FIX, REFAC: use f-string and os.path.join() for paths concat

decloud/analysis/crga_al_analysis.py

@@ -26,6 +26,7 @@ This scripts summarizes the number of samples that we can get from an Acquisitio
 suited for single optical image reconstruction from date SAR/optical pair, for different
 parameters of the AcquisitionsLayout
 """
+import os
 import argparse
 import logging
 from decloud.acquisitions.sensing_layout import AcquisitionsLayout, S1Acquisition, S2Acquisition
@@ -139,8 +140,8 @@ for max_s1s2_gap_hours in params.maxgaps1s2_list:
                     np_counts[pos[0], pos[1]] += nb_samples_in_patch
 
                 # Export
-                out_fn = "count_gap{}_range{}-{}_{}.tif".format(max_s1s2_gap_hours, int_radius, ext_radius, tile_name)
-                out_fn = system.pathify(params.out_dir) + out_fn
+                out_fn = f"count_gap{max_s1s2_gap_hours}_range{int_radius}-{ext_radius}_{tile_name}.tif"
+                out_fn = os.path.join(params.out_dir, out_fn)
                 logging.info("Saving %s", out_fn)
                 raster.save_numpy_array_as_raster(ref_fn=ref_fn, np_arr=np_counts, out_fn=out_fn, scale=scale)
 

decloud/analysis/orbits_analysis.py

@@ -24,6 +24,7 @@ DEALINGS IN THE SOFTWARE.
 """
 Analyze the S1 and S2 orbits
 """
+import os
 import argparse
 import numpy as np
 import logging
@@ -80,5 +81,5 @@ for tile_name, tile_handler in th.items():
 
     # Export with pyotb
     out = np.add(initialized_raster, histo_array)  # this is a pyotb object
-    out_fn = system.pathify(params.out_dir) + "{}_s1s2gap_hist.tif".format(tile_name)
+    out_fn = os.path.join(params.out_dir, f"{tile_name}_s1s2gap_hist.tif")
     out.write(out_fn)

decloud/analysis/patches_coverage.py

@@ -24,6 +24,7 @@ DEALINGS IN THE SOFTWARE.
 """
 Compute the number of S1 and S2 images used for each patch.
 """
+import os
 import argparse
 import logging
 import numpy as np
@@ -59,7 +60,7 @@ scale = float(params.patch_size) / float(constants.PATCHSIZE_REF)
 for al_bname, al in als:
     for tile_name, tile_handler in th.items():
         # Output files prefix
-        out_prefix = system.pathify(params.out_dir) + tile_name + "_" + al_bname
+        out_prefix = os.join(params.out_dir, tile_name + "_" + al_bname)
 
         # Reference raster grid
         ref_fn = tile_handler.s2_images[0].clouds_stats_fn
@@ -94,6 +95,6 @@ for al_bname, al in als:
 
         # Export
         for key in ["s1", "s2"]:
-            out_fn = "{}_{}_freq.tif".format(out_prefix, key)
+            out_fn = f"{out_prefix}_{key}_freq.tif"
             logging.info("Saving %s", out_fn)
             raster.save_numpy_array_as_raster(ref_fn=ref_fn, np_arr=np_counts[key], out_fn=out_fn, scale=scale)

decloud/analysis/tile_coverage.py

@@ -24,6 +24,7 @@ DEALINGS IN THE SOFTWARE.
 """
 Compute cloud coverage and pixel validity from an input set of tiles
 """
+import os
 import argparse
 import logging
 import numpy as np
@@ -46,7 +47,7 @@ def compute_stats(tile_name, tile_handler):
     :param tile_handler: Tile handler instance
     """
     ref_fn = tile_handler.s2_images[0].clouds_stats_fn
-    out_prefix = system.pathify(params.out_dir) + tile_name
+    out_prefix = os.path.join(params.out_dir, tile_name)
 
     # Statistics
     cloud_cov = np.sum(np.multiply(tile_handler.s2_images_validity, tile_handler.s2_images_cloud_coverage), axis=0)