# 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
print "Scaling Density"
rho = np.real(rho)
rho = np.real(np.exp(rho/rhozero))
# Test the density to check its PDF is lognormal (optional - feel free to comment out)
nbins = ngrid/10
fr.testForLognormalPDF(rho, nbins)
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)
# Scale density by rhozero
print "Scaling Density"
rho = np.real(rho)
rho = rhozero * np.real(np.exp(rho * deltarho))
# Test the density to check its PDF is lognormal (optional - feel free to comment out)
fr.testForLognormalPDF(rho, ngrid)
# Write density grid to file
fr.writeCuboidGridToFile(x, y, z, ngrid, ngrid, ngrid, rho, dx, dy, dz,
massunit, distunit, masskey, distkey, filename)
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)
# Scale density by rhozero
print "Scaling Density"
rho = np.real(rho)
rho = rhozero*np.real(np.exp(rho*deltarho))
# Test the density to check its PDF is lognormal (optional - feel free to comment out)
fr.testForLognormalPDF(rho, ngrid)
# Write density grid to file
fr.writeCuboidGridToFile(x,y,z,ngrid,ngrid,ngrid,rho,dx,dy,dz,massunit,distunit,masskey,distkey,filename)
) # 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 print "Scaling Density" rho = np.real(rho) rho = np.real(np.exp(rho / rhozero)) # Test the density to check its PDF is lognormal (optional - feel free to comment out) nbins = ngrid / 10 fr.testForLognormalPDF(rho, nbins)
