# 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)
示例#4
0
# 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