Extended Binary Search Function (python)
0
$begingroup$
I wrote a function to find the closest value in a list to a given search value. What prompted me to write it was as boilerplate for a prime number problem so I could find the closest prime to a given number.
My Code
'''
* This function finds the closest value in a sorted list to a given search value.
* Parameters:
* `lst` is the list to be searched.
* `item` is the value to be searched for.
* `current` stores the current best match.
* `control` controls the search behaviour of the function.
* `up` means find the closest value >= to `item`.
* `down` means find the closest value <= to `item`.
* `up(strict)` means find the closest value > to `item`.
* `down(strict)` means find the closest value < to "`tem`.
* `neutral` means find the closest value to `item`.
* Return:
* Returns the closest match in `lst`.
* None is returned if no value in the list satisfies the condition (e.g an empty list).
'''
def mins(lst, f = None):
mn = min(lst) if f is None else min(lst, key = f)
return (i for i in lst if i == mn)
def maxes(lst, f = None):
mx = max(lst) if key is None else max(lst, key = f)
return (i for i in lst if i == mx)
def xBinSearch(lst, item, control="neutral", current=None):
n = len(lst)
var = round(n/2)
if n > 1:
if control == "up":
if lst[var] == item:
return lst[var]
elif lst[var] > item: #The solution is in `lst[:var+1]`.
current = lst[var] if current == None or abs(current - item) > abs(lst[var] - item) else current #Update "current" to contain the current closest match.
return xBinSearch(lst[:var], item, control, current)
#Search the eligible space. If the solution is `lst[var]`, it is already stored in `current`.
else: #The solution is not in `lst[:var+1]`
return xBinSearch(lst[var+1:], item, control, current) if var + 1 < n else current
#Search the eligible space if it exists, else (if there is no where left to search), return the current best match.
elif control == "down":
if lst[var] == item:
return lst[var]
elif lst[var] < item: #The solution is not in `lst[:var]`.
current = lst[var] if current == None or abs(current - item) > abs(lst[var] - item) else current #Update "current" to contain the current closest match.
return xBinSearch(lst[var:], item, control, current) #Search the eligible space.
else: #The solution is not in lst[var:]
return xBinSearch(lst[:var], item, control, current) if var + 1 < n else current
#Search the eligible space if it exists, else (if there is no where left to search), return the current best match.
elif control == "up(strict)":
if lst[var] > item: #The solution is in `lst[:var+1]`.
current = lst[var] if current == None or abs(current - item) > abs(lst[var] - item) else current #Update "current" to contain the current closest match.
return xBinSearch(lst[:var], item, control, current)
#Search the eligible space. If the solution is `lst[var]`, it is already stored in `current`.
else: #The solution is not in `lst[:var+1]`
return xBinSearch(lst[var+1:], item, control, current) if var + 1 < n else current
#Search the eligible space if it exists, else (if there is no where left to search), return the current best match.
elif control == "down(strict)":
if lst[var] < item: #The solution is not in `lst[:var]`.
current = lst[var] if current == None or abs(current - item) > abs(lst[var] - item) else current #Update "current" to contain the current closest match.
return xBinSearch(lst[var:], item, control, current) #Search the eligible space.
else: #The solution is not in lst[var:]
return xBinSearch(lst[:var], item, control, current) if var + 1 < n else current #Search the eligible space if it exists, else (if there is no where left to search), return the current best match.
else:
check = [("b", lst[var], abs(lst[var]-item))] #`check[0]` => `var`.
if var-1 >= 0:
check.append(("a", lst[var-1], abs(lst[var-1]-item))) #`check[1]` => `var-1`.
if var+1 < n:
check.append(("c", lst[var+1], abs(lst[var+1]-item))) #`check[2]` => `var+1`.
mn = [x for x in mins(check, f = lambda x: x[2])] #The closest values to `item` from among the slice.
if "a" in mn and "c" not in mn: #The solution is not in `lst[var+1:]`
current = check[1][1] if current == None or abs(current - item) > check[1][2] else current
return xBinSearch(lst[:var+1], item, control, current)
elif "b" in mn and ("a" not in mn and "c" not in mn):
#The solution is neither in `lst[:var]` nor in `lst[:var+1]` so is therefore `lst[var]`.
return lst[var]
elif "c" in mn and "a" not in mn: #The solution is not in `lst[:var]`
current = check[2][1] if current == None or abs(current - item) > check[2][2] else current
return xBinSearch(lst[var+1:], item, control, current)
else: #The solution is in either lst[:var] or lst[var+1:]
current = check[0][1] if current == None or abs(current - item) > check[0][2] else current
return min([xBinSearch(lst[:var], item, control, current), xBinSearch(lst[var+1:], item, control, current)], key = lambda x: abs(x - item))
else:
if n == 1:
if control == "up":
if lst[0] >= item: #If it is an eligible solution.
current = lst[0] if current == None or abs(current - item) > abs(lst[0] - item) else current
#Modify `current` accordingly.
elif control == "down":
if lst[0] <= item: #If it is an eligible solution.
current = lst[0] if current == None or abs(current - item) > abs(lst[0] - item) else current
#Modify `current` accordingly.
if control == "up(strict)":
if lst[0] > item: #If it is an eligible solution.
current = lst[0] if current == None or abs(current - item) > abs(lst[0] - item) else current
#Modify `current` accordingly.
elif control == "down(strict)":
if lst[0] < item: #If it is an eligible solution.
current = lst[0] if current == None or abs(current - item) > abs(lst[0] - item) else current
#Modify `current` accordingly.
else:
current = lst[0] if current == None or abs(current - item) > abs(lst[0] - item) else current
#Modify `current` accordingly.
return current
python performance algorithm binary-search
asked 11 mins ago
Tobi AlafinTobi Alafin
21017
$endgroup$
add a comment |
0
$begingroup$
I wrote a function to find the closest value in a list to a given search value. What prompted me to write it was as boilerplate for a prime number problem so I could find the closest prime to a given number.
My Code
'''
* This function finds the closest value in a sorted list to a given search value.
* Parameters:
* `lst` is the list to be searched.
* `item` is the value to be searched for.
* `current` stores the current best match.
* `control` controls the search behaviour of the function.
* `up` means find the closest value >= to `item`.
* `down` means find the closest value <= to `item`.
* `up(strict)` means find the closest value > to `item`.
* `down(strict)` means find the closest value < to "`tem`.
* `neutral` means find the closest value to `item`.
* Return:
* Returns the closest match in `lst`.
* None is returned if no value in the list satisfies the condition (e.g an empty list).
'''
def mins(lst, f = None):
mn = min(lst) if f is None else min(lst, key = f)
return (i for i in lst if i == mn)
def maxes(lst, f = None):
mx = max(lst) if key is None else max(lst, key = f)
return (i for i in lst if i == mx)
def xBinSearch(lst, item, control="neutral", current=None):
n = len(lst)
var = round(n/2)
if n > 1:
if control == "up":
if lst[var] == item:
return lst[var]
elif lst[var] > item: #The solution is in `lst[:var+1]`.
current = lst[var] if current == None or abs(current - item) > abs(lst[var] - item) else current #Update "current" to contain the current closest match.
return xBinSearch(lst[:var], item, control, current)
#Search the eligible space. If the solution is `lst[var]`, it is already stored in `current`.
else: #The solution is not in `lst[:var+1]`
return xBinSearch(lst[var+1:], item, control, current) if var + 1 < n else current
#Search the eligible space if it exists, else (if there is no where left to search), return the current best match.
elif control == "down":
if lst[var] == item:
return lst[var]
elif lst[var] < item: #The solution is not in `lst[:var]`.
current = lst[var] if current == None or abs(current - item) > abs(lst[var] - item) else current #Update "current" to contain the current closest match.
return xBinSearch(lst[var:], item, control, current) #Search the eligible space.
else: #The solution is not in lst[var:]
return xBinSearch(lst[:var], item, control, current) if var + 1 < n else current
#Search the eligible space if it exists, else (if there is no where left to search), return the current best match.
elif control == "up(strict)":
if lst[var] > item: #The solution is in `lst[:var+1]`.
current = lst[var] if current == None or abs(current - item) > abs(lst[var] - item) else current #Update "current" to contain the current closest match.
return xBinSearch(lst[:var], item, control, current)
#Search the eligible space. If the solution is `lst[var]`, it is already stored in `current`.
else: #The solution is not in `lst[:var+1]`
return xBinSearch(lst[var+1:], item, control, current) if var + 1 < n else current
#Search the eligible space if it exists, else (if there is no where left to search), return the current best match.
elif control == "down(strict)":
if lst[var] < item: #The solution is not in `lst[:var]`.
current = lst[var] if current == None or abs(current - item) > abs(lst[var] - item) else current #Update "current" to contain the current closest match.
return xBinSearch(lst[var:], item, control, current) #Search the eligible space.
else: #The solution is not in lst[var:]
return xBinSearch(lst[:var], item, control, current) if var + 1 < n else current #Search the eligible space if it exists, else (if there is no where left to search), return the current best match.
else:
check = [("b", lst[var], abs(lst[var]-item))] #`check[0]` => `var`.
if var-1 >= 0:
check.append(("a", lst[var-1], abs(lst[var-1]-item))) #`check[1]` => `var-1`.
if var+1 < n:
check.append(("c", lst[var+1], abs(lst[var+1]-item))) #`check[2]` => `var+1`.
mn = [x for x in mins(check, f = lambda x: x[2])] #The closest values to `item` from among the slice.
if "a" in mn and "c" not in mn: #The solution is not in `lst[var+1:]`
current = check[1][1] if current == None or abs(current - item) > check[1][2] else current
return xBinSearch(lst[:var+1], item, control, current)
elif "b" in mn and ("a" not in mn and "c" not in mn):
#The solution is neither in `lst[:var]` nor in `lst[:var+1]` so is therefore `lst[var]`.
return lst[var]
elif "c" in mn and "a" not in mn: #The solution is not in `lst[:var]`
current = check[2][1] if current == None or abs(current - item) > check[2][2] else current
return xBinSearch(lst[var+1:], item, control, current)
else: #The solution is in either lst[:var] or lst[var+1:]
current = check[0][1] if current == None or abs(current - item) > check[0][2] else current
return min([xBinSearch(lst[:var], item, control, current), xBinSearch(lst[var+1:], item, control, current)], key = lambda x: abs(x - item))
else:
if n == 1:
if control == "up":
if lst[0] >= item: #If it is an eligible solution.
current = lst[0] if current == None or abs(current - item) > abs(lst[0] - item) else current
#Modify `current` accordingly.
elif control == "down":
if lst[0] <= item: #If it is an eligible solution.
current = lst[0] if current == None or abs(current - item) > abs(lst[0] - item) else current
#Modify `current` accordingly.
if control == "up(strict)":
if lst[0] > item: #If it is an eligible solution.
current = lst[0] if current == None or abs(current - item) > abs(lst[0] - item) else current
#Modify `current` accordingly.
elif control == "down(strict)":
if lst[0] < item: #If it is an eligible solution.
current = lst[0] if current == None or abs(current - item) > abs(lst[0] - item) else current
#Modify `current` accordingly.
else:
current = lst[0] if current == None or abs(current - item) > abs(lst[0] - item) else current
#Modify `current` accordingly.
return current
python performance algorithm binary-search
asked 11 mins ago
Tobi AlafinTobi Alafin
21017
$endgroup$
add a comment |
0
0
0
$begingroup$
I wrote a function to find the closest value in a list to a given search value. What prompted me to write it was as boilerplate for a prime number problem so I could find the closest prime to a given number.
My Code
'''
* This function finds the closest value in a sorted list to a given search value.
* Parameters:
* `lst` is the list to be searched.
* `item` is the value to be searched for.
* `current` stores the current best match.
* `control` controls the search behaviour of the function.
* `up` means find the closest value >= to `item`.
* `down` means find the closest value <= to `item`.
* `up(strict)` means find the closest value > to `item`.
* `down(strict)` means find the closest value < to "`tem`.
* `neutral` means find the closest value to `item`.
* Return:
* Returns the closest match in `lst`.
* None is returned if no value in the list satisfies the condition (e.g an empty list).
'''
def mins(lst, f = None):
mn = min(lst) if f is None else min(lst, key = f)
return (i for i in lst if i == mn)
def maxes(lst, f = None):
mx = max(lst) if key is None else max(lst, key = f)
return (i for i in lst if i == mx)
def xBinSearch(lst, item, control="neutral", current=None):
n = len(lst)
var = round(n/2)
if n > 1:
if control == "up":
if lst[var] == item:
return lst[var]
elif lst[var] > item: #The solution is in `lst[:var+1]`.
current = lst[var] if current == None or abs(current - item) > abs(lst[var] - item) else current #Update "current" to contain the current closest match.
return xBinSearch(lst[:var], item, control, current)
#Search the eligible space. If the solution is `lst[var]`, it is already stored in `current`.
else: #The solution is not in `lst[:var+1]`
return xBinSearch(lst[var+1:], item, control, current) if var + 1 < n else current
#Search the eligible space if it exists, else (if there is no where left to search), return the current best match.
elif control == "down":
if lst[var] == item:
return lst[var]
elif lst[var] < item: #The solution is not in `lst[:var]`.
current = lst[var] if current == None or abs(current - item) > abs(lst[var] - item) else current #Update "current" to contain the current closest match.
return xBinSearch(lst[var:], item, control, current) #Search the eligible space.
else: #The solution is not in lst[var:]
return xBinSearch(lst[:var], item, control, current) if var + 1 < n else current
#Search the eligible space if it exists, else (if there is no where left to search), return the current best match.
elif control == "up(strict)":
if lst[var] > item: #The solution is in `lst[:var+1]`.
current = lst[var] if current == None or abs(current - item) > abs(lst[var] - item) else current #Update "current" to contain the current closest match.
return xBinSearch(lst[:var], item, control, current)
#Search the eligible space. If the solution is `lst[var]`, it is already stored in `current`.
else: #The solution is not in `lst[:var+1]`
return xBinSearch(lst[var+1:], item, control, current) if var + 1 < n else current
#Search the eligible space if it exists, else (if there is no where left to search), return the current best match.
elif control == "down(strict)":
if lst[var] < item: #The solution is not in `lst[:var]`.
current = lst[var] if current == None or abs(current - item) > abs(lst[var] - item) else current #Update "current" to contain the current closest match.
return xBinSearch(lst[var:], item, control, current) #Search the eligible space.
else: #The solution is not in lst[var:]
return xBinSearch(lst[:var], item, control, current) if var + 1 < n else current #Search the eligible space if it exists, else (if there is no where left to search), return the current best match.
else:
check = [("b", lst[var], abs(lst[var]-item))] #`check[0]` => `var`.
if var-1 >= 0:
check.append(("a", lst[var-1], abs(lst[var-1]-item))) #`check[1]` => `var-1`.
if var+1 < n:
check.append(("c", lst[var+1], abs(lst[var+1]-item))) #`check[2]` => `var+1`.
mn = [x for x in mins(check, f = lambda x: x[2])] #The closest values to `item` from among the slice.
if "a" in mn and "c" not in mn: #The solution is not in `lst[var+1:]`
current = check[1][1] if current == None or abs(current - item) > check[1][2] else current
return xBinSearch(lst[:var+1], item, control, current)
elif "b" in mn and ("a" not in mn and "c" not in mn):
#The solution is neither in `lst[:var]` nor in `lst[:var+1]` so is therefore `lst[var]`.
return lst[var]
elif "c" in mn and "a" not in mn: #The solution is not in `lst[:var]`
current = check[2][1] if current == None or abs(current - item) > check[2][2] else current
return xBinSearch(lst[var+1:], item, control, current)
else: #The solution is in either lst[:var] or lst[var+1:]
current = check[0][1] if current == None or abs(current - item) > check[0][2] else current
return min([xBinSearch(lst[:var], item, control, current), xBinSearch(lst[var+1:], item, control, current)], key = lambda x: abs(x - item))
else:
if n == 1:
if control == "up":
if lst[0] >= item: #If it is an eligible solution.
current = lst[0] if current == None or abs(current - item) > abs(lst[0] - item) else current
#Modify `current` accordingly.
elif control == "down":
if lst[0] <= item: #If it is an eligible solution.
current = lst[0] if current == None or abs(current - item) > abs(lst[0] - item) else current
#Modify `current` accordingly.
if control == "up(strict)":
if lst[0] > item: #If it is an eligible solution.
current = lst[0] if current == None or abs(current - item) > abs(lst[0] - item) else current
#Modify `current` accordingly.
elif control == "down(strict)":
if lst[0] < item: #If it is an eligible solution.
current = lst[0] if current == None or abs(current - item) > abs(lst[0] - item) else current
#Modify `current` accordingly.
else:
current = lst[0] if current == None or abs(current - item) > abs(lst[0] - item) else current
#Modify `current` accordingly.
return current
python performance algorithm binary-search
asked 11 mins ago
Tobi AlafinTobi Alafin
21017
$endgroup$
I wrote a function to find the closest value in a list to a given search value. What prompted me to write it was as boilerplate for a prime number problem so I could find the closest prime to a given number.
My Code
'''
* This function finds the closest value in a sorted list to a given search value.
* Parameters:
* `lst` is the list to be searched.
* `item` is the value to be searched for.
* `current` stores the current best match.
* `control` controls the search behaviour of the function.
* `up` means find the closest value >= to `item`.
* `down` means find the closest value <= to `item`.
* `up(strict)` means find the closest value > to `item`.
* `down(strict)` means find the closest value < to "`tem`.
* `neutral` means find the closest value to `item`.
* Return:
* Returns the closest match in `lst`.
* None is returned if no value in the list satisfies the condition (e.g an empty list).
'''
def mins(lst, f = None):
mn = min(lst) if f is None else min(lst, key = f)
return (i for i in lst if i == mn)
def maxes(lst, f = None):
mx = max(lst) if key is None else max(lst, key = f)
return (i for i in lst if i == mx)
def xBinSearch(lst, item, control="neutral", current=None):
n = len(lst)
var = round(n/2)
if n > 1:
if control == "up":
if lst[var] == item:
return lst[var]
elif lst[var] > item: #The solution is in `lst[:var+1]`.
current = lst[var] if current == None or abs(current - item) > abs(lst[var] - item) else current #Update "current" to contain the current closest match.
return xBinSearch(lst[:var], item, control, current)
#Search the eligible space. If the solution is `lst[var]`, it is already stored in `current`.
else: #The solution is not in `lst[:var+1]`
return xBinSearch(lst[var+1:], item, control, current) if var + 1 < n else current
#Search the eligible space if it exists, else (if there is no where left to search), return the current best match.
elif control == "down":
if lst[var] == item:
return lst[var]
elif lst[var] < item: #The solution is not in `lst[:var]`.
current = lst[var] if current == None or abs(current - item) > abs(lst[var] - item) else current #Update "current" to contain the current closest match.
return xBinSearch(lst[var:], item, control, current) #Search the eligible space.
else: #The solution is not in lst[var:]
return xBinSearch(lst[:var], item, control, current) if var + 1 < n else current
#Search the eligible space if it exists, else (if there is no where left to search), return the current best match.
elif control == "up(strict)":
if lst[var] > item: #The solution is in `lst[:var+1]`.
current = lst[var] if current == None or abs(current - item) > abs(lst[var] - item) else current #Update "current" to contain the current closest match.
return xBinSearch(lst[:var], item, control, current)
#Search the eligible space. If the solution is `lst[var]`, it is already stored in `current`.
else: #The solution is not in `lst[:var+1]`
return xBinSearch(lst[var+1:], item, control, current) if var + 1 < n else current
#Search the eligible space if it exists, else (if there is no where left to search), return the current best match.
elif control == "down(strict)":
if lst[var] < item: #The solution is not in `lst[:var]`.
current = lst[var] if current == None or abs(current - item) > abs(lst[var] - item) else current #Update "current" to contain the current closest match.
return xBinSearch(lst[var:], item, control, current) #Search the eligible space.
else: #The solution is not in lst[var:]
return xBinSearch(lst[:var], item, control, current) if var + 1 < n else current #Search the eligible space if it exists, else (if there is no where left to search), return the current best match.
else:
check = [("b", lst[var], abs(lst[var]-item))] #`check[0]` => `var`.
if var-1 >= 0:
check.append(("a", lst[var-1], abs(lst[var-1]-item))) #`check[1]` => `var-1`.
if var+1 < n:
check.append(("c", lst[var+1], abs(lst[var+1]-item))) #`check[2]` => `var+1`.
mn = [x for x in mins(check, f = lambda x: x[2])] #The closest values to `item` from among the slice.
if "a" in mn and "c" not in mn: #The solution is not in `lst[var+1:]`
current = check[1][1] if current == None or abs(current - item) > check[1][2] else current
return xBinSearch(lst[:var+1], item, control, current)
elif "b" in mn and ("a" not in mn and "c" not in mn):
#The solution is neither in `lst[:var]` nor in `lst[:var+1]` so is therefore `lst[var]`.
return lst[var]
elif "c" in mn and "a" not in mn: #The solution is not in `lst[:var]`
current = check[2][1] if current == None or abs(current - item) > check[2][2] else current
return xBinSearch(lst[var+1:], item, control, current)
else: #The solution is in either lst[:var] or lst[var+1:]
current = check[0][1] if current == None or abs(current - item) > check[0][2] else current
return min([xBinSearch(lst[:var], item, control, current), xBinSearch(lst[var+1:], item, control, current)], key = lambda x: abs(x - item))
else:
if n == 1:
if control == "up":
if lst[0] >= item: #If it is an eligible solution.
current = lst[0] if current == None or abs(current - item) > abs(lst[0] - item) else current
#Modify `current` accordingly.
elif control == "down":
if lst[0] <= item: #If it is an eligible solution.
current = lst[0] if current == None or abs(current - item) > abs(lst[0] - item) else current
#Modify `current` accordingly.
if control == "up(strict)":
if lst[0] > item: #If it is an eligible solution.
current = lst[0] if current == None or abs(current - item) > abs(lst[0] - item) else current
#Modify `current` accordingly.
elif control == "down(strict)":
if lst[0] < item: #If it is an eligible solution.
current = lst[0] if current == None or abs(current - item) > abs(lst[0] - item) else current
#Modify `current` accordingly.
else:
current = lst[0] if current == None or abs(current - item) > abs(lst[0] - item) else current
#Modify `current` accordingly.
return current
python performance algorithm binary-search
python performance algorithm binary-search
asked 11 mins ago
Tobi AlafinTobi Alafin
21017
asked 11 mins ago
Tobi AlafinTobi Alafin
21017
asked 11 mins ago
Tobi AlafinTobi Alafin
21017
asked 11 mins ago
Tobi AlafinTobi Alafin
21017
asked 11 mins ago
Tobi AlafinTobi Alafin
21017
21017
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