I have a function, which, given a number and a list of numbers returns if the number can be made out of the
numbers in a list, where numbers can be used as many times as needed:
def canSum(target_sum, numbers, memo = {}):
if target_sum in memo:
return memo[target_sum]
if target_sum == 0:
return True
if target_sum < 0:
return False
for n in numbers:
remainder = target_sum - n
if canSum(remainder, numbers) == True:
memo[target_sum] = True
return True, memo
memo[target_sum] = False
return False,memo
It should return True and False depending if the target_sum can be made by adding any numbers any amount of time in the numbers list.
For example canSum(4, [2]) should return True because 2+2 is 4 and so on.
However I can't understand where is my mistake, all of the below should return True.
canSum(4,[2])
# (False, {2: True, 4: False})
canSum(4,[2,1])
# (False, {2: True, 1: True, 3: True, 4: False})
canSum(4,[1,2])
# (True, {1: True, 2: True, 3: True, 4: True})
canSum(10,[2])
# (False, {2: True, 4: False, 6: False, 8: False, 10: False})
canSum(10,[2,3])
# (False, {2: True, 1: False, 4: False, 3: True, 6: False, 5: True, 8: False, 7: True, 10: False})
Also, is there a difference or a need to pass memo to the recursive function call? Which does not seem to make any difference.
if canSum(remainder, numbers) == True: # -> if canSum(remainder, numbers, memo) == True:
memo[target_sum] = True
return True, memo
Consider when you call canSum(0, [2]), the function will be return literal True. and if canSum(0, [2]) == True condition's will be satisfy. but when you call canSum(2, [2]), the function will be return a tuple of (True, {2: True}) and if canSum(2, [2]) == True condition's won't be satisfy. So when you call canSum(4, [2]), the function will return (False, {2: True, 4: False}).
You have to return in same format for every calls. I think this will be work.
def canSum(target_sum, numbers, memo={}):
if target_sum in memo:
return memo[target_sum], memo
if target_sum == 0:
return True, memo
if target_sum < 0:
return False, memo
for n in numbers:
remainder = target_sum - n
if canSum(remainder, numbers)[0]:
memo[target_sum] = True
return True, memo
memo[target_sum] = False
return False, memo
So, I have a series of actions to perform, based on 4 conditional variables - lets say x,y,z & t. Each of these variables have a possible True or False value. So, that is a total of 16 possible permutations. And I need to perform a different action for each permutation.
What is the best way to do this rather than making a huge if-else construct.
Lets see a simplified example. This is how my code would look if I try to contain all the different permutations into a large if-else construct.
if (x == True):
if (y == True):
if (z == True):
if (t == True):
print ("Case 1")
else:
print ("Case 2")
else:
if (t == True):
print ("Case 3")
else:
print ("Case 4")
else:
if (z == True):
if (t == True):
print ("Case 5")
else:
print ("Case 6")
else:
if (t == True):
print ("Case 7")
else:
print ("Case 8")
else:
if (y == True):
if (z == True):
if (t == True):
print ("Case 9")
else:
print ("Case 10")
else:
if (t == True):
print ("Case 11")
else:
print ("Case 12")
else:
if (z == True):
if (t == True):
print ("Case 13")
else:
print ("Case 14")
else:
if (t == True):
print ("Case 15")
else:
print ("Case 16")
Is there any way to simplify this? Obviously, my objective for each case is more complicated than just printing "Case 1".
You can use a map of cases to results:
cases = { (True, True, True, True): "Case 1",
(True, True, True, False): "Case 2",
(True, True, False, True): "Case 3",
(True, True, False, False):"Case 4",
(True, False, True, True): "Case 5",
(True, False, True, False):"Case 6",
(True, False, False, True): "Case 7",
(True, False, False, False):"Case 8",
(False, True, True, True): "Case 9",
(False, True, True, False):"Case 10",
(False, True, False, True): "Case 11",
(False, True, False, False):"Case 12",
(False, False, True, True): "Case 13",
(False, False, True, False):"Case 14",
(False, False, False, True): "Case 15",
(False, False, False, False):"Case 16"}
print(cases[(x,y,z,t])
If you want to do something else/different for each case, you could add a function to that map.
cases = { (True, True, True, True): foo_func,
(True, True, True, False): bar_func,
...}
result = cases[(x,y,x,t)](*args)
You can also use one of the masking solutions to make the code shorter, or if you have too many cases to write out, but for smaller sets of cases, this explicit representation will be clearer and easier to maintain.
you could get your case number directly from binary manipulation of your booleans:
case = (x^1) << 3 | (y^1) << 2 | (z^1) << 1 | (t^1) + 1
print(f'Case {case}')
if you look at John Kugelman's answer you see that x, y, z, t are just the 'bits' of your case number (where True=0 and False=1)... so i construct an int setting those bits (and then add 1 because you start counting at 1).
if the numbering is arbitrary you can simplify that down to x << 3 | y << 2 | z << 1 | t and take it from there.
this is easily extensible to a larger number of boolean variables.
then to do something based on the case number i suggest you create a dictionary containing the case as key and the function or data or whatever as value. something like:
case_functions = {1: func_1, 2: func_2, ...}
res = case_functions(case)(some argument)
You could shove all the values into a tuple and use 16 tuple comparisons.
if (x, y, z, t) == (True, True, True, True): print("Case 1")
elif (x, y, z, t) == (True, True, True, False): print("Case 2")
elif (x, y, z, t) == (True, True, False, True): print("Case 3")
elif (x, y, z, t) == (True, True, False, False): print("Case 4")
elif (x, y, z, t) == (True, False, True, True): print("Case 5")
elif (x, y, z, t) == (True, False, True, False): print("Case 6")
elif (x, y, z, t) == (True, False, False, True): print("Case 7")
elif (x, y, z, t) == (True, False, False, False): print("Case 8")
elif (x, y, z, t) == (False, True, True, True): print("Case 9")
elif (x, y, z, t) == (False, True, True, False): print("Case 10")
elif (x, y, z, t) == (False, True, False, True): print("Case 11")
elif (x, y, z, t) == (False, True, False, False): print("Case 12")
elif (x, y, z, t) == (False, False, True, True): print("Case 13")
elif (x, y, z, t) == (False, False, True, False): print("Case 14")
elif (x, y, z, t) == (False, False, False, True): print("Case 15")
elif (x, y, z, t) == (False, False, False, False): print("Case 16")
This could be converted into a dict lookup or use clever binary packing tricks, but the advantages here are (a) it's straightforward and readable; (b) there's no need for lambdas or functions; and (c) you can put anything into the 16 cases.
This is a flexible solution that offers scalability and a certain level of simplicity.
Firstly, you'll need to create the methods that will run per output. These are the "complicated" versions of your print("case X") statements
#Define your method outcomes here...
#Note that this follows a binary layout starting with
# a + b + c + d = false
def action1(): #binary 0 (a'b'c'd')
print("case 1")
def action2(): #binary 1 (a'b'c'd)
print("case 2")
def action3(): #binary 2 (a'b'cd')
print("case 3")
def action4(): #binary 3 (a'b'cd)
print("case 4")
def action5(): #binary 4 (a'bc'd')
print("case 5") #etc...
def action6():
print("case 6")
def action7():
print("case 7")
def action8():
print("case 8")
def action9():
print("case 9")
def action10():
print("case 10")
def action11():
print("case 11")
def action12():
print("case 12")
def action13():
print("case 13")
def action14():
print("case 14")
def action15():
print("case 15")
def action16():
print("case 16")
def actionDefault():
print("Error!")
Then, you can easily reference these specific action methods later by creating a method name list and then creating a method to reference the method list when called.
import itertools #Generates all permutations
import sys #Allows us to get the current module
#Returns the index of the actionList we should execute
def evaluateActionIndex(varList):
allcombinations = itertools.product([False, True], repeat=len(varList))
i = 0
for subset in allcombinations: #for each of the possible combinations...
if list(subset) == varList: #Check to see if we want to execute this index.
return i
i = i + 1 #Increment the target index
return -1 #Execute default method (-1 index)
def performAction(index):
actionList = [action1.__name__, action2.__name__, action3.__name__, action4.__name__,
action5.__name__, action6.__name__, action7.__name__, action8.__name__,
action9.__name__, action10.__name__, action11.__name__, action12.__name__,
action13.__name__, action14.__name__, action15.__name__, action16.__name__,
actionDefault.__name__]
method = getattr(sys.modules[__name__], actionList[index]) #Get method by name
method() #Execute Method
We can perform some action by using:
#Mock up some control inputs
a = False
b = True
c = False
d = False
controlVariables = [a, b, c, d] #All Your Control Variables
#Execute control sequence
performAction(evaluateActionIndex(controlVariables))
I've tested this and it works effectively. You can add as many control variables as you need to the controlVariables list.
That's genious. Bits! Very clean.
I was searching for a solution to this for a long time.
Here's a javascript version:
//assuming you have your variables in an array
let q = evaluatedQuery = ["wd:Q82955", "wd:Q212238", "", "wd:Q116"]
//lenght of the binary string
let possibleCases = evaluatedQuery.length
let binaryCase = ""
for (let i = 0; i < possibleCases; i++) {
// this "!!" makes a value truthy or falsy,
// and converts that to an integer "!!q[i] ^ 0"
binaryCase = `${binaryCase}${!!q[i] ^ 0}`
}
//this finds out which of (q*q = 16) cases its gonna be
let parsedBinaryCase = parseInt(binaryCase, 2) + 1
//this converts it to an array for easy handling
let binaryCaseArr = binaryCase.split("")
//this filers out falsy values by taking falsy values index
let boundQueryElements = evaluatedQuery.filter((el, i) => {
return !binaryCaseArr[i] != !!el ^ 0
})
console.log(binaryCase) //output: 1101
console.log(parsedBinaryCase) //output: 14
console.log(boundQueryElements) //output: ['wd:Q82955','wd:Q212238','wd:Q116']
//and this is a clean way to handle those 16 cases
//in this example it would go to case 14
switch (parsedBinaryCase) {
case 1:
break
case 2:
break
case 3:
break
case 4:
break
case 5:
break
case 6:
break
case 7:
break
case 8:
break
case 9:
break
case 10:
break
case 11:
break
case 12:
break
case 13:
break
case 14:
// for (let el in boundQueryElements) {
// }
break
case 15:
break
case 16:
break
default:
}
It, like, 'flattens' the tree structure.
Just use the binary-ness of True and False values:
x = True
y = True
z = True
t = True
total = bin(x + 2 * y + 4 * z + 8 * t)
print(total)
print(int(total, 2))
Outputs:
0b1111
15
Whereas
x = False
y = True
z = False
t = True
total = bin(x + 2 * y + 4 * z + 8 * t)
print(total)
print(int(total, 2))
Yields:
0b1010
10
Now you can easily use the int(total, 2) value to determine which case you are dealing with
So you could convert your code to a single level of indents:
case = int(total, 2)
if case == 0:
print('case 0')
elif case == 1:
print('case 1')
elif case == 2:
print('case 2')
...
When there are this many cases I usually prefer writing helper functions that make the code easier to maintain, e.g.:
def compare(xyzt, binaryval):
boolval = tuple(digit == '1' for digit in binaryval)
return all(a == b for a, b in zip(xyzt, boolval))
then your if statement can be written as:
xyzt = (x, y, z, t)
if compare(xyzt, '1111'): ...
elif compare(xyzt, '1110'): ...
elif compare(xyzt, '1100'): ...
etc.
which makes it much easier to verify that you've considered all the cases.
I think this is a nice place for a registry of handlers. This won't give you the shortest code, but I think it gives you code that is easier to read and more maintainable, which is one interpretation of "simpler". I'd do something like this:
registry.py
handlers = dict()
def register(x, y, z, t):
if (x, y, z, t) in handlers:
raise ValueError("Handler already registered for {}/{}/{}/{}".format(
x, y, z, t))
def insert(f):
handlers[(x, y, z, t)] = f
return insert
def handle(x, y, z, t):
if (x, y, z, t) not in handlers:
raise KeyError("No handler registered for {}/{}/{}/{}".format(
x, y, z, t))
return handlers[(x, y, z, t)]()
handlers.py
from delegation import register, handle
#register(x=True, y=True, z=False, t=True)
def some_descriptive_name():
print("hi!")
#register(x=True, y=False, z=True, t=False)
def another_good_name():
print("Yes hello.")
# etc.
main.py
from handlers import handle
x, y, z, t = True, False, False, True
handle(x, y, z, t)
This lets you see exactly the conditions under which each handler will be activated. Separating your handlers into their own functions makes for cleaner testing as well. I've added a check to make sure you're not trying to handle the same conditions more than once and an error message for if a set of conditions isn't handled. It'd be easy to add a check to make sure that all cases are handled, too.
If your actions need to make use of variables (besides the four conditionals) you can do that as well; just change the signature and return value of handle like so:
def handle(x, y, z, t, *args, **kwargs):
...
return handlers[(x, y, z, t)](*args, **kwargs)
and, of course, add arguments to the handlers.
Extending on #Reedinationer's answer:
# your functions
def f0(): print('case 1')
def f1(): print('case 2')
def f2(): print('case 3')
#.
#.
def f15(): print('case 16')
list_of_functions = [f0, f1, f2] # assuming there are 16 functions in total
x = False
y = False
z = False
t = False
total = bin(x + 2 * y + 4 * z + 8 * t)
index = int(total, 2)
list_of_functions[index]() # will print('case 1')
Tested on python 2.7 and 3.7
Alright boys and girls here we go. To start off I have a couple of questions. Since my program is large I will simply ask questions in stages, this question being the first. I'm creating a program that generates a truth table for postfix logical expressions. Here are the operators allowed and their logical equivalents:
Operators:
= Logical Equivalence (≡ or ↔)
`->` or `<=` Logical Implication (→)
+ Disjunction (∨), AKA “or”
* Conjunction (∧), AKA “and”
`~` or `!` Negation (¬), AKA “not”
Here are some examples of input and output:
input
p True =
output
p p True =
False False
True True
input
p !
output
p p !
False True
True False
input
p q =
output
p q p q =
False False True
False True False
True False False
True True True
Ok I don't really know where to begin, but I'm not asking for anybody to write this program for me. I know I need to write code using a Python dict, that matches the keys to the corresponding proposition. But how do I know which ones to put for keys and which ones to put for values? Also, in the case of:
`->` or `<=` Logical Implication (→)
and
`~` or `!` Negation (¬), AKA “not”
How do I assign 2 different inputs to be able to be used in a python dict? I hope this isn't too confusing, I'm very noob at python, any help is appreciated. Thank you!
UPDATE
Ok here is the code I have now:
propositions = {
'=' : (2, {(True, True): True,
(True, False): False,
(False, True) : False,
(False, False): True,
}),
'->' : (2, {(True, True): True,
(True, False): False,
(False, True): True,
(False, False): True,
}),
'+' : (2, {(True, True): True,
(True, False): True,
(False, True): True,
(False, False): False,
}),
'*' : (2, {(True, True): True,
(True, False): False,
(False, True): False,
(False, False): False,
}),
'!' : (1, {True: False,
False: True})}
prop = sys.stdin.readline()
prop = prop.split()
prop = prop[::-1]
for x in prop:
I believe I successfully reversed the string and removed all whitespaces, but I am still a bit confused on iterating through it.
SECOND UPDATE here is my code:
propositions = {
'=' : (2, {(True, True): True,
(True, False): False,
(False, True) : False,
(False, False): True,
}),
'->' : (2, {(True, True): True,
(True, False): False,
(False, True): True,
(False, False): True,
}),
'+' : (2, {(True, True): True,
(True, False): True,
(False, True): True,
(False, False): False,
}),
'*' : (2, {(True, True): True,
(True, False): False,
(False, True): False,
(False, False): False,
}),
'!' : (1, {True: False,
False: True})}
prop = sys.stdin.readline()
prop = prop.strip().split()
prop = reversed(prop)
def evaluate():
token = next(prop)
try:
nargs, table = propositions[token]
except KeyError:
if token.lower() in ('true', '1'):
return True
elif token.lower() in ('false', '0'):
return False
else:
return token
return table[tuple(evaluate() for i in range(nargs))]
You have to build your dicts in the order of resolution from outer to inner:
master_dict = {
'=': (2, {(True, True): True,
(True, False): False,
...
}),
...
'!': (1, {True: False,
False: True})}
The numbers indicate how many operands the operator takes.
To parse an input read it from right to left.
Use a recursive function, that consumes one token from the right.
(1) If the token is an operator (i.e. a key in your dictionary) retrieve the corresponding value from your master dict.
The number stored first is the number of arguments the operator takes. So your function must now call itself as many times as there are arguments. Be sure to keep track of which tokens have already be read. One neat way of doing this is using a list iterator, which will spit out each element exactly once, so you can't get the indexing wrong. Once you have all the arguments you apply the truth table you've just retrieved, read out the result and return it.
(2) If the token is not an oprator your function must just return it.
prop = sys.stdin.readline()
def solve_no_var(prop):
rev_iter = reversed(prop)
def evaluate():
token = next(rev_iter)
try:
nargs, table = propositions[token]
except KeyError:
if token.lower() in ('true', '1'):
return True
elif token.lower() in ('false', '0'):
return False
else:
return token
return table[tuple(evaluate() for i in range(nargs))]
return evaluate()
def solve(prop):
prop = prop.strip().split()
variables = list(set(prop) - set(propositions)
- {'True', 'TRUE', 'true', '1', 'False', 'FALSE', 'false', '0'})
lookup = {v: [j for j, p in enumerate(prop) if p == v] for v in variables}
N = len(variables)
print((N*" {:6} ").format(*variables), 'result')
for p in itertools.product(("True", "False"), repeat=N):
prop_nv = prop.copy()
for v, b in zip (variables, p):
for j in lookup[v]:
prop_nv[j] = b
res = solve_no_var(prop_nv)
print(((N+1)*" {:6} ").format(*(p + (res,))))
solve(prop)