🔀 Merge branch 'model/with_arthern2006accumulation' (#151)

Closes #151 Train and tune ESRGAN with Antarctic Snow Accumulation input.
weiji14 · Jun 18, 2019 · baa12ce · baa12ce
2 parents 3e2c512 + e8ae274
commit baa12ce
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Showing 8 changed files with 4,208 additions and 3,080 deletions.
diff --git a/deepbedmap.ipynb b/deepbedmap.ipynb
diff --git a/deepbedmap.py b/deepbedmap.py
diff --git a/features/environment.py b/features/environment.py
@@ -68,6 +68,7 @@ def _quick_download_lowres_misc_datasets():
             "misc/REMA_100m_dem",
             "misc/REMA_200m_dem_filled",
             "misc/MEaSUREs_IceFlowSpeed_450m",
+            "misc/Arthern_accumulation_bedmap2_grid1",
         ]:
 
             if not os.path.exists(path=f"{geotiff}.tif"):

diff --git a/features/steps/test_deepbedmap.py b/features/steps/test_deepbedmap.py
@@ -19,19 +19,19 @@ def get_model_input_raster_images(context):
     ):
         quilt.install(package="weiji14/deepbedmap/model/test", force=True)
         pkg = quilt.load(pkginfo="weiji14/deepbedmap/model/test")
-        input_tiles = pkg.X_tile(), pkg.W1_tile(), pkg.W2_tile()
+        input_tiles = pkg.X_tile(), pkg.W1_tile(), pkg.W2_tile(), pkg.W3_tile()
     else:
         input_tiles = context.deepbedmap.get_deepbedmap_model_inputs(
             window_bound=context.window_bound
         )
-    context.X_tile, context.W1_tile, context.W2_tile = input_tiles
+    context.X_tile, context.W1_tile, context.W2_tile, context.W3_tile = input_tiles
 
 
 @when("pass those images into our trained neural network model")
 def predict_using_trained_neural_network(context):
     model = context.deepbedmap.load_trained_model()
     context.Y_hat = model.forward(
-        x=context.X_tile, w1=context.W1_tile, w2=context.W2_tile
+        x=context.X_tile, w1=context.W1_tile, w2=context.W2_tile, w3=context.W3_tile
     ).array