mohanr

import org.apache.http.HttpEntity;
import org.apache.http.client.fluent.Content;
import org.apache.http.client.methods.CloseableHttpResponse;
import org.apache.http.client.methods.HttpGet;
import org.apache.http.impl.client.CloseableHttpClient;
import org.apache.http.impl.client.HttpClients;

import java.io.BufferedReader;
import java.io.IOException;
import java.io.InputStreamReader;

mohanr

<div ng-app="app" ng-controller="MainCtrl" ng-init="textboxes = ['Text1','Text2','Text3']">
    <div ng-repeat="box in textboxes">
        {{box}}
        <copyoftextbox ng-model="models[$index]" name={{box}} index={{$index}}></copyoftextbox>
    </div>
</div>

var app = angular.module("app", []);
app.controller('MainCtrl', function($scope) {
  $scope.models = ['model1','model2','model3'];

mohanr

let insert l a = 
    if List.mem_assoc a l
    then 
      let n = List.assoc a l in (a, n+1)::(List.remove_assoc a l)
    else (a, 1)::l

let letters (word : string) : char MultiSet.t  = 
  let rec insert (l :  char MultiSet.t) (c : string) (i : int) : char MultiSet.t =
    if ( String.length c  > 1 ) then
      insert (  MultiSet.insert l (String.get c i) )  ( String.sub c 1  ((String.length c) - 1)  )  0

mohanr

(package-initialize)
 
(load "/home/mohan/.opam/4.02.1/share/emacs/site-lisp/tuareg-site-file")
(let ((opam-share (ignore-errors (car (process-lines "opam" "config" "var"
"share")))))
(when (and opam-share (file-directory-p opam-share))
;; Register Merlin
(add-to-list 'load-path (expand-file-name "emacs/site-lisp" opam-share))
(autoload 'merlin-mode "merlin" nil t nil)
;; Automatically start it in OCaml buffers

mohanr

module Simulator where
import Numeric.LinearAlgebra
import Graphics.Matplotlib
import Control.Monad.State
import qualified Data.Map as Map
import Text.Printf
import System.Random
import Control.Monad
import Data.Array
import Data.Foldable

mohanr

import tensorflow as tf
import numpy as np

v = tf.constant([1.,-2.,0.5])
tv = tf.convert_to_tensor(v,dtype=np.float32)

with tf.Session() as sess:
    x = tf.nn.softmax(tv)
    tf.Print(x, [x], message="Softmax")
    print(sess.run(x))

mohanr

type  edge = ( int * int * int ) list
module type EDGECOMPARE = sig
  type t
  val compare :  'a  list -> 'a list ->bool 
end

module EDGECOMPARE_weight : EDGECOMPARE with type t = edge = struct
             type t = edge
             let compare l r =  ( List.nth l ( List.length l/ 2 )) ==  ( List.nth r (List.length r/2))

mohanr

(library
  (modules graph)
  (name graph)
  )
(test
  (name kruskaltest)
  (modules kruskaltest)
  (libraries alcotest graph))

mohanr

let testcompare () = Alcotest.(check bool) "Test for weight comparison" true (Graph.EDGECOMPARE_weight.compare [1,2,4] [ 5,6,7] ) 

 let () =   
   Alcotest.run "Weights" 
     [
         ("test compare weights of edges", [
           Alcotest.test_case "Compare weights" `Quick testcompare;
   ]);
  ]

mohanr