numpy.random.uniform has incorrect default arguments

[MatheusCPatrocinio]

I've been learning how to use Numba and I was trying to make an approximation to pi using Monte Carlo method, as it follows:

#Compute an aproximation to pi using Monte Carlo:
import numpy as np
from numba import njit,jit,float64


@njit
#Area of a circle: A = pi*radius**2 => pi= A/(radius**2)
#Let's consider a quadrant [0,1]x[0,1]
#And our circle has radius=1
#Thus the Area of the circle that is present in the quadrant will be A/4

def find_pi(n:float64,radius=1.0):
  x,y = np.random.uniform(high=radius,size=n),np.random.uniform(high=radius,size=n) #here we are generating uniformly random points in the quadrant with x and y coordinates
  h = np.sqrt(x**2+y**2) #we need to find the distance between to origin of the quadrant and the point, i.e., the hypotenuse
  #now, every point that has hypotenuse smaller or equal than the radius 1 is part of the 1/4 of area of the circle
  #we are going to divide the number of points inside the radius over the total of points generated in the quadrant
  points_inside = np.where(h<=radius,1,0)
  fourth_area = points_inside.sum()/n #now I compute the aproximation of 1/4 of the circle's area
  pi = (fourth_area*4)/(radius**2)
  return pi

And I get this error message:

---------------------------------------------------------------------------
TypingError                               Traceback (most recent call last)
[<ipython-input-15-33f07fb29275>](https://localhost:8080/#) in <cell line: 1>()
----> 1 find_pi(10_000_000.0)

1 frames
[/usr/local/lib/python3.10/dist-packages/numba/core/dispatcher.py](https://localhost:8080/#) in _compile_for_args(self, *args, **kws)
    466                 e.patch_message(msg)
    467 
--> 468             error_rewrite(e, 'typing')
    469         except errors.UnsupportedError as e:
    470             # Something unsupported is present in the user code, add help info

[/usr/local/lib/python3.10/dist-packages/numba/core/dispatcher.py](https://localhost:8080/#) in error_rewrite(e, issue_type)
    407                 raise e
    408             else:
--> 409                 raise e.with_traceback(None)
    410 
    411         argtypes = []

TypingError: Failed in nopython mode pipeline (step: nopython frontend)
No implementation of function Function(<built-in method uniform of numpy.random.mtrand.RandomState object at 0x7e9d9658b840>) found for signature:
 
 >>> uniform(high=float64, size=float64)
 
There are 4 candidate implementations:
      - Of which 4 did not match due to:
      Overload in function '_OverloadWrapper._build.<locals>.ol_generated': File: numba/core/overload_glue.py: Line 129.
        With argument(s): '(high=float64, size=float64)':
       Rejected as the implementation raised a specific error:
         TypingError: missing a required argument: 'a'
  raised from /usr/local/lib/python3.10/dist-packages/numba/core/typing/templates.py:412

During: resolving callee type: Function(<built-in method uniform of numpy.random.mtrand.RandomState object at 0x7e9d9658b840>)
During: typing of call at <ipython-input-13-ec36feddfd93> (14)


File "<ipython-input-13-ec36feddfd93>", line 14:
def find_pi(n:float64,radius=1.0):
  x,y = np.random.uniform(high=radius,size=n),np.random.uniform(high=radius,size=n) #here we are generating uniformly random points in the quadrant with x and y coordinates
  ^

Could someone help me? I've tried to set all the variables to float64 type, but haven't been successfull.

-->

• [x ] I have tried using the latest released version of Numba (most recent is
  visible in the change log (https://github.com/numba/numba/blob/main/CHANGE_LOG).
• [ x] I have included a self contained code sample to reproduce the problem.
  i.e. it's possible to run as 'python bug.py'.

[sklam]

The problem:

 Rejected as the implementation raised a specific error:
         TypingError: missing a required argument: 'a'

is caused by a resolved issue #8161 that the argument names in Numba's implementation does not match NumPy's.

However, once you use 0.58.0rc1 or the latest main (bd7ebcf), the error becomes:

   Rejected as the implementation raised a specific error:
     TypingError: missing a required argument: 'low'

There's another issue that the default argument is not matching NumPy's.

For now, you can workaround this by defining low as well; For example

x,y = np.random.uniform(low=0.0, high=radius,size=n),np.random.uniform(low=0.0, high=radius,size=n)

[sklam]

(renamed issue to provide more detail of the problem)