Merge pull request #22 from gregory-halverson/main

upgrading to python 3.11 and tensorflow 2.19

Author: gregory-halverson

.github/workflows/ci.yml

@@ -13,7 +13,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ["3.10"]
+        python-version: ["3.10", "3.11"]
 
     steps:
       - name: Checkout repository

FLiESANN/run_FLiES_ANN_inference.py

@@ -70,8 +70,47 @@ def run_FLiES_ANN_inference(
         split_atypes_ctypes=split_atypes_ctypes
     )
 
+    # Convert DataFrame to numpy array and reshape for the model
+    inputs_array = inputs.values
+    
+    # Check what input shape the model expects and adapt accordingly
+    # Different TensorFlow/Keras versions may have different input requirements
+    try:
+        model_input_shape = ANN_model.input_shape
+        if len(model_input_shape) == 3:
+            # Model expects 3D input: (batch_size, sequence_length, features)
+            # Reshape from (batch_size, features) to (batch_size, 1, features)
+            inputs_array = inputs_array.reshape(inputs_array.shape[0], 1, inputs_array.shape[1])
+            expects_3d = True
+        elif len(model_input_shape) == 2:
+            # Model expects 2D input: (batch_size, features)
+            # Keep the original 2D shape
+            expects_3d = False
+        else:
+            # Fallback: try 2D first
+            expects_3d = False
+    except (AttributeError, TypeError):
+        # If input_shape is not available, try 2D first
+        expects_3d = False
+    
     # Run inference using the ANN model
-    outputs = ANN_model.predict(inputs)
+    try:
+        outputs = ANN_model.predict(inputs_array)
+    except ValueError as e:
+        error_msg = str(e)
+        if not expects_3d and ("expected shape" in error_msg or "incompatible" in error_msg):
+            # Try reshaping to 3D if 2D failed
+            inputs_array = inputs.values  # Reset to original 2D shape
+            inputs_array = inputs_array.reshape(inputs_array.shape[0], 1, inputs_array.shape[1])
+            outputs = ANN_model.predict(inputs_array)
+            expects_3d = True
+        else:
+            raise e
+    
+    # Handle output dimensions based on input dimensions used
+    if expects_3d and len(outputs.shape) == 3:
+        outputs = outputs.squeeze(axis=1)
+    
     shape = COT.shape
 
     # Prepare the results dictionary

FLiESANN/version.txt

@@ -1 +1 @@
-1.4.2
+1.5.0

Processing FLiES with a raster and default parameters.ipynb

@@ -3,7 +3,7 @@ requires = ["setuptools>=60", "setuptools-scm>=8.0", "wheel"]
 
 [project]
 name = "FLiESANN"
-version = "1.4.2"
+version = "1.5.0"
 description = "Forest Light Environmental Simulator (FLiES) Radiative Transfer Model Artificial Neural Network (ANN) Implementation in Python"
 readme = "README.md"
 authors = [
@@ -15,7 +15,7 @@ classifiers = [
 ]
 dependencies = [
     "GEOS5FP>=1.1.1",
-    "keras==2.15",
+    "keras",
     "koppengeiger",
     "MCD12C1-2019-v006",
     "NASADEM>=1.1.1",
@@ -26,7 +26,7 @@ dependencies = [
     "sentinel-tiles",
     "solar-apparent-time",
     "sun-angles",
-    "tensorflow==2.15.1"
+    "tensorflow"
 ]
 
 requires-python = ">=3.10"