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Merge branch 'develop' into documentation

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fjosw 2023-03-09 14:26:18 +00:00
commit dd14b35905
2 changed files with 17 additions and 15 deletions
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5
examples/08_combined_fit_example.ipynb
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@ -9,7 +9,10 @@
"source": [
"import pyerrors as pe\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt"
"import matplotlib.pyplot as plt\n",
"from packaging import version\n",
"if version.parse(pe.__version__) < version.parse(\"2.6.0\"):\n",
" raise Exception(f\"v2.6.0 or newer is required for this example, you are using {pe.__version__}\")"
]
},
{

27
pyerrors/fits.py
View file

@ -240,13 +240,7 @@ def least_squares(x, y, func, priors=None, silent=False, **kwargs):
loc_priors = []
for i_n, i_prior in enumerate(priors):
if isinstance(i_prior, Obs):
loc_priors.append(i_prior)
elif isinstance(i_prior, str):
loc_val, loc_dval = _extract_val_and_dval(i_prior)
loc_priors.append(cov_Obs(loc_val, loc_dval ** 2, '#prior' + str(i_n) + f"_{np.random.randint(2147483647):010d}"))
else:
raise TypeError("Prior entries need to be 'Obs' or 'str'.")
loc_priors.append(_construct_prior_obs(i_prior, i_n))
prior_mask = np.arange(len(priors))
output.priors = loc_priors
@ -260,13 +254,8 @@ def least_squares(x, y, func, priors=None, silent=False, **kwargs):
prior_mask.append(pos)
else:
raise TypeError("Prior position needs to be an integer.")
if isinstance(prior, Obs):
loc_priors.append(prior)
elif isinstance(prior, str):
loc_val, loc_dval = _extract_val_and_dval(prior)
loc_priors.append(cov_Obs(loc_val, loc_dval ** 2, '#prior' + str(pos) + f"_{np.random.randint(2147483647):010d}"))
else:
raise TypeError("Prior entries need to be 'Obs' or 'str'.")
loc_priors.append(_construct_prior_obs(prior, pos))
output.priors[pos] = loc_priors[-1]
if max(prior_mask) >= n_parms:
raise ValueError("Prior position out of range.")
@ -823,3 +812,13 @@ def _extract_val_and_dval(string):
else:
factor = 1
return float(split_string[0]), float(split_string[1][:-1]) * factor
def _construct_prior_obs(i_prior, i_n):
if isinstance(i_prior, Obs):
return i_prior
elif isinstance(i_prior, str):
loc_val, loc_dval = _extract_val_and_dval(i_prior)
return cov_Obs(loc_val, loc_dval ** 2, '#prior' + str(i_n) + f"_{np.random.randint(2147483647):010d}")
else:
raise TypeError("Prior entries need to be 'Obs' or 'str'.")