app_filesystem_version.py

import json
import os
from pathlib import Path

import paho.mqtt.client as mqtt
import streamlit as st
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.patches import Rectangle

import secrets

from time import time, sleep

# Initialize Streamlit app
st.title("Light-mixing Control Panel")

# Description and context
st.markdown(
    """
This application accesses a public test demo located in Toronto, ON, Canada (as of 2024-07-27). 
For more context, you can refer to this [Colab notebook](https://colab.research.google.com/github/sparks-baird/self-driving-lab-demo/blob/main/notebooks/4.2-paho-mqtt-colab-sdl-demo-test.ipynb) 
and the [self-driving-lab-demo project](https://github.com/sparks-baird/self-driving-lab-demo).
You may also be interested in the Acceleration Consortium's ["Hello World" microcourse](https://ac-microcourses.readthedocs.io/en/latest/courses/hello-world/index.html) for self-driving labs.
"""
)

max_power = 0.35
max_value = round(max_power * 255)

with st.form("mqtt_form"):

    # MQTT Configuration
    HIVEMQ_HOST = st.text_input(
        "Enter your HiveMQ host:",
        "248cc294c37642359297f75b7b023374.s2.eu.hivemq.cloud",
        type="password",
    )
    HIVEMQ_USERNAME = st.text_input("Enter your HiveMQ username:", "sgbaird")
    HIVEMQ_PASSWORD = st.text_input(
        "Enter your HiveMQ password:", "D.Pq5gYtejYbU#L", type="password"
    )
    PORT = st.number_input(
        "Enter the port number:", min_value=1, max_value=65535, value=8883
    )

    # User input for the Pico ID
    PICO_ID = st.text_input("Enter your Pico ID:", "test", type="password")

    # Information about the maximum power reduction
    st.info(
        f"The upper limit for RGB power levels has been set to {max_value} instead of 255. NeoPixels are bright 😎"
    )

    # Sliders for RGB values
    R = st.slider("Select the Red value:", min_value=0, max_value=max_value, value=0)
    G = st.slider("Select the Green value:", min_value=0, max_value=max_value, value=0)
    B = st.slider("Select the Blue value:", min_value=0, max_value=max_value, value=0)

    submit_button = st.form_submit_button(label="Send RGB Command")

command_topic = f"sdl-demo/picow/{PICO_ID}/GPIO/28/"
sensor_data_topic = f"sdl-demo/picow/{PICO_ID}/as7341/"


# random session id to keep track of the session and filter out old data
experiment_id = secrets.token_hex(4)  # 4 bytes = 8 characters
sensor_data_file = f"sensor_data-{experiment_id}.json"

# TODO: Session ID using st.session_state to have history of commands and sensor data

# file_path = Path(sensor_data_file)
# file_path.unlink(missing_ok=True)


# Singleton: https://docs.streamlit.io/develop/api-reference/caching-and-state/st.cache_resource
# (on_message to be set later since filename is dynamic)
@st.cache_resource
def get_paho_client(
    sensor_data_topic, hostname, username, password=None, port=8883, tls=True
):
    client = mqtt.Client(mqtt.CallbackAPIVersion.VERSION2, protocol=mqtt.MQTTv5)

    def on_connect(client, userdata, flags, rc, properties=None):
        if rc != 0:
            print("Connected with result code " + str(rc))
        client.subscribe(sensor_data_topic, qos=1)

    client.on_connect = on_connect

    if tls:
        client.tls_set(tls_version=mqtt.ssl.PROTOCOL_TLS_CLIENT)
    client.username_pw_set(username, password)
    client.connect(hostname, port)
    client.loop_start()  # Use a non-blocking loop

    return client


def send_and_receive(client, command_topic, msg, queue_timeout=15):
    print("Sending command...")
    result = client.publish(command_topic, json.dumps(msg), qos=2)
    result.wait_for_publish()  # Ensure the message is sent

    if result.rc == mqtt.MQTT_ERR_SUCCESS:
        print(f"Command sent: {msg} to topic {command_topic}")
    else:
        print(f"Failed to send command: {result.rc}")

    timeout = time() + queue_timeout  # Set timeout

    while True:
        if time() > timeout:
            st.error("No sensor data received within the timeout period.")
            return None
        if os.path.exists(sensor_data_file):
            with open(sensor_data_file, "r") as f:
                sensor_data = json.load(f)

            file_path = Path(sensor_data_file)
            file_path.unlink(missing_ok=True)

            return sensor_data


# Helper function to plot discrete spectral sensor data
def plot_spectra(sensor_data):
    """https://chatgpt.com/share/210d2fee-ca64-45a5-866e-e6df6e56bd1c"""
    wavelengths = np.array([410, 440, 470, 510, 550, 583, 620, 670])
    intensities = np.array(
        [
            sensor_data["ch410"],
            sensor_data["ch440"],
            sensor_data["ch470"],
            sensor_data["ch510"],
            sensor_data["ch550"],
            sensor_data["ch583"],
            sensor_data["ch620"],
            sensor_data["ch670"],
        ]
    )

    fig, ax = plt.subplots(figsize=(10, 6))

    num_points = 100  # for "fake" color bar effect

    # Adding rectangles for color bar effect
    dense_wavelengths = np.linspace(wavelengths.min(), wavelengths.max(), num_points)
    rect_height = max(intensities) * 0.02  # Height of the rectangles

    for dw in dense_wavelengths:
        rect = Rectangle(
            (
                dw - (wavelengths.max() - wavelengths.min()) / num_points / 2,
                -rect_height * 2,
            ),
            (wavelengths.max() - wavelengths.min()) / num_points,
            rect_height * 3,
            color=plt.cm.rainbow(
                (dw - wavelengths.min()) / (wavelengths.max() - wavelengths.min())
            ),
            edgecolor="none",
        )
        ax.add_patch(rect)

    # Main scatter plot
    scatter = ax.scatter(
        wavelengths, intensities, c=wavelengths, cmap="rainbow", edgecolor="k"
    )

    # Adding vertical lines from the x-axis to each point
    for wavelength, intensity in zip(wavelengths, intensities):
        ax.vlines(wavelength, 0, intensity, color="gray", linestyle="--", linewidth=1)

    # Adjust limits and labels with larger font size
    ax.set_xlim(wavelengths.min() - 10, wavelengths.max() + 10)
    ax.set_ylim(
        0, max(intensities) + 15
    )  # Ensure the lower y limit is 0 and add buffer
    ax.set_xticks(wavelengths)
    ax.set_xlabel("Wavelength (nm)", fontsize=14)
    ax.set_ylabel("Intensity", fontsize=14)
    ax.set_title("Spectral Intensity vs. Wavelength", fontsize=16)
    ax.tick_params(axis="both", which="major", labelsize=12)

    st.pyplot(fig)


# Publish button
if submit_button:
    if not PICO_ID or not HIVEMQ_HOST or not HIVEMQ_USERNAME or not HIVEMQ_PASSWORD:
        st.error("Please enter all required fields.")
    else:
        st.info(
            f"Please wait while the command {R, G, B} for experiment {experiment_id} is sent..."
        )

        client = get_paho_client(
            sensor_data_topic,
            HIVEMQ_HOST,
            HIVEMQ_USERNAME,
            password=HIVEMQ_PASSWORD,
            port=int(PORT),
            tls=True,
        )

        def on_message(client, userdata, msg):
            with open(sensor_data_file, "w") as f:
                json.dump(json.loads(msg.payload), f)

        client.on_message = on_message

        command_msg = {"R": R, "G": G, "B": B}
        sensor_data = send_and_receive(
            client, command_topic, command_msg, queue_timeout=15
        )

        if sensor_data:
            received_cmd = sensor_data["_input_message"]
            R1 = received_cmd["R"]
            G1 = received_cmd["G"]
            B1 = received_cmd["B"]
            st.success(
                f"Command {R1, G1, B1} for experiment {experiment_id} sent successfully!"
            )
            plot_spectra(sensor_data)
            st.write("Sensor Data Received:", sensor_data)