Disable warnings originating from scipy

Question

As I integrate a function at different parameter values, I often encounter errors like:

 lsoda--  warning..internal t (=r1) and h (=r2) are
   such that in the machine, t + h = t on the next step  
   (h = step size). solver will continue anyway

While I understand the technical aspects of the error, I am at a loss as to how I might suppress it from being printed to stdout. I've looked into numpy.seterr(), but as this error message appears to be generated from the underlying C/Fortran code it has no effect. And while python script.py > /dev/null is effective, it obviously also hides other, helpful information that might be printed.

Is there some way of disabling these lsoda warnings and errors, or otherwise preventing them from being printed to stdout?

score 6 · Accepted Answer · edited May 23 '17 at 12:09

Using J.F. Sebastian's stdout_redirected, you could redirect stdout at the file descriptor level to os.devnull.

with stdout_redirected():
    soln2 = integrate.odeint(f, y2, t2, mxstep = 5000)

Outside of the with-statement, stdout still gets printed. Inside the with-suite, stdout is suppressed.

For example, here is Caeiro's odeint example whose lsoda warnings are suppressed with stdout_redirected.

import os
import sys
import contextlib
import numpy as np
import scipy.integrate as integrate
from numpy import pi

def fileno(file_or_fd):
    fd = getattr(file_or_fd, 'fileno', lambda: file_or_fd)()
    if not isinstance(fd, int):
        raise ValueError("Expected a file (`.fileno()`) or a file descriptor")
    return fd

@contextlib.contextmanager
def stdout_redirected(to=os.devnull, stdout=None):
    """
    https://stackoverflow.com/a/22434262/190597 (J.F. Sebastian)
    """
    if stdout is None:
       stdout = sys.stdout

    stdout_fd = fileno(stdout)
    # copy stdout_fd before it is overwritten
    #NOTE: `copied` is inheritable on Windows when duplicating a standard stream
    with os.fdopen(os.dup(stdout_fd), 'wb') as copied: 
        stdout.flush()  # flush library buffers that dup2 knows nothing about
        try:
            os.dup2(fileno(to), stdout_fd)  # $ exec >&to
        except ValueError:  # filename
            with open(to, 'wb') as to_file:
                os.dup2(to_file.fileno(), stdout_fd)  # $ exec > to
        try:
            yield stdout # allow code to be run with the redirected stdout
        finally:
            # restore stdout to its previous value
            #NOTE: dup2 makes stdout_fd inheritable unconditionally
            stdout.flush()
            os.dup2(copied.fileno(), stdout_fd)  # $ exec >&copied


#Constants and parameters
alpha=1/137.
k=1.e-9     
T=40.    
V= 6.e-6
r = 6.9673e12
u = 1.51856e7

#defining dy/dt's
def f(y, t):
       A, B, C, D, E = y
       # the model equations
       f0 = 1.519e21*(-2*k/T*(k - (alpha/pi)*(B+V))*A) 
       f1 = ((3*B**2 + 3*C**2 + 6*B*C + 2*pi**2*B*T + pi**2*T**2)**-1
             *(-f0*alpha/(3*pi**3) - 2*r*(B**3 + 3*B*C**2 + pi**2*T**2*B) 
               - u*(D**3 - E**3)))
       f2 = u*(D**3 - E**3)/(3*C**2)
       f3 = -u*(D**3 - E**3)/(3*D**2)
       f4 = u*(D**3 - E**3)/(3*E**2) + r*(B**3 + 3*B*C**2 + pi**2*T**2*B)/(3*E**2)
       return [f0, f1, f2, f3, f4]


t  = np.linspace(1e-15, 1e-10, 1000000)   # time grid
y2 = [2e13, 0, 50, 50, 25]
t2  = np.linspace(1.e-10, 1.e-5, 1000000)  

with stdout_redirected():
    soln2 = integrate.odeint(f, y2, t2, mxstep = 5000)

The warnings which lsoda writes to stdout are suppressed.

Disable warnings originating from scipy

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