l1_ratio in cnmf.paras.init for call to NMF()

flatironinstitute · Jan 14, 2025 · 6cf6c27 · 6cf6c27
1 parent 3ed5256
commit 6cf6c27
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Showing 2 changed files with 15 additions and 5 deletions.
diff --git a/caiman/source_extraction/cnmf/initialization.py b/caiman/source_extraction/cnmf/initialization.py
@@ -339,7 +339,7 @@ def initialize_components(Y, K=30, gSig=[5, 5], gSiz=None, ssub=1, tsub=1, nIter
     elif method == 'sparse_nmf':
         Ain, Cin, _, b_in, f_in = sparseNMF(
             Y_ds, nr=K, nb=nb, max_iter_snmf=max_iter_snmf, alpha=alpha_snmf,
-            sigma_smooth=sigma_smooth_snmf, remove_baseline=remove_baseline, perc_baseline=perc_baseline_snmf)
+            sigma_smooth=sigma_smooth_snmf, remove_baseline=remove_baseline, perc_baseline=perc_baseline_snmf, options=options_total)
 
     elif method == 'compressed_nmf':
         Ain, Cin, _, b_in, f_in = compressedNMF(
@@ -485,7 +485,7 @@ def ICA_PCA(Y_ds, nr, sigma_smooth=(.5, .5, .5), truncate=2, fun='logcosh',
     return A_in, C_in, center, b_in, f_in
 
 def sparseNMF(Y_ds, nr, max_iter_snmf=200, alpha=0.5, sigma_smooth=(.5, .5, .5),
-              remove_baseline=True, perc_baseline=20, nb=1, truncate=2):
+              remove_baseline=True, perc_baseline=20, nb=1, truncate=2, options=None):
     """
     Initialization using sparse NMF
 
@@ -511,6 +511,9 @@ def sparseNMF(Y_ds, nr, max_iter_snmf=200, alpha=0.5, sigma_smooth=(.5, .5, .5),
         nb: int
             Number of background components
 
+        options: dict
+            Extra options for sparseNMF
+
     Returns:
         A: np.array
             2d array of size (# of pixels) x nr with the spatial components.
@@ -523,6 +526,12 @@ def sparseNMF(Y_ds, nr, max_iter_snmf=200, alpha=0.5, sigma_smooth=(.5, .5, .5),
             2d array of size nr x 2 [ or 3] with the components centroids
     """
     logger = logging.getLogger("caiman")
+
+    if options is not None and 'l1_ratio' in options:
+        l1_ratio_thresh = options['l1_ratio']
+    else:
+        l1_ratio_thresh = 0.0
+
     m = scipy.ndimage.gaussian_filter(np.transpose(
         Y_ds, np.roll(np.arange(Y_ds.ndim), 1)), sigma=sigma_smooth,
         mode='nearest', truncate=truncate)
@@ -539,15 +548,15 @@ def sparseNMF(Y_ds, nr, max_iter_snmf=200, alpha=0.5, sigma_smooth=(.5, .5, .5),
     d = np.prod(dims)
     yr = np.reshape(m1, [T, d], order='F')
 
-    logger.debug(f"Running SparseNMF with alpha_W={alpha}")
+    logger.debug(f"Running SparseNMF with alpha_W={alpha} and l1_ratio={l1_ratio_thresh}")
     mdl = NMF(n_components=nr, 
               verbose=False, 
               init='nndsvd', 
               tol=1e-10,
               max_iter=max_iter_snmf, 
               shuffle=False, 
               alpha_W=alpha, 
-              l1_ratio=0.0)
+              l1_ratio=l1_ratio_thresh)
     C = mdl.fit_transform(yr).T
     A = mdl.components_.T
     A_in = A

diff --git a/caiman/source_extraction/cnmf/params.py b/caiman/source_extraction/cnmf/params.py
@@ -718,7 +718,8 @@ def __init__(self, fnames=None, dims=None, dxy=(1, 1),
             'gSiz': gSiz,
             'init_iter': init_iter,
             'kernel': None,           # user specified template for greedyROI
-            'lambda_gnmf' :1,         # regularization weight for graph NMF
+            'lambda_gnmf': 1,         # regularization weight for graph NMF
+            'l1_ratio': 0.0,
             'maxIter': 5,             # number of HALS iterations
             'max_iter_snmf': 500,
             'method_init': method_init,    # can be greedy_roi, corr_pnr sparse_nmf, local_NMF