This is Total Magnetic Intensity (TMI) data from the Black Hills Norite in South Australia.
Reference: https://doi.org/10.1071/ASEG2016ab115
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import geosoft.gxpy.gx as gx
import geosoft.gxpy.utility as gxu
import geosoft.gxpy.grid as gxgrd
import geosoft.gxpy.grid_utility as gxgrdu
from IPython.display import Image
gxc = gx.GXpy()
gxu.check_version('9.4.0b0')
# get the sample data from github
url = 'https://github.com/GeosoftInc/gxpy/raw/master/examples/data/'
grid = 'bhn_tmi_250m.grd'
gxu.url_retrieve(url + grid)
gxu.url_retrieve(url + grid + '.gi')
gxu.url_retrieve(url + grid + '.xml')
grd = gxgrd.Grid.open(grid)
Image(grd.image_file(shade=True, pix_width=500))
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In [2]:
gdx = gxgrdu.derivative(grd, gxgrdu.DERIVATIVE_X)
Image(gdx.image_file(shade=True, pix_width=500))
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In [3]:
gdy = gxgrdu.derivative(grd, gxgrdu.DERIVATIVE_Y)
Image(gdy.image_file(shade=True, pix_width=500))
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In [4]:
gdz = gxgrdu.derivative(grd, gxgrdu.DERIVATIVE_Z)
Image(gdz.image_file(shade=True, pix_width=500))
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Z derivative using space-domain convolution:
In [5]:
gdz = gxgrdu.derivative(grd, gxgrdu.DERIVATIVE_Z, fft=False)
Image(gdz.image_file(shade=True, pix_width=500))
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In [6]:
gdxy = gxgrdu.derivative(grd, gxgrdu.DERIVATIVE_XY)
Image(gdxy.image_file(shade=True, pix_width=500))
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In [7]:
gdxyz = gxgrdu.derivative(grd, gxgrdu.DERIVATIVE_XYZ)
Image(gdxyz.image_file(shade=True, pix_width=500))
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In [8]:
gdt = gxgrdu.derivative(grd, gxgrdu.TILT_ANGLE)
Image(gdt.image_file(shade=True, pix_width=500))
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