SV randomization - generating non-overlapping memory regions using constraints - constraints

I want to generate random regions in memory such that they do not overlap. Below code is generating such regions but they are in order (i.e., region-0 is before region-1, region-1 is before region-2).
But I want to have the regions in random order. I can use shuffle() in post_randomize, but I want to know if we can do this using just constraints ?
class test;
typedef struct{
rand int unsigned indx;
rand bit [31:0] addr_s;
rand bit [31:0] addr_e;
rand bit [31:0] sz;
} regions_t;
rand regions_t regions[];
constraint c_regions{
regions.size() == 3;
foreach(regions[i]) {
regions[i].indx == i;
regions[i].sz inside {10, 20}; // size of each region
regions[i].addr_e == regions[i].addr_s + regions[i].sz - 1;
regions[i].addr_s < regions[i].addr_e;
regions[i].addr_e < 60; // uppler limit of all memory regions
foreach(regions[j]) {
//if(i!=j) !((regions[i].addr_s >= regions[j].addr_s) && (regions[i].addr_s <= regions[j].addr_e));
if(i<j) (regions[i].addr_e < regions[j].addr_s);
}
}
}
function void post_randomize();
//regions.shuffle();
$display($sformatf("post_randomize(): regions = %0p", regions));
endfunction : post_randomize
endclass: test
program prog;
test tst;
initial begin
tst = new();
repeat(10) begin
tst.randomize();
end
end
endprogram: prog
This constraint if(i!=j) !((regions[i].addr_s >= regions[j].addr_s) && (regions[i].addr_s <= regions[j].addr_e)); seems to be working, but wanted to sure if it will have issues.

Change your last inner foreach loop to what I show below. You were very close/
typedef bit [7:0] addr_t;
class test;
typedef struct{
int unsigned indx;
addr_t addr_s;
addr_t addr_e;
int sz;
} regions_t;
rand regions_t regions[];
constraint c_regions{
regions.size() == 3;
foreach(regions[i]) {
regions[i].indx == i;
regions[i].sz inside {10, 20}; // size of each region
regions[i].addr_e == regions[i].addr_s + regions[i].sz - 1;
regions[i].addr_s < regions[i].addr_e;
regions[i].addr_e < 80; // upper limit of all memory regions
foreach(regions[j]) // start address cannot be inside another range
i!=j -> !(regions[i].addr_s inside {[regions[j].addr_s:regions[j].addr_e]});
}
}
function void post_randomize();
$display($sformatf("post_randomize(): regions = %p", regions));
endfunction : post_randomize
endclass: test
module prog;
test tst;
initial begin
tst = new();
repeat(10) begin
assert(tst.randomize());
end
end
endmodule: prog

Related

How to write constraint for a transaction class in which I need only 50% packets to be randomized?

I need to write a transaction class such that each packet has a random SA[7:0] field, DA[7:0] field & a DATA field.
The length of the data is random between 1 byte to 64 bytes. The content of the DATA field can be random (or) some other fixed pattern.50% of packets to have random data in all bytes of data. 25% of packets to have 8’h55 in all bytes of data. 25% of packets to have 8’hAA in all bytes of data
class my_transaction extends uvm_sequence_item;
'uvm_object_utils(my_transaction);
function new(string name="my_transaction")
super.new(name);
endfunction
rand bit[7:0] SA;
rand bit[7:0] DA;
rand bit[7:0] data[];
constraint my_c { data.size() inside [1:64] };
????how to write constraint for dynamic array data[] here ??
endclass
I was working on a similar approach to Matthew's, but I prefer not to use post_randomize for randomization if easily avoided
module top;
class A;
rand bit[7:0] data[];
typedef enum {RAND, h55, hAA} knob_t;
rand knob_t knobs[];
constraint size_c { data.size() inside {[1:64]}; data.size == knobs.size; }
constraint dist_c {
foreach(knobs[i]) knobs[i] dist {RAND := 50, h55 := 25, hAA := 25}; }
constraint data_element_c {
foreach (data[i]) {
knobs[i] == h55 -> data[i] == 8'h55;
knobs[i] == hAA -> data[i] == 8'hAA;
} }
endclass
A a = new;
initial
repeat (10)
begin
assert(a.randomize);
$display("%p", a);
end
endmodule
Two things are your friend:
i) a control knob. A control knob is a variable that gets randomised in order to control the randomisation process. So, let's randomise a variable to decide whether we want the data array to be random, 55 or AA.
typedef enum {RANDOM, FIVE_FIVE, A_A} control_knob_t;
rand control_knob_t control_knob;
constraint dist_constraint { control_knob dist {RANDOM := 2, FIVE_FIVE := 1, A_A := 1}; }
ii) post_randomize method. This is SystemVerilog, not UVM. post_randomize is called after the randomisation of the class has taken place and allows you to do things once randomisation has occurred. In this case, we'll let the standard randomisation randomise the length of the data array and then we'll fill in the values of data in the post_randomize method.
function void post_randomize;
case (control_knob)
RANDOM: foreach (data[i])
data[i] = $urandom_range(0,255);
FIVE_FIVE: foreach (data[i])
data[i] = 8'h55;
A_A: foreach (data[i])
data[i] = 8'haa;
endcase
endfunction
[MCVE] :
module M;
class C;
rand bit[7:0] data[];
typedef enum {RANDOM, FIVE_FIVE, A_A} control_knob_t;
rand control_knob_t control_knob;
constraint my_c { data.size() inside {[1:4]}; }
constraint dist_constraint { control_knob dist {RANDOM := 2, FIVE_FIVE := 1, A_A := 1}; }
function void post_randomize;
case (control_knob)
RANDOM: foreach (data[i])
data[i] = $urandom_range(0,255);
FIVE_FIVE: foreach (data[i])
data[i] = 8'h55;
A_A: foreach (data[i])
data[i] = 8'haa;
endcase
endfunction
endclass
C c;
initial
begin
c = new;
repeat (100)
begin
c.randomize;
$display("c = %p", c);
end
end
endmodule
https://www.edaplayground.com/x/2cPk

MPI program runtime error MPI_GATHER, qsub mpijobparallel

I am trying to run this fast fourier implementation code. It compiles fine but gives this error at runtime. I have no idea about the error or what it means. Can anyone help me out?
I compiled and run the program by:
mpicc -o exec test.c
./exec
CODE:
This is the code that I found on GITHUB. Its the parallel version of fast fourier algorithm.
#include <stdio.h>
#include <mpi.h> //To use MPI
#include <complex.h> //to use complex numbers
#include <math.h> //for cos() and sin()
#include "timer.h" //to use timer
#define PI 3.14159265
#define bigN 16384 //Problem Size
#define howmanytimesavg 3
int main()
{
int my_rank,comm_sz;
MPI_Init(NULL,NULL); //start MPI
MPI_Comm_size(MPI_COMM_WORLD,&comm_sz); ///how many processes are we
using?
MPI_Comm_rank(MPI_COMM_WORLD,&my_rank); //which process is this?
double start,finish;
double avgtime = 0;
FILE *outfile;
int h;
if(my_rank == 0) //if process 0 open outfile
{
outfile = fopen("ParallelVersionOutput.txt", "w"); //open from current
directory
}
for(h = 0; h < howmanytimesavg; h++) //loop to run multiple times for AVG
time.
{
if(my_rank == 0) //If it's process 0 starts timer
{
start = MPI_Wtime();
}
int i,k,n,j; //Basic loop variables
double complex evenpart[(bigN / comm_sz / 2)]; //array to save the data
for EVENHALF
double complex oddpart[(bigN / comm_sz / 2)]; //array to save the data
for ODDHALF
double complex evenpartmaster[ (bigN / comm_sz / 2) * comm_sz]; //array
to save the data for EVENHALF
double complex oddpartmaster[ (bigN / comm_sz / 2) * comm_sz]; //array
to save the data for ODDHALF
double storeKsumreal[bigN]; //store the K real variable so we can abuse
symmerty
double storeKsumimag[bigN]; //store the K imaginary variable so we can
abuse symmerty
double subtable[(bigN / comm_sz)][3]; //Each process owns a subtable
from the table below
double table[bigN][3] = //TABLE of numbers to use
{
0,3.6,2.6, //n, Real,Imaginary CREATES TABLE
1,2.9,6.3,
2,5.6,4.0,
3,4.8,9.1,
4,3.3,0.4,
5,5.9,4.8,
6,5.0,2.6,
7,4.3,4.1,
};
if(bigN > 8) //Everything after row 8 is all 0's
{
for(i = 8; i < bigN; i++)
{
table[i][0] = i;
for(j = 1; j < 3;j++)
{
table[i][j] = 0.0; //set to 0.0
}
}
}
int sendandrecvct = (bigN / comm_sz) * 3; //how much to send and
recieve??
MPI_Scatter(table,sendandrecvct,MPI_DOUBLE,subtable,sendandrecvct,MPI_DOUBLE,0,MPI_COMM_WORLD); //scatter the table to subtables
for (k = 0; k < bigN / 2; k++) //K coeffiencet Loop
{
/* Variables used for the computation */
double sumrealeven = 0.0; //sum of real numbers for even
double sumimageven = 0.0; //sum of imaginary numbers for even
double sumrealodd = 0.0; //sum of real numbers for odd
double sumimagodd = 0.0; //sum of imaginary numbers for odd
for(i = 0; i < (bigN/comm_sz)/2; i++) //Sigma loop EVEN and ODD
{
double factoreven , factorodd = 0.0;
int shiftevenonnonzeroP = my_rank * subtable[2*i][0]; //used to shift index numbers for correct results for EVEN.
int shiftoddonnonzeroP = my_rank * subtable[2*i + 1][0]; //used to shift index numbers for correct results for ODD.
/* -------- EVEN PART -------- */
double realeven = subtable[2*i][1]; //Access table for real number at spot 2i
double complex imaginaryeven = subtable[2*i][2]; //Access table for imaginary number at spot 2i
double complex componeeven = (realeven + imaginaryeven * I); //Create the first component from table
if(my_rank == 0) //if proc 0, dont use shiftevenonnonzeroP
{
factoreven = ((2*PI)*((2*i)*k))/bigN; //Calculates the even factor for Cos() and Sin()
// *********Reduces computational time*********
}
else //use shiftevenonnonzeroP
{
factoreven = ((2*PI)*((shiftevenonnonzeroP)*k))/bigN; //Calculates the even factor for Cos() and Sin()
// *********Reduces computational time*********
}
double complex comptwoeven = (cos(factoreven) - (sin(factoreven)*I)); //Create the second component
evenpart[i] = (componeeven * comptwoeven); //store in the evenpart array
/* -------- ODD PART -------- */
double realodd = subtable[2*i + 1][1]; //Access table for real number at spot 2i+1
double complex imaginaryodd = subtable[2*i + 1][2]; //Access table for imaginary number at spot 2i+1
double complex componeodd = (realodd + imaginaryodd * I); //Create the first component from table
if (my_rank == 0)//if proc 0, dont use shiftoddonnonzeroP
{
factorodd = ((2*PI)*((2*i+1)*k))/bigN;//Calculates the odd factor for Cos() and Sin()
// *********Reduces computational time*********
}
else //use shiftoddonnonzeroP
{
factorodd = ((2*PI)*((shiftoddonnonzeroP)*k))/bigN;//Calculates the odd factor for Cos() and Sin()
// *********Reduces computational time*********
}
double complex comptwoodd = (cos(factorodd) - (sin(factorodd)*I));//Create the second component
oddpart[i] = (componeodd * comptwoodd); //store in the oddpart array
}
/*Process ZERO gathers the even and odd part arrays and creates a evenpartmaster and oddpartmaster array*/
MPI_Gather(evenpart,(bigN / comm_sz / 2),MPI_DOUBLE_COMPLEX,evenpartmaster,(bigN / comm_sz / 2), MPI_DOUBLE_COMPLEX,0,MPI_COMM_WORLD);
MPI_Gather(oddpart,(bigN / comm_sz / 2),MPI_DOUBLE_COMPLEX,oddpartmaster,(bigN / comm_sz / 2), MPI_DOUBLE_COMPLEX,0,MPI_COMM_WORLD);
if(my_rank == 0)
{
for(i = 0; i < (bigN / comm_sz / 2) * comm_sz; i++) //loop to sum the EVEN and ODD parts
{
sumrealeven += creal(evenpartmaster[i]); //sums the realpart of the even half
sumimageven += cimag(evenpartmaster[i]); //sums the imaginarypart of the even half
sumrealodd += creal(oddpartmaster[i]); //sums the realpart of the odd half
sumimagodd += cimag(oddpartmaster[i]); //sums the imaginary part of the odd half
}
storeKsumreal[k] = sumrealeven + sumrealodd; //add the calculated reals from even and odd
storeKsumimag[k] = sumimageven + sumimagodd; //add the calculated imaginary from even and odd
storeKsumreal[k + bigN/2] = sumrealeven - sumrealodd; //ABUSE symmetry Xkreal + N/2 = Evenk - OddK
storeKsumimag[k + bigN/2] = sumimageven - sumimagodd; //ABUSE symmetry Xkimag + N/2 = Evenk - OddK
if(k <= 10) //Do the first 10 K's
{
if(k == 0)
{
fprintf(outfile," \n\n TOTAL PROCESSED SAMPLES : %d\n",bigN);
}
fprintf(outfile,"================================\n");
fprintf(outfile,"XR[%d]: %.4f XI[%d]: %.4f \n",k,storeKsumreal[k],k,storeKsumimag[k]);
fprintf(outfile,"================================\n");
}
}
}
if(my_rank == 0)
{
GET_TIME(finish); //stop timer
double timeElapsed = finish-start; //Time for that iteration
avgtime = avgtime + timeElapsed; //AVG the time
fprintf(outfile,"Time Elaspsed on Iteration %d: %f Seconds\n", (h+1),timeElapsed);
}
}
if(my_rank == 0)
{
avgtime = avgtime / howmanytimesavg; //get avg time
fprintf(outfile,"\nAverage Time Elaspsed: %f Seconds", avgtime);
fclose(outfile); //CLOSE file ONLY proc 0 can.
}
MPI_Barrier(MPI_COMM_WORLD); //wait to all proccesses to catch up before finalize
MPI_Finalize(); //End MPI
return 0;
}
ERROR:
Fatal error in PMPI_Gather: Invalid datatype, error stack:
PMPI_Gather(904): MPI_Gather(sbuf=0x7fffb62799a0, scount=8192,
MPI_DATATYPE_NULL, rbuf=0x7fffb6239980, rcount=8192, MPI_DATATYPE_NULL,
root=0, MPI_COMM_WORLD) failed
PMPI_Gather(815): Datatype for argument sendtype is a null datatype
[unset]: write_line error; fd=-1 buf=:cmd=abort exitcode=537490947
:
system msg for write_line failure : Bad file descriptor
There is no MPI_DATATYPE_NULL in your code, but you only use MPI_DOUBLE_COMPLEX. Note the latter type is a Fortran datatype, and using it in C is not correct strictly speaking.
My guess is that MPI_DOUBLE_COMPLEX is causing the issue (type not defined or not initialized because you invoked the C version of MPI_Init()).
You can obviously rewrite your code in Fortran, or use your own derived datatype for a C double complex number.
Meanwhile, I suggest you write simple C and Fortran helloworld programs that use MPI_DOUBLE_COMPLEX (MPI_Bcast() of one element for example) to confirm the issue is with MPI_DOUBLE_COMPLEX and is restricted to C or not.

OpenCL: Inserting local atomic_inc to reduction kernel

I am trying to include a local atomic similar to that described by DarkZeros here within a working reduction kernel. The kernel finds a largest value within a set of points; the aim of the local atomic is to allow me to filter selected point_ids into an output array without any gaps.
At present when I use the local atomic to increment the addition to a local array the kernel runs but produces a wrong overall highest point. If the atomic line is commented out then a correct result returns.
What is going on here and how do I fix it?
Simplified kernel code:
__kernel void reduce(__global const float4* dataSet, __global const int* input, const unsigned int items, //points and index
__global int* output, __local float4* shared, const unsigned int n, //finding highest
__global int* filtered, __global const float2* tri_input, const unsigned int pass, //finding filtered
__global int* global_count //global count
){
//set everything up
const unsigned int group_id = get_global_id(0) / get_local_size(0);
const unsigned int local_id = get_local_id(0);
const unsigned int group_size = items;
const unsigned int group_stride = 2 * group_size;
const int local_stride = group_stride * group_size;
__local float4 *zeroIt = &shared[local_id];
zeroIt->x = 0; zeroIt->y = 0; zeroIt->z = 0; zeroIt->w = 0;
volatile __local int local_count_set_1;
volatile __local int global_val_set_1;
volatile __local int filter_local[64];
if(local_id==0){
local_count_set_1 = 0;
global_val_set_1 = -1;
}
barrier(CLK_LOCAL_MEM_FENCE);
int i = group_id * group_stride + local_id;
while (i < n){
//load up a pair of points using the index to locate them within a massive dataSet
int ia = input[i];
float4 a = dataSet[ia-1];
int ib = input[i + group_size];
float4 b = dataSet[ib-1];
//on the first pass kernel increment a local count
if(pass == 0){
filter_local[atomic_inc(&local_count_set_1)] = 1; //including this line causes an erroneous highest point result
//filter_local[local_id] = 1; //but including this line does not
//atomic_inc(&local_count_set_1); //and neither does this one
}
//find the highest of the pair
float4 result;
if(a.z>b.z) result = a;
else result = b;
//load up the previous highest result locally
float4 s = shared[local_id];
//if the previous highest beat this, stick, else twist
if(s.z>result.z){ result = s; }
shared[local_id] = result;
i += local_stride;
}
barrier(CLK_LOCAL_MEM_FENCE);
if (group_size >= 512){
if (local_id < 256) {
__local float4 *a = &shared[local_id];
__local float4 *b = &shared[local_id+256];
if(b->z>a->z){ shared[local_id] = shared[local_id+256]; }
}}
//repeat barrier ops in increments down to group_size>=2 - this filters the highest result in shared
//finally, return the filtered highest result of shared to the global level
barrier(CLK_LOCAL_MEM_FENCE);
if(local_id == 0){
__local float4 *v = &shared[0];
int send = v->w ;
output[group_id] = send+1;
}}
[UPDATE]: When the atomic_inc line is included the 'wrong' highest point result is always a point near the end of the test dataset. I'm guessing that this means that the atomic_inc is affecting a latter comparison, but I'm not sure exactly what or where yet.
[UPDATE]: Edited code to simplify/clarify/update with debugging tweaks. Still not working and it is driving me loopy.
Total face-palm moment. In the setup phase of the kernel there are the lines:
if(local_id==0){
local_count_set_1 = 0;
global_val_set_1 = -1;
}
barrier(CLK_LOCAL_MEM_FENCE);
When these are split and the local_count_set_1 is included within the while loop, the error does not occur. i.e:
if(local_id==0) global_val_set_1 = -1;
barrier(CLK_LOCAL_MEM_FENCE);
while (i < n){
if(local_id==0) local_count_set_1 = 0;
barrier(CLK_LOCAL_MEM_FENCE);
....
if(pass = 0){
filter_local[atomic_inc(&local_count_set_1)] = 1;
}
....
I'm hoping this fixes the issue // will update if not.
Aaaand that's a weekend I'll never get back.

Facing incorrect output while linking programs

I am having a trouble in calling the user defined functions in the main program, using unix. the program is executing only for the number generation in the main program. but when i call the predefined function . the output retrieved is incorrect. Can someone please correct me where i have done it wrong
My main program states as
#include <stdio.h>
#include <stdlib.h>
void sort1(int []);
int main(void) {
int array[100];
int i , j;
printf("ten random numbers in [1,1000]\n");
for (i = 1; i <= 10; i++)
{
generate random numbers
}
printf("The list of Hundred random numbers are \n");
for (j = 1; j <= 10; j++ )
{
//to print the random numbers
}
sort1(array);
return 0;
}
//this is my user defined function: sort1.c
include <stdio.h>
int sort1(int a[])
{
int array[100], i, d, swap, e=10;
// algortithm
}
}
printf("Sorted list in ascending order:\n");
for ( i= 0 ; i< e ; i++ )
printf("%d\n", array[i]);
}
I get the output as
ten random numbers in [1,1000]
The list of Hundred random numbers are
--This gives correct output
Sorted list in ascending order:
1
-1442229816
0
-1444472964
#include <stdio.h>
#include <stdlib.h>
void sort1(int []);
int main(void) {
int array[100];
int i;
printf("ten random numbers in [1,1000]\n");
for (i = 1; i <= 10; i++)
{
array[i] = rand()%1000 + 1;
}
printf("The list of Hundred random numbers are \n");
for (i = 1; i <= 10; i++ )
{
printf("Element[%d] = %d\n", i, array[i] );
}
//Up to here it's ok but you have set the values in the positions 1-10 of the array so keep consistent with it
sort1(array);
printf("Sorted list in ascending order:\n");
for ( i= 1 ; i<= 10 ; i++ )
printf("%d\n", array[i]);
return 0;
}
void sort1(int a[])
{
int i,swap,sorted=0;
while(sorted==0){ //flag to know if array is sorted 0 means not sorted.
sorted=1; // we set the flag to sorted at start of sweep
for (i= 1 ; i<= (10-1); i++) //sweep through array
{
if (a[i] > a[i+1]) //check if sorted
{
swap = a[i];
a[i] = a[i+1];
a[i+1] = swap;
sorted=0; //if not sorted set flag to 0 and swap
}
}
}
}
Main problems in your code:
1) array[100] is not initialized in sort1 function.
2) I do not understand your sorting algorithm but in any case you are checking for values of a[0] which are not initialized so take care of the array positions you use each time and be consistent with it.
3) function prototype does not match

Are there any example of Mutual recursion?

Are there any examples for a recursive function that calls an other function which calls the first one too ?
Example :
function1()
{
//do something
function2();
//do something
}
function2()
{
//do something
function1();
//do something
}
Mutual recursion is common in code that parses mathematical expressions (and other grammars). A recursive descent parser based on the grammar below will naturally contain mutual recursion: expression-terms-term-factor-primary-expression.
expression
+ terms
- terms
terms
terms
term + terms
term - terms
term
factor
factor * term
factor / term
factor
primary
primary ^ factor
primary
( expression )
number
name
name ( expression )
The proper term for this is Mutual Recursion.
http://en.wikipedia.org/wiki/Mutual_recursion
There's an example on that page, I'll reproduce here in Java:
boolean even( int number )
{
if( number == 0 )
return true;
else
return odd(abs(number)-1)
}
boolean odd( int number )
{
if( number == 0 )
return false;
else
return even(abs(number)-1);
}
Where abs( n ) means return the absolute value of a number.
Clearly this is not efficient, just to demonstrate a point.
An example might be the minmax algorithm commonly used in game programs such as chess. Starting at the top of the game tree, the goal is to find the maximum value of all the nodes at the level below, whose values are defined as the minimum of the values of the nodes below that, whose values are defines as the maximum of the values below that, whose values ...
I can think of two common sources of mutual recursion.
Functions dealing with mutually recursive types
Consider an Abstract Syntax Tree (AST) that keeps position information in every node. The type might look like this:
type Expr =
| Int of int
| Var of string
| Add of ExprAux * ExprAux
and ExprAux = Expr of int * Expr
The easiest way to write functions that manipulate values of these types is to write mutually recursive functions. For example, a function to find the set of free variables:
let rec freeVariables = function
| Int n -> Set.empty
| Var x -> Set.singleton x
| Add(f, g) -> Set.union (freeVariablesAux f) (freeVariablesAux g)
and freeVariablesAux (Expr(loc, e)) =
freeVariables e
State machines
Consider a state machine that is either on, off or paused with instructions to start, stop, pause and resume (F# code):
type Instruction = Start | Stop | Pause | Resume
The state machine might be written as mutually recursive functions with one function for each state:
type State = State of (Instruction -> State)
let rec isOff = function
| Start -> State isOn
| _ -> State isOff
and isOn = function
| Stop -> State isOff
| Pause -> State isPaused
| _ -> State isOn
and isPaused = function
| Stop -> State isOff
| Resume -> State isOn
| _ -> State isPaused
It's a bit contrived and not very efficient, but you could do this with a function to calculate Fibbonacci numbers as in:
fib2(n) { return fib(n-2); }
fib1(n) { return fib(n-1); }
fib(n)
{
if (n>1)
return fib1(n) + fib2(n);
else
return 1;
}
In this case its efficiency can be dramatically enhanced if the language supports memoization
In a language with proper tail calls, Mutual Tail Recursion is a very natural way of implementing automata.
Here is my coded solution. For a calculator app that performs *,/,- operations using mutual recursion. It also checks for brackets (()) to decide the order of precedence.
Flow:: expression -> term -> factor -> expression
Calculator.h
#ifndef CALCULATOR_H_
#define CALCULATOR_H_
#include <string>
using namespace std;
/****** A Calculator Class holding expression, term, factor ********/
class Calculator
{
public:
/**Default Constructor*/
Calculator();
/** Parameterized Constructor common for all exception
* #aparam e exception value
* */
Calculator(char e);
/**
* Function to start computation
* #param input - input expression*/
void start(string input);
/**
* Evaluates Term*
* #param input string for term*/
double term(string& input);
/* Evaluates factor*
* #param input string for factor*/
double factor(string& input);
/* Evaluates Expression*
* #param input string for expression*/
double expression(string& input);
/* Evaluates number*
* #param input string for number*/
string number(string n);
/**
* Prints calculates value of the expression
* */
void print();
/**
* Converts char to double
* #param c input char
* */
double charTONum(const char* c);
/**
* Get error
*/
char get_value() const;
/** Reset all values*/
void reset();
private:
int lock;//set lock to check extra parenthesis
double result;// result
char error_msg;// error message
};
/**Error for unexpected string operation*/
class Unexpected_error:public Calculator
{
public:
Unexpected_error(char e):Calculator(e){};
};
/**Error for missing parenthesis*/
class Missing_parenthesis:public Calculator
{
public:
Missing_parenthesis(char e):Calculator(e){};
};
/**Error if divide by zeros*/
class DivideByZero:public Calculator{
public:
DivideByZero():Calculator(){};
};
#endif
===============================================================================
Calculator.cpp
//============================================================================
// Name : Calculator.cpp
// Author : Anurag
// Version :
// Copyright : Your copyright notice
// Description : Calculator using mutual recursion in C++, Ansi-style
//============================================================================
#include "Calculator.h"
#include <iostream>
#include <string>
#include <math.h>
#include <exception>
using namespace std;
Calculator::Calculator():lock(0),result(0),error_msg(' '){
}
Calculator::Calculator(char e):result(0), error_msg(e) {
}
char Calculator::get_value() const {
return this->error_msg;
}
void Calculator::start(string input) {
try{
result = expression(input);
print();
}catch (Unexpected_error e) {
cout<<result<<endl;
cout<<"***** Unexpected "<<e.get_value()<<endl;
}catch (Missing_parenthesis e) {
cout<<"***** Missing "<<e.get_value()<<endl;
}catch (DivideByZero e) {
cout<<"***** Division By Zero" << endl;
}
}
double Calculator::expression(string& input) {
double expression=0;
if(input.size()==0)
return 0;
expression = term(input);
if(input[0] == ' ')
input = input.substr(1);
if(input[0] == '+') {
input = input.substr(1);
expression += term(input);
}
else if(input[0] == '-') {
input = input.substr(1);
expression -= term(input);
}
if(input[0] == '%'){
result = expression;
throw Unexpected_error(input[0]);
}
if(input[0]==')' && lock<=0 )
throw Missing_parenthesis(')');
return expression;
}
double Calculator::term(string& input) {
if(input.size()==0)
return 1;
double term=1;
term = factor(input);
if(input[0] == ' ')
input = input.substr(1);
if(input[0] == '*') {
input = input.substr(1);
term = term * factor(input);
}
else if(input[0] == '/') {
input = input.substr(1);
double den = factor(input);
if(den==0) {
throw DivideByZero();
}
term = term / den;
}
return term;
}
double Calculator::factor(string& input) {
double factor=0;
if(input[0] == ' ') {
input = input.substr(1);
}
if(input[0] == '(') {
lock++;
input = input.substr(1);
factor = expression(input);
if(input[0]==')') {
lock--;
input = input.substr(1);
return factor;
}else{
throw Missing_parenthesis(')');
}
}
else if (input[0]>='0' && input[0]<='9'){
string nums = input.substr(0,1) + number(input.substr(1));
input = input.substr(nums.size());
return stod(nums);
}
else {
result = factor;
throw Unexpected_error(input[0]);
}
return factor;
}
string Calculator::number(string input) {
if(input.substr(0,2)=="E+" || input.substr(0,2)=="E-" || input.substr(0,2)=="e-" || input.substr(0,2)=="e-")
return input.substr(0,2) + number(input.substr(2));
else if((input[0]>='0' && input[0]<='9') || (input[0]=='.'))
return input.substr(0,1) + number(input.substr(1));
else
return "";
}
void Calculator::print() {
cout << result << endl;
}
void Calculator::reset(){
this->lock=0;
this->result=0;
}
int main() {
Calculator* cal = new Calculator;
string input;
cout<<"Expression? ";
getline(cin,input);
while(input!="."){
cal->start(input.substr(0,input.size()-2));
cout<<"Expression? ";
cal->reset();
getline(cin,input);
}
cout << "Done!" << endl;
return 0;
}
==============================================================
Sample input-> Expression? (42+8)*10 =
Output-> 500
Top down merge sort can use a pair of mutually recursive functions to alternate the direction of merge based on level of recursion.
For the example code below, a[] is the array to be sorted, b[] is a temporary working array. For a naive implementation of merge sort, each merge operation copies data from a[] to b[], then merges b[] back to a[], or it merges from a[] to b[], then copies from b[] back to a[]. This requires n · ceiling(log2(n)) copy operations. To eliminate the copy operations used for merging, the direction of merge can be alternated based on level of recursion, merge from a[] to b[], merge from b[] to a[], ..., and switch to in place insertion sort for small runs in a[], as insertion sort on small runs is faster than merge sort.
In this example, MergeSortAtoA() and MergeSortAtoB() are the mutually recursive functions.
Example java code:
static final int ISZ = 64; // use insertion sort if size <= ISZ
static void MergeSort(int a[])
{
int n = a.length;
if(n < 2)
return;
int [] b = new int[n];
MergeSortAtoA(a, b, 0, n);
}
static void MergeSortAtoA(int a[], int b[], int ll, int ee)
{
if ((ee - ll) <= ISZ){ // use insertion sort on small runs
InsertionSort(a, ll, ee);
return;
}
int rr = (ll + ee)>>1; // midpoint, start of right half
MergeSortAtoB(a, b, ll, rr);
MergeSortAtoB(a, b, rr, ee);
Merge(b, a, ll, rr, ee); // merge b to a
}
static void MergeSortAtoB(int a[], int b[], int ll, int ee)
{
int rr = (ll + ee)>>1; // midpoint, start of right half
MergeSortAtoA(a, b, ll, rr);
MergeSortAtoA(a, b, rr, ee);
Merge(a, b, ll, rr, ee); // merge a to b
}
static void Merge(int a[], int b[], int ll, int rr, int ee)
{
int o = ll; // b[] index
int l = ll; // a[] left index
int r = rr; // a[] right index
while(true){ // merge data
if(a[l] <= a[r]){ // if a[l] <= a[r]
b[o++] = a[l++]; // copy a[l]
if(l < rr) // if not end of left run
continue; // continue (back to while)
while(r < ee){ // else copy rest of right run
b[o++] = a[r++];
}
break; // and return
} else { // else a[l] > a[r]
b[o++] = a[r++]; // copy a[r]
if(r < ee) // if not end of right run
continue; // continue (back to while)
while(l < rr){ // else copy rest of left run
b[o++] = a[l++];
}
break; // and return
}
}
}
static void InsertionSort(int a[], int ll, int ee)
{
int i, j;
int t;
for (j = ll + 1; j < ee; j++) {
t = a[j];
i = j-1;
while(i >= ll && a[i] > t){
a[i+1] = a[i];
i--;
}
a[i+1] = t;
}
}

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