            showarrow=False,
            text='Magnetization |M<sub>z</sub>|',
            font=dict(
                family='Times New Roman',
                size=22
            ),
            textangle=-90,
            xref='paper',
            yref='paper'
        ),
    ])

fig.update_xaxes(type="log", range=[2,5], showline=True, linewidth=2, linecolor='black', dtick=1, tickvals=[100,1000,10000,100000], ticktext=["10<sup>2</sup>","10<sup>3</sup>","10<sup>4</sup>","10<sup>5</sup>"])
fig.update_yaxes(showline=True, linewidth=2, linecolor='black')

iplot(fig, filename='dropdown')