rpgoldman

The python script triggered the segmentation fault that is summarized in the gdb backtrace. Python provided no information beyond "Segmentation fault".

The two data files should be placed in a directory named ap as a sibling of the python script. These files are taken from the lda-c repository of the Blei lab.

	(defrecord complex [real imag])

	(defn add [c1 c2 & x]
	(if (nil? x)
	(complex. (+ (:real c1) (:real c2))
	(+ (:imag c1) (:imag c2)))
	(add (add c1 c2) (first x) (rest x))))

	;; probably this last line is buggy --- there's almost certainly an idiomatic way to do
	;; what I would do as (apply ADD (add c1 c2) (first x) (rest x))

	(ns rpg.bug
	(:require clojure.contrib.math))

	(defprotocol CPARTS
	(real [c])
	(imag [c])
	(modulus [c])
	(phase [c]))

	(defrecord complex [real imag]

	Vectorized sample posterior predictive took 590.47s
	273802490 function calls (273799694 primitive calls) in 590.469 seconds

	This is from a very slow run of `pm.fast_sample_posterior_predictive` -- it generated 1/40 the samples in 50x the time.

	Ordered by: standard name

	ncalls tottime percall cumtime percall filename:lineno(function)
	176 0.000 0.000 0.012 0.000 <__array_function__ internals>:2(all)
	7200000 7.833 0.000 90.115 0.000 <__array_function__ internals>:2(any)

	Vectorized sample posterior predictive took 11.62 seconds
	2259149 function calls (2258633 primitive calls) in 11.615 seconds

	This is for a successful, quick run of `pm.fast_sample_posterior_predictive`

	Ordered by: standard name

	ncalls tottime percall cumtime percall filename:lineno(function)
	2 0.000 0.000 0.000 0.000 <__array_function__ internals>:2(all)
	48000 0.128 0.000 1.304 0.000 <__array_function__ internals>:2(any)

	# Here's what I do to get my background data (sorry, not public)
	df = dd.read_csv('r1c5va879uaex_r1c639xp952g4.csv', assume_missing=True)

	# Now, in order to add a column, I need to be able to add metadata --
	# if I don't, I get mysterious errors about failing to infer types
	newmeta = df._meta.copy() # get the original metadata
	# add new column to metadata
	newmeta.insert(len(newmeta.columns), 'well', 'foo')
	# specify the dtype of the new column
	newmeta = newmeta.astype({'well': str})

	\def\year{2021}
	%
	%Filename: aaai21-mod.sty
	%
	\typeout{Conference Style for AAAI for LaTeX 2e -- version for the AAAI-21 conference - MODIFIED}
	% WARNING: IF YOU ARE USING THIS STYLE SHEET FOR AN AAAI PUBLICATION, YOU
	% MAY NOT MODIFY IT FOR ANY REASON. MODIFICATIONS (IN YOUR SOURCE
	% OR IN THIS STYLE SHEET WILL RESULT IN REJECTION OF YOUR PAPER).
	%
	% WARNING: This style is NOT guaranteed to work. It is provided in the

	import argparse
	import os

	from rdflib import Graph
	from sys import stdout


	def JSON_prefixes(g: Graph, stream):
	"""
	Extract prefix definitions from `g` `and write them to `stream`.

	openapi: 3.0.0
	info:
	description: 'Owlery provides a web API for an [OWL API](http://owlapi.sourceforge.net)-based
	reasoner containing a configurable set of ontologies (a "knowledgebase"). '
	version: 1.0.0
	title: Owlery API
	contact:
	email: [email protected]
	license:
	name: MIT