gilesvangruisen

def _highest_density_interval(self, pmf, p=.9, title=''):
    # If we pass a DataFrame, just call this recursively on the columns
    if(isinstance(pmf, pd.DataFrame)):
        return pd.DataFrame([self._highest_density_interval(pmf[col], title=str(col)) for col in pmf],
                            index=pmf.columns)

    # Broadcast the probability distribution to an artificial set of samples by
    # repeating each index value N times where N = probability sample_precision
    sample_precision = 1000000
    samples_repeats = np.array(pmf.values * sample_precision)#.astype(int)

gilesvangruisen

name: rspec

on:
  pull_request:
    branches:
      - "master"
  push:
    branches:
      - "master"

gilesvangruisen

Start Date,End Date,# Days,Location
12/30/2014,1/1/2015,2,"Quechee, VT"
1/1/2015,1/4/2015,3,"Newport, RI"
1/4/2015,1/13/2015,9,"Somerville, MA"
1/13/2015,1/17/2015,4,"San Francisco, CA"
1/18/2015,1/22/2015,4,"Somerville, MA"
1/22/2015,1/27/2015,5,"Newport, RI"
1/27/2015,2/7/2015,11,"Somerville, MA"
2/7/2015,2/8/2015,1,"Newport, RI"
2/8/2015,2/18/2015,10,"Somerville, MA"

gilesvangruisen

//
//  LocalStore.swift
//  FPAPI
//
//  Created by Giles Van Gruisen on 3/23/15.
//  Copyright (c) 2015 Remarkable.io. All rights reserved.
//

import Foundation
import AwesomeCache

gilesvangruisen

infix operator --> { associativity left precedence 160 }

func --><T, S>(argument: T?, body: (T) -> (S)) -> S? {

    if let value = argument {
        return body(value) as S
    } else {
        return nil
    }
}

gilesvangruisen

// Binary search

func binarySearch<T: Comparable>(target: T, collection: [T]) -> Int {

    var min = 0
    var max = countElements(collection) - 1

    return binaryMakeGuess(min, max, target, collection)

}

gilesvangruisen

@interface Publisher : NSObject

- (void)subscribe:(void(^)(id object))subscriptionBlock;

- (void)publish:(id)object;

@end