CODEWITHSUNDEEP
pythonr
jon
jon

Reputation: 11366

writing module in python compared to R

I am new to python, so far working more on R. I am trying to learn myself - excuse me if this too basic question. 

The following is R program / function that can output nice plot. 
     # funcomp does some calculations 
    funcomp <- function(x){
               z = x ^2 
               k= z + x 
               return(k)
               }
    #funplot apply funcomp internally and produce plot. 
    funplot <- function(x){
              y <- funcomp(x)
              plot(x,y)
              }

Applying the function: 

funplot(1:10)

I was trying do same in python.

# funcomp does some calculations 
def funcomp(x):
       z = x ** 2
       k= z + x
       return k       

def funplot(x):
    y = funcomp(x)
    import matplotlib.pyplot as plt
    plt.plot(x, y)

First I just put the above code in the python interpreter.
Applying the function, give me an error. 

funcomp(1:10) 
funplot(1:10)

I saved the code in the file trial.py and saved to working directory. And apply the function and got same error.

import trial
trial.funcomp(1:10)
trial.funplot(1:10)

What is problem here and how can I achieve this ?

Edit: I following suggestions below I tried, but does not work well:

trial.fumcomp(range(1,11))
AttributeError: 'module' object has no attribute 'fumcomp'

trial.funplot(range(1,11)) 
      2 def funcomp(x):
----> 3        z = x**2
      4        k= z + x
      5        return k

TypeError: unsupported operand type(s) for ^: 'list' and 'int'

Upvotes: 1

Views: 53

Answers (1)

Simon
Simon

Reputation: 10841

Instead of:

1:10

... use:

range(1,11)

Further, note that Python does not do vector calculations automatically so you have to explicitly ask Python to do that. I've used a list comprehension for that purpose in funcomp() (by the way, one problem is that you attempted to call fumcomp(), which doesn't exist in your code - hence the error message):

# funcomp does some calculations 
def funcomp(x):
       z = x ** 2
       k= z + x
       return k       

def funplot(x):
    y = [funcomp(xx) for xx in x]
    import matplotlib.pyplot as plt
    plt.plot(x, y)

Given these lines of code:

import trial
import matplotlib.pyplot as plt
trial.funplot(range(1,11))  
plt.show()

... the output is:

enter image description here

If you want Python to behave more like R, though, you would be best to use numpy, e.g. given the code in trial2.py:

# funcomp does some calculations 
def funcomp(x):
       z = x ** 2
       k= z + x
       return k       

def funplot(x):
    y = funcomp(x)
    import matplotlib.pyplot as plt
    plt.plot(x, y)

The following code gives the same graph as shown above:

import trial2
import numpy as np
import matplotlib.pyplot as plt
trial2.funplot(np.array(range(1,11)))
plt.show()

... because numpy arrays are computed as vectors, just as in R.

Upvotes: 1

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