Takahiro Ueda tueda

Easily accessible datasets

Rdatasets (2293)
UC Irvine Machine Learning Repository (665)
OpenIntro Data Sets (284)
SSDSE (6)

Undocumented environment variables

External channels

FORM_PIPES

ParFORM

PF_LOG
PF_RBUFS

my-madminer-jupyter-env

Docker is required.
NVIDIA Container Toolkit is required to use GPU. See this.

Usage:

git clone https://gist.github.com/ac4a004de14b34e4e746e6412cf70249.git my-madminer-jupyter-env

!pip install git+https://gist.github.com/tueda/ec0181f0f4c8961d49dc659f79cbfd4a

from google.colab import drive
drive.mount('/content/drive')

import colab_cache

cache = colab_cache.Cache('hello-2.12.1')
if cache.exists():

	SOURCES := $(wildcard *.tex)
	DOCUMENTS := $(SOURCES:.tex=.pdf)
	CLEANFILES := \
	$(foreach doc,$(DOCUMENTS),"$(doc)") \
	$(foreach doc,$(SOURCES:.tex=.aux),"$(doc)") \
	$(foreach doc,$(SOURCES:.tex=.log),"$(doc)")

	all: $(DOCUMENTS)

	clean:

	def plot_data(data, *, figsize=None, columns=None, col_wrap=5, cat_threshold=5):
	import matplotlib.pyplt as plt
	import seaborn as sns
	import pandas as pd

	if not columns:
	columns = data.columns
	n_rows = len(columns) // col_wrap + 1
	if not figsize:
	figsize = (col_wrap * 4, n_rows * 3)

	#!/bin/bash
	#
	# Usage:
	# ./x [update\|clean]
	# [4.1.0\|4.2.0\|4.2.1\|4.3.0\|4.3.1]
	# [check\|time [-n <times>]]
	# [coverage\|gprof\|valgrind [<valgrind options>]\|helgrind\|drd\|sanitize]
	# [form\|vorm\|tform\|tvorm\|parform\|parvorm]
	# [-np <nprocs>]
	# [args...]

	* Example:
	* form -D M=10 -D N=15 test11.frm
	Symbol x1,...,x`M';
	Local F = (x1+...+x`M')^`N';
	.end

	#!/bin/sh
	#
	# @file auto-cherry-pick.sh
	#
	# Usage:
	# auto-cherry-pick.sh ref1...ref2:
	#
	set -eu

	output=auto-cherry-pick.log

	chunkifyString[s_String, n_Integer] :=
	StringJoin @@@ Partition[Characters[s], UpTo[n]];

	writeRationalApproximation[
	stream_, x_, n_, width_:72
	] := Module[{s, lines, i},
	s = Rationalize[x, Abs[x * 10^(-n)]] // InputForm // ToString;
	lines = chunkifyString[s, width - 1];
	Do[
	s = lines[[i]];