from repo2data.repo2data import Repo2Data
import os 
import pickle
import matplotlib.pyplot as plt
import chart_studio.plotly as py
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
from IPython.display import display, HTML
from plotly import tools

from contextlib import contextmanager
import sys, os

@contextmanager
def suppress_stdout():
    with open(os.devnull, "w") as devnull:
        old_stdout = sys.stdout
        sys.stdout = devnull
        try:  
            yield
        finally:
            sys.stdout = old_stdout

with suppress_stdout():
    data_req_path = os.path.join("..","..","..", "binder", "data_requirement.json")
    repo2data = Repo2Data(data_req_path)
    DATA_ROOT = os.path.join(repo2data.install()[0],"t1-book-neurolibre")
    filename = os.path.join(DATA_ROOT,"02",'figure_5.pkl')

with open(filename, 'rb') as f:
    params, data_mean, data_mean_div_sin, data_mean_div_tan, data_std, data_std_div_sin, data_std_div_tan, params_highres, signal_WM, signal_WM_div_sin, signal_WM_div_tan = pickle.load(f)

config={'showLink': False, 'displayModeBar': False}

init_notebook_mode(connected=True)

data1 = dict(
        visible = True,
        x = params_highres["EXC_FA"],
        y = signal_WM,
        name = 'Analytical Solutions',
        text = params["EXC_FA"],
        mode = 'lines', 
        line = dict(
            color = ('rgb(0, 0, 0)'),
            dash = 'dot'),
        hoverinfo='none')

data2 = dict(
        visible = True,
        x = signal_WM_div_tan,
        y = signal_WM_div_sin,
        name = 'Analytical Solutions',
        text = params_highres["EXC_FA"],
        mode = 'lines',
        xaxis='x2',
        yaxis='y2',
        line = dict(
            color = ('rgb(0, 0, 0)'),
            dash = 'dot'
            ),
        hoverinfo='none',
        showlegend=False)

data3 = dict(
        visible = True,
        x = params["EXC_FA"],
        y = data_mean,
        name = 'Nonlinear Form - Noisy',
        text = ["Flip angle: " + str(x) + "°" for x in params["EXC_FA"]],
        mode = 'markers',
        hoverinfo = 'y+text',
        line = dict(
            color = ('rgb(22, 96, 167)'),
            ),
        error_y=dict(
            type='data',
            array=data_std,
            visible=True,
            color = ('rgb(142, 192, 240)')
        ))

data4 = dict(
        visible = True,
        x = data_mean_div_tan,
        y = data_mean_div_sin,
        name = 'Linear Form - Noisy',
        text = ["Flip angle: " + str(x) + "°" for x in params["EXC_FA"]],
        mode = 'markers',
        xaxis='x2',
        yaxis='y2',
        hoverinfo = 'x+y+text',
        line = dict(
            color = ('rgb(205, 12, 24)'),
            ),
        error_x=dict(
            type='data',
            array=data_std_div_tan,
            visible=True,
            color = ('rgb(248, 135, 142)')
        ),
        error_y=dict(
            type='data',
            array=data_std_div_sin,
            visible=True,
            color = ('rgb(248, 135, 142)')
        ))

data = [data1, data2, data3, data4]

layout = go.Layout(
    width=580,
    height=450,
    margin=go.layout.Margin(
        l=80,
        r=80,
        b=60,
        t=60,
    ),
    annotations=[
        dict(
            x=0.5004254919715793,
            y=-0.14,
            showarrow=False,
            text='Excitation Flip Angle (<i>θ<sub>n</sub></i>)',
            font=dict(
                family='Times New Roman',
                size=22,
                color=('rgb(21, 91, 158)')
            ),
            xref='paper',
            yref='paper'
        ),
        dict(
            x=-0.17,
            y=0.5,
            showarrow=False,
            text='Signal (<i>S<sub>n</sub></i>)',
            font=dict(
                family='Times New Roman',
                size=22,
                color=('rgb(21, 91, 158)')
            ),
            textangle=-90,
            xref='paper',
            yref='paper'
        ),
        dict(
            x=0.5004254919715793,
            y=1.15,
            showarrow=False,
            text='<i>S<sub>n</sub></i> / tan(<i>θ<sub>n</sub></i>)',
            font=dict(
                family='Times New Roman',
                size=22,
                color=('rgb(169, 10, 20)') 
            ),
            xref='paper',
            yref='paper'
        ),
        dict(
            x=1.16,
            y=0.5,
            showarrow=False,
            text='<i>S<sub>n</sub></i> / sin(<i>θ<sub>n</sub></i>)',
            font=dict(
                family='Times New Roman',
                size=22,
                color=('rgb(169, 10, 20)') 
            ),
            xref='paper',
            yref='paper',
            textangle=-90,
        ),
    ],
    xaxis=dict(
        autorange=False,
        range=[params['EXC_FA'][0], params['EXC_FA'][-1]],
        showgrid=False,
        linecolor='black',
        linewidth=2
    ),
    yaxis=dict(
        autorange=True,
        showgrid=False,
        linecolor='black',
        linewidth=2
    ),
    xaxis2=dict(
        autorange=False,
        range=[0, 1],
        showgrid=False,
        mirror=True,
        overlaying= 'x',
        anchor= 'y2',
        side= 'top',
        linecolor='black',
        linewidth=2
    ),
    yaxis2=dict(
        autorange=False,
        range=[0, 1],
        showgrid=False,
        overlaying= 'y',
        anchor= 'x',
        side= 'right',
        linecolor='black',
        linewidth=2
    ),
    legend=dict(
        x=0.32,
        y=0.98,
        traceorder='normal',
        font=dict(
            family='Times New Roman',
            size=12,
            color='#000'
        ),
        bordercolor='#000000',
        borderwidth=2
    ),
    plot_bgcolor='white'
)

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

iplot(fig, filename = 'vfa_fig_5.html', config = config)