lattice/pyerrors
1
0
Fork 0
mirror of https://github.com/fjosw/pyerrors.git synced 2025-06-30 16:59:27 +02:00
Code Issues Projects Releases Packages Wiki Activity

[Feat] Add type hints to pyerrors modules

Browse source
This commit is contained in:
Fabian Joswig 2024-12-25 11:09:58 +01:00
parent 997d360db3
commit 3db8eb2989
11 changed files with 236 additions and 207 deletions
Download patch file Download diff file Expand all files Collapse all files

13
pyerrors/misc.py
View file

@ -1,3 +1,4 @@
from __future__ import annotations
import platform
import numpy as np
import scipy
@ -7,6 +8,8 @@ import pandas as pd
import pickle
from .obs import Obs
from .version import __version__
from numpy import float64, int64, ndarray
from typing import List, Type, Union
def print_config():
@ -54,7 +57,7 @@ def errorbar(x, y, axes=plt, **kwargs):
axes.errorbar(val["x"], val["y"], xerr=err["x"], yerr=err["y"], **kwargs)
def dump_object(obj, name, **kwargs):
def dump_object(obj: Corr, name: str, **kwargs):
"""Dump object into pickle file.
Parameters
@ -78,7 +81,7 @@ def dump_object(obj, name, **kwargs):
pickle.dump(obj, fb)
def load_object(path):
def load_object(path: str) -> Union[Obs, Corr]:
"""Load object from pickle file.
Parameters
@ -95,7 +98,7 @@ def load_object(path):
return pickle.load(file)
def pseudo_Obs(value, dvalue, name, samples=1000):
def pseudo_Obs(value: Union[float, int64, float64, int], dvalue: Union[float, float64, int], name: str, samples: int=1000) -> Obs:
"""Generate an Obs object with given value, dvalue and name for test purposes
Parameters
@ -132,7 +135,7 @@ def pseudo_Obs(value, dvalue, name, samples=1000):
return res
def gen_correlated_data(means, cov, name, tau=0.5, samples=1000):
def gen_correlated_data(means: Union[ndarray, List[float]], cov: ndarray, name: str, tau: Union[float, ndarray]=0.5, samples: int=1000) -> List[Obs]:
""" Generate observables with given covariance and autocorrelation times.
Parameters
@ -174,7 +177,7 @@ def gen_correlated_data(means, cov, name, tau=0.5, samples=1000):
return [Obs([dat], [name]) for dat in corr_data.T]
def _assert_equal_properties(ol, otype=Obs):
def _assert_equal_properties(ol: Union[List[Obs], List[CObs], ndarray], otype: Type[Obs]=Obs):
otype = type(ol[0])
for o in ol[1:]:
if not isinstance(o, otype):