I have two arrays of pointers, and I want to use gtest/gmock to assert that they contain the same content, possibly in different order. I tried things like
vector<unique_ptr<int>> a;
vector<unique_ptr<int>> b;
a.push_back(make_unique<int>(42));
a.push_back(make_unique<int>(142));
b.push_back(make_unique<int>(142));
b.push_back(make_unique<int>(42));
// I want this to compile & pass
ASSERT_THAT(a, Pointwise(UnorderedElementsAreArray(), b));
But that didn't work.
Gmock does not provide directly what you want. The problem is that as your arrays contain pointers, you cannot compare their elements directly and have to use matchers for that. You can construct an array of matchers from one of your source arrays, but that will not make things simpler for you.
But you have some options, depending on what your actual needs are. If you have two arrays and need is to compare whether they the same after sorting, just sort the arrays:
auto sorted_a = std::sort(a.begin(), a.end(), [](auto x, auto y) {
return *x < *y;
});
auto sorted_b = std::sort(b.begin(), b.end(), [](auto x, auto y) {
return *x < *y;
});
and then define a helper matcher and compare them using it:
MATCHER(PointeesAreEqual, "") {
return *std::get<0>(arg) == *std::get<1>(arg);
}
EXPECT_THAT(a, Pointwise(PointeesAreEqual, b))
But if you simply want to check that an array consists of certain elements, in an arbitrary order, you can write something like this:
EXPECT_THAT(a, UnorderedElementsAre(Pointee(42), Pointee(142));
I have some classes (and will need quite a few more) that look like this:
use Unit;
class Unit::Units::Ampere is Unit
{
method TWEAK { with self {
.si = True;
# m· kg· s· A ·K· mol· cd
.si-signature = [ 0, 0, 0, 1, 0, 0, 0 ];
.singular-name = "ampere";
.plural-name = "ampere";
.symbol = "A";
}}
sub postfix:<A> ($value) returns Unit::Units::Ampere is looser(&prefix:<->) is export(:short) {
return Unit::Units::Ampere.new( :$value );
};
sub postfix:<ampere> ($value) returns Unit::Units::Ampere is looser(&prefix:<->) is export(:long) {
$value\A;
};
}
I would like to be able to construct and export the custom operators dynamically at runtime. I know how to work with EXPORT, but how do I create a postfix operator on the fly?
I ended up basically doing this:
sub EXPORT
{
return %(
"postfix:<A>" => sub is looser(&prefix:<->) {
#do something
}
);
}
which is disturbingly simple.
For the first question, you can create dynamic subs by returning a sub from another. To accept only an Ampere parameter (where "Ampere" is chosen programmatically), use a type capture in the function signature:
sub make-combiner(Any:U ::Type $, &combine-logic) {
return sub (Type $a, Type $b) {
return combine-logic($a, $b);
}
}
my &int-adder = make-combiner Int, {$^a + $^b};
say int-adder(1, 2);
my &list-adder = make-combiner List, {(|$^a, |$^b)};
say list-adder(<a b>, <c d>);
say list-adder(1, <c d>); # Constraint type check fails
Note that when I defined the inner sub, I had to put a space after the sub keyword, lest the compiler think I'm calling a function named "sub". (See the end of my answer for another way to do this.)
Now, on to the hard part: how to export one of these generated functions? The documentation for what is export really does is here: https://docs.perl6.org/language/modules.html#is_export
Half way down the page, they have an example of adding a function to the symbol table without being able to write is export at compile time. To get the above working, it needs to be in a separate file. To see an example of a programmatically determined name and programmatically determined logic, create the following MyModule.pm6:
unit module MyModule;
sub make-combiner(Any:U ::Type $, &combine-logic) {
anon sub combiner(Type $a, Type $b) {
return combine-logic($a, $b);
}
}
my Str $name = 'int';
my $type = Int;
my package EXPORT::DEFAULT {
OUR::{"&{$name}-eater"} := make-combiner $type, {$^a + $^b};
}
Invoke Perl 6:
perl6 -I. -MMyModule -e "say int-eater(4, 3);"
As hoped, the output is 7. Note that in this version, I used anon sub, which lets you name the "anonymous" generated function. I understand this is mainly useful for generating better stack traces.
All that said, I'm having trouble dynamically setting a postfix operator's precedence. I think you need to modify the Precedence role of the operator, or create it yourself instead of letting the compiler create it for you. This isn't documented.
I am using libclang to parse a objective c source code file. The following code finds all Objective-C instance method declarations, but it also finds declarations in the includes:
enum CXCursorKind curKind = clang_getCursorKind(cursor);
CXString curKindName = clang_getCursorKindSpelling(curKind);
const char *funcDecl="ObjCInstanceMethodDecl";
if(strcmp(clang_getCString(curKindName),funcDecl)==0{
}
How can I skip everything, which comes from header includes? I am only interested in my own Objective-C instance method declarations in the source file, not in any of the includes.
e.g. the following should not be included
...
Location: /System/Library/Frameworks/Foundation.framework/Headers/NSObject.h:15:9:315
Type:
TypeKind: Invalid
CursorKind: ObjCInstanceMethodDecl
...
Answering this question because I couldn't believe that hard-coding paths comparisons was the only solution, and indeed, there is a clang_Location_isFromMainFile function that does exactly what you want, so that you can filter unwanted results in the visitor, like this :
if (clang_Location_isFromMainFile (clang_getCursorLocation (cursor)) == 0) {
return CXChildVisit_Continue;
}
The only way I know would be to skip unwanted paths during the AST visit. You can for example put something like the following in your visitor function. Returning CXChildVisit_Continue avoids visiting the entire file.
CXFile file;
unsigned int line, column, offset;
CXString fileName;
char * canonicalPath = NULL;
clang_getExpansionLocation (clang_getCursorLocation (cursor),
&file, &line, &column, &offset);
fileName = clang_getFileName (file);
if (clang_getCString (fileName)) {
canonicalPath = realpath (clang_getCString (fileName), NULL);
}
clang_disposeString (fileName);
if (strcmp(canonicalPath, "/canonical/path/to/your/source/file") != 0) {
return CXChildVisit_Continue;
}
Also, why compare CursorKindSpelling instead of the CursorKind directly?
I want to make a selection before apply one of two animations,
what I thought is: make a Point one, if my myImageView is at the Point one, then apply animationNo1, else apply animationNo2, but I got this:"used struct type value where scalar is required", at line if (myImageView.layer.position = one)
What I do? how can I fix this?
Does anyone know exactly what makes the problem happen?
CGPoint one = CGPointMake(myImageView.layer.position.x, 100);
if (myImageView.layer.position = one)
{
animationNo1
}
else
{
animationNo2
}
First of all, your if-statement will not do what you think. If you want to compare something you have to use == (ie 2 =)
and you can't compare CGPoints like this.
use
if (CGPointEqualToPoint(one, self.view.layer.position))
if (myImageView.layer.position = one) { animationNo1 }
should be
if (CGPointIsEqualToPoint(myImageView.layer.position, one)) { animationNo1 }
You used a single = meaning assignment, rather than a == for comparison. But the == wouldn't do what you wanted here anyway.
You are passing a struct (int this case position) instead of a scalar. To do what you want you need to use CGPointIsEqualToPoint:
if (CGPointEqualToPoint(one, self.view.layer.position))
Full code with corrections:
CGPoint one = CGPointMake(myImageView.layer.position.x, 100);
if (CGPointEqualToPoint(one, self.view.layer.position))
{
animationNo1
}
else
{
animationNo2
}
Also, as others have pointed out: Be careful about = vs ==. They are different. In this case you don't use == for comparison fortunately, but if you use = for other stuff it will make it true instead of checking to see if it is true.
I'm writing a function to find triangle numbers and the natural way to write it is recursively:
function triangle (x)
if x == 0 then return 0 end
return x+triangle(x-1)
end
But attempting to calculate the first 100,000 triangle numbers fails with a stack overflow after a while. This is an ideal function to memoize, but I want a solution that will memoize any function I pass to it.
Mathematica has a particularly slick way to do memoization, relying on the fact that hashes and function calls use the same syntax:
triangle[0] = 0;
triangle[x_] := triangle[x] = x + triangle[x-1]
That's it. It works because the rules for pattern-matching function calls are such that it always uses a more specific definition before a more general definition.
Of course, as has been pointed out, this example has a closed-form solution: triangle[x_] := x*(x+1)/2. Fibonacci numbers are the classic example of how adding memoization gives a drastic speedup:
fib[0] = 1;
fib[1] = 1;
fib[n_] := fib[n] = fib[n-1] + fib[n-2]
Although that too has a closed-form equivalent, albeit messier: http://mathworld.wolfram.com/FibonacciNumber.html
I disagree with the person who suggested this was inappropriate for memoization because you could "just use a loop". The point of memoization is that any repeat function calls are O(1) time. That's a lot better than O(n). In fact, you could even concoct a scenario where the memoized implementation has better performance than the closed-form implementation!
You're also asking the wrong question for your original problem ;)
This is a better way for that case:
triangle(n) = n * (n - 1) / 2
Furthermore, supposing the formula didn't have such a neat solution, memoisation would still be a poor approach here. You'd be better off just writing a simple loop in this case. See this answer for a fuller discussion.
I bet something like this should work with variable argument lists in Lua:
local function varg_tostring(...)
local s = select(1, ...)
for n = 2, select('#', ...) do
s = s..","..select(n,...)
end
return s
end
local function memoize(f)
local cache = {}
return function (...)
local al = varg_tostring(...)
if cache[al] then
return cache[al]
else
local y = f(...)
cache[al] = y
return y
end
end
end
You could probably also do something clever with a metatables with __tostring so that the argument list could just be converted with a tostring(). Oh the possibilities.
In C# 3.0 - for recursive functions, you can do something like:
public static class Helpers
{
public static Func<A, R> Memoize<A, R>(this Func<A, Func<A,R>, R> f)
{
var map = new Dictionary<A, R>();
Func<A, R> self = null;
self = (a) =>
{
R value;
if (map.TryGetValue(a, out value))
return value;
value = f(a, self);
map.Add(a, value);
return value;
};
return self;
}
}
Then you can create a memoized Fibonacci function like this:
var memoized_fib = Helpers.Memoize<int, int>((n,fib) => n > 1 ? fib(n - 1) + fib(n - 2) : n);
Console.WriteLine(memoized_fib(40));
In Scala (untested):
def memoize[A, B](f: (A)=>B) = {
var cache = Map[A, B]()
{ x: A =>
if (cache contains x) cache(x) else {
val back = f(x)
cache += (x -> back)
back
}
}
}
Note that this only works for functions of arity 1, but with currying you could make it work. The more subtle problem is that memoize(f) != memoize(f) for any function f. One very sneaky way to fix this would be something like the following:
val correctMem = memoize(memoize _)
I don't think that this will compile, but it does illustrate the idea.
Update: Commenters have pointed out that memoization is a good way to optimize recursion. Admittedly, I hadn't considered this before, since I generally work in a language (C#) where generalized memoization isn't so trivial to build. Take the post below with that grain of salt in mind.
I think Luke likely has the most appropriate solution to this problem, but memoization is not generally the solution to any issue of stack overflow.
Stack overflow usually is caused by recursion going deeper than the platform can handle. Languages sometimes support "tail recursion", which re-uses the context of the current call, rather than creating a new context for the recursive call. But a lot of mainstream languages/platforms don't support this. C# has no inherent support for tail-recursion, for example. The 64-bit version of the .NET JITter can apply it as an optimization at the IL level, which is all but useless if you need to support 32-bit platforms.
If your language doesn't support tail recursion, your best option for avoiding stack overflows is either to convert to an explicit loop (much less elegant, but sometimes necessary), or find a non-iterative algorithm such as Luke provided for this problem.
function memoize (f)
local cache = {}
return function (x)
if cache[x] then
return cache[x]
else
local y = f(x)
cache[x] = y
return y
end
end
end
triangle = memoize(triangle);
Note that to avoid a stack overflow, triangle would still need to be seeded.
Here's something that works without converting the arguments to strings.
The only caveat is that it can't handle a nil argument. But the accepted solution can't distinguish the value nil from the string "nil", so that's probably OK.
local function m(f)
local t = { }
local function mf(x, ...) -- memoized f
assert(x ~= nil, 'nil passed to memoized function')
if select('#', ...) > 0 then
t[x] = t[x] or m(function(...) return f(x, ...) end)
return t[x](...)
else
t[x] = t[x] or f(x)
assert(t[x] ~= nil, 'memoized function returns nil')
return t[x]
end
end
return mf
end
I've been inspired by this question to implement (yet another) flexible memoize function in Lua.
https://github.com/kikito/memoize.lua
Main advantages:
Accepts a variable number of arguments
Doesn't use tostring; instead, it organizes the cache in a tree structure, using the parameters to traverse it.
Works just fine with functions that return multiple values.
Pasting the code here as reference:
local globalCache = {}
local function getFromCache(cache, args)
local node = cache
for i=1, #args do
if not node.children then return {} end
node = node.children[args[i]]
if not node then return {} end
end
return node.results
end
local function insertInCache(cache, args, results)
local arg
local node = cache
for i=1, #args do
arg = args[i]
node.children = node.children or {}
node.children[arg] = node.children[arg] or {}
node = node.children[arg]
end
node.results = results
end
-- public function
local function memoize(f)
globalCache[f] = { results = {} }
return function (...)
local results = getFromCache( globalCache[f], {...} )
if #results == 0 then
results = { f(...) }
insertInCache(globalCache[f], {...}, results)
end
return unpack(results)
end
end
return memoize
Here is a generic C# 3.0 implementation, if it could help :
public static class Memoization
{
public static Func<T, TResult> Memoize<T, TResult>(this Func<T, TResult> function)
{
var cache = new Dictionary<T, TResult>();
var nullCache = default(TResult);
var isNullCacheSet = false;
return parameter =>
{
TResult value;
if (parameter == null && isNullCacheSet)
{
return nullCache;
}
if (parameter == null)
{
nullCache = function(parameter);
isNullCacheSet = true;
return nullCache;
}
if (cache.TryGetValue(parameter, out value))
{
return value;
}
value = function(parameter);
cache.Add(parameter, value);
return value;
};
}
}
(Quoted from a french blog article)
In the vein of posting memoization in different languages, i'd like to respond to #onebyone.livejournal.com with a non-language-changing C++ example.
First, a memoizer for single arg functions:
template <class Result, class Arg, class ResultStore = std::map<Arg, Result> >
class memoizer1{
public:
template <class F>
const Result& operator()(F f, const Arg& a){
typename ResultStore::const_iterator it = memo_.find(a);
if(it == memo_.end()) {
it = memo_.insert(make_pair(a, f(a))).first;
}
return it->second;
}
private:
ResultStore memo_;
};
Just create an instance of the memoizer, feed it your function and argument. Just make sure not to share the same memo between two different functions (but you can share it between different implementations of the same function).
Next, a driver functon, and an implementation. only the driver function need be public
int fib(int); // driver
int fib_(int); // implementation
Implemented:
int fib_(int n){
++total_ops;
if(n == 0 || n == 1)
return 1;
else
return fib(n-1) + fib(n-2);
}
And the driver, to memoize
int fib(int n) {
static memoizer1<int,int> memo;
return memo(fib_, n);
}
Permalink showing output on codepad.org. Number of calls is measured to verify correctness. (insert unit test here...)
This only memoizes one input functions. Generalizing for multiple args or varying arguments left as an exercise for the reader.
In Perl generic memoization is easy to get. The Memoize module is part of the perl core and is highly reliable, flexible, and easy-to-use.
The example from it's manpage:
# This is the documentation for Memoize 1.01
use Memoize;
memoize('slow_function');
slow_function(arguments); # Is faster than it was before
You can add, remove, and customize memoization of functions at run time! You can provide callbacks for custom memento computation.
Memoize.pm even has facilities for making the memento cache persistent, so it does not need to be re-filled on each invocation of your program!
Here's the documentation: http://perldoc.perl.org/5.8.8/Memoize.html
Extending the idea, it's also possible to memoize functions with two input parameters:
function memoize2 (f)
local cache = {}
return function (x, y)
if cache[x..','..y] then
return cache[x..','..y]
else
local z = f(x,y)
cache[x..','..y] = z
return z
end
end
end
Notice that parameter order matters in the caching algorithm, so if parameter order doesn't matter in the functions to be memoized the odds of getting a cache hit would be increased by sorting the parameters before checking the cache.
But it's important to note that some functions can't be profitably memoized. I wrote memoize2 to see if the recursive Euclidean algorithm for finding the greatest common divisor could be sped up.
function gcd (a, b)
if b == 0 then return a end
return gcd(b, a%b)
end
As it turns out, gcd doesn't respond well to memoization. The calculation it does is far less expensive than the caching algorithm. Ever for large numbers, it terminates fairly quickly. After a while, the cache grows very large. This algorithm is probably as fast as it can be.
Recursion isn't necessary. The nth triangle number is n(n-1)/2, so...
public int triangle(final int n){
return n * (n - 1) / 2;
}
Please don't recurse this. Either use the x*(x+1)/2 formula or simply iterate the values and memoize as you go.
int[] memo = new int[n+1];
int sum = 0;
for(int i = 0; i <= n; ++i)
{
sum+=i;
memo[i] = sum;
}
return memo[n];