data_types.jl

Author: boriskaus

docs/src/man/Tutorial_AlpineData.md

@@ -126,10 +126,10 @@ units = unique(tag) #get different units
 We will use these units later to save the Moho data separately for each tectonic unit.
 
 ### 2.2 Converting the data to a `GMG` dataset
-To convert this data to a `GMG` dataset, we now have to interpolate it to a regular grid. You can generate the respective grid with the `GMG` function `LonLatDepthGrid`
+To convert this data to a `GMG` dataset, we now have to interpolate it to a regular grid. You can generate the respective grid with the `GMG` function `lonlatdepthGrid`
 
 ```julia
-Lon,Lat,Depth = LonLatDepthGrid(9.9:0.02:15.1,45.0:.02:49.0,0km);
+Lon,Lat,Depth = lonlatdepthGrid(9.9:0.02:15.1,45.0:.02:49.0,0km);
 nothing #hide
 ```
 

docs/src/man/Tutorial_Basic.md

@@ -156,7 +156,7 @@ search: CrossSection CrossSectionVolume CrossSectionPoints CrossSectionSurface F
   Example:
   ≡≡≡≡≡≡≡≡
 
-  julia> Lon,Lat,Depth   =   LonLatDepthGrid(10:20,30:40,(-300:25:0)km);
+  julia> Lon,Lat,Depth   =   lonlatdepthGrid(10:20,30:40,(-300:25:0)km);
   julia> Data            =   Depth*2;                # some data
   julia> Vx,Vy,Vz        =   ustrip(Data*3),ustrip(Data*4),ustrip(Data*5);
   julia> Data_set3D      =   GeoData(Lon,Lat,Depth,(Depthdata=Data,LonData=Lon, Velocity=(Vx,Vy,Vz)));
@@ -209,7 +209,7 @@ First we need do define a `ProjectionPoint`  around which we project the data
 ```julia
 proj = ProjectionPoint(Lon=12.0,Lat =43)
 
-Topo_cart = Convert2CartData(Topo_Alps, proj)
+Topo_cart = convert2CartData(Topo_Alps, proj)
 ```
 
 ````
@@ -225,7 +225,7 @@ CartData
 And do the same with the tomography:
 
 ```julia
-Tomo_cart = Convert2CartData(Tomo_Alps, proj)
+Tomo_cart = convert2CartData(Tomo_Alps, proj)
 ```
 
 ````
@@ -259,7 +259,7 @@ Yet, because of the curvature of the Earth, the resulting 3D model is not strict
 This can be achieved in a relatively straightforward manner, by creating a new 3D dataset that is slightly within the curved boundaries of the projected data set:
 
 ```julia
-Tomo_rect = CartData(XYZGrid(-550.0:10:600, -500.0:10:700, -600.0:5:-17));
+Tomo_rect = CartData(xyzGrid(-550.0:10:600, -500.0:10:700, -600.0:5:-17));
 ```
 
 the routine `projectCartData` will then project the data from the geographic coordinates to the new rectilinear grid:
@@ -281,7 +281,7 @@ CartData
 we can do the same with topography:
 
 ```julia
-Topo_rect = CartData(XYZGrid(-550.0:1:600, -500.0:1:700, 0))
+Topo_rect = CartData(xyzGrid(-550.0:1:600, -500.0:1:700, 0))
 Topo_rect = projectCartData(Topo_rect, Topo_Alps, proj)
 ```
 

docs/src/man/Tutorial_FaultDensity.md

@@ -76,7 +76,7 @@ data   = faults.data[indlon,indlat]
 Create GeoData from restricted data
 
 ```julia
-Lon3D,Lat3D, Faults = LonLatDepthGrid(Lon,Lat,0);
+Lon3D,Lat3D, Faults = lonlatdepthGrid(Lon,Lat,0);
 Faults[:,:,1]       = data
 Data_Faults         = GeoData(Lon3D,Lat3D,Faults,(Faults=Faults,))
 ```

docs/src/man/Tutorial_Jura.md

@@ -109,7 +109,7 @@ proj = ProjectionPoint(Lon=6, Lat=46.5)
 We can simply transfer the TopoGeology map to Cartesian values with:
 
 ```julia
-Convert2CartData(Topo,proj)
+convert2CartData(Topo,proj)
 ```
 
 ```julia
@@ -127,7 +127,7 @@ It is therefore better to use the `projectCartData` to project the `GeoData` str
 Let's first create this structure by using `x`,`y` coordinates that are slightly within the ranges given above:
 
 ```julia
-TopoGeology_cart = CartData(XYZGrid(range(-70,150,length=3500), range(-105,130,length=2500), 0.0))
+TopoGeology_cart = CartData(xyzGrid(range(-70,150,length=3500), range(-105,130,length=2500), 0.0))
 ```
 
 ```julia
@@ -170,10 +170,10 @@ CartData
 ```
 
 Finally, we can also transfer the cross-section to cartesian coordinates. As this is just for visualization, we will
-use `Convert2CartData` in this case
+use `convert2CartData` in this case
 
 ```julia
-CrossSection_1_cart = Convert2CartData(CrossSection_1,proj)
+CrossSection_1_cart = convert2CartData(CrossSection_1,proj)
 ```
 
 for visualization, it is nice if we can remove the part of the cross-section that is above the topography.
@@ -219,8 +219,8 @@ We create both a surface and a 3D block
 ```julia
 nx, ny, nz = 1024, 1024, 128
 x,y,z = range(-100,180,nx), range(-50,70,ny), range(-8,4,nz)
-ComputationalSurf  =  CartData(XYZGrid(x,y,0))
-ComputationalGrid  =  CartData(XYZGrid(x,y,z))
+ComputationalSurf  =  CartData(xyzGrid(x,y,0))
+ComputationalGrid  =  CartData(xyzGrid(x,y,z))
 ```
 
 Re-interpolate the rotated to the new grid:

docs/src/man/Tutorial_LaPalma.md

@@ -71,16 +71,16 @@ proj = ProjectionPoint(Lon=-17.84, Lat=28.56)
 Once this is done you can convert the topographic data to the cartesian reference frame
 
 ```julia
-EQ_cart   = Convert2CartData(data_all_EQ, proj);
-Topo_cart = Convert2CartData(Topo, proj)
+EQ_cart   = convert2CartData(data_all_EQ, proj);
+Topo_cart = convert2CartData(Topo, proj)
 ```
 
 It is important to realize that the cartesian coordinates of the topographic grid is no longer strictly orthogonal after this conversion. You don't notice that in the current example, as the model domain is rather small.
 In other cases, however, this is quite substantial (e.g., India-Asia collision zone).
 LaMEM needs an orthogonal grid of topography, which we can create with:
 
 ```julia
-Topo_model = CartData(XYZGrid(-35:.1:30,-15:.2:45,0));
+Topo_model = CartData(xyzGrid(-35:.1:30,-15:.2:45,0));
 nothing #hide
 ```
 
@@ -102,7 +102,7 @@ It is useful to plot the earthquake density in 3D, which indicates where most ac
 For this, we first create a 3D grid of the region:
 
 ```julia
-Grid_3D = CartData(XYZGrid(-35:.3:30,-15:.25:45,-50:.5:5))
+Grid_3D = CartData(xyzGrid(-35:.3:30,-15:.25:45,-50:.5:5))
 ```
 
 Next we check how many earthquakes are around the grid points:

docs/src/man/Tutorial_MohoTopo_Spada.md

@@ -108,7 +108,7 @@ data_Moho_combined = GeoData(lon, lat, depth, (MohoDepth=depth*km,))
 Next, we define a regular lon/lat grid
 
 ```julia
-Lon, Lat, Depth  = LonLatDepthGrid(4.1:0.1:11.9,42.5:.1:49,-30km)
+Lon, Lat, Depth  = lonlatdepthGrid(4.1:0.1:11.9,42.5:.1:49,-30km)
 ```
 
 We will use a nearest neighbor interpolation method to fit a surface through the data, which has the advantage that it will take the discontinuities into account.

docs/src/man/datastructures.md

@@ -9,7 +9,7 @@ GeoData
 CartData
 UTMData
 ParaviewData
-LonLatDepthGrid
-XYZGrid
+lonlatdepthGrid
+xyzGrid
 ProjectionPoint
 ```

docs/src/man/projection.md

@@ -47,7 +47,7 @@ ProjectionPoint(37.5, 17.3, 703311.4380385976, 4.152826288024972e6, 33, true)
 
 Projecting the `GeoData` set using this projection point is done with:
 ```julia
-julia> Convert2UTMzone(Topo,p)
+julia> convert2UTMzone(Topo,p)
 UTMData 
   UTM zone : 33-33 North
     size   : (165, 75, 1)
@@ -61,7 +61,7 @@ Whereas this is now in UTM Data (in meters), it is distorted.
 
 Often it is more convenient to have this in `CartData`, which is done in a similar manner:
 ```julia
-julia> Topo_Cart = Convert2CartData(Topo,p)
+julia> Topo_Cart = convert2CartData(Topo,p)
 CartData 
     size   : (165, 75, 1)
     x      ϵ [ -2778.3805979523936 km : 2878.039855346856 km]
@@ -77,7 +77,7 @@ Whereas this is ok to look at and compare with a LaMEM model setup, we cannot us
 #### 2. Projecting data
 For use with LaMEM, you would need an orthogonal cartesian grid. From the last command above we get some idea on the area, so we can create this:
 ```julia
-julia> Topo_Cart_orth  = CartData(XYZGrid(-2000:20:2000,-1000:20:1000,0))
+julia> Topo_Cart_orth  = CartData(xyzGrid(-2000:20:2000,-1000:20:1000,0))
 CartData 
     size   : (201, 101, 1)
     x      ϵ [ -2000.0 km : 2000.0 km]
@@ -104,7 +104,7 @@ You can do similar projections with full 3D data sets or pointwise data.
 #### 3. List of relevant functions
 
 ```@docs
-GeophysicalModelGenerator.Convert2CartData
+GeophysicalModelGenerator.convert2CartData
 GeophysicalModelGenerator.projectCartData
-GeophysicalModelGenerator.Convert2UTMzone
+GeophysicalModelGenerator.convert2UTMzone
 ```

docs/src/man/tools.md

@@ -15,8 +15,8 @@ InterpolateTopographyOnPlane
 ParseColumns_CSV_File
 RotateTranslateScale!
 pointData2NearestGrid
-Convert2UTMzone
-Convert2CartData
+convert2UTMzone
+convert2CartData
 projectCartData
 drape_on_topo
 LithostaticPressure!

docs/src/man/tutorial_Coastlines.md

@@ -20,7 +20,7 @@ The parameter resolution should be either `c`,`l`,`i`,`h` or `f` (standing for c
 
 ##### 1.2 Save in Paraview
 ```julia
-julia> Lon,Lat,Depth    =   LonLatDepthGrid(lon[ind_lon],lat[ind_lat],0km);
+julia> Lon,Lat,Depth    =   lonlatdepthGrid(lon[ind_lon],lat[ind_lat],0km);
 julia> data_surf        =   zeros(size(Lon));
 julia> data_surf[:,:,1] =   data[ind_lon,ind_lat]
 julia> data_surface     =   GeoData(Lon, Lat, Depth, (SurfaceType=data_surf,))