Create an Interactive Control Chart from a Data Stream

statistical-process-control-api.py

import requests
from plotly.subplots import make_subplots
import plotly.graph_objects as go

# Inputs
HOSTNAME = "https://statistical-process-control1.p.rapidapi.com"
HEADERS = headers: {
    'X-RapidAPI-Host': 'statistical-process-control1.p.rapidapi.com',
    'X-RapidAPI-Key': 'YOUR-KEY"
}

data = [82,84,75,79,84,81,81,105,80,106,74,76,73,82]
N = 1

# Endpoints
URL_SPC = f"{HOSTNAME}/spc/control/variable/{N}"
URL_NELSON = f"{HOSTNAME}/spc/rules/nelson"

# Compute SPC
resp_spc = requests.request("POST", URL_SPC, data={'data': ",".join([str(x) for x in data])})
data_spc = resp_spc.json()

print(data_spc)

# Compute Nelson Rules
resp_nelson = requests.request("POST", URL_NELSON, data={'data': ",".join([str(x) for x in data])})
data_nelson = resp_nelson.json()

print(data_nelson)

# Plot
fig = make_subplots(rows=2, shared_xaxes=True)
fig.update_layout(title_text=f"{data_spc['kind']} Chart with Nelson Rules Overlay",
                  hovermode="x")

# X
fig.add_trace(go.Scatter(y=data, name='X', line={'color':'black'}), row=1, col=1)
fig.add_trace(go.Scatter(y=[data_spc['x_bar']]*data_spc['k'], name='X̄', mode='lines', line={'color': 'blue', 'width': 2}), row=1, col=1)
fig.add_trace(go.Scatter(y=[data_spc['x_ucl']]*data_spc['k'], name='X UCL', mode='lines', line={'color': 'red', 'width': 2}), row=1, col=1)
fig.add_trace(go.Scatter(y=[data_spc['x_lcl']]*data_spc['k'], name='X LCL', mode='lines', line={'color': 'red', 'width': 2}), row=1, col=1)

colors_nelson = ['darkred', 'firebrick', 'maroon', 'crimson', 'indianred', 'salmon', 'lightcoral', 'darksalmon']
for idx, fail in enumerate(data_nelson['failed_rules']):
    if fail:
        #print(data_nelson['failed_indices'][idx], [data[i] for i in data_nelson['failed_indices'][idx]])
        fig.add_trace(go.Scatter(x=data_nelson['failed_indices'][idx], y=[data[i] for i in data_nelson['failed_indices'][idx]],
                                 name=f'X Nelson Rule {idx+1}', mode='markers', marker={'size': (idx+1)*2, 'color': colors_nelson[idx]}), row=1, col=1)

fig['layout']['xaxis']['title'] = 'Observation'
fig['layout']['yaxis']['title'] = 'Individual Value'

# Moving Range
fig.add_trace(go.Scatter(y=data_spc['mr'], name='MR', line={'color': 'darkslategrey'}), row=2, col=1)
fig.add_trace(go.Scatter(y=[data_spc['mr_bar']]*data_spc['k'], name='M̅R̅', mode='lines', line={'color': 'royalblue', 'width': 2}), row=2, col=1)
fig.add_trace(go.Scatter(y=[data_spc['mr_ucl']]*data_spc['k'], name='MR UCL', mode='lines', line={'color': 'darkred', 'width': 2}), row=2, col=1)
fig.add_trace(go.Scatter(y=[data_spc['mr_lcl']]*data_spc['k'], name='MR LCL', mode='lines', line={'color': 'darkred', 'width': 2}), row=2, col=1)

fig['layout']['xaxis2']['title'] = 'Observation'
fig['layout']['yaxis2']['title'] = 'Moving Range'

fig.show()