Dev

echopype/mask/shoal.py

@@ -31,17 +31,17 @@
 import pathlib
 from typing import Union
 
-import numpy as np
+import dask.array as da
 import xarray as xr
 from dask_image.ndmorph import binary_closing, binary_opening
 
 WEILL_DEFAULT_PARAMETERS = {
-    "thr": -70,
+    "thr": -55,
     "maxvgap": 5,
     "maxhgap": 5,
-    "minvlen": 0,
-    "minhlen": 0,
-    "dask_chunking": {"ping_time": 1000, "range_sample": 1000},
+    "minvlen": 5,
+    "minhlen": 5,
+    "dask_chunking": {"ping_time": 100, "range_sample": 100},
 }
 
 
@@ -116,29 +116,50 @@ def _weill(
     minvlen = parameters["minvlen"]
     minhlen = parameters["minhlen"]
     dask_chunking = parameters["dask_chunking"]
+    dask_chunking = tuple(map(int, dask_chunking.values()))
 
     channel_Sv = source_Sv.sel(channel=desired_channel)
     Sv = channel_Sv["Sv"].chunk(dask_chunking)
+    print("Chunk sizes:", Sv.chunks)
 
-    mask = xr.where(Sv > thr, True, False).chunk(dask_chunking)
+    mask = xr.where(Sv > thr, True, False).chunk(dask_chunking).drop("channel")
+    print(tfc(mask))
+    dask_mask = da.from_array(mask)
 
     # close shoal gaps smaller than the specified box
-    if maxvgap > 0 & maxhgap > 0:
-        closing_array = np.ones(maxhgap, maxvgap)
-        mask = binary_closing(
-            mask,
+    if maxvgap > 0 and maxhgap > 0:
+        print("Closing\n")
+        closing_array = da.ones(shape=(maxhgap, maxvgap), dtype=bool)
+        dask_mask = binary_closing(
+            dask_mask,
             structure=closing_array,
             iterations=1,
-        )
+        ).compute()
+        print(tfc(dask_mask))
 
     # drop shoals smaller than the specified box
-    if minvlen > 0 & minhlen > 0:
-        opening_array = np.ones(minhlen, minhlen)
-        mask = binary_opening(
-            mask,
+
+    if minvlen > 0 and minhlen > 0:
+        print("Opening\n")
+        opening_array = da.ones(shape=(minhlen, minvlen), dtype=bool)
+        dask_mask = binary_opening(
+            dask_mask,
             structure=opening_array,
             iterations=1,
-        )
+        ).compute()
+        print(tfc(dask_mask))
+
+    mask.values = dask_mask
+
+    # if minvlen > 0 | minhlen > 0:
+    # values = mask.values
+    # label_image = dask_image.ndmeasure.label(values)
+    # print(label_image.values.unique())
+    # print(label_image)
 
-    mask = mask.drop("channel")
     return mask
+
+
+def tfc(mask):
+    count_true = mask.sum().compute().item()
+    return count_true

echopype/tests/conftest.py

@@ -20,8 +20,8 @@ def _setup_file(file_name):
         download_ftp_file(ftp, FTP_PARTIAL_PATH, file_name, TEST_DATA_FOLDER)
     return os.path.join(TEST_DATA_FOLDER, file_name)
 
-def download_ftp_file(ftp, remote_path, file_name, local_path):
 
+def download_ftp_file(ftp, remote_path, file_name, local_path):
     # Construct the full paths
     remote_file_path = os.path.join(remote_path, file_name)
     local_file_path = os.path.join(local_path, file_name)
@@ -103,6 +103,7 @@ def setup_test_data_jr179():
     file_name = "JR179-D20080410-T150637.raw"
     return _setup_file(file_name)
 
+
 def _setup_file(file_name):
     test_data_path = os.path.join(TEST_DATA_FOLDER, file_name)
     FTP_MAIN = "ftp://ftp.bas.ac.uk"
@@ -143,8 +144,27 @@ def raw_dataset_jr179(setup_test_data_jr179):
     ed = _get_raw_dataset(setup_test_data_jr179)
     return ed
 
+
 def _get_sv_dataset(file_path):
     ed = ep.open_raw(file_path, sonar_model="ek60")
     Sv = ep.calibrate.compute_Sv(ed).compute()
     return Sv
 
+
+@pytest.fixture(scope="session")
+def ed_ek_60_for_Sv():
+    bucket = "ncei-wcsd-archive"
+    base_path = "data/raw/Bell_M._Shimada/SH1707/EK60/"
+    filename = "Summer2017-D20170620-T011027.raw"
+    rawdirpath = base_path + filename
+
+    s3raw_fpath = f"s3://{bucket}/{rawdirpath}"
+    storage_opts = {"anon": True}
+    ed = ep.open_raw(s3raw_fpath, sonar_model="EK60", storage_options=storage_opts)  # type: ignore
+    return ed
+
+
+@pytest.fixture(scope="session")
+def ek60_Sv(ed_ek_60_for_Sv):
+    sv_echopype_EK60 = ep.calibrate.compute_Sv(ed_ek_60_for_Sv).compute()
+    return sv_echopype_EK60