--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/target_screen.py	Thu Sep 26 13:03:05 2024 +0000
@@ -0,0 +1,59 @@
+import argparse
+
+import numpy as np
+import pandas as pd
+
+
+def mz_match(marker, peak, ppm):
+    return np.abs(marker - peak) <= ((peak + marker) / 2) * ppm * 1e-06
+
+
+def rt_match(marker, peak, tol):
+    return np.abs(marker - peak) <= tol
+
+
+def find_matches(peaks, markers, ppm, rt_tol):
+    # Create a meshgrid of all combinations of mz and rt values
+    marker_mz = markers['mz'].values[:, np.newaxis]
+    peak_mz = peaks['mz'].values
+    marker_rt = markers['rt'].values[:, np.newaxis]
+    peak_rt = peaks['rt'].values
+
+    # Calculate mz and rt matches
+    mz_matches = mz_match(marker_mz, peak_mz, ppm)
+    rt_matches = rt_match(marker_rt, peak_rt, rt_tol)
+
+    # Find the indices where both mz and rt match
+    match_indices = np.where(mz_matches & rt_matches)
+
+    # Create a DataFrame of hits
+    matched_markers = markers.iloc[match_indices[0]].reset_index(drop=True)
+    matched_peaks = peaks.iloc[match_indices[1]].reset_index(drop=True)
+    hits = pd.concat([matched_markers[['formula']].reset_index(drop=True), matched_peaks], axis=1)
+
+    # Calculate mz and rt differences
+    hits['mz_diff'] = np.abs(matched_markers['mz'].values - matched_peaks['mz'].values)
+    hits['rt_diff'] = np.abs(matched_markers['rt'].values - matched_peaks['rt'].values)
+
+    return hits
+
+
+def main():
+    parser = argparse.ArgumentParser(description='Find matches between peaks and markers.')
+    parser.add_argument('--peaks', required=True, help='Path to the peaks parquet file.')
+    parser.add_argument('--markers', required=True, help='Path to the markers CSV file.')
+    parser.add_argument('--output', required=True, help='Path to the output TSV file.')
+    parser.add_argument('--ppm', type=int, default=5, help='PPM tolerance for mz matching.')
+    parser.add_argument('--rt_tol', type=int, default=10, help='RT tolerance for rt matching.')
+    args = parser.parse_args()
+
+    peaks = pd.read_parquet(args.peaks)
+    markers = pd.read_csv(args.markers, sep='\t')
+
+    hits = find_matches(peaks, markers, args.ppm, args.rt_tol)
+
+    hits.to_csv(args.output, sep='\t', index=False)
+
+
+if __name__ == "__main__":
+    main()