numpy.random.default_rng

ToolPythonBeginner

Classification with scikit-learn: telling two populations apart

• rng = np.random.default_rng(SEED)
• rng_fresh = np.random.default_rng(SEED + 1)

ToolPythonBeginner

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

• rng = np.random.default_rng(42)

ToolPythonIntermediate

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

• rng = np.random.default_rng(42)

RecipePythonBeginner

Fit a curve to data with error bars and draw a confidence band

• rng = np.random.default_rng(7)

ToolPythonBeginner

Matplotlib from the ground up: a two-panel figure for one journal column

• rng = np.random.default_rng(3)

ToolPythonBeginner

Minimization with scipy.optimize.minimize: the shape of a seven-atom cluster

• rng = np.random.default_rng(1)
• rng_raw = np.random.default_rng(1)

ToolPythonBeginner

Numerical integration with scipy.integrate: the area under a measured peak

• rng = np.random.default_rng(4)

ToolPythonBeginner

Random numbers with numpy.random: ten thousand reproducible random walks

• a = np.random.default_rng(SEED)
• b = np.random.default_rng(SEED)
• unseeded = [np.random.default_rng().random(10) for _ in range(2)]
• rng = np.random.default_rng(SEED) # the generator every later step draws from
• rng = np.random.default_rng(seed_seq)

ConceptPythonBeginner

The Fourier transform: asking a signal how much of each frequency it contains

• rng = np.random.default_rng(42)

ToolPythonBeginner

pandas from the ground up: a week of temperature logs

• rng = np.random.default_rng(SEED)

ToolPythonBeginner

scipy.stats from the ground up: is the difference between two samples real?

• rng = np.random.default_rng(159)