app.py

import json
import queue

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

# 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.
"""
)

# 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")

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

max_power = 0.35
max_value = round(max_power * 255)

# 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)

# # Initialize session state for messages and lock state
if "messages" not in st.session_state:
    st.session_state.messages = []

# if "locked" not in st.session_state:
#     st.session_state.locked = False

# if "command_history" not in st.session_state:
#     st.session_state.command_history = []
# if "sensor_data_history" not in st.session_state:
#     st.session_state.sensor_data_history = []

# Queue to hold sensor data
sensor_data_queue = queue.Queue()


# Singleton: https://docs.streamlit.io/develop/api-reference/caching-and-state/st.cache_resource
@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
    )  # create new instance

    def on_message(client, userdata, msg):
        sensor_data_queue.put(json.loads(msg.payload))

    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
    client.on_message = on_message

    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=60):
    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}")

    try:
        sensor_data = sensor_data_queue.get(True, queue_timeout)
        return sensor_data
    except queue.Empty:
        st.error("No sensor data received within the timeout period.")
        return None


# 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 st.button("Send RGB Command", disabled=st.session_state.locked):
if st.button("Send RGB Command"):
    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.session_state.locked = True
        st.info("Please wait while the command is sent...")

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

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

        # st.session_state.locked = False

        print("Waiting for sensor data...")

        if sensor_data:
            st.success("Command sent successfully!")
            plot_spectra(sensor_data)
            st.write("Sensor Data Received:", sensor_data)