CODEWITHSUNDEEP
arrayspython-3.xnumpyfor-loopindexing
georgehere
georgehere

Reputation: 630

Indexing and doing mathematical calculation with Numpy Arrays Python

The code below calculates the Compounding values starting from 100 and the percentage gains gains. I want to write a code that goes start off with the entirety of the gains array [20,3,4,55,6.5] resulting in 212.19 at the end and then takes off the first index and recalculates the compounding value [3,4,55,6.5] resulting in 176.82., It would do this until the end of the gains array [6.5]. how would I be able to implement this to the code below and get the expected output?

import numpy as np 
Amount = 100

def moneyrisk(array):
    for counter,iterator in enumerate(array):
        Compounding = Amount * np.cumprod(array / 100 + 1)
    return Compounding

gains= np.array([20,3,4,55,6.5])
print(moneyrisk(gains))

Expected output:

[212.194008, 176.82834, 171.678, 165.075, 106.5]

Upvotes: 0

Views: 142

Answers (1)

Ivan
Ivan

Reputation: 40638

You could repeat the array to make a squared matrix, then remove the lower triangle, apply your function on each row. And, finally extract the last column:

Your moneyrisk function is given by:

>>> f = lambda x: 100*np.cumprod(x/100 + 1, 1) # notice the axis=1 option

Repeat rows:

>>> rep = gains[None].repeat(len(gains), 0)
array([[20. ,  3. ,  4. , 55. ,  6.5],
       [20. ,  3. ,  4. , 55. ,  6.5],
       [20. ,  3. ,  4. , 55. ,  6.5],
       [20. ,  3. ,  4. , 55. ,  6.5],
       [20. ,  3. ,  4. , 55. ,  6.5]])

Use np.triu to remove the lower triangle:

>>> rep_t = np.triu(rep, k=0)
array([[20. ,  3. ,  4. , 55. ,  6.5],
       [ 0. ,  3. ,  4. , 55. ,  6.5],
       [ 0. ,  0. ,  4. , 55. ,  6.5],
       [ 0. ,  0. ,  0. , 55. ,  6.5],
       [ 0. ,  0. ,  0. ,  0. ,  6.5]])

Apply f and select the last column:

>>> f(rep_t)
array([[120.      , 123.6     , 128.544   , 199.2432  , 212.194008],
       [100.      , 103.      , 107.12    , 166.036   , 176.82834 ],
       [100.      , 100.      , 104.      , 161.2     , 171.678   ],
       [100.      , 100.      , 100.      , 155.      , 165.075   ],
       [100.      , 100.      , 100.      , 100.      , 106.5     ]])

>>> f(rep_t)[:, -1]
array([212.194008, 176.82834 , 171.678   , 165.075   , 106.5     ])

Upvotes: 1

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