[FIX] Ignore real and imaginary scans in ADNI (aramis-lab#1029)

* log dcm2niix command in debug or warning mode depending on sucess or failure

* remove unused imports and explicit level of logging

* remove unused imports and explicit level of logging again

* Use Pathlib in path_to_bids and remove real and imaginary images generated by dcm2niix

* Apply suggestions from code review

clinica/iotools/bids_utils.py

@@ -833,10 +833,10 @@ def _build_dcm2niix_command(
     bids_sidecar: bool = True,
 ) -> list:
     """Generate the dcm2niix command from user inputs."""
-    command = ["dcm2niix", "-w", "0", "-f", output_fmt, "-o", output_dir]
+    command = ["dcm2niix", "-w", "0", "-f", output_fmt, "-o", str(output_dir)]
     command += ["-9", "-z", "y"] if compress else ["-z", "n"]
     command += ["-b", "y", "-ba", "y"] if bids_sidecar else ["-b", "n"]
-    command += [input_dir]
+    command += [str(input_dir)]
 
     return command
 
@@ -889,12 +889,16 @@ def run_dcm2niix(
         cprint(
             msg=(
                 "DICOM to BIDS conversion with dcm2niix failed:\n"
-                f"command: {command}\n"
+                f"command: {' '.join(command)}\n"
                 f"{completed_process.stdout.decode('utf-8')}"
             ),
             lvl="warning",
         )
         return False
+    cprint(
+        f"DICOM to BIDS conversion with dcm2niix failed:\ncommand: {' '.join(command)}\n",
+        lvl="debug",
+    )
     return True
 
 

clinica/iotools/converters/adni_to_bids/adni_modalities/adni_flair.py

@@ -40,10 +40,6 @@ def convert_adni_flair(
         If specified, it should be between 1 and the number of available CPUs.
         Default=1.
     """
-    from os import path
-
-    import pandas as pd
-
     from clinica.iotools.converters.adni_to_bids.adni_utils import (
         load_clinical_csv,
         paths_to_bids,
@@ -55,10 +51,11 @@ def convert_adni_flair(
         subjects = list(adni_merge.PTID.unique())
 
     cprint(
-        f"Calculating paths of FLAIR images. Output will be stored in {conversion_dir}."
+        f"Calculating paths of FLAIR images. Output will be stored in {conversion_dir}.",
+        lvl="info",
     )
     images = compute_flair_paths(source_dir, csv_dir, subjects, conversion_dir)
-    cprint("Paths of FLAIR images found. Exporting images into BIDS ...")
+    cprint("Paths of FLAIR images found. Exporting images into BIDS ...", lvl="info")
     # flair_paths_to_bids(images, dest_dir)
     paths_to_bids(
         images, destination_dir, "flair", mod_to_update=mod_to_update, n_procs=n_procs