app.py

import keras
import numpy
import gradio
import pandas
import glob
import os
import shutil
import math
import platform
import scipy.spatial
import plotly.graph_objects as go
import random
from huggingface_hub import from_pretrained_keras

def load_data():

  from datasets import load_dataset

  S = 5
  N = 1000
  D = 3
  F = 64
  G = 32

  data = load_dataset("cmudrc/wave-energy", data_files=["data.zip"], split='train')
  geometry = numpy.reshape(data['geometry'], (S*N, G*G*G))
  curves = numpy.reshape(data['curves'], (S*N, D*F))
  return None, None, S, N, D, F, G, curves, geometry

# Disable eager execution because its bad
from tensorflow.python.framework.ops import disable_eager_execution
disable_eager_execution()

class Mesh:
    def __init__(self):
        # Define blank values
        self.np = 0
        self.nf = 0
        self.X = []
        self.Y = []
        self.Z = []
        self.P = []

    def combine_meshes(self, ob1, ob2):
        # Check for largest mesh
        if ob1.nf < ob2.nf:
            coin_test = ob1.make_coin()
            coin_target = ob2.make_coin()
        else:
            coin_test = ob2.make_coin()
            coin_target = ob1.make_coin()
        # Check for duplicate panels
        deletion_list = []
        for iF in range(numpy.size(coin_test[1, 1, :])):
            panel_test = coin_test[:, :, iF]
            for iFF in range(numpy.size(coin_target[1, 1, :])):
                panel_target = coin_target[:, :, iFF]
                if numpy.sum(panel_test == panel_target) == 12:
                    coin_target = numpy.delete(coin_target, iFF, 2)
                    deletion_list.append(iF)
        coin_test = numpy.delete(coin_test, deletion_list, 2)

        # Concatenate unique meshes
        coin = numpy.concatenate((coin_test, coin_target), axis=2)
        self.np = numpy.size(coin[1, 1, :]) * 4
        self.nf = numpy.size(coin[1, 1, :])
        self.X = numpy.zeros(numpy.size(coin[1, 1, :]) * 4)
        self.Y = numpy.zeros(numpy.size(coin[1, 1, :]) * 4)
        self.Z = numpy.zeros(numpy.size(coin[1, 1, :]) * 4)
        self.P = numpy.zeros((numpy.size(coin[1, 1, :]), 4), dtype=int)

        iP = 0
        for iF in range(numpy.size(coin[1, 1, :])):
            for iC in range(4):
                self.X[iP] = coin[0, iC, iF]
                self.Y[iP] = coin[1, iC, iF]
                self.Z[iP] = coin[2, iC, iF]
                iP += 1
            self.P[iF, 0] = 1 + iF * 4
            self.P[iF, 1] = 2 + iF * 4
            self.P[iF, 2] = 3 + iF * 4
            self.P[iF, 3] = 4 + iF * 4

    def make_coin(self):
        coin = numpy.zeros((3, 4, self.nf))
        for iF in range(self.nf):
            for iC in range(4):
                coin[0, iC, iF] = self.X[self.P[iF, iC] - 1]
                coin[1, iC, iF] = self.Y[self.P[iF, iC] - 1]
                coin[2, iC, iF] = self.Z[self.P[iF, iC] - 1]
        return coin

    def delete_horizontal_panels(self):
        coin = self.make_coin()
        apex = numpy.min(self.Z)
        zLoc = numpy.zeros(4)
        deletion_list = []

        # Check every panel for horizontality and higher position than lowest point
        for iP in range(self.nf):
            for iC in range(4):
                zLoc[iC] = coin[2, iC, iP]
            if numpy.abs(numpy.mean(zLoc) - zLoc[0]) < 0.001 and numpy.mean(zLoc) > apex:
                deletion_list.append(iP)

        # Delete selected panels
        coin = numpy.delete(coin, deletion_list, 2)

        # Remake mesh
        self.np = numpy.size(coin[1, 1, :]) * 4
        self.nf = numpy.size(coin[1, 1, :])
        self.X = numpy.zeros(numpy.size(coin[1, 1, :]) * 4)
        self.Y = numpy.zeros(numpy.size(coin[1, 1, :]) * 4)
        self.Z = numpy.zeros(numpy.size(coin[1, 1, :]) * 4)
        self.P = numpy.zeros((numpy.size(coin[1, 1, :]), 4), dtype=int)

        iP = 0
        for iF in range(numpy.size(coin[1, 1, :])):
            for iC in range(4):
                self.X[iP] = coin[0, iC, iF]
                self.Y[iP] = coin[1, iC, iF]
                self.Z[iP] = coin[2, iC, iF]
                iP += 1
            self.P[iF, 0] = 1 + (iF) * 4
            self.P[iF, 1] = 2 + (iF) * 4
            self.P[iF, 2] = 3 + (iF) * 4
            self.P[iF, 3] = 4 + (iF) * 4




def writeMesh(msh, filename):
    with open(filename, 'w') as f:
        f.write('{:d}\n'.format(msh.np))
        f.write('{:d}\n'.format(msh.nf))
        for iP in range(msh.np):
            f.write('  {:.7f}  {:.7f}  {:.7f}\n'.format(msh.X[iP], msh.Y[iP], msh.Z[iP]))
        for iF in range(msh.nf):
            f.write('  {:d}  {:d}  {:d}  {:d}\n'.format(msh.P[iF, 0], msh.P[iF, 1], msh.P[iF, 2], msh.P[iF, 3]))
        return None



class box:
    def __init__(self, length, width, height, cCor):
        self.length = length
        self.width = width
        self.height = height
        self.xC = cCor[0]
        self.yC = cCor[1]
        self.zC = cCor[2]
        self.name = 'box'
        self.panelize()
        self.translate(self.xC, self.yC, self.zC)

    def panelize(self):
        self.nf = 6
        self.np = 8
        self.X = numpy.array(
            [-self.length / 2.0, self.length / 2.0, -self.length / 2.0, self.length / 2.0, -self.length / 2.0,
             self.length / 2.0, -self.length / 2.0, self.length / 2.0])
        self.Y = numpy.array([self.width / 2.0, self.width / 2.0, self.width / 2.0, self.width / 2.0, -self.width / 2.0,
                              -self.width / 2.0, -self.width / 2.0, -self.width / 2.0])
        self.Z = numpy.array(
            [-self.height / 2.0, -self.height / 2.0, self.height / 2.0, self.height / 2.0, -self.height / 2.0,
             -self.height / 2.0, self.height / 2.0, self.height / 2.0])
        self.P = numpy.zeros([6, 4], dtype=int)
        self.P[0, :] = numpy.array([3, 4, 2, 1])
        self.P[1, :] = numpy.array([4, 8, 6, 2])
        self.P[2, :] = numpy.array([8, 7, 5, 6])
        self.P[3, :] = numpy.array([7, 3, 1, 5])
        self.P[4, :] = numpy.array([2, 6, 5, 1])
        self.P[5, :] = numpy.array([8, 4, 3, 7])
        # Define triangles for plotting
        self.trii = numpy.zeros([2 * self.nf, 3], dtype=int)
        iT = 0
        for iTr in range(self.nf):
            self.trii[iT, :] = [self.P[iTr, 0] - 1, self.P[iTr, 1] - 1, self.P[iTr, 2] - 1]
            self.trii[iT + 1, :] = [self.P[iTr, 0] - 1, self.P[iTr, 2] - 1, self.P[iTr, 3] - 1]
            iT += 2

    def translate(self, xT, yT, zT):
        self.X += xT
        self.Y += yT
        self.Z += zT

    def rotate(self, a1, a2, theta):
        R = numpy.zeros([3, 3])
        # Normal vector through origin
        u = a2[0] - a1[0]
        v = a2[1] - a1[1]
        w = a2[2] - a1[2]
        u = u / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        v = v / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        w = w / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        # Translate mesh so that rotation axis starts from the origin
        self.X -= a1[0]
        self.Y -= a1[1]
        self.Z -= a1[2]

        # Rotation matrix
        R[0, 0] = u ** 2 + numpy.cos(theta) * (1 - u ** 2)
        R[0, 1] = u * v * (1 - numpy.cos(theta)) - w * numpy.sin(theta)
        R[0, 2] = u * w * (1 - numpy.cos(theta)) + v * numpy.sin(theta)
        R[1, 0] = u * v * (1 - numpy.cos(theta)) + w * numpy.sin(theta)
        R[1, 1] = v ** 2 + numpy.cos(theta) * (1 - v ** 2)
        R[1, 2] = v * w * (1 - numpy.cos(theta)) - u * numpy.sin(theta)
        R[2, 0] = w * u * (1 - numpy.cos(theta)) - v * numpy.sin(theta)
        R[2, 1] = w * v * (1 - numpy.cos(theta)) + u * numpy.sin(theta)
        R[2, 2] = w ** 2 + numpy.cos(theta) * (1 - w ** 2)

        for iP in range(self.np):
            p1 = numpy.array([self.X[iP], self.Y[iP], self.Z[iP]])
            p2 = numpy.dot(R, p1)
            self.X[iP] = p2[0]
            self.Y[iP] = p2[1]
            self.Z[iP] = p2[2]

        # Translate back to original position

        self.X += a1[0]
        self.Y += a1[1]
        self.Z += a1[2]

    def makeCoin(self):
        coin = numpy.zeros((3, 4, self.nf))
        for iF in range(self.nf):
            for iC in range(4):
                coin[0, iC, iF] = self.X[self.P[iF, iC] - 1]
                coin[1, iC, iF] = self.Y[self.P[iF, iC] - 1]
                coin[2, iC, iF] = self.Z[self.P[iF, iC] - 1]
        return coin




class cone:
    def __init__(self, diameter, height, cCor):
        self.diameter = diameter
        self.height = height
        self.xC = cCor[0]
        self.yC = cCor[1]
        self.zC = cCor[2]
        self.name = 'cone'
        self.panelize()
        self.translate(self.xC, self.yC, self.zC)

    def panelize(self):
        Ntheta = 18
        Nz = 3
        theta = [xx * 2 * numpy.pi / (Ntheta - 1) for xx in range(Ntheta)]
        self.nf = 0
        self.np = 0
        r = [0, self.diameter / 2.0, 0]
        z = [0, 0, -self.height]
        self.X = []
        self.Y = []
        self.Z = []
        self.P = numpy.zeros([(len(r) - 1) * (Ntheta - 1), 4], dtype=int)
        n = len(r)

        for iT in range(Ntheta):
            for iN in range(n):
                self.X.append(r[iN] * numpy.cos(theta[iT]))
                self.Y.append(r[iN] * numpy.sin(theta[iT]))
                self.Z.append(z[iN])
                self.np += 1

        iP = 0
        for iN in range(1, n):
            for iT in range(1, Ntheta):
                self.P[iP, 0] = iN + n * (iT - 1)
                self.P[iP, 1] = iN + 1 + n * (iT - 1)
                self.P[iP, 2] = iN + 1 + n * iT
                self.P[iP, 3] = iN + n * iT
                self.nf += 1
                iP += 1

        self.X = numpy.array(self.X)
        self.Y = numpy.array(self.Y)
        self.Z = numpy.array(self.Z)
        # Define triangles for plotting
        self.trii = numpy.zeros([2 * self.nf, 3], dtype=int)
        iT = 0
        for iTr in range(self.nf):
            self.trii[iT, :] = [self.P[iTr, 0] - 1, self.P[iTr, 1] - 1, self.P[iTr, 2] - 1]
            self.trii[iT + 1, :] = [self.P[iTr, 0] - 1, self.P[iTr, 2] - 1, self.P[iTr, 3] - 1]
            iT += 2

    def translate(self, xT, yT, zT):
        self.X += xT
        self.Y += yT
        self.Z += zT

    def rotate(self, a1, a2, theta):
        R = numpy.zeros([3, 3])
        # Normal vector through origin
        u = a2[0] - a1[0]
        v = a2[1] - a1[1]
        w = a2[2] - a1[2]
        u = u / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        v = v / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        w = w / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        # Translate mesh so that rotation axis starts from the origin
        self.X -= a1[0]
        self.Y -= a1[1]
        self.Z -= a1[2]

        # Rotation matrix
        R[0, 0] = u ** 2 + numpy.cos(theta) * (1 - u ** 2)
        R[0, 1] = u * v * (1 - numpy.cos(theta)) - w * numpy.sin(theta)
        R[0, 2] = u * w * (1 - numpy.cos(theta)) + v * numpy.sin(theta)
        R[1, 0] = u * v * (1 - numpy.cos(theta)) + w * numpy.sin(theta)
        R[1, 1] = v ** 2 + numpy.cos(theta) * (1 - v ** 2)
        R[1, 2] = v * w * (1 - numpy.cos(theta)) - u * numpy.sin(theta)
        R[2, 0] = w * u * (1 - numpy.cos(theta)) - v * numpy.sin(theta)
        R[2, 1] = w * v * (1 - numpy.cos(theta)) + u * numpy.sin(theta)
        R[2, 2] = w ** 2 + numpy.cos(theta) * (1 - w ** 2)

        for iP in range(self.np):
            p1 = numpy.array([self.X[iP], self.Y[iP], self.Z[iP]])
            p2 = numpy.dot(R, p1)
            self.X[iP] = p2[0]
            self.Y[iP] = p2[1]
            self.Z[iP] = p2[2]

        # Translate back to original position

        self.X += a1[0]
        self.Y += a1[1]
        self.Z += a1[2]

    def makeCoin(self):
        coin = numpy.zeros((3, 4, self.nf))
        for iF in range(self.nf):
            for iC in range(4):
                coin[0, iC, iF] = self.X[self.P[iF, iC] - 1]
                coin[1, iC, iF] = self.Y[self.P[iF, iC] - 1]
                coin[2, iC, iF] = self.Z[self.P[iF, iC] - 1]
        return coin



class cylinder:
    def __init__(self, diameter, height, cCor):
        self.diameter = diameter
        self.height = height
        self.xC = cCor[0]
        self.yC = cCor[1]
        self.zC = cCor[2]
        self.name = 'cylinder'
        self.panelize()
        self.translate(self.xC, self.yC, self.zC)

    def panelize(self):
        Ntheta = 18
        Nz = 3
        theta = [xx * 2 * numpy.pi / (Ntheta - 1) for xx in range(Ntheta)]
        self.nf = 0
        self.np = 0
        r = [0, self.diameter / 2.0, self.diameter / 2.0, 0]
        z = [0, 0, -self.height, -self.height]
        self.X = []
        self.Y = []
        self.Z = []
        self.P = numpy.zeros([(len(r) - 1) * (Ntheta - 1), 4], dtype=int)
        n = len(r)

        for iT in range(Ntheta):
            for iN in range(n):
                self.X.append(r[iN] * numpy.cos(theta[iT]))
                self.Y.append(r[iN] * numpy.sin(theta[iT]))
                self.Z.append(z[iN])
                self.np += 1

        iP = 0
        for iN in range(1, n):
            for iT in range(1, Ntheta):
                self.P[iP, 0] = iN + n * (iT - 1)
                self.P[iP, 1] = iN + 1 + n * (iT - 1)
                self.P[iP, 2] = iN + 1 + n * iT
                self.P[iP, 3] = iN + n * iT
                self.nf += 1
                iP += 1

        self.X = numpy.array(self.X)
        self.Y = numpy.array(self.Y)
        self.Z = numpy.array(self.Z)
        # Define triangles for plotting
        self.trii = numpy.zeros([2 * self.nf, 3], dtype=int)
        iT = 0
        for iTr in range(self.nf):
            self.trii[iT, :] = [self.P[iTr, 0] - 1, self.P[iTr, 1] - 1, self.P[iTr, 2] - 1]
            self.trii[iT + 1, :] = [self.P[iTr, 0] - 1, self.P[iTr, 2] - 1, self.P[iTr, 3] - 1]
            iT += 2

    def translate(self, xT, yT, zT):
        self.X += xT
        self.Y += yT
        self.Z += zT

    def rotate(self, a1, a2, theta):
        R = numpy.zeros([3, 3])
        # Normal vector through origin
        u = a2[0] - a1[0]
        v = a2[1] - a1[1]
        w = a2[2] - a1[2]
        u = u / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        v = v / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        w = w / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        # Translate mesh so that rotation axis starts from the origin
        self.X -= a1[0]
        self.Y -= a1[1]
        self.Z -= a1[2]

        # Rotation matrix
        R[0, 0] = u ** 2 + numpy.cos(theta) * (1 - u ** 2)
        R[0, 1] = u * v * (1 - numpy.cos(theta)) - w * numpy.sin(theta)
        R[0, 2] = u * w * (1 - numpy.cos(theta)) + v * numpy.sin(theta)
        R[1, 0] = u * v * (1 - numpy.cos(theta)) + w * numpy.sin(theta)
        R[1, 1] = v ** 2 + numpy.cos(theta) * (1 - v ** 2)
        R[1, 2] = v * w * (1 - numpy.cos(theta)) - u * numpy.sin(theta)
        R[2, 0] = w * u * (1 - numpy.cos(theta)) - v * numpy.sin(theta)
        R[2, 1] = w * v * (1 - numpy.cos(theta)) + u * numpy.sin(theta)
        R[2, 2] = w ** 2 + numpy.cos(theta) * (1 - w ** 2)

        for iP in range(self.np):
            p1 = numpy.array([self.X[iP], self.Y[iP], self.Z[iP]])
            p2 = numpy.dot(R, p1)
            self.X[iP] = p2[0]
            self.Y[iP] = p2[1]
            self.Z[iP] = p2[2]

        # Translate back to original position

        self.X += a1[0]
        self.Y += a1[1]
        self.Z += a1[2]

    def makeCoin(self):
        coin = numpy.zeros((3, 4, self.nf))
        for iF in range(self.nf):
            for iC in range(4):
                coin[0, iC, iF] = self.X[self.P[iF, iC] - 1]
                coin[1, iC, iF] = self.Y[self.P[iF, iC] - 1]
                coin[2, iC, iF] = self.Z[self.P[iF, iC] - 1]
        return coin




class hemicylinder:
    def __init__(self, diameter, height, cCor):
        self.diameter = diameter
        self.height = height
        self.xC = cCor[0]
        self.yC = cCor[1]
        self.zC = cCor[2]
        self.name = 'hemicylinder'
        self.panelize()
        self.translate(self.xC, self.yC, self.zC)

    def panelize(self):
        Ntheta = 18
        Nz = 3
        theta = [xx * numpy.pi / (Ntheta - 1) - numpy.pi / 2.0 for xx in range(Ntheta)]
        self.nf = 0
        self.np = 0
        r = [0, self.diameter / 2.0, self.diameter / 2.0, 0]
        z = [self.height / 2.0, self.height / 2.0, -self.height / 2.0, -self.height / 2.0]
        self.X = []
        self.Y = []
        self.Z = []
        self.P = numpy.zeros([(len(r) - 1) * (Ntheta - 1), 4], dtype=int)
        n = len(r)

        for iT in range(Ntheta):
            for iN in range(n):
                self.Z.append(-r[iN] * numpy.cos(theta[iT]))
                self.X.append(r[iN] * numpy.sin(theta[iT]))
                self.Y.append(z[iN])
                self.np += 1

        iP = 0
        for iN in range(1, n):
            for iT in range(1, Ntheta):
                self.P[iP, 3] = iN + n * (iT - 1)
                self.P[iP, 2] = iN + 1 + n * (iT - 1)
                self.P[iP, 1] = iN + 1 + n * iT
                self.P[iP, 0] = iN + n * iT
                self.nf += 1
                iP += 1

        self.X = numpy.array(self.X)
        self.Y = numpy.array(self.Y)
        self.Z = numpy.array(self.Z)
        # Define triangles for plotting
        self.trii = numpy.zeros([2 * self.nf, 3], dtype=int)
        iT = 0
        for iTr in range(self.nf):
            self.trii[iT, :] = [self.P[iTr, 0] - 1, self.P[iTr, 1] - 1, self.P[iTr, 2] - 1]
            self.trii[iT + 1, :] = [self.P[iTr, 0] - 1, self.P[iTr, 2] - 1, self.P[iTr, 3] - 1]
            iT += 2

    def translate(self, xT, yT, zT):
        self.X += xT
        self.Y += yT
        self.Z += zT

    def rotate(self, a1, a2, theta):
        R = numpy.zeros([3, 3])
        # Normal vector through origin
        u = a2[0] - a1[0]
        v = a2[1] - a1[1]
        w = a2[2] - a1[2]
        u = u / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        v = v / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        w = w / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        # Translate mesh so that rotation axis starts from the origin
        self.X -= a1[0]
        self.Y -= a1[1]
        self.Z -= a1[2]

        # Rotation matrix
        R[0, 0] = u ** 2 + numpy.cos(theta) * (1 - u ** 2)
        R[0, 1] = u * v * (1 - numpy.cos(theta)) - w * numpy.sin(theta)
        R[0, 2] = u * w * (1 - numpy.cos(theta)) + v * numpy.sin(theta)
        R[1, 0] = u * v * (1 - numpy.cos(theta)) + w * numpy.sin(theta)
        R[1, 1] = v ** 2 + numpy.cos(theta) * (1 - v ** 2)
        R[1, 2] = v * w * (1 - numpy.cos(theta)) - u * numpy.sin(theta)
        R[2, 0] = w * u * (1 - numpy.cos(theta)) - v * numpy.sin(theta)
        R[2, 1] = w * v * (1 - numpy.cos(theta)) + u * numpy.sin(theta)
        R[2, 2] = w ** 2 + numpy.cos(theta) * (1 - w ** 2)

        for iP in range(self.np):
            p1 = numpy.array([self.X[iP], self.Y[iP], self.Z[iP]])
            p2 = numpy.dot(R, p1)
            self.X[iP] = p2[0]
            self.Y[iP] = p2[1]
            self.Z[iP] = p2[2]

        # Translate back to original position

        self.X += a1[0]
        self.Y += a1[1]
        self.Z += a1[2]

    def makeCoin(self):
        coin = numpy.zeros((3, 4, self.nf))
        for iF in range(self.nf):
            for iC in range(4):
                coin[0, iC, iF] = self.X[self.P[iF, iC] - 1]
                coin[1, iC, iF] = self.Y[self.P[iF, iC] - 1]
                coin[2, iC, iF] = self.Z[self.P[iF, iC] - 1]
        return coin


class sphere:
    def __init__(self, diameter, cCor):
        self.diameter = diameter
        self.xC = cCor[0]
        self.yC = cCor[1]
        self.zC = cCor[2]
        self.name = 'sphere'
        self.panelize()
        self.translate(self.xC, self.yC, self.zC)

    def panelize(self):
        Ntheta = 18
        Nthetad2 = int(Ntheta / 2)
        Nz = 3
        theta = [xx * 2 * numpy.pi / (Ntheta - 1) for xx in range(Ntheta)]
        phi = [xx * numpy.pi / (Ntheta / 2 - 1) for xx in range(Nthetad2)]
        self.nf = 0
        self.np = 0
        r = self.diameter / 2.0
        self.X = []
        self.Y = []
        self.Z = []
        self.P = numpy.zeros([(Ntheta - 1) * (Nthetad2 - 1), 4], dtype=int)

        for iT in range(Nthetad2):
            for iTT in range(Ntheta):
                self.X.append(r * numpy.cos(theta[iTT]) * numpy.sin(phi[iT]))
                self.Y.append(r * numpy.sin(theta[iTT]) * numpy.sin(phi[iT]))
                self.Z.append(r * numpy.cos(phi[iT]))
                self.np += 1

        iP = 0
        for iN in range(1, Ntheta):
            for iT in range(1, Nthetad2):
                self.P[iP, 3] = iN + Ntheta * (iT - 1)
                self.P[iP, 2] = iN + 1 + Ntheta * (iT - 1)
                self.P[iP, 1] = iN + 1 + Ntheta * iT
                self.P[iP, 0] = iN + Ntheta * iT
                self.nf += 1
                iP += 1
        self.X = numpy.array(self.X)
        self.Y = numpy.array(self.Y)
        self.Z = numpy.array(self.Z)
        # Define triangles for plotting
        self.trii = numpy.zeros([2 * self.nf, 3], dtype=int)
        iT = 0
        for iTr in range(self.nf):
            self.trii[iT, :] = [self.P[iTr, 0] - 1, self.P[iTr, 1] - 1, self.P[iTr, 2] - 1]
            self.trii[iT + 1, :] = [self.P[iTr, 0] - 1, self.P[iTr, 2] - 1, self.P[iTr, 3] - 1]
            iT += 2

    def translate(self, xT, yT, zT):
        self.X += xT
        self.Y += yT
        self.Z += zT

    def rotate(self, a1, a2, theta):
        R = numpy.zeros([3, 3])
        # Normal vector through origin
        u = a2[0] - a1[0]
        v = a2[1] - a1[1]
        w = a2[2] - a1[2]
        u = u / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        v = v / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        w = w / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        # Translate mesh so that rotation axis starts from the origin
        self.X -= a1[0]
        self.Y -= a1[1]
        self.Z -= a1[2]

        # Rotation matrix
        R[0, 0] = u ** 2 + numpy.cos(theta) * (1 - u ** 2)
        R[0, 1] = u * v * (1 - numpy.cos(theta)) - w * numpy.sin(theta)
        R[0, 2] = u * w * (1 - numpy.cos(theta)) + v * numpy.sin(theta)
        R[1, 0] = u * v * (1 - numpy.cos(theta)) + w * numpy.sin(theta)
        R[1, 1] = v ** 2 + numpy.cos(theta) * (1 - v ** 2)
        R[1, 2] = v * w * (1 - numpy.cos(theta)) - u * numpy.sin(theta)
        R[2, 0] = w * u * (1 - numpy.cos(theta)) - v * numpy.sin(theta)
        R[2, 1] = w * v * (1 - numpy.cos(theta)) + u * numpy.sin(theta)
        R[2, 2] = w ** 2 + numpy.cos(theta) * (1 - w ** 2)

        for iP in range(self.np):
            p1 = numpy.array([self.X[iP], self.Y[iP], self.Z[iP]])
            p2 = numpy.dot(R, p1)
            self.X[iP] = p2[0]
            self.Y[iP] = p2[1]
            self.Z[iP] = p2[2]

        # Translate back to original position

        self.X += a1[0]
        self.Y += a1[1]
        self.Z += a1[2]

    def makeCoin(self):
        coin = numpy.zeros((3, 4, self.nf))
        for iF in range(self.nf):
            for iC in range(4):
                coin[0, iC, iF] = self.X[self.P[iF, iC] - 1]
                coin[1, iC, iF] = self.Y[self.P[iF, iC] - 1]
                coin[2, iC, iF] = self.Z[self.P[iF, iC] - 1]
        return coin





class hemisphere:
    def __init__(self, diameter, cCor):
        self.diameter = diameter
        self.xC = cCor[0]
        self.yC = cCor[1]
        self.zC = cCor[2]
        self.name = 'hemisphere'
        self.panelize()
        self.translate(self.xC, self.yC, self.zC)

    def panelize(self):
        Ntheta = 18
        theta = [xx * 2 * numpy.pi / (Ntheta - 1) for xx in range(Ntheta)]
        phi = [xx * numpy.pi / 2.0 / (Ntheta / 2 - 1) for xx in range(Ntheta / 2)]
        self.nf = 0
        self.np = 0
        r = self.diameter / 2.0
        self.X = []
        self.Y = []
        self.Z = []
        self.P = numpy.zeros([(Ntheta - 1) * (Ntheta / 2 - 1), 4], dtype=int)

        for iT in range(Ntheta / 2):
            for iTT in range(Ntheta):
                self.X.append(r * numpy.cos(theta[iTT]) * numpy.sin(phi[iT]))
                self.Y.append(r * numpy.sin(theta[iTT]) * numpy.sin(phi[iT]))
                self.Z.append(-r * numpy.cos(phi[iT]))
                self.np += 1

        iP = 0
        for iN in range(1, Ntheta):
            for iT in range(1, Ntheta / 2):
                self.P[iP, 0] = iN + Ntheta * (iT - 1)
                self.P[iP, 1] = iN + 1 + Ntheta * (iT - 1)
                self.P[iP, 2] = iN + 1 + Ntheta * iT
                self.P[iP, 3] = iN + Ntheta * iT
                self.nf += 1
                iP += 1

        self.X = numpy.array(self.X)
        self.Y = numpy.array(self.Y)
        self.Z = numpy.array(self.Z)
        # Define triangles for plotting
        self.trii = numpy.zeros([2 * self.nf, 3], dtype=int)
        iT = 0
        for iTr in range(self.nf):
            self.trii[iT, :] = [self.P[iTr, 0] - 1, self.P[iTr, 1] - 1, self.P[iTr, 2] - 1]
            self.trii[iT + 1, :] = [self.P[iTr, 0] - 1, self.P[iTr, 2] - 1, self.P[iTr, 3] - 1]
            iT += 2

    def translate(self, xT, yT, zT):
        self.X += xT
        self.Y += yT
        self.Z += zT

    def rotate(self, a1, a2, theta):
        R = numpy.zeros([3, 3])
        # Normal vector through origin
        u = a2[0] - a1[0]
        v = a2[1] - a1[1]
        w = a2[2] - a1[2]
        u = u / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        v = v / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        w = w / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        # Translate mesh so that rotation axis starts from the origin
        self.X -= a1[0]
        self.Y -= a1[1]
        self.Z -= a1[2]

        # Rotation matrix
        R[0, 0] = u ** 2 + numpy.cos(theta) * (1 - u ** 2)
        R[0, 1] = u * v * (1 - numpy.cos(theta)) - w * numpy.sin(theta)
        R[0, 2] = u * w * (1 - numpy.cos(theta)) + v * numpy.sin(theta)
        R[1, 0] = u * v * (1 - numpy.cos(theta)) + w * numpy.sin(theta)
        R[1, 1] = v ** 2 + numpy.cos(theta) * (1 - v ** 2)
        R[1, 2] = v * w * (1 - numpy.cos(theta)) - u * numpy.sin(theta)
        R[2, 0] = w * u * (1 - numpy.cos(theta)) - v * numpy.sin(theta)
        R[2, 1] = w * v * (1 - numpy.cos(theta)) + u * numpy.sin(theta)
        R[2, 2] = w ** 2 + numpy.cos(theta) * (1 - w ** 2)

        for iP in range(self.np):
            p1 = numpy.array([self.X[iP], self.Y[iP], self.Z[iP]])
            p2 = numpy.dot(R, p1)
            self.X[iP] = p2[0]
            self.Y[iP] = p2[1]
            self.Z[iP] = p2[2]

        # Translate back to original position

        self.X += a1[0]
        self.Y += a1[1]
        self.Z += a1[2]

    def makeCoin(self):
        coin = numpy.zeros((3, 4, self.nf))
        for iF in range(self.nf):
            for iC in range(4):
                coin[0, iC, iF] = self.X[self.P[iF, iC] - 1]
                coin[1, iC, iF] = self.Y[self.P[iF, iC] - 1]
                coin[2, iC, iF] = self.Z[self.P[iF, iC] - 1]
        return coin




class pyramid:
    def __init__(self, length, width, height, cCor):
        self.length = length
        self.width = width
        self.height = height
        self.xC = cCor[0]
        self.yC = cCor[1]
        self.zC = cCor[2]
        self.name = 'pyramid'
        self.panelize()
        self.translate(self.xC, self.yC, self.zC)

    def panelize(self):
        self.nf = 6
        self.np = 8
        self.X = numpy.array(
            [0.0, 0.0, -self.length / 2.0, self.length / 2.0, 0.0, 0.0, -self.length / 2.0, self.length / 2.0])
        self.Y = numpy.array(
            [0.0, 0.0, self.width / 2.0, self.width / 2.0, 0.0, 0.0, -self.width / 2.0, -self.width / 2.0])
        self.Z = numpy.array([-self.height, -self.height, 0.0, 0.0, -self.height, -self.height, 0.0, 0.0])
        self.P = numpy.zeros([6, 4], dtype=int)
        self.P[0, :] = numpy.array([3, 4, 2, 1])
        self.P[1, :] = numpy.array([4, 8, 6, 2])
        self.P[2, :] = numpy.array([8, 7, 5, 6])
        self.P[3, :] = numpy.array([7, 3, 1, 5])
        self.P[4, :] = numpy.array([5, 6, 5, 1])
        self.P[5, :] = numpy.array([8, 4, 3, 7])
        # Define triangles for plotting
        self.trii = numpy.zeros([2 * self.nf, 3], dtype=int)
        iT = 0
        for iTr in range(self.nf):
            self.trii[iT, :] = [self.P[iTr, 0] - 1, self.P[iTr, 1] - 1, self.P[iTr, 2] - 1]
            self.trii[iT + 1, :] = [self.P[iTr, 0] - 1, self.P[iTr, 2] - 1, self.P[iTr, 3] - 1]
            iT += 2

    def translate(self, xT, yT, zT):
        self.X += xT
        self.Y += yT
        self.Z += zT

    def rotate(self, a1, a2, theta):
        R = numpy.zeros([3, 3])
        # Normal vector through origin
        u = a2[0] - a1[0]
        v = a2[1] - a1[1]
        w = a2[2] - a1[2]
        u = u / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        v = v / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        w = w / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        # Translate mesh so that rotation axis starts from the origin
        self.X -= a1[0]
        self.Y -= a1[1]
        self.Z -= a1[2]

        # Rotation matrix
        R[0, 0] = u ** 2 + numpy.cos(theta) * (1 - u ** 2)
        R[0, 1] = u * v * (1 - numpy.cos(theta)) - w * numpy.sin(theta)
        R[0, 2] = u * w * (1 - numpy.cos(theta)) + v * numpy.sin(theta)
        R[1, 0] = u * v * (1 - numpy.cos(theta)) + w * numpy.sin(theta)
        R[1, 1] = v ** 2 + numpy.cos(theta) * (1 - v ** 2)
        R[1, 2] = v * w * (1 - numpy.cos(theta)) - u * numpy.sin(theta)
        R[2, 0] = w * u * (1 - numpy.cos(theta)) - v * numpy.sin(theta)
        R[2, 1] = w * v * (1 - numpy.cos(theta)) + u * numpy.sin(theta)
        R[2, 2] = w ** 2 + numpy.cos(theta) * (1 - w ** 2)

        for iP in range(self.np):
            p1 = numpy.array([self.X[iP], self.Y[iP], self.Z[iP]])
            p2 = numpy.dot(R, p1)
            self.X[iP] = p2[0]
            self.Y[iP] = p2[1]
            self.Z[iP] = p2[2]

        # Translate back to original position

        self.X += a1[0]
        self.Y += a1[1]
        self.Z += a1[2]

    def makeCoin(self):
        coin = numpy.zeros((3, 4, self.nf))
        for iF in range(self.nf):
            for iC in range(4):
                coin[0, iC, iF] = self.X[self.P[iF, iC] - 1]
                coin[1, iC, iF] = self.Y[self.P[iF, iC] - 1]
                coin[2, iC, iF] = self.Z[self.P[iF, iC] - 1]
        return coin





class wedge:
    def __init__(self, length, width, height, cCor):
        self.length = length
        self.width = width
        self.height = height
        self.xC = cCor[0]
        self.yC = cCor[1]
        self.zC = cCor[2]
        self.name = 'wedge'
        self.panelize()
        self.translate(self.xC, self.yC, self.zC)

    def panelize(self):
        self.nf = 6
        self.np = 8
        self.X = numpy.array(
            [0.0, 0.0, -self.length / 2.0, self.length / 2.0, 0.0, 0.0, -self.length / 2.0, self.length / 2.0])
        self.Y = numpy.array([self.width / 2.0, self.width / 2.0, self.width / 2.0, self.width / 2.0, -self.width / 2.0,
                              -self.width / 2.0, -self.width / 2.0, -self.width / 2.0])
        self.Z = numpy.array([-self.height, -self.height, 0.0, 0.0, -self.height, -self.height, 0.0, 0.0])
        self.P = numpy.zeros([6, 4], dtype=int)
        self.P[0, :] = numpy.array([3, 4, 2, 1])
        self.P[1, :] = numpy.array([4, 8, 6, 2])
        self.P[2, :] = numpy.array([8, 7, 5, 6])
        self.P[3, :] = numpy.array([7, 3, 1, 5])
        self.P[4, :] = numpy.array([2, 6, 5, 1])
        self.P[5, :] = numpy.array([8, 4, 3, 7])
        # Define triangles for plotting
        self.trii = numpy.zeros([2 * self.nf, 3], dtype=int)
        iT = 0
        for iTr in range(self.nf):
            self.trii[iT, :] = [self.P[iTr, 0] - 1, self.P[iTr, 1] - 1, self.P[iTr, 2] - 1]
            self.trii[iT + 1, :] = [self.P[iTr, 0] - 1, self.P[iTr, 2] - 1, self.P[iTr, 3] - 1]
            iT += 2

    def translate(self, xT, yT, zT):
        self.X += xT
        self.Y += yT
        self.Z += zT

    def rotate(self, a1, a2, theta):
        R = numpy.zeros([3, 3])
        # Normal vector through origin
        u = a2[0] - a1[0]
        v = a2[1] - a1[1]
        w = a2[2] - a1[2]
        u = u / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        v = v / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        w = w / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        # Translate mesh so that rotation axis starts from the origin
        self.X -= a1[0]
        self.Y -= a1[1]
        self.Z -= a1[2]

        # Rotation matrix
        R[0, 0] = u ** 2 + numpy.cos(theta) * (1 - u ** 2)
        R[0, 1] = u * v * (1 - numpy.cos(theta)) - w * numpy.sin(theta)
        R[0, 2] = u * w * (1 - numpy.cos(theta)) + v * numpy.sin(theta)
        R[1, 0] = u * v * (1 - numpy.cos(theta)) + w * numpy.sin(theta)
        R[1, 1] = v ** 2 + numpy.cos(theta) * (1 - v ** 2)
        R[1, 2] = v * w * (1 - numpy.cos(theta)) - u * numpy.sin(theta)
        R[2, 0] = w * u * (1 - numpy.cos(theta)) - v * numpy.sin(theta)
        R[2, 1] = w * v * (1 - numpy.cos(theta)) + u * numpy.sin(theta)
        R[2, 2] = w ** 2 + numpy.cos(theta) * (1 - w ** 2)

        for iP in range(self.np):
            p1 = numpy.array([self.X[iP], self.Y[iP], self.Z[iP]])
            p2 = numpy.dot(R, p1)
            self.X[iP] = p2[0]
            self.Y[iP] = p2[1]
            self.Z[iP] = p2[2]

        # Translate back to original position

        self.X += a1[0]
        self.Y += a1[1]
        self.Z += a1[2]

    def makeCoin(self):
        coin = numpy.zeros((3, 4, self.nf))
        for iF in range(self.nf):
            for iC in range(4):
                coin[0, iC, iF] = self.X[self.P[iF, iC] - 1]
                coin[1, iC, iF] = self.Y[self.P[iF, iC] - 1]
                coin[2, iC, iF] = self.Z[self.P[iF, iC] - 1]
        return coin





class torus:
    def __init__(self, diamOut, diamIn, cCor):
        self.diamOut = diamOut
        self.diamIn = diamIn
        self.xC = cCor[0]
        self.yC = cCor[1]
        self.zC = cCor[2]
        self.name = 'torus'
        self.panelize()
        self.translate(self.xC, self.yC, self.zC)

    def panelize(self):
        Ntheta = 18
        Nphi = 18
        theta = [xx * 2 * numpy.pi / (Ntheta - 1) for xx in range(Ntheta)]
        phi = [xx * 2 * numpy.pi / (Nphi - 1) for xx in range(Nphi)]
        self.nf = 0
        self.np = 0
        self.X = []
        self.Y = []
        self.Z = []
        R = self.diamOut / 2.0
        r = self.diamIn / 2.0

        for iT in range(Ntheta):
            for iP in range(Nphi):
                self.X.append((R + r * numpy.cos(theta[iT])) * numpy.cos(phi[iP]))
                self.Y.append((R + r * numpy.cos(theta[iT])) * numpy.sin(phi[iP]))
                self.Z.append(r * numpy.sin(theta[iT]))
                self.np += 1

        self.nf = (Ntheta - 1) * (Nphi - 1)
        self.P = numpy.zeros([self.nf, 4], dtype=int)
        iPan = 0
        for iT in range(Ntheta - 1):
            for iP in range(Nphi - 1):
                self.P[iPan, 0] = iP + iT * Nphi + 1
                self.P[iPan, 1] = iP + 1 + iT * Nphi + 1
                self.P[iPan, 2] = iP + 1 + Ntheta + iT * Nphi + 1
                self.P[iPan, 3] = iP + Ntheta + iT * Nphi + 1
                iPan += 1

        self.X = numpy.array(self.X)
        self.Y = numpy.array(self.Y)
        self.Z = numpy.array(self.Z)
        # Define triangles for plotting
        self.trii = numpy.zeros([2 * self.nf, 3], dtype=int)
        iT = 0
        for iTr in range(self.nf):
            self.trii[iT, :] = [self.P[iTr, 0] - 1, self.P[iTr, 1] - 1, self.P[iTr, 2] - 1]
            self.trii[iT + 1, :] = [self.P[iTr, 0] - 1, self.P[iTr, 2] - 1, self.P[iTr, 3] - 1]
            iT += 2

    def translate(self, xT, yT, zT):
        self.X += xT
        self.Y += yT
        self.Z += zT

    def rotate(self, a1, a2, theta):
        R = numpy.zeros([3, 3])
        # Normal vector through origin
        u = a2[0] - a1[0]
        v = a2[1] - a1[1]
        w = a2[2] - a1[2]
        u = u / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        v = v / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        w = w / numpy.sqrt(u ** 2 + v ** 2 + w ** 2)
        # Translate mesh so that rotation axis starts from the origin
        self.X -= a1[0]
        self.Y -= a1[1]
        self.Z -= a1[2]

        # Rotation matrix
        R[0, 0] = u ** 2 + numpy.cos(theta) * (1 - u ** 2)
        R[0, 1] = u * v * (1 - numpy.cos(theta)) - w * numpy.sin(theta)
        R[0, 2] = u * w * (1 - numpy.cos(theta)) + v * numpy.sin(theta)
        R[1, 0] = u * v * (1 - numpy.cos(theta)) + w * numpy.sin(theta)
        R[1, 1] = v ** 2 + numpy.cos(theta) * (1 - v ** 2)
        R[1, 2] = v * w * (1 - numpy.cos(theta)) - u * numpy.sin(theta)
        R[2, 0] = w * u * (1 - numpy.cos(theta)) - v * numpy.sin(theta)
        R[2, 1] = w * v * (1 - numpy.cos(theta)) + u * numpy.sin(theta)
        R[2, 2] = w ** 2 + numpy.cos(theta) * (1 - w ** 2)

        for iP in range(self.np):
            p1 = numpy.array([self.X[iP], self.Y[iP], self.Z[iP]])
            p2 = numpy.dot(R, p1)
            self.X[iP] = p2[0]
            self.Y[iP] = p2[1]
            self.Z[iP] = p2[2]

        # Translate back to original position

        self.X += a1[0]
        self.Y += a1[1]
        self.Z += a1[2]

    def makeCoin(self):
        coin = numpy.zeros((3, 4, self.nf))
        for iF in range(self.nf):
            for iC in range(4):
                coin[0, iC, iF] = self.X[self.P[iF, iC] - 1]
                coin[1, iC, iF] = self.Y[self.P[iF, iC] - 1]
                coin[2, iC, iF] = self.Z[self.P[iF, iC] - 1]
        return coin

def make_voxels_without_figure(shape, length, height, width, diameter):
    pos = [0, 0, 0]
    if shape == "box":
        mesh = box(length, width, height, pos)
    elif shape == "cone":
        mesh = cone(diameter, height, pos)
    elif shape == "cylinder":
        mesh = cylinder(diameter, height, pos)
    elif shape == "sphere":
        mesh = sphere(diameter, pos)
    elif shape == "wedge":
        mesh = wedge(length, width, height, pos)

    hull_points = numpy.array([mesh.X.tolist(), mesh.Y.tolist(), mesh.Z.tolist()]).T

    # Set up test points
    G = 32
    ex = 5 - 5 / G
    x, y, z = numpy.meshgrid(numpy.linspace(-ex, ex, G),
                              numpy.linspace(-ex, ex, G),
                              numpy.linspace(-(9.5 - 5 / G), 0.5 - 5 / G, G))
    test_points = numpy.vstack((x.ravel(), y.ravel(), z.ravel())).T

    hull = scipy.spatial.Delaunay(hull_points)
    within = hull.find_simplex(test_points) >= 0

    return within*1.0
    
    
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

curves, geometry, S, N, D, F, G, new_curves, new_geometry = load_data()

class Network(object):

  def __init__(self, type):
      # Instantiate variables
      # self.curves = curves
      # self.new_curves = new_curves
      # self.geometry = geometry
      # self.new_geometry = new_geometry
      # self.S = S
      # self.N = N
      # self.D = D
      # self.F = F
      # self.G = G

      # Load network
      # with open(structure, 'r') as file:
      #     self.network = keras.models.model_from_json(file.read())
      #     self.network.load_weights(weights)
      self.network = from_pretrained_keras("cmudrc/wave-energy-analysis") if type == "forward" else from_pretrained_keras("cmudrc/wave-energy-synthesis")

  def analysis(self, idx=None):
      print(idx)

      if idx is None:
          idx = numpy.random.randint(1, S * N)
      else:
        idx = int(idx)

      # Get the input
      data_input = new_geometry[idx:(idx+1), :]
      other_data_input = data_input.reshape((G, G, G), order='F')

      # Get the outputs
      print(data_input.shape)
      predicted_output = self.network.predict(data_input)
      true_output = new_curves[idx].reshape((3, F))
      predicted_output = predicted_output.reshape((3, F))

      f = numpy.linspace(0.05, 2.0, 64)
      fd = pandas.DataFrame(f).rename(columns={0: "Frequency"})
      df_pred = pandas.DataFrame(predicted_output.transpose()).rename(columns={0: "Surge", 1: "Heave", 2: "Pitch"})
      df_true = pandas.DataFrame(true_output.transpose()).rename(columns={0: "Surge", 1: "Heave", 2: "Pitch"})

      # return idx, other_data_input, true_output, predicted_output
      return pandas.concat([fd, df_pred], axis=1), pandas.concat([fd, df_true], axis=1)


  def analysis_from_geometry(self, geometry):
      # Get the outputs
      predicted_output = self.network.predict(numpy.array([geometry.flatten().tolist()]))
      predicted_output = predicted_output.reshape((3, F))

      f = numpy.linspace(0.05, 2.0, 64)
      fd = pandas.DataFrame(f).rename(columns={0: "Frequency"})
      df_pred = pandas.DataFrame(predicted_output.transpose()).rename(columns={0: "Surge", 1: "Heave", 2: "Pitch"})
      good_frame = pandas.concat([fd, df_pred], axis=1)

      return good_frame, good_frame

  def synthesis(self, idx=None):
      print(idx)

      if idx is None:
          idx = numpy.random.randint(1, S * N)
      else:
        idx = int(idx)

      # Get the input
      data_input = new_curves[idx:(idx+1), :]
      other_data_input = data_input.reshape((3, F))

      # Get the outputs
      predicted_output = self.network.predict(data_input)
      true_output = new_geometry[idx].reshape((G, G, G), order='F')
      predicted_output = predicted_output.reshape((G, G, G), order='F')

      # return idx, other_data_input, true_output, predicted_output
      return predicted_output, true_output
      
  
  def synthesis_from_spectrum(self, other_data_input):
      # Get the input
      data_input = other_data_input.reshape((1, 3*F))
 
      # Get the outputs
      predicted_output = self.network.predict(data_input)
      predicted_output = predicted_output.reshape((G, G, G), order='F')

      # return idx, other_data_input, true_output, predicted_output
      return predicted_output

  def get_geometry(self, idx=None):

      if idx is None:
          idx = numpy.random.randint(1, S * N)
      else:
        idx = int(idx)

      idx = int(idx)

      # Get the input
      data_input = new_geometry[idx:(idx+1), :]
      other_data_input = data_input.reshape((G, G, G), order='F')

      # return idx, other_data_input, true_output, predicted_output
      return other_data_input


  def get_performance(self, idx=None):

      if idx is None:
          idx = numpy.random.randint(1, S *N)
      else:
        idx = int(idx)

      idx = int(idx)

      # Get the input
      data_input = new_curves[idx:(idx+1), :]
      other_data_input = data_input.reshape((3,  F))

      f = numpy.linspace(0.05, 2.0, 64)
      fd = pandas.DataFrame(f).rename(columns={0: "Frequency"})
      df_pred = pandas.DataFrame(other_data_input.transpose()).rename(columns={0: "Surge", 1: "Heave", 2: "Pitch"})
      table = pandas.concat([fd, df_pred], axis=1)

      return table


def plotly_fig(values):
    X, Y, Z = numpy.mgrid[0:1:32j, 0:1:32j, 0:1:32j]
    fig = go.Figure(data=go.Volume(
        x=X.flatten(),
        y=Y.flatten(),
        z=Z.flatten(),
        value=values.flatten(),
        isomin=0.0,
        isomax=1.0,
        opacity=0.1, # needs to be small to see through all surfaces
        surface_count=21, # needs to be a large number for good volume rendering
        colorscale='haline'
        ))
    return fig 


value_net = Network("forward")

def performance(index):
    return value_net.get_performance(index)

def geometry(index):
    values = value_net.get_geometry(index)
    return plotly_fig(values)

def simple_analysis(index, choice, shape, length, width, height, diameter): 
    forward_net = Network("forward")
    # forward_net = Network("16forward_structure.json", "16forward_weights.h5")
    if choice == "Construct Shape from Parameters":  
        return forward_net.analysis_from_geometry(make_voxels_without_figure(shape, length, height, width, diameter))
    elif choice == "Pick Shape from Dataset":
        return forward_net.analysis(index)
    

def simple_synthesis(index):
    inverse_net = Network("inverse")
    # inverse_net = Network("16inverse_structure.json", "16inverse_weights.h5")
    pred, true = inverse_net.synthesis(index)
    return plotly_fig(pred), plotly_fig(true)
    
def synthesis_from_spectrum(df):
    inverse_net = Network("inverse")
    # inverse_net = Network("16inverse_structure.json", "16inverse_weights.h5")
    pred = inverse_net.synthesis_from_spectrum(df.to_numpy()[:, 1:])
    return plotly_fig(pred)
   
    

def change_textbox(choice, length, height, width, diameter):
    fig = make_voxels(choice, length, height, width, diameter)
    if choice == "cylinder":
        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)]
    elif choice == "sphere":
        return [gradio.Slider.update(visible=False), gradio.Slider.update(visible=False), gradio.Slider.update(visible=True), gradio.Slider.update(visible=False), gradio.Plot.update(fig)]
    elif choice == "box":
        return [gradio.Slider.update(visible=True), gradio.Slider.update(visible=True), gradio.Slider.update(visible=False), gradio.Slider.update(visible=True), gradio.Plot.update(fig)]
    elif choice == "wedge":
        return [gradio.Slider.update(visible=True), gradio.Slider.update(visible=True), gradio.Slider.update(visible=False), gradio.Slider.update(visible=True), gradio.Plot.update(fig)]
    elif choice == "cone":
        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)]

  

def randomize_analysis(choice):
    if choice == "Construct Shape from Parameters": 
        length = random.uniform(3.0, 10.0)
        height = random.uniform(3.0, 10.0)
        width = random.uniform(3.0, 10.0)
        diameter = random.uniform(3.0, 10.0)
        choice2 = random.choice(["box", "cone", "sphere", "wedge", "cone"]) 
        if choice2 == "box" or choice2 == "wedge":
            return [gradio.Radio.update(choice2), gradio.Slider.update(length), gradio.Slider.update(height), gradio.Slider.update(width), gradio.Slider.update(), gradio.Number.update(), gradio.Plot.update(make_voxels(choice2, length, height, width, diameter))]
        elif choice2 == "cone" or choice2 == "cylinder":
            return [gradio.Radio.update(choice2), gradio.Slider.update(), gradio.Slider.update(height), gradio.Slider.update(), gradio.Slider.update(diameter), gradio.Number.update(), gradio.Plot.update(make_voxels(choice2, length, height, width, diameter))]
        elif choice2 == "sphere":
            return [gradio.Radio.update(choice2), gradio.Slider.update(), gradio.Slider.update(), gradio.Slider.update(), gradio.Slider.update(diameter), gradio.Number.update(), gradio.Plot.update(make_voxels(choice2, length, height, width, diameter))]
    elif choice == "Pick Shape from Dataset":
        num = random.randint(1, 4999)
        return [gradio.Radio.update(), gradio.Slider.update(), gradio.Slider.update(), gradio.Slider.update(), gradio.Slider.update(), gradio.Number.update(num), gradio.Plot.update(geometry(num))]
    
   
   
def geometry_change(choice, choice2, num, length, width, height, diameter):
    if choice == "Construct Shape from Parameters":  
        [slider1, slider2, slider3, slider4, plot] = change_textbox(choice2, length, height, width, diameter)
        return [gradio.Radio.update(visible=True), slider1, slider2, slider3, slider4, gradio.Number.update(visible=False), gradio.Timeseries.update(visible=False), gradio.Plot.update(make_voxels(choice2, length, height, width, diameter))]
    elif choice == "Pick Shape from Dataset":
        return [gradio.Radio.update(visible=False), gradio.Slider.update(visible=False), gradio.Slider.update(visible=False), gradio.Slider.update(visible=False), gradio.Slider.update(visible=False), gradio.Number.update(visible=True), gradio.Timeseries.update(visible=True), gradio.Plot.update(geometry(num))]
   
with gradio.Blocks() as demo:
    with gradio.Accordion("✨ Read about the underlying ML model here! ✨", open=False):
        with gradio.Row():
            with gradio.Column():
                gradio.Markdown("# Toward the Rapid Design of Engineered Systems Through Deep Neural Networks")
                gradio.HTML("Christopher McComb, Carnegie Mellon University")
                gradio.Markdown("__Abstract__: The design of a system commits a significant portion of the final cost of that system. Many computational approaches have been developed to assist designers in the analysis (e.g., computational fluid dynamics) and synthesis (e.g., topology optimization) of engineered systems. However, many of these approaches are computationally intensive, taking significant time to complete an analysis and even longer to iteratively synthesize a solution. The current work proposes a methodology for rapidly evaluating and synthesizing engineered systems through the use of deep neural networks. The proposed methodology is applied to the analysis and synthesis of offshore structures such as oil platforms. These structures are constructed in a marine environment and are typically designed to achieve specific dynamics in response to a known spectrum of ocean waves. Results show that deep learning can be used to accurately and rapidly synthesize and analyze offshore structure.")
            with gradio.Column():
                download = gradio.HTML("<a href=\"https://huggingface.co/spaces/cmudrc/wecnet/resolve/main/McComb2019_Chapter_TowardTheRapidDesignOfEngineer.pdf\" style=\"width: 60%; display: block; margin: auto;\"><img src=\"https://huggingface.co/spaces/cmudrc/wecnet/resolve/main/coverpage.png\"></a>")
    
    gradio.Markdown("When designing offshore structure, like [wave energy converters](https://www.nrel.gov/news/program/2021/how-wave-energy-could-go-big-by-getting-smaller.html), it's important to know what forces will be placed on the structure as waves come at different speeds. Likewise, if we have some idea of how we want the structure to respond to different waves, we can use that to guide the design of the shape of the structure. We call the first process _Analysis_, and the second process _Synthesis_. This demo has ML models that do both, very quickly.")
    
    with gradio.Tab("Analysis"):        
                 
        with gradio.Row():
            with gradio.Column():                          
                whence_commeth_geometry = gradio.Radio(
                    ["Construct Shape from Parameters", "Pick Shape from Dataset"], label="How would you like to generate the shape of the offshore structure for analysis?", value="Construct Shape from Parameters"
                )
                radio = gradio.Radio(
                    ["box", "cone", "cylinder", "sphere", "wedge"], label="What kind of shape would you like to generate?", value="sphere"
                )
                height = gradio.Slider(label="Height", interactive=True, minimum=3.0, maximum=10.0, value=6.5, visible=False)
                width = gradio.Slider(label="Width", interactive=True, minimum=3.0, maximum=10.0, value=6.5, visible=False)
                diameter = gradio.Slider(label="Diameter", interactive=True, minimum=3.0, maximum=10.0, value=6.5, visible=True)
                length = gradio.Slider(label="Length", interactive=True, minimum=3.0, maximum=10.0, value=6.5, visible=False)
            
                
                num = gradio.Number(42, label="Type the index of the spectrum you would like to use or randomly select it.", visible=False)
                
                btn1 = gradio.Button("Randomize")                                   
            with gradio.Column():
                geo = gradio.Plot(make_voxels("sphere", 6.5, 6.5, 6.5, 6.5), label="Geometry")
                
    
        with gradio.Row():
            btn2 = gradio.Button("Estimate Spectrum")
    
        with gradio.Row():
          with gradio.Column():
              pred = gradio.Timeseries(x="Frequency", y=['Surge', 'Heave', 'Pitch'], label="Predicted")
    
          with gradio.Column():
              true = gradio.Timeseries(x="Frequency", y=['Surge', 'Heave', 'Pitch'], label="True", visible=False)
        
        radio.change(fn=change_textbox, inputs=[radio, length, height, width, diameter], outputs=[height, width, diameter, length, geo])    
        height.change(fn=make_voxels, inputs = [radio, length, height, width, diameter], outputs=[geo])    
        width.change(fn=make_voxels, inputs = [radio, length, height, width, diameter], outputs=[geo])    
        diameter.change(fn=make_voxels, inputs = [radio, length, height, width, diameter], outputs=[geo])    
        length.change(fn=make_voxels, inputs = [radio, length, height, width, diameter], outputs=[geo])
        whence_commeth_geometry.change(fn=geometry_change, inputs=[whence_commeth_geometry, radio, num, length, width, height, diameter], outputs=[radio, height, width, diameter, length, num, true, geo])
        num.change(fn=geometry, inputs=[num], outputs=[geo])
        
        btn1.click(fn=randomize_analysis, inputs=[whence_commeth_geometry], outputs=[radio, length, height, width, diameter, num, geo])
        btn2.click(fn=simple_analysis, inputs=[num, whence_commeth_geometry, radio, length, width, height, diameter], outputs=[pred, true], api_name="analyze")
    with gradio.Tab("Synthesis"): 
        with gradio.Row():
            with gradio.Column():                         
                whence_commeth_performance = gradio.Radio(
                    ["Pick Spectrum from Dataset"], label="How would you like to generate the desired response spectrum to synthesize from?", value="Construct Spectrum from Table"
                )
                num = gradio.Number(42, label="Type the index of the shape you would like to use or randomly select it.")
                btn1 = gradio.Button("Randomize")    
            with gradio.Column():
                perf = gradio.Timeseries(x="Frequency", y=['Surge', 'Heave', 'Pitch'], label="Performance")
    
        with gradio.Row():
            btn2 = gradio.Button("Synthesize Geometry")
    
        with gradio.Row():
          with gradio.Column():
              pred = gradio.Plot(label="Predicted")
    
          with gradio.Column():
              true = gradio.Plot(label="True")
    

        btn1.click(fn=lambda: random.randint(1, 4999), inputs=[], outputs=num)
        num.change(fn=performance, inputs=[num], outputs=[perf])
        btn2.click(fn=simple_synthesis, inputs=[num], outputs=[pred, true], api_name="synthesize")
    
demo.launch()