rpgoldman

(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))

rpgoldman

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

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

(defrecord complex [real imag]

rpgoldman

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)

rpgoldman

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)

rpgoldman

# 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})

rpgoldman

rpgoldman

\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

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.

rpgoldman

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`.

rpgoldman

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: balhoff@renci.org
  license:
    name: MIT