Comments (1)
brianhie
commented on August 21, 2024
@adamov-artem you can call to_numpy() to get the count matrix, then do the PCA/geosketch routine, and then use the indices returned by gs() to index into your data frame using iloc().
For example,
X = data_frame.to_numpy()
# PCA.
from fbpca import pca
U, s, Vt = pca(X, k=100) # E.g., 100 PCs.
X_dimred = U[:, :100] * s[:100]
# Sketch.
from geosketch import gs
N = 20000 # Number of samples to obtain from the data set.
sketch_index = gs(X_dimred, N, replace=False)
data_frame_sketch = data_frame.iloc[sketch_index, :]
from geosketch.
Related Issues (10)
- Missing MatrixMarket headers HOT 1
- Label count mismatch HOT 1
- Determining optimal sampling rate HOT 2
- Not really the rarest cell types? HOT 2
- Index issue of the R wrapper HOT 2
- How could results of geosketch be replicatable? HOT 1
- FutureWarning: The sklearn.cluster.k_means_ module is deprecated in version 0.22 and will be removed in version 0.24. HOT 2
- Bug, Non-random output - same observation sampled repeatedly in subsequent calls to gs() with same sketch size HOT 5
- Data Location for Replication HOT 2
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from geosketch.