shahrzad

//  Copyright (c) 2014 Hartmut Kaiser
//
//  Distributed under the Boost Software License, Version 1.0. (See accompanying
//  file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)

// This is the fourth in a series of examples demonstrating the development of
// a fully distributed solver for a simple 1D heat distribution problem.
//
// This example builds on example three. It futurizes the code from that
// example. Compared to example two this code runs much more efficiently. It

shahrzad

//   Copyright (c) 2018 Shahrzad Shirzad
//
//   Distributed under the Boost Software License, Version 1.0. (See accompanying
//   file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)

#include <phylanx/phylanx.hpp>
#include <hpx/hpx_init.hpp>

#include <iostream>

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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jun 18 17:45:27 2018

@author: shahrzad
"""

from rdkit import Chem
from rdkit.Chem import MACCSkeys

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from scipy.spatial import Voronoi, voronoi_plot_2d
import numpy as np
import pandas as pd
import matplotlib
import sys,os,argparse
from biopandas.mol2 import PandasMol2
import matplotlib.pyplot as plt
import glob
import cv2
from rdkit import Chem

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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jul  6 14:25:57 2018

@author: shahrzad
"""
import numpy as np
import time
import math

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import pandas as pd
import numpy as np
import time
import argparse
import sys

if not len(sys.argv) == 7 :
    print("This program requires the following 6 arguments seperated by a space ")
    print("row_stop col_stop num_factors iterations regularization alpha")
    exit(-57)

shahrzad

from phylanx import Phylanx
import numpy as np

@Phylanx
def ALS(ratings, regularization, num_factors, iterations, alpha, enable_output):
    num_users = np.shape(ratings)[0]
    num_items = np.shape(ratings)[1]
    
    conf = alpha * ratings
    conf_u = np.zeros((num_items,1))

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#Python implementation of the ALS algorithm
import numpy as np

def ALS(ratings, regularization, num_factors, iterations, alpha, enable_output):
    num_users = np.shape(ratings)[0]
    num_items = np.shape(ratings)[1]
    
    conf = alpha * ratings
    conf_u = np.zeros((num_items,1))
    conf_i = np.zeros((num_items,1))

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define(als, ratings, regularization, num_factors, iterations, alpha, enable_output,
        block(
            define(num_users, shape(ratings, 0)),
            define(num_items, shape(ratings, 1)),
            define(conf, alpha * ratings),

            define(conf_u, constant(0.0, make_list(num_items))),
            define(conf_i, constant(0.0,make_list(num_users))),

            define(c_u, constant(0.0, make_list(num_items, num_items))),

shahrzad

import pandas as pd
import numpy as np
import time
import argparse
import sys

if not len(sys.argv) == 7 :
    print("This program requires the following 6 arguments seperated by a space ")
    print("row_stop col_stop num_factors iterations regularization alpha")
    exit(-57)