pyerrors.py renamed to obs.py, h5py added as dependency

pyerrors/__init__.py

@@ -1,4 +1,4 @@
-from .pyerrors import *
+from .obs import *
 from .correlators import *
 from .fits import *
 from . import dirac

pyerrors/correlators.py

@@ -3,7 +3,7 @@ import numpy as np
 import autograd.numpy as anp
 import matplotlib.pyplot as plt
 import scipy.linalg
-from .pyerrors import Obs, dump_object, reweight, correlate
+from .obs import Obs, dump_object, reweight, correlate
 from .fits import least_squares
 from .linalg import eigh, inv, cholesky
 from .roots import find_root

pyerrors/fits.py

@@ -11,7 +11,7 @@ from scipy.odr import ODR, Model, RealData
 import iminuit
 from autograd import jacobian
 from autograd import elementwise_grad as egrad
-from .pyerrors import Obs, derived_observable, covariance, pseudo_Obs
+from .obs import Obs, derived_observable, covariance, pseudo_Obs
 
 
 class Fit_result(Sequence):

pyerrors/input/bdio.py

@@ -4,7 +4,7 @@
 import ctypes
 import hashlib
 import autograd.numpy as np  # Thinly-wrapped numpy
-from ..pyerrors import Obs
+from ..obs import Obs
 
 
 def read_ADerrors(file_path, bdio_path='./libbdio.so', **kwargs):

pyerrors/input/hadrons.py

@@ -4,7 +4,7 @@
 import os
 import h5py
 import numpy as np
-from ..pyerrors import Obs, CObs
+from ..obs import Obs, CObs
 from ..correlators import Corr
 from ..npr import Npr_matrix
 

pyerrors/input/misc.py

@@ -6,7 +6,7 @@ import fnmatch
 import re
 import struct
 import numpy as np  # Thinly-wrapped numpy
-from ..pyerrors import Obs
+from ..obs import Obs
 
 
 def read_pbp(path, prefix, **kwargs):

pyerrors/input/openQCD.py

@@ -6,7 +6,7 @@ import fnmatch
 import re
 import struct
 import numpy as np  # Thinly-wrapped numpy
-from ..pyerrors import Obs
+from ..obs import Obs
 from ..fits import fit_lin
 
 

pyerrors/input/sfcf.py

@@ -5,7 +5,7 @@ import os
 import fnmatch
 import re
 import numpy as np  # Thinly-wrapped numpy
-from ..pyerrors import Obs
+from ..obs import Obs
 
 
 def read_sfcf(path, prefix, name, **kwargs):

pyerrors/linalg.py

@@ -4,7 +4,7 @@
 import numpy as np
 from autograd import jacobian
 import autograd.numpy as anp  # Thinly-wrapped numpy
-from .pyerrors import derived_observable, CObs, Obs
+from .obs import derived_observable, CObs, Obs
 
 from functools import partial
 from autograd.extend import defvjp

pyerrors/misc.py

@@ -2,7 +2,7 @@
 # coding: utf-8
 
 import numpy as np
-from .pyerrors import Obs
+from .obs import Obs
 
 
 def gen_correlated_data(means, cov, name, tau=0.5, samples=1000):

pyerrors/mpm.py

@@ -3,7 +3,7 @@
 
 import numpy as np
 import scipy.linalg
-from .pyerrors import Obs
+from .obs import Obs
 from .linalg import svd, eig, pinv
 
 
@@ -105,8 +105,6 @@ def matrix_pencil_method_old(data, p, noise_level=None, verbose=1, **kwargs):
     # Moore–Penrose pseudoinverse
     pinv_y1 = pinv(y1)
 
-    # Note: Automatic differentiation of eig is implemented in the git of autograd
-    # but not yet released to PyPi (1.3). The code is currently part of pyerrors
     e = eig((pinv_y1 @ y2), **kwargs)
     energy_levels = -np.log(np.abs(e))
     return sorted(energy_levels, key=lambda x: abs(x.value))

pyerrors/roots.py

@@ -3,7 +3,7 @@
 
 import scipy.optimize
 from autograd import jacobian
-from .pyerrors import derived_observable, pseudo_Obs
+from .obs import derived_observable, pseudo_Obs
 
 
 def find_root(d, func, guess=1.0, **kwargs):

setup.py

@@ -9,5 +9,5 @@ setup(name='pyerrors',
       author_email='fabian.joswig@ed.ac.uk',
       packages=find_packages(),
       python_requires='>=3.6.0',
-      install_requires=['numpy>=1.16', 'autograd>=1.2', 'numdifftools', 'matplotlib>=3.3', 'scipy', 'iminuit<2']
+      install_requires=['numpy>=1.16', 'autograd>=1.2', 'numdifftools', 'matplotlib>=3.3', 'scipy', 'iminuit<2', 'h5py']
      )