Making FCU-Net compatible with 14.9

py4DSTEM/braggvectors/diskdetection_aiml.py

@@ -8,6 +8,8 @@
 import json
 import shutil
 import numpy as np
+from pathlib import Path
+
 
 from scipy.ndimage import gaussian_filter
 from time import time
@@ -437,9 +439,9 @@ def find_Bragg_disks_aiml_serial(
         raise ImportError("Import Error: Please install crystal4D before proceeding")
 
     # Make the peaks PointListArray
-    # dtype = [('qx',float),('qy',float),('intensity',float)]
-    peaks = BraggVectors(datacube.Rshape, datacube.Qshape)
-
+    dtype = [("qx", float), ("qy", float), ("intensity", float)]
+    # peaks = BraggVectors(datacube.Rshape, datacube.Qshape)
+    peaks = PointListArray(dtype=dtype, shape=(datacube.R_Nx, datacube.R_Ny))
     # check that the filtered DP is the right size for the probe kernel:
     if filter_function:
         assert callable(filter_function), "filter_function must be callable"
@@ -518,7 +520,7 @@ def find_Bragg_disks_aiml_serial(
             subpixel=subpixel,
             upsample_factor=upsample_factor,
             filter_function=filter_function,
-            peaks=peaks.vectors_uncal.get_pointlist(Rx, Ry),
+            peaks=peaks.get_pointlist(Rx, Ry),
             model_path=model_path,
         )
     t2 = time() - t0
@@ -884,7 +886,7 @@ def _get_latest_model(model_path=None):
             + "https://www.tensorflow.org/install"
             + "for more information"
         )
-    from py4DSTEM.io.google_drive_downloader import download_file_from_google_drive
+    from py4DSTEM.io.google_drive_downloader import gdrive_download
 
     tf.keras.backend.clear_session()
 
@@ -894,7 +896,12 @@ def _get_latest_model(model_path=None):
         except:
             pass
         # download the json file with the meta data
-        download_file_from_google_drive("FCU-Net", "./tmp/model_metadata.json")
+        gdrive_download(
+            "FCU-Net",
+            destination="./tmp/",
+            filename="model_metadata.json",
+            overwrite=True,
+        )
         with open("./tmp/model_metadata.json") as f:
             metadata = json.load(f)
             file_id = metadata["file_id"]
@@ -918,7 +925,8 @@ def _get_latest_model(model_path=None):
         else:
             print("Checking the latest model on the cloud... \n")
             filename = file_path + file_type
-            download_file_from_google_drive(file_id, filename)
+            filename = Path(filename)
+            gdrive_download(file_id, destination="./tmp", filename=filename.name)
             try:
                 shutil.unpack_archive(filename, "./tmp", format="zip")
             except:

py4DSTEM/braggvectors/diskdetection_aiml_cuda.py

@@ -124,8 +124,9 @@ def find_Bragg_disks_aiml_CUDA(
     """
 
     # Make the peaks PointListArray
-    # dtype = [('qx',float),('qy',float),('intensity',float)]
-    peaks = BraggVectors(datacube.Rshape, datacube.Qshape)
+    dtype = [("qx", float), ("qy", float), ("intensity", float)]
+    # peaks = BraggVectors(datacube.Rshape, datacube.Qshape)
+    peaks = PointListArray(dtype=dtype, shape=(datacube.R_Nx, datacube.R_Ny))
 
     # check that the filtered DP is the right size for the probe kernel:
     if filter_function:
@@ -221,7 +222,7 @@ def find_Bragg_disks_aiml_CUDA(
             subpixel=subpixel,
             upsample_factor=upsample_factor,
             filter_function=filter_function,
-            peaks=peaks.vectors_uncal.get_pointlist(Rx, Ry),
+            peaks=peaks.get_pointlist(Rx, Ry),
             get_maximal_points=get_maximal_points,
             blocks=blocks,
             threads=threads,

py4DSTEM/io/google_drive_downloader.py

@@ -57,7 +57,7 @@
     ),
     "small_dm3_3Dstack": ("small_dm3_3Dstack.dm3", "1B-xX3F65JcWzAg0v7f1aVwnawPIfb5_o"),
     "FCU-Net": (
-        "filename.name",
+        "model_metadata.json",
         "1-KX0saEYfhZ9IJAOwabH38PCVtfXidJi",
     ),
     "small_datacube": (
@@ -221,7 +221,8 @@ def gdrive_download(
         kwargs = {"fuzzy": True}
         if id_ in file_ids:
             f = file_ids[id_]
-            filename = f[0]
+            # Use the name in the collection filename passed
+            filename = filename if filename is not None else f[0]
             kwargs["id"] = f[1]
 
         # if its not in the list of files we expect

setup.py

@@ -21,7 +21,7 @@
     author_email="[email protected]",
     license="GNU GPLv3",
     keywords="STEM 4DSTEM",
-    python_requires=">=3.9,<=3.12",
+    python_requires=">=3.9,<3.13",
     install_requires=[
         "numpy >= 1.19",
         "scipy >= 1.5.2",
@@ -47,12 +47,18 @@
         "ipyparallel": ["ipyparallel >= 6.2.4", "dill >= 0.3.3"],
         "cuda": ["cupy >= 10.0.0"],
         "acom": ["pymatgen >= 2022", "mp-api == 0.24.1"],
-        "aiml": ["tensorflow == 2.4.1", "tensorflow-addons <= 0.14.0", "crystal4D"],
+        "aiml": [
+            "tensorflow <= 2.10.0",
+            "tensorflow-addons <= 0.16.1",
+            "crystal4D",
+            "typeguard == 2.7",
+        ],
         "aiml-cuda": [
-            "tensorflow == 2.4.1",
-            "tensorflow-addons <= 0.14.0",
+            "tensorflow <= 2.10.0",
+            "tensorflow-addons <= 0.16.1",
             "crystal4D",
             "cupy >= 10.0.0",
+            "typeguard == 2.7",
         ],
         "numba": ["numba >= 0.49.1"],
     },