Plot 3-D¶
In [1]:
import numpy as np
import plotly.graph_objects as go
import gstlearn as gl
import gstlearn.plot3D as gop
import gstlearn.document as gdoc
import IPython
import os
from numpy import pi, cos, sin
gdoc.setNoScroll()
On the Sphere¶
Definition of the Meshing
In [2]:
gl.defineDefaultSpace(gl.ESpaceType.SN)
mesh = gl.MeshSphericalExt()
err = mesh.resetFromDb(None,None,triswitch = "-r5",verbose=False)
Display a white skin around the meshing
In [3]:
blank = gop.SurfaceOnMesh(mesh, opacity=1)
In [4]:
fig = go.Figure(data = [blank])
fig.update_scenes(xaxis_visible=False, yaxis_visible=False, zaxis_visible=False )
f = fig.show()
We overlay the meshing
In [5]:
meshing = gop.Meshing(mesh)
In [6]:
fig = go.Figure(data = [blank, meshing])
fig.update_scenes(xaxis_visible=False, yaxis_visible=False, zaxis_visible=False )
f = fig.show()
Drawing a polygon (we use the one containing the land boundaries)
In [7]:
name = gdoc.loadData("boundaries", "world.poly")
poly = gl.Polygons.createFromNF(name)
poly.display()
Polygons -------- Number of Polygon Sets = 288
In [8]:
boundaries = gop.PolygonOnSphere(poly)
equator = gop.Equator(width=5)
meridians = gop.Meridians(angle=20,color='blue')
parallels = gop.Parallels(angle=30,color='red')
pole = gop.Pole()
poleaxis = gop.PolarAxis()
In [9]:
fig = go.Figure(data = [blank,boundaries,equator,meridians,parallels,pole,poleaxis])
fig.update_scenes(xaxis_visible=False, yaxis_visible=False, zaxis_visible=False )
f = fig.show()
Representing a function on the skin of the earth together with other decoration. The function is the result of a non-conditional simulation performed with SPDE on the Sphere.
In [10]:
model = gl.Model.createFromParam(gl.ECov.MATERN,range=1500,param=1)
S = gl.ShiftOpMatrix(mesh,model.getCovAniso(0))
Q = gl.PrecisionOpMatrix(S,model.getCovAniso(0))
result = Q.simulateOne()
In [11]:
simu = gop.SurfaceOnMesh(mesh, intensity=result, opacity=1)
In [12]:
fig = go.Figure(data = [simu,boundaries,equator,meridians,parallels,pole,poleaxis])
fig.update_scenes(xaxis_visible=False, yaxis_visible=False, zaxis_visible=False )
f = fig.show()
3D in General¶
We define the space dimension
In [13]:
ndim = 3
gl.defineDefaultSpace(gl.ESpaceType.RN, ndim)
Defining the output grid
In [14]:
nx = [61,81,61]
dx = [0.1, 0.1, 0.1]
x0 = [-3., -4., -6.]
grid = gl.DbGrid.create(nx=nx, dx=dx, x0=x0)
x = grid.getOneCoordinate(0)
y = grid.getOneCoordinate(1)
z = grid.getOneCoordinate(2)
val = x*x + y*y + z*z
grid.addColumns(val,"Data",gl.ELoc.Z)
glimits = grid.getRange("Data")
Defining a Data Set with Gradient and Tangent components
In [15]:
nech = 5
coormin = grid.getCoorMinimum()
coormax = grid.getCoorMaximum()
db = gl.Db.createFromBox(nech, coormin, coormax)
np.random.seed(123)
# Data
uid = db.addColumns(np.random.uniform(10.,20.,nech), "Data", gl.ELoc.Z)
# Gradient components
uid = db.addColumns(np.random.normal(0, 1, nech),"gx",gl.ELoc.G,0)
uid = db.addColumns(np.random.normal(0, 1, nech),"gy",gl.ELoc.G,1)
uid = db.addColumns(np.random.normal(0, 1, nech),"gz",gl.ELoc.G,2)
# Tangent components
uid = db.addColumns(np.random.normal(0, 1, nech),"tx",gl.ELoc.TGTE,0)
uid = db.addColumns(np.random.normal(0, 1, nech),"ty",gl.ELoc.TGTE,1)
uid = db.addColumns(np.random.normal(0, 1, nech),"tz",gl.ELoc.TGTE,2)
3-D Visualization
In [16]:
levels = [5., 25.]
surf1 = gop.IsoSurfaceOnDbGrid(grid, "Data", useSel=False, isomin=levels[0], isomax=levels[0])
surf2 = gop.IsoSurfaceOnDbGrid(grid, "Data", useSel=False, isomin=levels[1], isomax=levels[1])
point = gop.PointDb(db, size=5, nameColor = "Data")
gradient = gop.GradientDb(db,size=0.5,colorscale='blues',sizemode='absolute')
tangent = gop.TangentDb(db,size=0.5,colorscale='gray',sizemode='absolute')
In [17]:
fig = go.Figure(data = [ surf1, surf2, point, gradient, tangent])
f = fig.show()