import scipy.io as sio
import plotly.graph_objs as go
from ipywidgets import interactive, HBox, widgets, interact
import numpy as np
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
from IPython.core.display import display, HTML
import os
init_notebook_mode(connected=True)
config={'showLink': False, 'displayModeBar': False}

# If you run on your local machine comment out this line
os.chdir("/home/jovyan/content/04/subsection/01")

# Load matrix callculated in the previous section
matrix = sio.loadmat(file_name = "newmap.mat", matlab_compatible = True)
newmap = matrix['vect']


# Rotate to get picutre 
matrix = np.rot90(newmap)

# Get # of slices
slices_z = newmap.shape[0]

# Create list of Heatmaps, one for every slice 
data = []
for i in range(slices_z):
    z_current = np.rot90(matrix[i,:,:], 2)
    data_c = go.Heatmap(z = z_current, 
                        visible = False,
                        xtype = "scaled", 
                        ytype = "scaled",
                        colorscale = "viridis",
                        colorbar = dict(title = dict(text = "FA [°]")))
    data.append(data_c)

# Toggle frist slice to be visible
data[0]['visible'] = True

# Create steps and slider
steps = []
for i in range(slices_z):
    step = dict(
        method = 'restyle',  
        args = ['visible', [False]*slices_z],
        label = str(i)
    )
    step['args'][1][i] = True # Toggle i'th trace to "visible"
    steps.append(step)

sliders = [dict(
    active = 0,
    currentvalue = {'prefix':"Current slice is: <b>"},
    pad = {"t": 50, "b": 10},
    steps = steps
)]

# Setup the layout of the figure
layout = go.Layout(
    width=458,
    height=550,
    margin=go.layout.Margin(
        l=50,
        r=50,
        b=60,
        t=15,
    ),
    showlegend = False,
    autosize = False,
    sliders=sliders,
    xaxis = dict(showgrid = False,
                 showticklabels= False),
    yaxis = dict(showgrid = False,
                 showticklabels = False),
)

# Plot function saves as html or with ipplot
fig = dict(data=data, layout=layout)
plot(fig, filename = 'fig.html', config = config)

# THEBELAB
display(HTML('fig.html'))
# BINDER
# iplot(fig,config=config)