# Read in input data:
# fractalD - fractal dimension
# rhozero - density scaling parameter
# ngrid - Number of grid cells
# boxlength - Half length of box in code units (e.g. dimensions (-L,L))
# filename - output filename
fractalD, npower, rhozero, seed, ngrid, boxlength, filename = fr.readInputs_Cube()
# Define the cubic Grid
x,dr = fr.create1DGrid(ngrid,boxlength)
# Create Wavenumbers
k = fr.constructWavenumbers(ngrid, boxlength, dr)
# Compute a 3D power spectrum (power law k^-npower)
powerspec = fr.compute1DPowerLawPowerSpectrum(npower, ngrid, k)
# The power spectrum has no phase data - must generate it before Fourier Transform
# Use random phases to reconstruct the Fourier Transform of the density
rho_fft = fr.PowerSpectrumToFT(seed, powerspec)
# Compute the inverse fourier transform of rho_fft
rho = fr.InverseFFT(rho_fft)
# Scale density by rhozero
# fractalD - fractal dimension
# rhozero - density scaling parameter
# ngrid - Number of grid cells per dimension (i.e. total ngrid^3)
# boxlength - Half length of box in code units (e.g. dimensions (-L,L))
# filename - output filename
fractalD, npower, deltarho, rhozero, seed, distkey, distunit, masskey, massunit, ngrid, xlength, ylength, zlength, filename = fr.readInputs_Cuboid(
)
# Define the cuboid Grid
x, y, z, dx, dy, dz = fr.createCuboid(ngrid, ngrid, ngrid, xlength, ylength,
zlength, distkey)
# Create Wavenumbers
kx = fr.constructWavenumbers(ngrid, xlength, dx, distkey)
ky = fr.constructWavenumbers(ngrid, ylength, dy, distkey)
kz = fr.constructWavenumbers(ngrid, zlength, dz, distkey)
# Compute a 3D power spectrum (power law k^-npower)
powerspec = fr.computePowerLawPowerSpectrum(npower, ngrid, ngrid, ngrid, kx,
ky, kz)
# The power spectrum has no phase data - must generate it before Fourier Transform
# Use random phases to reconstruct the Fourier Transform of the density
rho_fft = fr.PowerSpectrumToFT(seed, powerspec)
# Compute the inverse fourier transform of rho_fft
rho = fr.InverseFFTN(rho_fft)
print "FRACTAL DENSITY DISTRIBUTION IN A 3D CUBOID"
print "-----"
# fractalD - fractal dimension
# rhozero - density scaling parameter
# ngrid - Number of grid cells per dimension (i.e. total ngrid^3)
# boxlength - Half length of box in code units (e.g. dimensions (-L,L))
# filename - output filename
fractalD, npower, deltarho, rhozero, seed, distkey, distunit, masskey, massunit, ngrid, xlength, ylength, zlength, filename = fr.readInputs_Cuboid()
# Define the cuboid Grid
x,y,z,dx,dy,dz = fr.createCuboid(ngrid,ngrid,ngrid,xlength,ylength,zlength,distkey)
# Create Wavenumbers
kx = fr.constructWavenumbers(ngrid, xlength, dx,distkey)
ky = fr.constructWavenumbers(ngrid, ylength, dy,distkey)
kz = fr.constructWavenumbers(ngrid, zlength, dz,distkey)
# Compute a 3D power spectrum (power law k^-npower)
powerspec = fr.computePowerLawPowerSpectrum(npower, ngrid, ngrid, ngrid, kx, ky, kz)
# The power spectrum has no phase data - must generate it before Fourier Transform
# Use random phases to reconstruct the Fourier Transform of the density
rho_fft = fr.PowerSpectrumToFT(seed, powerspec)
# Compute the inverse fourier transform of rho_fft
rho = fr.InverseFFTN(rho_fft)
# Read in input data: # fractalD - fractal dimension # rhozero - density scaling parameter # ngrid - Number of grid cells # boxlength - Half length of box in code units (e.g. dimensions (-L,L)) # filename - output filename fractalD, npower, rhozero, seed, ngrid, boxlength, filename = fr.readInputs_Cube( ) # Define the cubic Grid x, dr = fr.create1DGrid(ngrid, boxlength) # Create Wavenumbers k = fr.constructWavenumbers(ngrid, boxlength, dr) # Compute a 3D power spectrum (power law k^-npower) powerspec = fr.compute1DPowerLawPowerSpectrum(npower, ngrid, k) # The power spectrum has no phase data - must generate it before Fourier Transform # Use random phases to reconstruct the Fourier Transform of the density rho_fft = fr.PowerSpectrumToFT(seed, powerspec) # Compute the inverse fourier transform of rho_fft rho = fr.InverseFFT(rho_fft) # Scale density by rhozero