synapticarbors

synapticarbors

from __future__ import division
import logging
import numpy as np
log = logging.getLogger(__name__)


class ReplicasPerBinDriver(object):
    def __init__(self, sim_manager, plugin_config):
        super(ReplicasPerBinDriver, self).__init__()

synapticarbors

rm -f west.h5
BSTATES="--bstate initial,1.0"
#TSTATES="--tstate drift,10.01 --tstate bound,1.3"
#TSTATES="--tstate bound,1.2"
w_init $BSTATES $TSTATES "$@"

synapticarbors

from distutils.core import setup
from distutils.extension import Extension
from Cython.Build import cythonize

import numpy as np

include_dir = np.get_include()

extensions = [
        Extension('testlib', ['testlib.pyx', ], include_dirs=[include_dir, ])

synapticarbors

from __future__ import print_function

import numba as nb

import random
import time

from concurrent.futures import ThreadPoolExecutor, as_completed

synapticarbors

import numpy as np

from bokeh.layouts import column, row
from bokeh.models import CustomJS, ColumnDataSource, Slider
from bokeh.plotting import figure, output_file, show

from bokeh.core.property.containers import PropertyValueDict


output_file('test.html')

synapticarbors

'''
This script is based on the original work of Randal S. Olson (randalolson.com) for the Traveling Salesman Portrait project.
http://www.randalolson.com/2018/04/11/traveling-salesman-portrait-in-python/

Please check out the original project repository for information:

https://github.com/rhiever/Data-Analysis-and-Machine-Learning-Projects

The script was updated by Joshua L. Adelman, adapting the work of Antonio S. Chinchón described in the following blog post:
https://fronkonstin.com/2018/04/17/pencil-scribbles/

synapticarbors

synapticarbors

from tlib import *
from tlib cimport *

import numpy as np
cimport numpy as np


class A(object):

    def main(self, np.int32_t ix):

synapticarbors

import numpy as np
import numba as nb

from numba import types
from numba.extending import overload_method


@overload_method(types.Array, 'take')
def array_take(arr, indices):
   if isinstance(indices, types.Array):