File:Desert planet 8.png

1. 2. desert planet dem
   3. python3 source code
   5. 16.6.2023 0000.0000

import matplotlib.pyplot as plt import numpy as np import math from time import perf_counter from sys import getrefcount from PIL import Image, ImageOps

import noise

import netCDF4 as nc

def save_netcdf_elev(fn, dataa1): shp1=np.shape(dataa1) dimx1=shp1[1] dimy1=shp1[0] ds = nc.Dataset(fn, 'w', format='NETCDF4') latitude = ds.createDimension('latitude', dimy1) longitude = ds.createDimension('longitude', dimx1) lats = ds.createVariable('latitude', 'f4', ('latitude',)) lons = ds.createVariable('longitude', 'f4', ('longitude',)) data = ds.createVariable('z', 'f4', ('latitude', 'longitude',)) data.units = 'm' lats[:] = np.arange(-90, 90, 180/dimy1) lons[:] = np.arange(-180.0, 180, 360/dimx1) data[:, :] = np.flipud(dataa1) ds.close()

def normalize(arra): mini=np.min(arra) maxi=np.max(arra) deltai=maxi-mini return((arra-mini)/deltai)

dimx1=2000 dimy1=1000

outfilename1="desmo.png"

shape = (dimy1,dimx1)

scale = dimx1/2

octaves = 13 persistence = 0.5 ##0.5 lacunarity = 4.0 ## 2.0

1. 1. ar=0.5

ar=0.25

seed1=0 seed2=1

pi2=math.pi*2 pi=math.pi

t1 = perf_counter()

fiis=np.linspace(0,pi,dimy1) phiis=np.linspace(0,pi2,dimx1)

leni=len(fiis) lenj=len(phiis)

noise0 = np.zeros(shape) for i in range(shape[0]): for j in range(shape[1]): theta=fiis[i] phi=phiis[j] x=ar * math.sin(theta) * math.cos(phi) y=ar * math.sin(theta) * math.sin(phi) z=ar * math.cos(theta) noise0[i][j] = noise.pnoise3(x,y,z,octaves=octaves,persistence=persistence,lacunarity=lacunarity, repeatx=1024, repeaty=1024,repeatz=1024,base=seed1)

noise1 = np.zeros(shape) ar=0.25 for i in range(shape[0]): for j in range(shape[1]): theta=fiis[i] phi=phiis[j] x=ar * math.sin(theta) * math.cos(phi) y=ar * math.sin(theta) * math.sin(phi) z=ar * math.cos(theta) noise1[i][j] = noise.pnoise3(x,y,z,octaves=octaves,persistence=persistence,lacunarity=lacunarity, repeatx=1024, repeaty=1024,repeatz=1024,base=seed2)

noise2 = np.zeros(shape) ar=4 for i in range(shape[0]): for j in range(shape[1]): theta=fiis[i] phi=phiis[j] x=ar * math.sin(theta) * math.cos(phi) y=ar * math.sin(theta) * math.sin(phi) z=ar * math.cos(theta) noise2[i][j] = noise.pnoise3(x,y,z,octaves=octaves,persistence=persistence,lacunarity=lacunarity, repeatx=1024, repeaty=1024,repeatz=1024,base=seed2)

1. qnoise0= 2 * (0.5 - np.abs(0.5 -noise0) )
2. qnoise0b=np.power(qnoise0, 3)
3. qnoise0c=np.abs(qnoise0b)

1. qnoise0=np.power(noise0, 4)

qnoise0=np.copy(noise0)

qnoise1=np.where(qnoise0 < 0, np.power(qnoise0,2), np.power(qnoise0,0.5) )

qnoise2= 2 * (0.5 - np.abs(0.5 - qnoise1) )

qnoise3=np.power(qnoise2, 6)

qnoise4=np.exp(abs(qnoise3*noise1))

noisex=normalize(qnoise4)+normalize(np.exp(noise1))

1. siny=np.copy(noisez)*0

siny=np.zeros(shape) cosy=np.zeros(shape)

midi0=shape[0]/2

for i in range(shape[0]): for j in range(shape[1]): ii=i-midi0 ii2=float(ii)/float(midi0) ii3=ii2*math.pi/2 cosy[i, j]=1-(math.cos(ii3)*math.cos(ii3)) siny[i, j]=math.sin(ii3)

siny2=np.copy(siny) siny=np.where(siny>0,0,siny/2) siny2=np.where(siny2>0.4,siny2,0.4)

1. noisey=normalize(siny*noisex+noisex*0.2)

1. siny2=1-normalize(siny*siny*siny*siny*siny*siny)

noisey0=normalize(siny2*cosy*noisex+noisex*0.2)

1. noisey=siny

1. noisey=noise2

noisey1=normalize(noise2+siny2-0.4)

1. noisey=siny2

noisey3=normalize(noisey1-np.min(noisey1))/10

noisey=noisey0*(1-normalize(noisey3))

t2 = perf_counter() t3=t2-t1 print("T3:", t3)

1. I=noisex

1. I=noisey

I=noisey

maxiima1=(256.0*256.0)-1.0

I16 = (((I - I.min()) / (I.max() - I.min())) * maxiima1).astype(np.uint16)

img = Image.fromarray(I16)

img.save(outfilename1)

1. 1. desert planet dem, hmax=7400

noisez=noisey*8700

1. plt.imshow(noisey, cmap="terrain")
2. plt.imshow(noisey, cmap="YlOrBr")
3. plt.imshow(noisey, cmap="Oranges")

plt.imshow(np.flipud(noisey), cmap="copper_r")

shaded=1

if(shaded==1): x, y = np.gradient(noisey) slope = np.pi/2. - np.arctan(np.sqrt(x*x + y*y)) aspect = np.arctan2(-x, y) altitude = np.pi / 4. azimuth = np.pi / 2. shaded = np.sin(altitude) * np.sin(slope)+ np.cos(altitude) * np.cos(slope)* np.cos((azimuth - np.pi/2.) - aspect) plt.imshow(np.flipud(shaded), cmap='Greys', origin='lower', alpha=0.5) plt.imsave('desmap.png', noisey, cmap="copper_r")

fig = plt.figure(frameon=False)

fig.savefig("desmap2.png")

plt.show()

save_netcdf_elev("desdem.nc", noisez)

1. plt.show()

1. include "colors.inc"
2. include "functions.inc"

global_settings {

  assumed_gamma 1.5
  noise_generator 1

}

light_source {

  <10, 2, -10>*1000*1000*1000, rgb <1, 1, 1>

}

camera {

 location <0,4, -3>
 look_at <0,0,0>   
angle 35

}

1. declare planetex1= texture {

 pigment { 
 image_map {

  png "desmap.png"

//transmit all 0

       map_type 1

     interpolate 2
  

        }

}

normal {

bump_map {
png "desmo.png"
         bump_size 15
        map_type 1

     interpolate 2

}

//agate

}

finish { ambient 0}

//finish {diffuse 0.85 }

// rotate y*90

}

// clouds ...

1. declare cloudiness1=0.5; //## suitable 0.5
2. declare cloudturb1=1;
3. declare cloudturb2=2;

1. declare cloudpig1=pigment {

wrinkles // granite // agate //scale 1/10

scale 3 warp { turbulence cloudturb1 } scale 1/2

turbulence cloudturb2

//turbulence 1

pigment_map {
 [0 color rgbt <1,1,1,1>*1]
  [1-cloudiness1 color rgbt <1,1,1,1>]
[1 color rgbt <1,1,1,0>*4]

}

}

1. declare cloudes1=texture {

   pigment {
   gradient y    
   scale 2
   translate y*-1
  // sine_wave    

scale 3

warp {turbulence 0.7 }

//scale 1/3

 scale 1/2

   pigment_map {
       

[0.1 cloudpig1]

        [0.2 rgbt 1]  
 //     [0.5 cloudpig1]
          [0.7 rgbt 1]

 [0.75 cloudpig1]

   }

   }    

   finish {ambient 0}

}

// rayleigh based atm

1. declare atm_thickness1 = 0.01;

//#declare atm_color1 = rgb <pow(460/650, 4), pow(460/555, 4), 1>;

#declare atm_color1 = rgb  <1,0.5,0.3>*2; 

1. declare atm_amount1=1;

1. declare atm_density1 = density

{

    function
    {
      1*exp(-6.7*(sqrt(x*x+(y)*(y)+z*z)- 1 - 0.00001)/atm_thickness1)
   //   1*exp(-6.7*(sqrt(x*x+(y)*(y)+z*z)-1- 0.00001)/atm_thickness1)
   

} }

1. declare atm_media1 = media

{

    method 3
    intervals 3
    samples 3
    scattering
    { 4

color atm_amount1*atm_color1/atm_thickness1 // extinction 1

    }
    density {atm_density1}

}

1. declare atmos1 = difference

{

    sphere {0, 1.00001 + atm_thickness1}
 //   sphere {0, 1.00001}
    hollow
    pigment {rgbt 1}
    interior {media{atm_media1}}

}

1. declare cloudlayer1= object {

 sphere {0,1

texture {    cloudes1    } 

}

scale 1.003

}

#declare Polar1=

texture { pigment {

  color rgb <1,1,1>*5

}

  normal {
    granite
    scale 0.05   
    //  scale 5
     octaves 15
     
      turbulence 0.1
      bump_size 0.1 

}

finish { ambient 0}

}

1. declare eis1=texture {

 gradient y 

scale 2 translate y*1

scale 10 warp {turbulence 0.2 } scale 0.1

scale 100

warp {turbulence 0.2 } scale 0.01

texture_map {

      [0 Polar1] 
       [0.04  pigment {color rgbt 1}] 
         [0.97 pigment {color rgbt 1}] 
       [1 Polar1 ]

}

}

1. declare icecaps1=object {

sphere {0,1 scale 1.001 }

texture {eis1}

}

1. declare testplate1= object {

// plane {z,0 }

 sphere {0,1

// texture {pigment { wrinkles color_map {[0 color rgb <0,0,1>]}} }

  texture { planetex1

// scale 1 rotate z*90

// rotate x*-45

// rotate x*-90 }

// texture {    cloudes1    } 

}

// rotate x*-90 // rotate y*-90

}

union {

object {testplate1}  
object {icecaps1} 
object {atmos1}  
object {cloudlayer1}

// rotate y*-150 // rotate y*-90 // rotate x*30 }