cwindolf’s gists

cwindolf / ciline.py

Created September 12, 2024 21:01

Plot moving means and standard deviations

	def sliding_mean_and_stddev_interval(
	axis, xs, ys, n_neighbors=30, linewidth=1, color="k", ci_alpha=0.25
	):
	"""Plot moving means and standard deviations"""
	_1 = np.ones(2 * n_neighbors + 1)
	_ys = np.nan_to_num(ys)
	sliding_sum = correlate1d(_ys, _1, mode="constant")
	sliding_N = correlate1d(np.isfinite(ys).astype(float), _1, mode="constant")
	sliding_mean = sliding_sum / sliding_N
	sliding_sumsq = correlate1d(_ys**2, _1, mode="constant")

cwindolf / ppca.py

Last active April 11, 2024 15:18

Probabilistic PCA in PyTorch with missing data. See the very nice JMLR paper of Ilin and Raiko in 2010.

cwindolf / matplotlib_contextmanagers.py

Created June 21, 2023 17:27

Matplotlib context manager helpers

	import matplotlib.pyplot as plt
	import contextlib

	@contextlib.contextmanager
	def subplots(args, *kwargs):
	fig, axes = plt.subplots(args, *kwargs)
	try:
	yield fig, axes
	finally:
	plt.show()

cwindolf / runs_to_ranges.py

Created April 20, 2023 22:14

	def runs_to_ranges(x, one_more=False):
	ranges = []
	cur = x[0]
	b = x[0]
	for a, b in zip(x, x[1:]):
	assert b > a
	if b - a == 1:
	continue
	else:
	ranges.append(range(cur, a + 1 + one_more))

cwindolf / matplotlib_preamble_sans.py

Last active September 22, 2023 16:51

Example matplotlib config with latex fonts

	%config InlineBackend.figure_format = 'retina'
	import matplotlib.pyplot as plt
	from matplotlib.markers import MarkerStyle
	from matplotlib.transforms import offset_copy
	from matplotlib.patches import Ellipse, Rectangle, ConnectionPatch
	from matplotlib.lines import Line2D
	from matplotlib.legend_handler import HandlerTuple
	import contextlib

	plt.rc("figure", dpi=300)

cwindolf / inline_labels.py

Last active December 6, 2022 22:59

Inline {x,y}axis labels in Matplotlib

	# https://stackoverflow.com/a/74706214/3979938
	from matplotlib.transforms import offset_copy

	def inline_xlabel(ax, label):
	t = offset_copy(
	ax.transAxes,
	y=-(ax.xaxis.get_tick_padding() + ax.xaxis.get_tick_space()),
	fig=fig,
	units='points'
	)

cwindolf / normxcorr1d.py

Last active February 3, 2023 16:20

1D optionally normalized, optionally weighted, optionally centered cross-correlation in PyTorch (+ SciPy fallback), with API like F.conv1d

	try:
	import torch
	import torch.nn.functional as F
	HAVE_TORCH = True
	except ImportError:
	HAVE_TORCH = False

	def normxcorr1d(
	template,
	x,

cwindolf / regline.py

Created February 6, 2022 22:07

	def regline(x, y, ax=None, **kwargs):
	b = ((x - x.mean()) * (y - y.mean())).sum() / np.square(x - x.mean()).sum()
	a = y.mean() - b * x.mean()
	x0, x1 = ax.get_xlim()
	r = np.corrcoef(x, y)[0, 1]
	ax.plot([x0, x1], [a + b * x0, a + b * x1], lw=1)
	ax.text(
	0.1,
	0.9,
	f"$\\rho={r:.2f}$",

cwindolf / tukey_scatter.py

Last active February 6, 2022 22:07

	def tukey_scatter(x, y, iqrs=1.5, ax=None, **kwargs):
	ax = ax or plt.gca()
	x_25, x_75 = np.percentile(x, [25, 75])
	x_iqr = x_75 - x_25
	y_25, y_75 = np.percentile(x, [25, 75])
	y_iqr = y_75 - y_25
	inliers = np.flatnonzero(
	(x_25 - iqrs * x_iqr < x)
	& (x < x_75 + iqrs * x_iqr)
	& (y_25 - iqrs * y_iqr < y)

cwindolf / cmdstanpy_helpers.py

Created January 25, 2022 21:30

CmdStanPy helpers

	from pathlib import Path
	import cmdstanpy
	import ujson

	def stanc(name, code, workdir=".stan"):
	Path(workdir).mkdir(exist_ok=True)
	path = Path(workdir) / f"{name}.stan"
	with open(path, "w") as f:
	f.write(code)
	model = cmdstanpy.CmdStanModel(stan_file=path, stanc_options={'warn-pedantic': True})

Charlie Windolf cwindolf