app.py

# For neural networks
import keras
# For random calculations
import numpy
    
import gradio
import pandas


# New for geometry creation
import glob
import os
import shutil
import stat
import math
import platform
import scipy.spatial

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


# Big bunch of geometry stuff
import glob
import os
import shutil
import stat
import math
import platform
import scipy.spatial

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, structure, weights):
      # 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)

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

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

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

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

      return pandas.concat([fd, df_pred], axis=1), pandas.DataFrame()


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

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

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

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

      idx = int(idx)

      # Get the input
      data_input = self.new_geometry[idx:(idx+1), :]
      other_data_input = data_input.reshape((self.G, self.G, self.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, self.S * self.N)
      else:
        idx = int(idx)

      idx = int(idx)

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



import plotly.graph_objects as go


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=-0.1,
        isomax=0.8,
        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("16forward_structure.json", "16forward_weights.h5")

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("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("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("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)]


import random  

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", "pyramid", "cone"]) 
        return [gradio.Radio.update(choice2), gradio.Slider.update(length), gradio.Slider.update(width), gradio.Slider.update(height), 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":  
        return [gradio.Radio.update(visible=True), gradio.Slider.update(visible=True), gradio.Slider.update(visible=True), gradio.Slider.update(visible=True), gradio.Slider.update(visible=True), 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("Additive manufacturing is advantageous for producing lightweight components while maintaining function and form. This ability has been bolstered by the introduction of unit lattice cells and the gradation of those cells. In cases where loading varies throughout a part, it may be necessary to use multiple lattice cell types, also known as multi-lattice structures. In such structures, abrupt transitions between geometries may cause stress concentrations, making the boundary a primary failure point; thus, transition regions should be created between each lattice cell type. Although computational approaches have been proposed, smooth transition regions are still difficult to intuit and design, especially between lattices of drastically different geometries. This work demonstrates and assesses a method for using variational autoencoders to automate the creation of transitional lattice cells. In particular, the work focuses on identifying the relationships that exist within the latent space produced by the variational autoencoder. Through computational experimentation, it was found that the smoothness of transition regions was higher when the endpoints were located closer together in the latent space.")
            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>")
    
    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 shape 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")
        
        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])
    with gradio.Tab("Synthesis"):
        with gradio.Tab("Spectrum from Dataset"):    
                      
            with gradio.Row():
                with gradio.Column():
                    num = gradio.Number(42, label="data index")
                    btn1 = gradio.Button("Select")    
                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=performance, inputs=[num], outputs=[perf])
            btn2.click(fn=simple_synthesis, inputs=[num], outputs=[pred, true])
        with gradio.Tab("Spectrum from DataFrame"):
            with gradio.Row():
                perf = gradio.Timeseries(x="Frequency", y=['Surge', 'Heave', 'Pitch'], label="Performance")
        
            with gradio.Row():
                btn2 = gradio.Button("Synthesize Geometry")
        
            with gradio.Row():
                pred = gradio.Plot(label="Predicted")
        
            btn2.click(fn=synthesis_from_spectrum, inputs=[perf], outputs=[pred])
    
demo.launch()