#imports
import numpy as np
import matplotlib.pyplot as plt
import plotly.graph_objects as go
from scipy.signal import find_peaks
from tabulate import tabulate

#silicon standard
SiNIST = np.loadtxt('SiNIST.csv', delimiter=',')

SiX = SiNIST[:,0]
SiY = SiNIST[:,1]

SiIndices = find_peaks(SiY, prominence = 200)[0]

fig = go.Figure()
fig.add_trace(go.Scatter(
    y = SiY,
    mode = 'lines',
    line = dict(
        color ='firebrick',
        width = 1,
    ),
    showlegend = False
    )
)

fig.add_trace(go.Scatter(
    x = SiIndices,
    y = [SiY[j] for j in SiIndices],
    mode ='markers',
    marker = dict(
        size = 5,
        color = 'black',
        symbol = 'x'
    ),
    name = 'Detected Peaks'
    )
)

fig.update_layout(
    title = ({
        'text': 'Silicon Standard Diffractogram',
        'y': 0.9,
        'x': 0.5,
        'xanchor': 'center',
        'yanchor': 'top'}),
    xaxis_title = "2θ",
    yaxis_title = "Intensity",
    xaxis_showgrid = False,
    font = dict(
        family = 'Courier New, monospace',
        size = 12,
        color = '#000000'
    )
)

fig.update_xaxes(showticklabels = False),

fig.show()

plt.xlabel('2θ')
plt.ylabel('Intensity')
hideAxes = plt.gca()
hideAxes.axes.get_xaxis().set_ticks([])
hideAxes.axes.get_yaxis().set_ticks([])
plt.plot(SiX, SiY, linewidth = '.5', color = 'black')
plt.show()

for i, x, y in zip(SiIndices, SiX[SiIndices], SiY[SiIndices]):
    headers = ['Peak', '2θ', 'Intensity']
    table = zip(SiIndices, SiX[SiIndices], SiY[SiIndices])

print('\033[1m' + 'Detected Peaks:' + '\033[0m')
print(tabulate(table, headers, tablefmt = 'pretty'))

#silicon standard full list
peakSi = []

for i, (x, y) in enumerate(zip(SiX, SiY)):
    peakSi.append(i)

headers = ['Peak', '2θ', 'Intensity']
table = zip(peakSi, SiX, SiY)

np.set_printoptions(threshold = np.inf)
print(tabulate(table, headers, tablefmt = 'pretty'))