Update app.py

app.py

@@ -13,6 +13,30 @@ import plotly.graph_objects as go
 import random
 from huggingface_hub import from_pretrained_keras
 
+def load_data():
+
+  from datasets import load_dataset
+
+  data = load_dataset("cmudrc/wave-energy", data_files="data.csv", split='train').to_pandas()
+
+  # Open all the files we downloaded at the beginning and take out hte good bits
+  curves = data.iloc[:, [i for i in range(1, 3*64+1)]]
+  geometry = data.iloc[:, [i for i in range(1 + 3*64, 1 + 3*64 + 32**3)]]
+  S = 5
+  N = 1000
+  D = 3
+  F = 64
+  G = 32
+
+  flattened_curves = curves.values / 1000000
+  curvey_curves = [c.reshape([3, 64]) for c in flattened_curves]
+
+  flattened_geometry = geometry.values
+  round_geometry = [g.reshape([32, 32, 32]) for g in flattened_geometry]
+
+  # Return good bits to user
+  return curvey_curves, round_geometry, S, N, D, F, G, flattened_curves, flattened_geometry
+
 # Disable eager execution because its bad
 from tensorflow.python.framework.ops import disable_eager_execution
 disable_eager_execution()
@@ -1073,28 +1097,28 @@ def make_voxels(shape, length, height, width, diameter):
     return plotly_fig(make_voxels_without_figure(shape, length, height, width, diameter))
 
 # This function loads a fuckton of data
-def load_data():
-    # Open all the files we downloaded at the beginning and take out hte good bits
-    curves = numpy.load('data_curves.npz')['curves']
-    geometry = numpy.load('data_geometry.npz')['geometry']
-    constants = numpy.load('constants.npz')
-    S = constants['S']
-    N = constants['N']
-    D = constants['D']
-    F = constants['F']
-    G = constants['G']
-
-    # Some of the good bits need additional processining
-    new_curves = numpy.zeros((S*N, D * F))
-    for i, curveset in enumerate(curves):
-        new_curves[i, :] = curveset.T.flatten() / 1000000
-
-    new_geometry = numpy.zeros((S*N, G * G * G))
-    for i, geometryset in enumerate(geometry):
-        new_geometry[i, :] = geometryset.T.flatten()
-
-    # Return good bits to user
-    return curves, geometry, S, N, D, F, G, new_curves, new_geometry
+# def load_data():
+#     # Open all the files we downloaded at the beginning and take out hte good bits
+#     curves = numpy.load('data_curves.npz')['curves']
+#     geometry = numpy.load('data_geometry.npz')['geometry']
+#     constants = numpy.load('constants.npz')
+#     S = constants['S']
+#     N = constants['N']
+#     D = constants['D']
+#     F = constants['F']
+#     G = constants['G']
+
+#     # Some of the good bits need additional processining
+#     new_curves = numpy.zeros((S*N, D * F))
+#     for i, curveset in enumerate(curves):
+#         new_curves[i, :] = curveset.T.flatten() / 1000000
+
+#     new_geometry = numpy.zeros((S*N, G * G * G))
+#     for i, geometryset in enumerate(geometry):
+#         new_geometry[i, :] = geometryset.T.flatten()
+
+#     # Return good bits to user
+#     return curves, geometry, S, N, D, F, G, new_curves, new_geometry
 
 curves, geometry, S, N, D, F, G, new_curves, new_geometry = load_data()