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numpy.ones

Python. Called in 3 tutorials; each line below leads to its place in the tutorial.

ToolPythonBeginner

Classification with scikit-learn: telling two populations apart

y = np.concatenate([np.ones(600, dtype=int), np.zeros(1400, dtype=int)]) # 1 = signal, 0 = background
y_fresh = np.concatenate([np.ones(n_signal, dtype=int), np.zeros(10**6 - n_signal, dtype=int)])

ToolPythonBeginner

Counting cells with scipy.ndimage: how many are there, and how large?

f"{ndi.label(line, structure=np.ones((3, 3)))[1]} with eight neighbors")
print(f"cells of Step 3 with eight neighbors: {ndi.label(mask, structure=np.ones((3, 3)))[1]}")

ToolPythonIntermediate

Filtering with scipy.signal: mains hum and noise out of an ECG

step = np.r_[np.zeros(500), np.ones(500)]