Nopca

README.md

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 The plan for the open house event is to host a Jupyter Notebooks server on the Raspberry Pi, which can read data from the attached sensors and perform simple data processing and analysis on previously accumulated data.
+
+## Protocol
+* Pour the liquid to a cup (drinkable portion, like 150ml to 300ml)
+* Put sensors into a cup.
+* Wait for 1 min
+* read values (see the code for duration/frequency)
+* For non-water liquid, wash sensors with tap water (and then sm water)
+* Wipe liquid from conductivity sensor (but keep PH sensor wet)
+* Repeat the process for other liquids
+
+

plot_data.py

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+
+import pickle
+import numpy as np
+import matplotlib.pyplot as plt
+
+def plot_data_from_pickle(pickle_file='data.pickle', output_image='raw_data_plot.png'):
+    """
+    Loads data from a pickle file, and plots the mean of the first two channels against each other.
+
+    Args:
+        pickle_file (str): Path to the input pickle file.
+        output_image (str): Path to save the output PNG image.
+    """
+    with open(pickle_file, 'rb') as f:
+        data = pickle.load(f)
+
+    # Remove the specified data point if it exists
+    if "20250614_180011_test" in data:
+        del data["20250614_180011_test"]
+
+    # Extract the means of the first two channels and labels
+    labels = list(data.keys())
+    channel0_means = []
+    channel1_means = []
+    for key in labels:
+        # data[key] is a dict {0: [...], 1: [...], 2: [...]}
+        channel0_means.append(np.mean(data[key][0]))
+        channel1_means.append(np.mean(data[key][1]))
+
+    # Create a scatter plot
+    plt.figure(figsize=(10, 8))
+    plt.scatter(channel0_means, channel1_means)
+
+    # Add labels to the points
+    for i, label in enumerate(labels):
+        plt.annotate(label, (channel0_means[i], channel1_means[i]))
+
+    plt.xlabel('Mean of Channel 0')
+    plt.ylabel('Mean of Channel 1')
+    plt.title('Sensor Data (Mean of First Two Channels)')
+    plt.grid(True)
+
+    # Save the plot
+    plt.savefig(output_image)
+    print(f"Plot saved to {output_image}")
+
+if __name__ == '__main__':
+    plot_data_from_pickle()