# 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
from plotly.subplots import make_subplots
config={'showLink': False, 'displayModeBar': False}

init_notebook_mode(connected=True)

# PYTHON CODE

init_notebook_mode(connected=True)


## Setup for plots
fig = make_subplots(rows=2, cols=1, vertical_spacing = 0.2,
                    subplot_titles=(
    '<b>Signal</b>',
    '<b>Gaussian-Convolved</b>',))

# Setup signal
signal = np.zeros(100)
signal[10] = 1

signal[25:27] = 1

signal[50] = 1
signal[51] = -1

signal[50] = 1
signal[51] = -1

signal[70:90] = np.random.uniform(0.95,1.05,20)

# Compute convolution
mu = np.linspace(0.1,5,50)

gauss_convolved = np.zeros([100, len(mu)])

def gaussian(x, mu, sig):
    return (
        1.0 / (np.sqrt(2.0 * np.pi) * sig) * np.exp(-np.power((x - mu) / sig, 2.0) / 2)
    )

for ii in range(1,100):
    if ii <5 or ii>95:
        continue
    else:
        for jj in range(len(mu)):
            x = np.arange(ii-4, ii+5)
            gauss_convolved[ii, jj] = np.sum(signal[ii-4:ii+5]*gaussian(x, ii, mu[jj])/np.sum(gaussian(x, ii, mu[jj])))

position = np.arange(1,101)

signal_line = [dict(
            visible = False,
            x = position,
            y = signal,
            name = "Signal",
            mode = 'lines',
            hoverinfo = "y",
            showlegend=False) for ii in range(len(mu))]

signal_line[0]['visible'] = True

      
convolved_line = [dict(
            visible = False,
            x = position,
            y = gauss_convolved[:, ii],
            name = "Mean-Convolved",
            mode = 'lines',
            hoverinfo = "y",
            showlegend=False) for ii in range(len(mu))]

convolved_line[0]['visible'] = True


# Add traces
for ii in range(len(mu)):
    fig.add_trace(go.Scatter(signal_line[ii], line=dict(color="black", width=2)), row= 1, col=1)


for ii in range(len(mu)):
    fig.add_trace(go.Scatter(convolved_line[ii], line=dict(color="blue", width=2)), row= 2, col=1)


# Create and add slider
steps = []
      
for i in range(len(mu)):
    step = dict(
        method="update",
        args=[{"visible": [False] * len(fig.data), "showlegend": [False] * len(fig.data)},],  # layout attribute
        label = str(np.round(mu[i], 1))
    )
    step["args"][0]["visible"][i] = True  # Toggle i'th trace to "visible"
    step["args"][0]["visible"][i+1*len(mu)] = True  # Toggle i'th trace to "visible"

    steps.append(step)

sliders = [dict(
    active=0,
    currentvalue={"prefix": "Gaussian width: "},
    pad={"t": 50},
    steps=steps
)]

layout = go.Layout(
    width=750,
    height=600,
    margin=go.layout.Margin(
        l=100,
        r=80,
        b=100,
        t=130,
    ),
    xaxis=dict(
        showgrid=True,
        gridcolor='rgb(169,169,169)',
        linecolor='black',
        linewidth=2,
        range = [0,100]
    ),
    yaxis=dict(
        showgrid=True,
        gridcolor='rgb(169,169,169)',
        linecolor='black',
        linewidth=2,
        range = [-1.1,1.1]
    ),
    
    xaxis2=dict(
        showgrid=True,
        gridcolor='rgb(169,169,169)',
        linecolor='black',
        linewidth=2,
        range = [0,100]
    ),
    yaxis2=dict(
        showgrid=True,
        gridcolor='rgb(169,169,169)',
        linecolor='black',
        linewidth=2,
        range = [-1.1,1.1]
    ),
    
    legend=dict(
        x=0.25,
        y=1.3,
        traceorder='normal',
        font=dict(
            family='Times New Roman',
            size=12,
            color='#000'
        ),
        bordercolor='#000000',
        borderwidth=2
    ),
    sliders=sliders
)

fig.update_layout(layout)

iplot(fig, filename = 'fig3.html', config = config)