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Pad grids automatically before applying transformations #608

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2476017
Better comments in apply filter and a test notebook
leouieda Oct 21, 2025
25c1a97
Try to mute ifft lag warnings
leouieda Oct 22, 2025
e443ece
Add and remove padding automatically in apply_filter
leouieda Oct 22, 2025
238951c
Ignore a Ruff warning about replacing dict comp with fromkeys
leouieda Oct 22, 2025
bbf70f1
Add more tests and update older ones
leouieda Oct 23, 2025
27b4858
Fix the reduction to the pole test
leouieda Oct 29, 2025
38923f6
Remove Oasis Montaj test for reduction to the pole
leouieda Oct 30, 2025
4d2dd30
Come up with a better test for gaussian filters
leouieda Oct 30, 2025
2f886f6
Fix tilt angle test
leouieda Mar 30, 2026
175d35a
Merge branch 'main' into padding-inside
leouieda Mar 30, 2026
7169f6e
Adjust Euler tests after the new filters
leouieda Mar 31, 2026
d841ce3
Fix broken tests and add missing tests
leouieda Mar 31, 2026
6a3863c
Fix broken formatting
leouieda Mar 31, 2026
5f5b797
Update docstrings and add option to control padding in transformations
leouieda Apr 1, 2026
8551905
Update gallery examples to use built-in padding
leouieda Apr 1, 2026
8b09bab
Use padding in Gaussian filters and don't drop extra coords always
leouieda Apr 2, 2026
a99ea83
Remove test notebook
leouieda Apr 2, 2026
98ffd81
Remove Montaj testing grid
leouieda Apr 2, 2026
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17 changes: 1 addition & 16 deletions doc/gallery_src/transformations/reduction_to_pole.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,6 @@
import pygmt
import verde as vd
import xarray as xr
import xrft

import harmonica as hm

Expand All @@ -22,15 +21,6 @@
fname = ensaio.fetch_lightning_creek_magnetic(version=1)
magnetic_grid = xr.load_dataarray(fname)

# Pad the grid to increase accuracy of the FFT filter
pad_width = {
"easting": magnetic_grid.easting.size // 3,
"northing": magnetic_grid.northing.size // 3,
}
# drop the extra height coordinate
magnetic_grid_no_height = magnetic_grid.drop_vars("height")
magnetic_grid_padded = xrft.pad(magnetic_grid_no_height, pad_width)

# Define the inclination and declination of the region by the time of the data
# acquisition (1990).
inclination, declination = -52.98, 6.51
Expand All @@ -39,16 +29,11 @@
# that the sources share the same inclination and declination as the
# geomagnetic field.
rtp_grid = hm.reduction_to_pole(
magnetic_grid_padded, inclination=inclination, declination=declination
magnetic_grid, inclination=inclination, declination=declination
)

# Unpad the reduced to the pole grid
rtp_grid = xrft.unpad(rtp_grid, pad_width)

# Show the reduced to the pole grid
print("\nReduced to the pole magnetic grid:\n", rtp_grid)


# Plot original magnetic anomaly and the reduced to the pole
fig = pygmt.Figure()
with fig.subplot(nrows=1, ncols=2, figsize=("28c", "15c"), sharey="l"):
Expand Down
16 changes: 1 addition & 15 deletions doc/gallery_src/transformations/tga.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,6 @@
import pygmt
import verde as vd
import xarray as xr
import xrft

import harmonica as hm

Expand All @@ -22,21 +21,8 @@
fname = ensaio.fetch_lightning_creek_magnetic(version=1)
magnetic_grid = xr.load_dataarray(fname)

# Pad the grid to increase accuracy of the FFT filter
pad_width = {
"easting": magnetic_grid.easting.size // 3,
"northing": magnetic_grid.northing.size // 3,
}
# drop the extra height coordinate
magnetic_grid_no_height = magnetic_grid.drop_vars("height")
magnetic_grid_padded = xrft.pad(magnetic_grid_no_height, pad_width)

# Compute the total gradient amplitude of the grid
tga = hm.total_gradient_amplitude(magnetic_grid_padded)

# Unpad the total gradient amplitude grid
tga = xrft.unpad(tga, pad_width)

tga = hm.total_gradient_amplitude(magnetic_grid)
# Show the total gradient amplitude
print("\nTotal Gradient Amplitude:\n", tga)

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29 changes: 4 additions & 25 deletions doc/gallery_src/transformations/tilt.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,6 @@
import pygmt
import verde as vd
import xarray as xr
import xrft

import harmonica as hm

Expand All @@ -22,21 +21,8 @@
fname = ensaio.fetch_lightning_creek_magnetic(version=1)
magnetic_grid = xr.load_dataarray(fname)

# Pad the grid to increase accuracy of the FFT filter
pad_width = {
"easting": magnetic_grid.easting.size // 3,
"northing": magnetic_grid.northing.size // 3,
}
# drop the extra height coordinate
magnetic_grid_no_height = magnetic_grid.drop_vars("height")
magnetic_grid_padded = xrft.pad(magnetic_grid_no_height, pad_width)

# Compute the tilt of the grid
tilt_grid = hm.tilt_angle(magnetic_grid_padded)

# Unpad the tilt grid
tilt_grid = xrft.unpad(tilt_grid, pad_width)

tilt_grid = hm.tilt_angle(magnetic_grid)
# Show the tilt
print("\nTilt:\n", tilt_grid)

Expand All @@ -47,19 +33,12 @@
# Apply a reduction to the pole over the magnetic anomaly grid. We will assume
# that the sources share the same inclination and declination as the
# geomagnetic field.
rtp_grid_padded = hm.reduction_to_pole(
magnetic_grid_padded, inclination=inclination, declination=declination
rtp_grid = hm.reduction_to_pole(
magnetic_grid, inclination=inclination, declination=declination
)

# Unpad the reduced to the pole grid
rtp_grid = xrft.unpad(rtp_grid_padded, pad_width)

# Compute the tilt of the padded rtp grid
tilt_rtp_grid = hm.tilt_angle(rtp_grid_padded)

# Unpad the tilt grid
tilt_rtp_grid = xrft.unpad(tilt_rtp_grid, pad_width)

tilt_rtp_grid = hm.tilt_angle(rtp_grid)
# Show the tilt from RTP
print("\nTilt from RTP:\n", tilt_rtp_grid)

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16 changes: 1 addition & 15 deletions doc/gallery_src/transformations/upward_continuation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,7 +12,6 @@
import ensaio
import pygmt
import xarray as xr
import xrft

import harmonica as hm

Expand All @@ -21,22 +20,9 @@
fname = ensaio.fetch_lightning_creek_magnetic(version=1)
magnetic_grid = xr.load_dataarray(fname)

# Pad the grid to increase accuracy of the FFT filter
pad_width = {
"easting": magnetic_grid.easting.size // 3,
"northing": magnetic_grid.northing.size // 3,
}
# drop the extra height coordinate
magnetic_grid_no_height = magnetic_grid.drop_vars("height")
magnetic_grid_padded = xrft.pad(magnetic_grid_no_height, pad_width)

# Upward continue the magnetic grid, from 500 m to 1000 m
# (a height displacement of 500m)
upward_continued = hm.upward_continuation(magnetic_grid_padded, height_displacement=500)

# Unpad the upward continued grid
upward_continued = xrft.unpad(upward_continued, pad_width)

upward_continued = hm.upward_continuation(magnetic_grid, height_displacement=500)
# Show the upward continued grid
print("\nUpward continued magnetic grid:\n", upward_continued)

Expand Down
16 changes: 1 addition & 15 deletions doc/gallery_src/transformations/upward_derivative.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,6 @@
import pygmt
import verde as vd
import xarray as xr
import xrft

import harmonica as hm

Expand All @@ -22,21 +21,8 @@
fname = ensaio.fetch_lightning_creek_magnetic(version=1)
magnetic_grid = xr.load_dataarray(fname)

# Pad the grid to increase accuracy of the FFT filter
pad_width = {
"easting": magnetic_grid.easting.size // 3,
"northing": magnetic_grid.northing.size // 3,
}
# drop the extra height coordinate
magnetic_grid_no_height = magnetic_grid.drop_vars("height")
magnetic_grid_padded = xrft.pad(magnetic_grid_no_height, pad_width)

# Compute the upward derivative of the grid
deriv_upward = hm.derivative_upward(magnetic_grid_padded)

# Unpad the derivative grid
deriv_upward = xrft.unpad(deriv_upward, pad_width)

deriv_upward = hm.derivative_upward(magnetic_grid)
# Show the upward derivative
print("\nUpward derivative:\n", deriv_upward)

Expand Down
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