import reorg
Browse files
app.py
CHANGED
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@@ -1,13 +1,7 @@
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# For neural networks
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import keras
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# For random calculations
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import numpy
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import gradio
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import pandas
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# New for geometry creation
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import glob
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import os
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import shutil
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@@ -15,21 +9,13 @@ import stat
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import math
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import platform
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import scipy.spatial
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# Disable eager execution because its bad
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from tensorflow.python.framework.ops import disable_eager_execution
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disable_eager_execution()
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# Big bunch of geometry stuff
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import glob
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import os
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import shutil
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import stat
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import math
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import platform
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import scipy.spatial
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class Mesh:
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def __init__(self):
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# Define blank values
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@@ -1240,10 +1226,6 @@ class Network(object):
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return table
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import plotly.graph_objects as go
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def plotly_fig(values):
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X, Y, Z = numpy.mgrid[0:1:32j, 0:1:32j, 0:1:32j]
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fig = go.Figure(data=go.Volume(
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@@ -1302,8 +1284,7 @@ def change_textbox(choice, length, height, width, diameter):
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elif choice == "cone":
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return [gradio.Slider.update(visible=True), gradio.Slider.update(visible=False), gradio.Slider.update(visible=True), gradio.Slider.update(visible=False), gradio.Plot.update(fig)]
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import random
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def randomize_analysis(choice):
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if choice == "Construct Shape from Parameters":
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import keras
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import numpy
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import gradio
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import pandas
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import glob
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import os
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import shutil
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import math
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import platform
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import scipy.spatial
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import plotly.graph_objects as go
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import random
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# Disable eager execution because its bad
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from tensorflow.python.framework.ops import disable_eager_execution
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disable_eager_execution()
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class Mesh:
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def __init__(self):
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# Define blank values
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return table
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def plotly_fig(values):
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X, Y, Z = numpy.mgrid[0:1:32j, 0:1:32j, 0:1:32j]
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fig = go.Figure(data=go.Volume(
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elif choice == "cone":
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return [gradio.Slider.update(visible=True), gradio.Slider.update(visible=False), gradio.Slider.update(visible=True), gradio.Slider.update(visible=False), gradio.Plot.update(fig)]
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+
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def randomize_analysis(choice):
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if choice == "Construct Shape from Parameters":
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