Merge pull request #962 from MouseLand/dev

Dev

Author: carsen-stringer

suite2p/extraction/dcnv.py

@@ -105,7 +105,7 @@ def preprocess(F: np.ndarray, baseline: str, win_baseline: float, sig_baseline:
         window (in seconds) for max filter
 
     sig_baseline : float
-        width of Gaussian filter in seconds
+        width of Gaussian filter in frames
 
     fs : float
         sampling rate per plane

suite2p/gui/drawroi.py

@@ -59,6 +59,8 @@ def masks_and_traces(ops, stat_manual, stat_orig):
         manual_roi_stats[n]["compact"] = 1
         manual_roi_stats[n]["footprint"] = 2
         manual_roi_stats[n]["manual"] = 1  # Add manual key
+        if "iplane" in stat_orig[0]:
+            manual_roi_stats[n]["iplane"] = stat_orig[0]["iplane"]
 
     # subtract neuropil and compute skew, std from F
     dF = F - ops["neucoeff"] * Fneu

suite2p/io/save.py

@@ -6,7 +6,8 @@
 import pathlib
 
 
-def save_mat(ops, stat, F, Fneu, spks, iscell, redcell):
+def save_mat(ops, stat, F, Fneu, spks, iscell, redcell,
+             F_chan2=None, Fneu_chan2=None):
     ops_matlab = ops.copy()
     if ops_matlab.get("date_proc"):
         try:
@@ -24,16 +25,30 @@ def save_mat(ops, stat, F, Fneu, spks, iscell, redcell):
 
     stat = np.array(stat, dtype=object)
 
-    scipy.io.savemat(
-        file_name=os.path.join(ops["save_path"], "Fall.mat"), mdict={
-            "stat": stat,
-            "ops": ops_matlab,
-            "F": F,
-            "Fneu": Fneu,
-            "spks": spks,
-            "iscell": iscell,
-            "redcell": redcell
-        })
+    if F_chan2 is None:
+        scipy.io.savemat(
+            file_name=os.path.join(ops["save_path"], "Fall.mat"), mdict={
+                "stat": stat,
+                "ops": ops_matlab,
+                "F": F,
+                "Fneu": Fneu,
+                "spks": spks,
+                "iscell": iscell,
+                "redcell": redcell
+            })
+    else:
+        scipy.io.savemat(
+            file_name=os.path.join(ops["save_path"], "Fall.mat"), mdict={
+                "stat": stat,
+                "ops": ops_matlab,
+                "F": F,
+                "Fneu": Fneu,
+                "spks": spks,
+                "iscell": iscell,
+                "redcell": redcell,
+                "F_chan2": F_chan2,
+                "Fneu_chan2": Fneu_chan2
+            })
 
 
 def compute_dydx(ops1):
@@ -205,8 +220,6 @@ def combined(save_folder, save=True):
             matpath = os.path.join(ops["save_path"], "Fall.mat")
             save_mat(ops, stat, F, Fneu, spks, iscell, redcell)
 
-    return stat, ops, F, Fneu, spks, iscell[:,
-                                            0], iscell[:,
-                                                       1], redcell[:,
-                                                                   0], redcell[:,
-                                                                               1], hasred
+    return (stat, ops, F, Fneu, spks, 
+            iscell[:,0], iscell[:,1], 
+            redcell[:,0], redcell[:,1], hasred)

suite2p/io/tiff.py

@@ -475,7 +475,7 @@ def ome_to_binary(ops):
         ops1[ix]["frames_per_folder"][0] += 1
         ops1[ix]["meanImg"] += im.astype(np.float32)
         reg_file[ix].write(bytearray(im))
-        gc.collect()
+        #gc.collect()
 
         if ik % 1000 == 0:
             print("%d frames of binary, time %0.2f sec." % (ik, time.time() - t0))
@@ -491,7 +491,7 @@ def ome_to_binary(ops):
             ix = iplanes[ik]
             ops1[ix]["meanImg_chan2"] += im.astype(np.float32)
             reg_file_chan2[ix].write(bytearray(im))
-            gc.collect()
+            #gc.collect()
 
             if ik % 1000 == 0:
                 print("%d frames of binary, time %0.2f sec." % (ik, time.time() - t0))

suite2p/run_s2p.py

@@ -223,7 +223,8 @@ def pipeline(f_reg, f_raw=None, f_reg_chan2=None, f_raw_chan2=None,
                 iscell = np.load(os.path.join(ops["save_path"], "iscell.npy"))
                 redcell = np.load(os.path.join(
                     ops["save_path"], "redcell.npy")) if ops["nchannels"] == 2 else []
-                io.save_mat(ops, stat, F, Fneu, spks, iscell, redcell)
+                io.save_mat(ops, stat, F, Fneu, spks, iscell, redcell,
+                            F_chan2, Fneu_chan2)
         else:
             print("no ROIs found, only ops.npy file saved")
     else: