chiroptical

namespace impl {
    template <int n, bool isPositive>
    struct fib_impl {
        static constexpr int val = fib_impl<n - 1, isPositive>::val + fib_impl<n - 2, isPositive>::val;
    };

    template <>
    struct fib_impl<1, true> {
        static constexpr int val = 1;
    };

chiroptical

template <int n, int prev, int next, bool isPositive>
struct fib_impl {
    static constexpr int val = fib_impl<n - 1, next, prev + next, isPositive>::val;
};

template <int prev, int next>
struct fib_impl<0, prev, next, true> {
    static constexpr int val = prev;
};

chiroptical

#include <cstdlib>
#include <iostream>
#include <vector>
#include <sstream>
#include "pstl/execution"
#include "pstl/algorithm"
#include "pstl/numeric"
#include "pstl/memory"
#include "tbb/task_scheduler_init.h"

chiroptical

import Data.List.Split (splitOn)

main :: IO ()
main = do
  contents <- getContents
  let path = minPath $ csv3ToRoadSecs (lines contents)
  let repr = pictoralRepr (pathStr path)
  -- Need to deal with last character
  let lastRepr = foldPaths repr (prev repr)
  print $ "Minimum distance travelled: " ++ show (pathDist path)

chiroptical

#!/usr/bin/env python
from abc import ABCMeta, abstractmethod

class StorageStrategy(metaclass=ABCMeta):
    @abstractmethod
    def printSomething(self, something):
        pass

class MongoDBStorageStrategy(StorageStrategy):
    def printSomething(self, something):

chiroptical

#include <iostream>
#include <valarray>
#include <sstream>
#include <fstream>
#include <string>
#include <numeric>
#include <cmath>
#include <chrono>

using namespace std;

chiroptical

#include <math.h>

typedef struct {
    float mean;
    float std;
} MeanStd_f;

float compute_mean_f(
    const float *a,
    const int *x_dim,

chiroptical

{-# LANGUAGE OverloadedStrings #-}

module SemVer where

import Control.Applicative
import Text.Trifecta
import Data.Maybe

data NumberOrString =
      NOSS String

chiroptical

#!/usr/bin/env python3
import pandas as pd
import numpy as np
from pathlib import Path

from scipy import signal
from librosa import load

from sklearn.preprocessing import MinMaxScaler
from PIL import Image

chiroptical

getNeighborCellFromCell :: Maze -> Cell -> Direction -> Cell
getNeighborCellFromCell maze cell North = ...
getNeighborCellFromCell maze cell East = ...