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Warning messages promoted to RuntimeWarnings

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This commit is contained in:
Fabian Joswig 2021-10-15 12:11:06 +01:00
parent 8488df00fd
commit 4ca6f8ea49
3 changed files with 9 additions and 8 deletions
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5
pyerrors/correlators.py
View file

@ -1,3 +1,4 @@
import warnings
import numpy as np
import autograd.numpy as anp
import matplotlib.pyplot as plt
@ -130,7 +131,7 @@ class Corr:
raise Exception("Can not symmetrize odd T")
if np.argmax(np.abs(self.content)) != 0:
print('Warning: correlator does not seem to be symmetric around x0=0.')
warnings.warn("Correlator does not seem to be symmetric around x0=0.", RuntimeWarning)
newcontent = [self.content[0]]
for t in range(1, self.T):
@ -148,7 +149,7 @@ class Corr:
raise Exception("Can not symmetrize odd T")
if not all([o.zero_within_error() for o in self.content[0]]):
print('Warning: correlator does not seem to be anti-symmetric around x0=0.')
warnings.warn("Correlator does not seem to be anti-symmetric around x0=0.", RuntimeWarning)
newcontent = [self.content[0]]
for t in range(1, self.T):

7
pyerrors/fits.py
View file

@ -1,6 +1,7 @@
#!/usr/bin/env python
# coding: utf-8
import warnings
import numpy as np
import autograd.numpy as anp
import scipy.optimize
@ -300,7 +301,7 @@ def odr_fit(x, y, func, silent=False, **kwargs):
P_phi = A @ np.linalg.inv(A.T @ A) @ A.T
expected_chisquare = np.trace((np.identity(P_phi.shape[0]) - P_phi) @ W @ cov @ W)
if expected_chisquare <= 0.0:
print('Warning, negative expected_chisquare.')
warnings.warn("Negative expected_chisquare.", RuntimeWarning)
expected_chisquare = np.abs(expected_chisquare)
result_dict['chisquare/expected_chisquare'] = odr_chisquare(np.concatenate((output.beta, output.xplus.ravel()))) / expected_chisquare
if not silent:
@ -611,9 +612,7 @@ def error_band(x, func, beta):
"""Returns the error band for an array of sample values x, for given fit function func with optimized parameters beta."""
cov = covariance_matrix(beta)
if np.any(np.abs(cov - cov.T) > 1000 * np.finfo(np.float64).eps):
print('Warning, Covariance matrix is not symmetric within floating point precision')
print('cov - cov.T:')
print(cov - cov.T)
warnings.warn("Covariance matrix is not symmetric within floating point precision", RuntimeWarning)
deriv = []
for i, item in enumerate(x):

5
pyerrors/pyerrors.py
View file

@ -1,6 +1,7 @@
#!/usr/bin/env python
# coding: utf-8
import warnings
import pickle
import numpy as np
import autograd.numpy as anp # Thinly-wrapped numpy
@ -784,9 +785,9 @@ def correlate(obs_a, obs_b):
raise Exception('Shapes of ensemble', name, 'do not fit')
if obs_a.reweighted == 1:
print('Warning: The first observable is already reweighted.')
warnings.warn("The first observable is already reweighted.", RuntimeWarning)
if obs_b.reweighted == 1:
print('Warning: The second observable is already reweighted.')
warnings.warn("The second observable is already reweighted.", RuntimeWarning)
new_samples = []
for name in sorted(obs_a.names):