I am interested in creating a list / array of functions "G" consisting of many small functions "g". This essentially should correspond to a series of functions 'evolving' in time.
Each "g" takes-in two variables and returns the product of these variables with an outside global variable indexed at the same time-step.
Assume obs_mat (T x 1) is a pre-defined global array, and t corresponds to the time-steps
G = []
for t in range(T):
# tried declaring obs here too.
def g(current_state, observation_noise):
obs = obs_mat[t]
return current_state * observation_noise * obs
G.append(g)
Unfortunately when I test the resultant functions, they do not seem to pick up on the difference in the obs time-varying constant i.e. (Got G[0](100,100) same as G[5](100,100)). I tried playing around with the scope of obs but without much luck. Would anyone be able to help guide me in the right direction?
This is a common "gotcha" to referencing variables from an outer scope when in an inner function. The outer variable is looked up when the inner function is run, not when the inner function is defined (so all versions of the function see the variable's last value). For each function to see a different value, you either need to make sure they're looking in separate namespaces, or you need to bind the value to a default parameter of the inner function.
Here's an approach that uses an extra namespace:
def make_func(x):
def func(a, b):
return a*b*x
return func
list_of_funcs = [make_func(i) for i in range(10)]
Each inner function func has access to the x parameter in the enclosing make_func function. Since they're all created by separate calls to make_func, they each see separate namespaces with different x values.
Here's the other approach that uses a default argument (with functions created by a lambda expression):
list_of_funcs = [lambda a, b, x=i: a*b*x for i in range(10)]
In this version, the i variable from the list comprehension is bound to the default value of the x parameter in the lambda expression. This binding means that the functions wont care about the value of i changing later on. The downside to this solution is that any code that accidentally calls one of the functions with three arguments instead of two may work without an exception (perhaps with odd results).
The problem you are running into is one of scoping. Function bodies aren't evaluated until the fuction is actually called, so the functions you have there will use whatever is the current value of the variable within their scope at time of evaluation (which means they'll have the same t if you call them all after the for-loop has ended)
In order to see the value that you would like, you'd need to immediately call the function and save the result.
I'm not really sure why you're using an array of functions. Perhaps what you're trying to do is map a partial function across the time series, something like the following?
from functools import partial
def g(current_state, observation_noise, t):
obs = obs_mat[t]
return current_state * observation_noise * obs
g_maker = partial(g, current, observation)
results = list(map(g_maker, range(T)))
What's happening here is that partial creates a partially-applied function, which is merely waiting for its final value to be evaluated. That final value is dynamic (but the first two are fixed in this example), so mapping that partially-applied function over a range of values gets you answers for each value.
Honestly, this is a guess because it's hard to see what else you are trying to do with this data and it's hard to see what you're trying to achieve with the array of functions (and there are certainly other ways to do this).
The issue (assuming that your G.append call is mis-indented) is simply that the name t is mutated when you loop over the iterator returned by range(T). Since every function g you create stores returns the same name t, they wind up all returning the same value, T - 1. The fix is to de-reference the name (the simplest way to do this is by sending t into your function as a default value for an argument in g's argument list):
G = []
for t in range(T):
def g(current_state, observation_noise, t_kw=t):
obs = obs_mat[t_kw]
return current_state * observation_noise * obs
G.append(g)
This works because it creates another name that points at the value that t references during that iteration of the loop (you could still use t rather than t_kw and it would still just work because tg is bound to the value that tf is bound to - the value never changes, but tf is bound to another value on the next iteration, while tg still points at the "original" value.
I've seen references to curried functions in several articles and blogs but I can't find a good explanation (or at least one that makes sense!)
Currying is when you break down a function that takes multiple arguments into a series of functions that each take only one argument. Here's an example in JavaScript:
function add (a, b) {
return a + b;
}
add(3, 4); // returns 7
This is a function that takes two arguments, a and b, and returns their sum. We will now curry this function:
function add (a) {
return function (b) {
return a + b;
}
}
This is a function that takes one argument, a, and returns a function that takes another argument, b, and that function returns their sum.
add(3)(4); // returns 7
var add3 = add(3); // returns a function
add3(4); // returns 7
The first statement returns 7, like the add(3, 4) statement.
The second statement defines a new function called add3 that will
add 3 to its argument. (This is what some may call a closure.)
The third statement uses the add3 operation to add 3 to 4, again
producing 7 as a result.
In an algebra of functions, dealing with functions that take multiple arguments (or equivalent one argument that's an N-tuple) is somewhat inelegant -- but, as Moses Schönfinkel (and, independently, Haskell Curry) proved, it's not needed: all you need are functions that take one argument.
So how do you deal with something you'd naturally express as, say, f(x,y)? Well, you take that as equivalent to f(x)(y) -- f(x), call it g, is a function, and you apply that function to y. In other words, you only have functions that take one argument -- but some of those functions return other functions (which ALSO take one argument;-).
As usual, wikipedia has a nice summary entry about this, with many useful pointers (probably including ones regarding your favorite languages;-) as well as slightly more rigorous mathematical treatment.
Here's a concrete example:
Suppose you have a function that calculates the gravitational force acting on an object. If you don't know the formula, you can find it here. This function takes in the three necessary parameters as arguments.
Now, being on the earth, you only want to calculate forces for objects on this planet. In a functional language, you could pass in the mass of the earth to the function and then partially evaluate it. What you'd get back is another function that takes only two arguments and calculates the gravitational force of objects on earth. This is called currying.
It can be a way to use functions to make other functions.
In javascript:
let add = function(x){
return function(y){
return x + y
};
};
Would allow us to call it like so:
let addTen = add(10);
When this runs the 10 is passed in as x;
let add = function(10){
return function(y){
return 10 + y
};
};
which means we are returned this function:
function(y) { return 10 + y };
So when you call
addTen();
you are really calling:
function(y) { return 10 + y };
So if you do this:
addTen(4)
it's the same as:
function(4) { return 10 + 4} // 14
So our addTen() always adds ten to whatever we pass in. We can make similar functions in the same way:
let addTwo = add(2) // addTwo(); will add two to whatever you pass in
let addSeventy = add(70) // ... and so on...
Now the obvious follow up question is why on earth would you ever want to do that? It turns what was an eager operation x + y into one that can be stepped through lazily, meaning we can do at least two things
1. cache expensive operations
2. achieve abstractions in the functional paradigm.
Imagine our curried function looked like this:
let doTheHardStuff = function(x) {
let z = doSomethingComputationallyExpensive(x)
return function (y){
z + y
}
}
We could call this function once, then pass around the result to be used in lots of places, meaning we only do the computationally expensive stuff once:
let finishTheJob = doTheHardStuff(10)
finishTheJob(20)
finishTheJob(30)
We can get abstractions in a similar way.
Currying is a transformation that can be applied to functions to allow them to take one less argument than previously.
For example, in F# you can define a function thus:-
let f x y z = x + y + z
Here function f takes parameters x, y and z and sums them together so:-
f 1 2 3
Returns 6.
From our definition we can can therefore define the curry function for f:-
let curry f = fun x -> f x
Where 'fun x -> f x' is a lambda function equivilent to x => f(x) in C#. This function inputs the function you wish to curry and returns a function which takes a single argument and returns the specified function with the first argument set to the input argument.
Using our previous example we can obtain a curry of f thus:-
let curryf = curry f
We can then do the following:-
let f1 = curryf 1
Which provides us with a function f1 which is equivilent to f1 y z = 1 + y + z. This means we can do the following:-
f1 2 3
Which returns 6.
This process is often confused with 'partial function application' which can be defined thus:-
let papply f x = f x
Though we can extend it to more than one parameter, i.e.:-
let papply2 f x y = f x y
let papply3 f x y z = f x y z
etc.
A partial application will take the function and parameter(s) and return a function that requires one or more less parameters, and as the previous two examples show is implemented directly in the standard F# function definition so we could achieve the previous result thus:-
let f1 = f 1
f1 2 3
Which will return a result of 6.
In conclusion:-
The difference between currying and partial function application is that:-
Currying takes a function and provides a new function accepting a single argument, and returning the specified function with its first argument set to that argument. This allows us to represent functions with multiple parameters as a series of single argument functions. Example:-
let f x y z = x + y + z
let curryf = curry f
let f1 = curryf 1
let f2 = curryf 2
f1 2 3
6
f2 1 3
6
Partial function application is more direct - it takes a function and one or more arguments and returns a function with the first n arguments set to the n arguments specified. Example:-
let f x y z = x + y + z
let f1 = f 1
let f2 = f 2
f1 2 3
6
f2 1 3
6
A curried function is a function of several arguments rewritten such that it accepts the first argument and returns a function that accepts the second argument and so on. This allows functions of several arguments to have some of their initial arguments partially applied.
Currying means to convert a function of N arity into N functions of arity 1. The arity of the function is the number of arguments it requires.
Here is the formal definition:
curry(f) :: (a,b,c) -> f(a) -> f(b)-> f(c)
Here is a real world example that makes sense:
You go to ATM to get some money. You swipe your card, enter pin number and make your selection and then press enter to submit the "amount" alongside the request.
here is the normal function for withdrawing money.
const withdraw=(cardInfo,pinNumber,request){
// process it
return request.amount
}
In this implementation function expects us entering all arguments at once. We were going to swipe the card, enter the pin and make the request, then function would run. If any of those steps had issue, you would find out after you enter all the arguments. With curried function, we would create higher arity, pure and simple functions. Pure functions will help us easily debug our code.
this is Atm with curried function:
const withdraw=(cardInfo)=>(pinNumber)=>(request)=>request.amount
ATM, takes the card as input and returns a function that expects pinNumber and this function returns a function that accepts the request object and after the successful process, you get the amount that you requested. Each step, if you had an error, you will easily predict what went wrong. Let's say you enter the card and got error, you know that it is either related to the card or machine but not the pin number. Or if you entered the pin and if it does not get accepted you know that you entered the pin number wrong. You will easily debug the error.
Also, each function here is reusable, so you can use the same functions in different parts of your project.
Currying is translating a function from callable as f(a, b, c) into callable as f(a)(b)(c).
Otherwise currying is when you break down a function that takes multiple arguments into a series of functions that take part of the arguments.
Literally, currying is a transformation of functions: from one way of calling into another. In JavaScript, we usually make a wrapper to keep the original function.
Currying doesn’t call a function. It just transforms it.
Let’s make curry function that performs currying for two-argument functions. In other words, curry(f) for two-argument f(a, b) translates it into f(a)(b)
function curry(f) { // curry(f) does the currying transform
return function(a) {
return function(b) {
return f(a, b);
};
};
}
// usage
function sum(a, b) {
return a + b;
}
let carriedSum = curry(sum);
alert( carriedSum(1)(2) ); // 3
As you can see, the implementation is a series of wrappers.
The result of curry(func) is a wrapper function(a).
When it is called like sum(1), the argument is saved in the Lexical Environment, and a new wrapper is returned function(b).
Then sum(1)(2) finally calls function(b) providing 2, and it passes the call to the original multi-argument sum.
Here's a toy example in Python:
>>> from functools import partial as curry
>>> # Original function taking three parameters:
>>> def display_quote(who, subject, quote):
print who, 'said regarding', subject + ':'
print '"' + quote + '"'
>>> display_quote("hoohoo", "functional languages",
"I like Erlang, not sure yet about Haskell.")
hoohoo said regarding functional languages:
"I like Erlang, not sure yet about Haskell."
>>> # Let's curry the function to get another that always quotes Alex...
>>> am_quote = curry(display_quote, "Alex Martelli")
>>> am_quote("currying", "As usual, wikipedia has a nice summary...")
Alex Martelli said regarding currying:
"As usual, wikipedia has a nice summary..."
(Just using concatenation via + to avoid distraction for non-Python programmers.)
Editing to add:
See http://docs.python.org/library/functools.html?highlight=partial#functools.partial,
which also shows the partial object vs. function distinction in the way Python implements this.
Here is the example of generic and the shortest version for function currying with n no. of params.
const add = a => b => b ? add(a + b) : a;
const add = a => b => b ? add(a + b) : a;
console.log(add(1)(2)(3)(4)());
Currying is one of the higher-order functions of Java Script.
Currying is a function of many arguments which is rewritten such that it takes the first argument and return a function which in turns uses the remaining arguments and returns the value.
Confused?
Let see an example,
function add(a,b)
{
return a+b;
}
add(5,6);
This is similar to the following currying function,
function add(a)
{
return function(b){
return a+b;
}
}
var curryAdd = add(5);
curryAdd(6);
So what does this code means?
Now read the definition again,
Currying is a function of many arguments which is rewritten such that it takes first argument and return a function which in turns uses the remaining arguments and returns the value.
Still, Confused?
Let me explain in deep!
When you call this function,
var curryAdd = add(5);
It will return you a function like this,
curryAdd=function(y){return 5+y;}
So, this is called higher-order functions. Meaning, Invoking one function in turns returns another function is an exact definition for higher-order function. This is the greatest advantage for the legend, Java Script.
So come back to the currying,
This line will pass the second argument to the curryAdd function.
curryAdd(6);
which in turns results,
curryAdd=function(6){return 5+6;}
// Which results in 11
Hope you understand the usage of currying here.
So, Coming to the advantages,
Why Currying?
It makes use of code reusability.
Less code, Less Error.
You may ask how it is less code?
I can prove it with ECMA script 6 new feature arrow functions.
Yes! ECMA 6, provide us with the wonderful feature called arrow functions,
function add(a)
{
return function(b){
return a+b;
}
}
With the help of the arrow function, we can write the above function as follows,
x=>y=>x+y
Cool right?
So, Less Code and Fewer bugs!!
With the help of these higher-order function one can easily develop a bug-free code.
I challenge you!
Hope, you understood what is currying. Please feel free to comment over here if you need any clarifications.
Thanks, Have a nice day!
If you understand partial you're halfway there. The idea of partial is to preapply arguments to a function and give back a new function that wants only the remaining arguments. When this new function is called it includes the preloaded arguments along with whatever arguments were supplied to it.
In Clojure + is a function but to make things starkly clear:
(defn add [a b] (+ a b))
You may be aware that the inc function simply adds 1 to whatever number it's passed.
(inc 7) # => 8
Let's build it ourselves using partial:
(def inc (partial add 1))
Here we return another function that has 1 loaded into the first argument of add. As add takes two arguments the new inc function wants only the b argument -- not 2 arguments as before since 1 has already been partially applied. Thus partial is a tool from which to create new functions with default values presupplied. That is why in a functional language functions often order arguments from general to specific. This makes it easier to reuse such functions from which to construct other functions.
Now imagine if the language were smart enough to understand introspectively that add wanted two arguments. When we passed it one argument, rather than balking, what if the function partially applied the argument we passed it on our behalf understanding that we probably meant to provide the other argument later? We could then define inc without explicitly using partial.
(def inc (add 1)) #partial is implied
This is the way some languages behave. It is exceptionally useful when one wishes to compose functions into larger transformations. This would lead one to transducers.
Curry can simplify your code. This is one of the main reasons to use this. Currying is a process of converting a function that accepts n arguments into n functions that accept only one argument.
The principle is to pass the arguments of the passed function, using the closure (closure) property, to store them in another function and treat it as a return value, and these functions form a chain, and the final arguments are passed in to complete the operation.
The benefit of this is that it can simplify the processing of parameters by dealing with one parameter at a time, which can also improve the flexibility and readability of the program. This also makes the program more manageable. Also dividing the code into smaller pieces would make it reuse-friendly.
For example:
function curryMinus(x)
{
return function(y)
{
return x - y;
}
}
var minus5 = curryMinus(1);
minus5(3);
minus5(5);
I can also do...
var minus7 = curryMinus(7);
minus7(3);
minus7(5);
This is very great for making complex code neat and handling of unsynchronized methods etc.
I found this article, and the article it references, useful, to better understand currying:
http://blogs.msdn.com/wesdyer/archive/2007/01/29/currying-and-partial-function-application.aspx
As the others mentioned, it is just a way to have a one parameter function.
This is useful in that you don't have to assume how many parameters will be passed in, so you don't need a 2 parameter, 3 parameter and 4 parameter functions.
As all other answers currying helps to create partially applied functions. Javascript does not provide native support for automatic currying. So the examples provided above may not help in practical coding. There is some excellent example in livescript (Which essentially compiles to js)
http://livescript.net/
times = (x, y) --> x * y
times 2, 3 #=> 6 (normal use works as expected)
double = times 2
double 5 #=> 10
In above example when you have given less no of arguments livescript generates new curried function for you (double)
A curried function is applied to multiple argument lists, instead of just
one.
Here is a regular, non-curried function, which adds two Int
parameters, x and y:
scala> def plainOldSum(x: Int, y: Int) = x + y
plainOldSum: (x: Int,y: Int)Int
scala> plainOldSum(1, 2)
res4: Int = 3
Here is similar function that’s curried. Instead
of one list of two Int parameters, you apply this function to two lists of one
Int parameter each:
scala> def curriedSum(x: Int)(y: Int) = x + y
curriedSum: (x: Int)(y: Int)Intscala> second(2)
res6: Int = 3
scala> curriedSum(1)(2)
res5: Int = 3
What’s happening here is that when you invoke curriedSum, you actually get two traditional function invocations back to back. The first function
invocation takes a single Int parameter named x , and returns a function
value for the second function. This second function takes the Int parameter
y.
Here’s a function named first that does in spirit what the first traditional
function invocation of curriedSum would do:
scala> def first(x: Int) = (y: Int) => x + y
first: (x: Int)(Int) => Int
Applying 1 to the first function—in other words, invoking the first function
and passing in 1 —yields the second function:
scala> val second = first(1)
second: (Int) => Int = <function1>
Applying 2 to the second function yields the result:
scala> second(2)
res6: Int = 3
An example of currying would be when having functions you only know one of the parameters at the moment:
For example:
func aFunction(str: String) {
let callback = callback(str) // signature now is `NSData -> ()`
performAsyncRequest(callback)
}
func callback(str: String, data: NSData) {
// Callback code
}
func performAsyncRequest(callback: NSData -> ()) {
// Async code that will call callback with NSData as parameter
}
Here, since you don't know the second parameter for callback when sending it to performAsyncRequest(_:) you would have to create another lambda / closure to send that one to the function.
Most of the examples in this thread are contrived (adding numbers). These are useful for illustrating the concept, but don't motivate when you might actually use currying in an app.
Here's a practical example from React, the JavaScript user interface library. Currying here illustrates the closure property.
As is typical in most user interface libraries, when the user clicks a button, a function is called to handle the event. The handler typically modifies the application's state and triggers the interface to re-render.
Lists of items are common user interface components. Each item might have an identifier associated with it (usually related to a database record). When the user clicks a button to, for example, "like" an item in the list, the handler needs to know which button was clicked.
Currying is one approach for achieving the binding between id and handler. In the code below, makeClickHandler is a function that accepts an id and returns a handler function that has the id in its scope.
The inner function's workings aren't important for this discussion. But if you're curious, it searches through the array of items to find an item by id and increments its "likes", triggering another render by setting the state. State is immutable in React so it takes a bit more work to modify the one value than you might expect.
You can think of invoking the curried function as "stripping" off the outer function to expose an inner function ready to be called. That new inner function is the actual handler passed to React's onClick. The outer function is a closure for the loop body to specify the id that will be in scope of a particular inner handler function.
const List = () => {
const [items, setItems] = React.useState([
{name: "foo", likes: 0},
{name: "bar", likes: 0},
{name: "baz", likes: 0},
].map(e => ({...e, id: crypto.randomUUID()})));
// .----------. outer func inner func
// | currying | | |
// `----------` V V
const makeClickHandler = (id) => (event) => {
setItems(prev => {
const i = prev.findIndex(e => e.id === id);
const cpy = {...prev[i]};
cpy.likes++;
return [
...prev.slice(0, i),
cpy,
...prev.slice(i + 1)
];
});
};
return (
<ul>
{items.map(({name, likes, id}) =>
<li key={id}>
<button
onClick={
/* strip off first function layer to get a click
handler bound to `id` and pass it to onClick */
makeClickHandler(id)
}
>
{name} ({likes} likes)
</button>
</li>
)}
</ul>
);
};
ReactDOM.createRoot(document.querySelector("#app"))
.render(<List />);
button {
font-family: monospace;
font-size: 2em;
}
<script crossorigin src="https://unpkg.com/react#18/umd/react.development.js"></script>
<script crossorigin src="https://unpkg.com/react-dom#18/umd/react-dom.development.js"></script>
<div id="app"></div>
Here you can find a simple explanation of currying implementation in C#. In the comments, I have tried to show how currying can be useful:
public static class FuncExtensions {
public static Func<T1, Func<T2, TResult>> Curry<T1, T2, TResult>(this Func<T1, T2, TResult> func)
{
return x1 => x2 => func(x1, x2);
}
}
//Usage
var add = new Func<int, int, int>((x, y) => x + y).Curry();
var func = add(1);
//Obtaining the next parameter here, calling later the func with next parameter.
//Or you can prepare some base calculations at the previous step and then
//use the result of those calculations when calling the func multiple times
//with different input parameters.
int result = func(1);
"Currying" is the process of taking the function of multiple arguments and converting it into a series of functions that each take a single argument and return a function of a single argument, or in the case of the final function, return the actual result.
The other answers have said what currying is: passing fewer arguments to a curried function than it expects is not an error, but instead returns a function that expects the rest of the arguments and returns the same result as if you had passed them all in at once.
I’ll try to motivate why it’s useful. It’s one of those tools that you never realized you needed until you do. Currying is above all a way to make your programs more expressive - you can combine operations together with less code.
For example, if you have a curried function add, you can write the equivalent of JS x => k + x (or Python lambda x: k + x or Ruby { |x| k + x } or Lisp (lambda (x) (+ k x)) or …) as just add(k). In Haskelll you can even use the operator: (k +) or (+ k) (The two forms let you curry either way for non-commutative operators: (/ 9) is a function that divides a number by 9, which is probably the more common use case, but you also have (9 /) for a function that divides 9 by its argument.) Besides being shorter, the curried version contains no made-up parameter name like the x found in all the other versions. It’s not needed. You’re defining a function that adds some constant k to a number, and you don’t need to give that number a name just to talk about the function. Or even to define it. This is an example of what’s called “point-free style”. You can combine operations together given nothing but the operations themselves. You don’t have to declare anonymous functions that do nothing but apply some operation to their argument, because *that’s what the operations already are.
This becomes very handy with higher-order functions when they’re defined in a currying-friendly way. For instance, a curried map(fn, list) let’s you define a mapper with just map(fn) that can be applied it to any list later. But currying a map defined instead as map(list, fn) just lets you define a function that will apply some other function to a constant list, which is probably less generally useful.
Currying reduces the need for things like pipes and threading. In Clojure, you might define a temperature conversion function using the threading macro ->: (defn f2c (deg) (-> deg (- 32) (* 5) (/ 9)). That’s cool, it reads nicely left to right (“subtract 32, multiply by 5 and divide by 9.”) and you only have to mention the parameter twice instead of once for every suboperation… but it only works because -> is a macro that transforms the whole form syntactically before anything is evaluated. It turns into a regular nested expression behind the scenes: (/ (* (- deg 32) 5) 9). If the math ops were curried, you wouldn’t need a macro to combine them so nicely, as in Haskell let f2c = (subtract 32) & (* 5) & (/ 9). (Although it would admittedly be more idiomatic to use function composition, which reads right to left: (/ 9) . (* 5) . (subtract 32).)
Again, it’s hard to find good demo examples; currying is most useful in complex cases where it really helps the readability of the solution, but those take so much explanation just to get you to understand the problem that the overall lesson about currying can get lost in the noise.
There is an example of "Currying in ReasonML".
let run = () => {
Js.log("Curryed function: ");
let sum = (x, y) => x + y;
Printf.printf("sum(2, 3) : %d\n", sum(2, 3));
let per2 = sum(2);
Printf.printf("per2(3) : %d\n", per2(3));
};
Below is one of currying example in JavaScript, here the multiply return the function which is used to multiply x by two.
const multiply = (presetConstant) => {
return (x) => {
return presetConstant * x;
};
};
const multiplyByTwo = multiply(2);
// now multiplyByTwo is like below function & due to closure property in JavaScript it will always be able to access 'presetConstant' value
// const multiplyByTwo = (x) => {
// return presetConstant * x;
// };
console.log(`multiplyByTwo(8) : ${multiplyByTwo(8)}`);
Output
multiplyByTwo(8) : 16
I have these three functions:
When I run the first 2 functions, There's no problem, but when I run the last function (LMTD), It says 'Division by zero' yet when I debug some of the arguments have values, some don't. I know what I have to do, but I want to know why I have to do it, because it makes no sense to me.
Tinn-function doesn't have Tut's arguments, so I have to add them to Tinn-function's arguments. Same goes for Tut, that doesn't know all of Tinn's arguments, and LMTD has to have both of Tinn and Tut's arguments. If I do that, it all runs smoothly. Why do I have to do this?
Public Function Tinn(Tw, Qw, Qp, Q, deltaT)
Tinn = (((Tw * Qw) + (Tut(Q, fd, mix) * Q)) / Qp) + deltaT
End Function
Public Function Tut(Q, fd, mix)
Tut = Tinn(Tw, Qw, Qp, Q, deltaT) _
- (avgittEffektAiUiLMTD() / ((Q * fd * mix) / 3600))
End Function
Public Function LMTD(Tsjo)
LMTD = ((Tinn(Tw, Qw, Qp, Q, deltaT) - Tsjo) - (Tut(Q, fd, mix) - Tsjo)) _
/ (WorksheetFunction.Ln((Tinn(Tw, Qw, Qp, Q, deltaT) - Tsjo) _
/ (Tut(Q, fd, mix) - Tsjo)))
End Function
I will try to give a useful and complete explanation on how arguments are being passed:
As far as I can tell, LMTD is the main function calling the other function.
Each time a new function is called, it is placed on top of what they call the "stack";
The principle of Stack involves that memory is allocated and deallocated at one end of the memory (top of the stack): memory is allocated to those local variables declared and used in the function on top of the stack (function that is called gets in scope and forms a new layer on top of the stack) while these local variables are being released as soon as the function goes out of scope (when the value is returned). Something generally referred to as "Last In First Out" (LIFO).
So if you consider LMTD the base (which is probably not the ultimate base, since it is must be called by another sub routine or function), Tinn and Tut are placed on top of the stack whenever these functions are being called.
However (and here is the point),
Variables not locally declared in functions and passed as argument are standard passed by Reference, they are pointer variables containing the memory address of the arguments sent by the function (or sub) on the lower layer of the stack.
When a function takes parameters by reference (default), it can change the values contained by the memory addresses that are passed and thus the original variable value can be changed when the called function is returned.
This example illustrates it:
Sub Base_Sub()
Dim i as single
Dim c as single
Dim d as single
c = 5
d = 6
i = Function_1(c, d)
End Sub
Function Function_1(c, d)
c = 7 'Notice that the variables c and d are also changed in the Base_sub
d = 5
Function_1 = c + d
End Function
On the contrary, if you would send variable by value (byVal keyword), this would mean that a copy of the original variable (that is passed as argument) is made and the original variable remains untouched while the copy is being manipulated in the function. In other words, this copy would become a local variable on top of the stack and released as soon as the function goes out of scope.
So without looking into dept into your code to deep, when you call many functions in one routine, it may help you to keep this general concept of the different layers in mind.
In order to keep an eye on your local variables, use the "locals" window in VBA for follow-up or use debug.print to follow up in the immediate window.
What could help you gain more transparency regarding the error is by performing a check. For example
for Tinn function:
If QP = 0 then
'Notify problem at QP.
end if
I'm sorry if my explanation was more than you expected, but I tried to be as complete as possible on this one.