Convert Crystfel feature list to pandas Dataframe

examples/find_peaks.py

@@ -9,4 +9,7 @@ f = h5py.File(os.path.join(THIS_DIR, 'monolithic_img_1.h5'), 'r')
 arr = f['data/data'][()]
 print("Image shape:", arr.shape)
 
-find_peaks_single_panel(arr, os.path.join(THIS_DIR, '1panel.geom'))
+peaks_tbl = find_peaks_single_panel(arr, os.path.join(THIS_DIR, '1panel.geom'))
+
+print(f"Found {len(peaks_tbl)} peaks")
+print(peaks_tbl.head())

pycrystfel/bindings.pyx

 import os
 import numpy as np
+import pandas as pd
 
-from libc.stdint cimport uintptr_t
+cimport cython
 from libc.stdlib cimport malloc, free
 cimport numpy as cnp
 
@@ -19,6 +20,35 @@ def inspect_geom_file(path):
     print("photon energy:", beam.photon_energy)
     crystfel.free_detector_geometry(det)
 
+cdef featurelist_to_dataframe(crystfel.ImageFeatureList *flist):
+    cdef:
+        int i, nfeat = crystfel.image_feature_count(flist)
+        crystfel.imagefeature *feat
+        cnp.ndarray[cnp.npy_double, ndim=1] ss, fs, rx, ry, rz, it
+
+    ss = np.zeros(nfeat, np.double)
+    fs = np.zeros(nfeat, np.double)
+    rx = np.zeros(nfeat, np.double)
+    ry = np.zeros(nfeat, np.double)
+    rz = np.zeros(nfeat, np.double)
+    it = np.zeros(nfeat, np.double)
+
+    with cython.boundscheck(False), cython.wraparound(False):
+        for i in range(nfeat):
+            feat = crystfel.image_get_feature(flist, i)
+            ss[i] = feat.ss
+            fs[i] = feat.fs
+            rx[i] = feat.rx
+            ry[i] = feat.ry
+            rz[i] = feat.rz
+            it[i] = feat.intensity
+
+    return pd.DataFrame({
+        'ss': ss, 'fs': fs, 'rx': rx, 'ry': ry, 'rz': rz, 'intensity': it,
+    })
+
+
+
 def find_peaks_single_panel(cnp.ndarray[cnp.npy_float, ndim=2] data, str geom_file):
     cdef:
         crystfel.beam_params beam
@@ -40,9 +70,4 @@ def find_peaks_single_panel(cnp.ndarray[cnp.npy_float, ndim=2] data, str geom_fi
     )
     print("Done peak search")
 
-    npeaks = crystfel.image_feature_count(image.features)
-    print(f"Found {npeaks} peaks")
-
-    for i in range(min(10, npeaks)):
-        peak = crystfel.image_get_feature(image.features, i)
-        print(f"Peak {i}: ({peak.ss}, {peak.fs})\t Intensity={peak.intensity}")
+    return featurelist_to_dataframe(image.features)