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#---------------------------
# Field generator module
# PabloVD
# Started: 11/5/20
#---------------------------
import numpy as np
from scipy import interpolate, ndimage
from source.fields import gaussian_field, perlin_field, warped_perlin_field, brownian_surface, cos_field
# Filter the field with a gaussian window
def smooth_field(field,sigmagauss,gridsize=None):
if gridsize==None: gridsize=field.shape[0]
x, y = np.linspace(0,field.shape[0],num=field.shape[0]), np.linspace(0,field.shape[1],num=field.shape[1])
# Interpolation
f = interpolate.interp2d(x,y,field,kind="linear")
qx = np.linspace(x[0],x[-1], num = gridsize)
qy = np.linspace(y[0],y[-1], num = gridsize)
# Filtering
smooth = ndimage.filters.gaussian_filter(f(qx,qy),sigmagauss)
return smooth
# Remove regions below sea level
def mainland(field,threshold):
for i, row in enumerate(field):
for j, el in enumerate(row):
if el<threshold: field[i,j]=0.
return field
# Normalize the values of the field between 0 and 1
def normalize_field(field):
min, max = np.amin(field), np.amax(field)
newfield = (field-min)/(max-min)
return newfield
# A gaussian function
def central_gaussian(x,y,x_c,y_c,sig):
return np.exp(-((x-x_c)**2.+(y-y_c)**2.)/2./sig**2.)
# Multiply the field by a gaussian mask to ensure an island in the center of the image
def masked_field(field,sig=None):
a, b = field.shape[0], field.shape[1]
if sig==None: sig = a/2.
x, y = np.linspace(0,a-1,num=a), np.linspace(0,b-1,num=b)
X, Y = np.meshgrid(x,y)
mask = central_gaussian(X,Y,a/2,b/2,sig)
field = field*mask
return field
# Generate a map of islands applying different processes:
# 1. Generate a random field, either gaussian or perlin
# 2. Normalize the field between 0 and 1
# 3. Smooth the field with a gaussian filter
# 4. Retain only the mainland above a certain threshold
def generate_map(kind_noise,boxsize,llavor,params,sigma,threshold,boxsizey=None,make_island=0):
if boxsizey==None: boxsizey=boxsize
np.random.seed(seed=llavor)
if kind_noise=="gauss":
indexlaw = params
field = gaussian_field(boxsize,llavor,indexlaw)
elif kind_noise=="perlin":
scale,octaves,persistence,lacunarity,boxsizey = params
field = perlin_field(boxsize,llavor,scale,octaves,persistence,lacunarity,boxsizey=boxsizey)
#field = perlin_field(boxsize,llavor,*params)
elif kind_noise=="warped_perlin":
scale,octaves,persistence,lacunarity,boxsizey = params
field = warped_perlin_field(boxsize,llavor,scale,octaves,persistence,lacunarity,boxsizey=boxsizey)
elif kind_noise=="fbm":
hurst = params
field = brownian_surface(boxsize, H=hurst)
elif kind_noise=="cos":
scale,octaves,persistence,lacunarity,boxsizey = params
field = cos_field(boxsize,llavor,scale,octaves,persistence,lacunarity,boxsizey=boxsizey)
else:
print("Kind of noise not valid.")
return np.zeros((boxsize,boxsizey))
field = normalize_field(field)
if make_island:
field = masked_field(field)
field = smooth_field(field,sigma,gridsize=2*boxsize)
field = mainland(field,threshold)
return field
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