Demedian(
*args ,
dim: str = time,
)-> None
Remove the median along a given dimension of a DASCore patch.
NaN values are ignored when computing the median, consistent with Patch.median. They remain NaN in the output but do not affect any other sample.
Parameters
|
Parameter
|
Description
|
|
patch :
|
The patch to remove the median from.
|
|
dim : str
|
Dimension name (e.g., “time”, “distance”).
|
Example
import matplotlib.pyplot as plt
import dascore as dc
import numpy as np
patch = dc.get_example_patch('example_event_2')
nx,nt = patch.data.shape
# Add some periodic common-mode noise
x = np.linspace(0, 6 * np.pi, nt)
y = np.sin(x) * patch.data.max() / 30
Y = y[np.newaxis, :] * np.ones((nx,nt), dtype=float)
patch0 = patch + Y
# Prepare figure
fig, axs = plt.subplots(1, 3, figsize=(20,8), layout='constrained')
# Show patch with common-mode noise
ax0 = patch0.viz.waterfall(ax = axs[0], show=False)
_ = ax0.set_title('Original with common-mode noise');
# Show demedian applied patch
patch1 = patch0.demedian(dim='distance')
ax1 = patch1.viz.waterfall(ax = axs[1], show=False)
_ = ax1.set_title('Removed common-mode noise');
# Show difference
ax2 = (patch0-patch1).viz.waterfall(ax = axs[2], show=False)
_ = ax2.set_title('Difference');
plt.show() # doctest: +SKIP
plt.close(fig)
Methods
|
Name
|
Description
|
|
check
|
Refuse a patch which does not carry what the operation needs.
|
|
get_metadata
|
Return the axis to remove the median along.
|
|
model_copy
|
Copy the model, dropping cached values the update invalidates.
|
|
new
|
Create new instance with some attributed updated.
|
|
numpy_kernel
|
Return the data with the NaN-ignoring median of each slice removed.
|
|
demedian
|
Remove the median along a given dimension of a DASCore patch.
|
|
reconcile
|
Return metadata or a patch holding the final data; default as is.
|
|
run
|
Run the operation: check, get_metadata, kernel, reconcile, record.
|
