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Okay, so I’m premed who likes to code, so I’m just gonna start now. I did a question yesterday on binary search and I will attempt to answer it again right now.
def binary_search(nums, target):
left = 0
right = len(nums) - 1
while(left < right):
mid = int((left+right)/2)
if( nums[mid] < target ):
left = mid + 1
elif( nums[mid] > target ):
right = mid - 1
elif( nums[mid] == target ):
return mid
else:
passSomething like that I think…. let me double check
So I got it wrong. I needed left <= right for it to include the arrays/lists are that exactly 1 in length.
Also, needed to return -1 for the wrong answer.
def binary_search(nums, target):
left = 0
right = len(nums) - 1
while(left <= right): # change here
mid = int((left+right)/2)
if( nums[mid] < target ):
left = mid + 1
elif( nums[mid] > target ):
right = mid - 1
elif( nums[mid] == target ):
return mid
else:
pass
return -1 # another change hereOkay, and today I worked on another question. It called the robbery house question, or largest sum of the nonadjacent values. I saw it on TikTok. Essentially, you have a list of numbers or an array of numbers and your goal is to determine the largest sum given any numbers that are not adjacent to each other, where all the numbers are greater than or equal to zero. There’s also some other restraints…
My answer is pseudocode was really not pseudocode here…
if( len(nums) == 0 ):
return None # I know it's possible to return 0 but I like to get an error
elif( len(nums) == 1 ):
return nums[1] # Here I definitely know to return the value
# if it's just length 1 list
elif( len(nums) == 2 ):
return max(nums[0],nums[1]) # just whatever max
else:
pass # not actually sure what to do here
path1 = nums[0]
path2 = nums[1]
sum1 = generate_path(path1)
sum2 = generate_path(path2)
def generate_path(nums, i):
# input list and index
# iterates through the list to find maximum possible value
# returns sum
return max(path1,path2)and it failed… :(
So I looked up the solution and found out how this is wrong… What it looks like people do is use dynamic programming to contain the largest value as it iterates down the array. What I put, though, is pretty similar I think.
My attempt to recall the solution from memory:
def find_sum(hvals, n): # hvals is the list and n is the length of hvals
if( n == 0 ):
return 0
if( n == 1 ):
return hvals[0]
if( n == 2 ):
return max(hvals[0],hvals[1])
df = [0]*n # create list with same number of zeroes
for i in range(2,n-3): # start from 3rd value
df[i] = max(df[i]+hval[i+2],df[i]+hval[i+3])
#shooooooooooooooot i dont remember...oh shit… we had to go back in the list, not forwards…
def find_sum(hvals, n): # hvals is the list and n is the length of hvals
if( n == 0 ):
return 0
if( n == 1 ):
return hvals[0]
if( n == 2 ):
return max(hvals[0],hvals[1])
df = [0]*n # create list with same number of zeroes
df[0] = hval[0]
df[1] = max(hval[0],hval[1])
for i in range(2,n): # start from 3rd value
df[i] = max(hval[i] + df[i-2], hval[i] + df[i-3])
# oh shit yeah this makes sense, because now hval at i
# will always be within the limits of the array
# I don't have to worry about limits if df's index
# is the one that changes
return df[-1] # which means return the last valueGot it… :)
i def did not skip a day Question 1: First Bad Version Today I got to solve a problem called first bad version. What you essentially do is try to find which is the bad version given that a function tells you whether or not it is a bad version. All versions after a bad version become bad. For example FFTTTTTTT, The index at 2 or the 3rd item is...
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The first step…trying to get scanpy… pip install scanpy This basically failed… I needed python tables and thank the lord for this I can finally start…haha I lied c:\users\melton\appdata\local\programs\python\python39\lib\site-packages\tables\__init__.py in <module> 12 13 # Necessary imports to get versions stored on the cython extension ---> 14 from .utilsextension import ( 15 get_pytables_version, get_hdf5_version, blosc_compressor_list, 16 blosc_compcode_to_compname_ as blosc_compcode_to_compname, tables\utilsextension.pyx in init tables.utilsextension() __init__.pxd in numpy.import_array() ImportError: numpy.core.multiarray failed to import...
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