def loadGRDFile(fileName, plotIt=False):
"""
Load a data matrix in Geosoft *.grd format and return
a dictionary with gridded data
"""
try:
import geosoft.gxpy.grid as gxgrd
import geosoft.gxpy.gx as gx
except ImportError:
print("geosoft module not installed. loadGRDFile ")
return
gxc = gx.GXpy()
data = dataGrid()
with gxgrd.Grid(fileName) as grid:
lim = grid.extent_2d()
data.limits = np.r_[lim[0], lim[2], lim[1], lim[3]]
# coordinate_system = grid.coordinate_system
temp = grid.xyzv()[:, :, 3]
temp[temp == -99999] = np.nan
data._values = temp
data.nx, data.ny = grid.nx, grid.ny
data.dx, data.dy = grid.dx, grid.dy
data.x0, data.y0 = grid.x0 - grid.dx / 2, grid.y0 - grid.dy / 2
if plotIt:
xLoc = np.asarray(range(data.nx)) * data.dx + data.x0
yLoc = np.asarray(range(data.ny)) * data.dy + data.y0
fig, axs = plt.figure(figsize=(8, 8)), plt.subplot()
fig, im, cbar = Simulator.plotData2D(xLoc,
yLoc,
data.values,
marker=False,
fig=fig,
ax=axs,
colorbar=True)
axs.grid(True)
cbar.set_label("TMI (nT)")
plt.show()
fig.savefig("./images/SearchQuestII.png", bbox_inches="tight")
return data
def rungx():
project = gxpj.Geosoft_project()
# there must be grids in the project
if len(project.project_grids) == 0:
raise Exception('This project contains no grids.')
# default grid will be the current grid, or the first grid in the list of project grids
if project.current_grid:
default_grid = project.current_grid
else:
default_grid = project.project_grids[0]
# ask the user to select a grid
grid_name = gxpj.get_user_input(title='Vertical derivative of a grid',
prompt='Grid to process',
kind='list',
items=project.project_grids,
default=default_grid)
# ask for a new grid file name
new_grid = gxpj.get_user_input(
title='Vertical derivative of a grid',
prompt='Output vertical derivative grid name',
kind='file',
filemask='*.grd')
# calculate vertical derivative
with gxgrd.Grid(grid_name) as g_input:
with gxgrd.Grid.new(new_grid,
properties=g_input.properties(),
overwrite=True) as g_output:
gxapi.GXIMU.grid_vd(g_input.gximg, g_output.gximg)
# open the vertical derivative grid
gxpj.add_document(new_grid)
import geosoft.gxpy.gx as gx
import geosoft.gxpy.view as gxview
import geosoft.gxpy.group as gxgroup
import geosoft.gxpy.agg as gxagg
import geosoft.gxpy.grid as gxgrd
import geosoft.gxpy.viewer as gxviewer
gxc = gx.GXpy()
grid_file = 'Wittichica Creek Residual Total Field.grd'
# create a 3D view
with gxview.View_3d.new("TMI on a plane",
area_2d=gxgrd.Grid(grid_file).extent_2d(),
coordinate_system=gxgrd.Grid(grid_file).coordinate_system,
overwrite=True) as v:
v3d_name = v.file_name
# add the grid image to the view, with shading, ands contour
gxgroup.Aggregate_group.new(v, gxagg.Aggregate_image.new(grid_file, shade=True, contour=20))
gxgroup.contour(v, 'TMI_contour', grid_file)
# display the map in a Geosoft viewer
gxviewer.view_document(v3d_name, wait_for_close=False)
import geosoft.gxpy.gx as gx
import geosoft.gxpy.map as gxmap
import geosoft.gxpy.view as gxview
import geosoft.gxpy.group as gxgroup
import geosoft.gxpy.agg as gxagg
import geosoft.gxpy.grid as gxgrd
import geosoft.gxpy.viewer as gxviewer
gxc = gx.GXpy()
# create a map from grid coordinate system and extent
with gxgrd.Grid('Wittichica Creek Residual Total Field.grd') as grd:
grid_file_name = grd.file_name_decorated
# create a map for this grid on A4 media, scale to fit the extent
with gxmap.Map.new('Wittichica residual TMI',
data_area=grd.extent_2d(),
media="A4",
margins=(1, 3.5, 3, 1),
coordinate_system=grd.coordinate_system,
overwrite=True) as gmap:
map_file_name = gmap.file_name
# draw into the views on the map. We are reopening the map as the Aggregate class only works with a closed grid.
with gxmap.Map.open(map_file_name) as gmap:
# work with the data view, draw a line around the data view
with gxview.View.open(gmap, "data") as v:
# add the grid image to the view, with shading, 20 nT contour interval to match default contour lines
with gxagg.Aggregate_image.new(grid_file_name, shade=True, contour=20) as agg: