GraphingIEEE/csvtoepsgraphV4.py at main · DeepeshPatidar/GraphingIEEE · GitHub

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# This script processes subfolders, reads all CSV files from each subfolder,
# combines them into a single IEEE-style plot, and saves the output in the same subfolder.

import os
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker

# ================= IEEE STYLE (No LaTeX) =================
plt.rcParams.update({
    "text.usetex": False,
    "font.family": "serif",
    "font.serif": ["Latin Modern Roman", "Times New Roman"],
    "font.size": 8,
    "axes.labelsize": 8,
    "xtick.labelsize": 7,
    "ytick.labelsize": 7,
    "axes.linewidth": 0.8,
    "axes.edgecolor": "black",
    "axes.labelcolor": "black",
    "xtick.color": "black",
    "ytick.color": "black",
})
# ==========================================================

parent_folder = r"D:\Project\IITDelhi\onosokki\till\log10\testinput"

# Get all subfolders
subfolders = [f for f in os.listdir(parent_folder)
              if os.path.isdir(os.path.join(parent_folder, f))]

colors = ['blue', 'red', 'magenta', 'green', 'purple', 'brown']

for subfolder_name in subfolders:
    subfolder_path = os.path.join(parent_folder, subfolder_name)

    # Get all CSV files in this subfolder
    csv_files = [f for f in os.listdir(subfolder_path)
                 if f.lower().endswith(".csv")]

    if len(csv_files) == 0:
        print(f"⏭️  Skipping {subfolder_name} (No CSV files found)")
        continue

    print(f"📁 Processing {subfolder_name} ({len(csv_files)} files)...")

    # ============== IEEE FIGURE ==================
    fig, ax = plt.subplots(figsize=(3.5, 2.5))

    max_final_time = 0
    plot_count = 0

    for idx, fname in enumerate(csv_files):
        csv_path = os.path.join(subfolder_path, fname)

        try:
            df = pd.read_csv(csv_path)
        except Exception as e:
            print(f"  ⚠️  Error reading {fname}: {e}")
            continue

        # Check if required columns exist
        if "Time" not in df.columns or "dB(A)" not in df.columns:
            print(f"  ⚠️  {fname} - Missing 'Time' or 'dB(A)' columns")
            continue

        time = pd.to_numeric(df["Time"], errors="coerce")
        spl = pd.to_numeric(df["dB(A)"], errors="coerce")

        # Remove rows with NaN values
        valid = ~(time.isna() | spl.isna())
        time = time[valid].reset_index(drop=True)
        spl = spl[valid].reset_index(drop=True)

        if len(time) == 0:
            print(f"  ⚠️  {fname} - No numeric data")
            continue

        # Use color cycling if more than 6 files
        color = colors[idx % len(colors)]
        ax.plot(time, spl, color=color, linewidth=1.2,
                label=f"Run {plot_count + 1}")
        max_final_time = max(max_final_time, time.max())
        plot_count += 1

    if plot_count == 0:
        print(f"  ❌ {subfolder_name} - No valid CSV files to plot")
        plt.close()
        continue

    ax.set_xlabel("Time (s)")
    ax.set_ylabel("SPL dB(A)")
    ax.legend(loc='best', fontsize=6)

    # Set X-axis to show fewer, readable labels (every 2 seconds)
    ax.xaxis.set_major_locator(ticker.MultipleLocator(2.0))
    ax.xaxis.set_minor_locator(ticker.MultipleLocator(0.5))
    ax.minorticks_on()

    # Force the end value to appear on x-axis
    ax.set_xlim(left=0, right=max_final_time)

    # Create custom ticks
    max_tick = int(max_final_time / 2.0) * 2.0
    custom_ticks = list(range(0, int(max_tick) + 1, 2))

    if max_final_time not in custom_ticks and max_final_time != max_tick:
        custom_ticks.append(max_final_time)

    custom_ticks.sort()
    ax.set_xticks(custom_ticks)

    # Grid
    ax.grid(True, which='major', linestyle='-', linewidth=0.4, alpha=0.5, color='gray')
    ax.grid(True, which='minor', linestyle=':', linewidth=0.4, alpha=0.5, color='gray')

    plt.tight_layout(pad=0.2)

    # Save in the same subfolder
    output_name = f"{subfolder_name}_combined"

    plt.savefig(os.path.join(subfolder_path, output_name + ".eps"),
                format="eps", bbox_inches="tight", dpi=1200)
    plt.savefig(os.path.join(subfolder_path, output_name + ".pdf"),
                format="pdf", bbox_inches="tight", dpi=1200)

    plt.close()

    print(f"  ✅ Combined plot created: {output_name}")

print("\n✅ All subfolders processed!")