Avoid using multiple if statements

Question

I am trying to create an if statement to check a condition for each iteration

          for in range(100):
            B10 = np.random.randint(0, precip.shape[0])
            T10 = np.random.randint(0, precip.shape[0] )

            if np.abs(B10-T10) <=30:
                T10 = np.random.randint(0, precip.shape[0])

I want to create an if condition that will get new values of T10 until the condition above is met for every iteration. How can I do this?

@h4z3 something of sort, just not sure how to use it in my code — user11036847
– user11036847, Commented Sep 25, 2019 at 14:59

lmiguelvargasf · Accepted Answer · 2019-09-25 14:59:58Z

3

Use a while loop instead of a for loop:

B10 = np.random.randint(0, precip.shape[0])
T10 = np.random.randint(0, precip.shape[0])
while np.abs(B10-T10) <= 30:
    B10 = np.random.randint(0, precip.shape[0])
    T10 = np.random.randint(0, precip.shape[0])

or you can avoid redeclaring variables using the following:

while True:
    B10 = np.random.randint(0, precip.shape[0])
    T10 = np.random.randint(0, precip.shape[0])
    if not (np.abs(B10-T10) <=30):
        break

In general, it is a good practice to use a for loop when you know the number of iterations of your loop or when you are using collections. However, when you don't know it, i.e., when it depends on a condition, you should use a while loop.

answered Sep 25, 2019 at 14:59

lmiguelvargasf

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Comments

David Nehme · Accepted Answer · 2019-09-25 15:04:12Z

1

Avoid the loop and the if statement by generating the random numbers your want. In your code, T10 will be a random value between max(0, B10 - 30) and min(UB, B10 + 10), inclusive.

max_delta = 30
B10 = np.random.randint(0, UB)
T10 = np.random.randint(max(0, B10 - max_delta), min(UB, B10 + max_delta  + 1))

where UB = precip.shape[0].

answered Sep 25, 2019 at 15:04

David Nehme

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zipa · Accepted Answer · 2019-09-25 15:04:44Z

1

If I get you right, this should do it:

df['B10'] = np.random.randint(0, df.shape[0], df.shape[0])
df['T10'] = df['B10'].apply(lambda x: np.random.randint(0, x+1))

answered Sep 25, 2019 at 15:04

zipa

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Md Rehan · Accepted Answer · 2019-09-25 15:12:14Z

1

T10 = np.random.randint(0, precip.shape[0])
while True:
    B10 = np.random.randint(0, precip.shape[0])
    T10 = np.random.randint(0, precip.shape[0])
    if not (np.abs(B10-T10) <=30):
        break

answered Sep 25, 2019 at 15:12

Md Rehan

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