Chris Barnes clbarnes

## autopep8.sh
autopep8 path/to/project/directory --recursive --in-place --pep8-passes 2000 --verbose

## remove_self_loops.m
function W_ = remove_self_loops(W)
% REMOVE_SELF_LOOPS    Removal of self-self connections from an input
% matrix
%
%   W_ = remove_self_loops(W);
%
%   Return a copy of the input matrix with all self-self connections
%      removed (i.e. the primary diagonal set to all 0s).
%
%   Inputs: W           binary or weighted connectivity matrix

## arbitrary_integration.py
from inspect import signature
from scipy.integrate import quad


def get_fn_str(fn, lims=(0, 1), existing_string=None, arg_count=0):
    """
    Recursively generate a string which, when evaluated, will integrate an arbitrary function over all of its variables within the given limits.
    """
    if existing_string is None:
        return get_fn_str(fn, lims=lims, existing_string="quad({{}}, {}, {})[0]".format(lims[0], lims[1]),

## timestamped_zip.sh
#!/bin/bash

timestamp=$(date +"%Y-%m-%d_%H:%M:%S")
zip -r "backup_$timestamp.zip" *

## p15_example.py
from problog.tasks import sample
from problog.program import PrologString

modeltext = """
my_uniform(0,10)::a.
0.5::b.
c :- value(a, A), A >= 3; b.
query(a).
query(b).
query(c).

## reinstall_problog.sh
#!/bin/bash

set -e

STARTING_ENV="$CONDA_DEFAULT_ENV"

if test -z "$1" ; then
  TARGET_ENV="$1"
  source activate TARGET_ENV
else

## elegans_neuron_classes.py
class NodeClassifier:
    def __init__(self):
        self._nodes = set(NODES)
        self._subs = dict(ALLOWED_SUBSTITUTIONS)

    def __getitem__(self, key):
        if key in self._nodes:
            return [key]

        ret = []

## module.py
"""
And here's the easiest way to get that file in modules installed in this way.
"""
import os
import sys

DATAFILE_PATH = os.path.abspath('path_to_something')

## cycle_gen.py
def cycle_gen(sequence):
  while True:
    yield from sequence

## list.csv
1
2
3
	function W_ = remove_self_loops(W)
	% REMOVE_SELF_LOOPS Removal of self-self connections from an input
	% matrix
	%
	% W_ = remove_self_loops(W);
	%
	% Return a copy of the input matrix with all self-self connections
	% removed (i.e. the primary diagonal set to all 0s).
	%
	% Inputs: W binary or weighted connectivity matrix
	from inspect import signature
	from scipy.integrate import quad


	def get_fn_str(fn, lims=(0, 1), existing_string=None, arg_count=0):
	"""
	Recursively generate a string which, when evaluated, will integrate an arbitrary function over all of its variables within the given limits.
	"""
	if existing_string is None:
	return get_fn_str(fn, lims=lims, existing_string="quad({{}}, {}, {})[0]".format(lims[0], lims[1]),
	#!/bin/bash

	timestamp=$(date +"%Y-%m-%d_%H:%M:%S")
	zip -r "backup_$timestamp.zip" *
	from problog.tasks import sample
	from problog.program import PrologString

	modeltext = """
	my_uniform(0,10)::a.
	0.5::b.
	c :- value(a, A), A >= 3; b.
	query(a).
	query(b).
	query(c).
	#!/bin/bash

	set -e

	STARTING_ENV="$CONDA_DEFAULT_ENV"

	if test -z "$1" ; then
	TARGET_ENV="$1"
	source activate TARGET_ENV
	else
	class NodeClassifier:
	def __init__(self):
	self._nodes = set(NODES)
	self._subs = dict(ALLOWED_SUBSTITUTIONS)

	def __getitem__(self, key):
	if key in self._nodes:
	return [key]

	ret = []
	"""
	And here's the easiest way to get that file in modules installed in this way.
	"""
	import os
	import sys

	DATAFILE_PATH = os.path.abspath('path_to_something')