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first version of new bookeeping system

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Fabian Joswig 2021-11-01 17:14:30 +00:00
parent b86dda2394
commit e4d7d56180
4 changed files with 38 additions and 54 deletions
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pyerrors/pyerrors.py
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@ -24,9 +24,6 @@ class Obs:
Attributes
----------
e_tag_global : int
Integer which determines which part of the name belongs
to the ensemble and which to the replicum.
S_global : float
Standard value for S (default 2.0)
S_dict : dict
@ -41,12 +38,11 @@ class Obs:
Standard value for N_sigma (default 1.0)
"""
__slots__ = ['names', 'shape', 'r_values', 'deltas', 'N', '_value', '_dvalue',
'ddvalue', 'reweighted', 'S', 'tau_exp', 'N_sigma', 'e_names',
'e_content', 'e_dvalue', 'e_ddvalue', 'e_tauint', 'e_dtauint',
'ddvalue', 'reweighted', 'S', 'tau_exp', 'N_sigma',
'e_dvalue', 'e_ddvalue', 'e_tauint', 'e_dtauint',
'e_windowsize', 'e_rho', 'e_drho', 'e_n_tauint', 'e_n_dtauint',
'idl', 'is_merged', 'tag', '__dict__']
e_tag_global = 0
S_global = 2.0
S_dict = {}
tau_exp_global = 0.0
@ -141,6 +137,19 @@ class Obs:
def dvalue(self):
return self._dvalue
@property
def e_names(self):
return sorted(set([o.split('|')[0] for o in self.names]))
@property
def e_content(self):
res = {}
for e, e_name in enumerate(self.e_names):
res[e_name] = sorted(filter(lambda x: x.startswith(e_name + '|'), self.names))
if e_name in self.names:
res[e_name].append(e_name)
return res
def expand_deltas(self, deltas, idx, shape):
"""Expand deltas defined on idx to a regular, contiguous range, where holes are filled by 0.
If idx is of type range, the deltas are not changed
@ -202,23 +211,12 @@ class Obs:
N_sigma : float
number of standard deviations from zero until the tail is
attached to the autocorrelation function (default 1)
e_tag : int
number of characters which label the ensemble. The remaining
ones label replica (default 0)
fft : bool
determines whether the fft algorithm is used for the computation
of the autocorrelation function (default True)
"""
if 'e_tag' in kwargs:
e_tag_local = kwargs.get('e_tag')
if not isinstance(e_tag_local, int):
raise TypeError('Error: e_tag is not integer')
else:
e_tag_local = Obs.e_tag_global
self.e_names = sorted(set([o[:e_tag_local] for o in self.names]))
self.e_content = {}
e_content = self.e_content
self.e_dvalue = {}
self.e_ddvalue = {}
self.e_tauint = {}
@ -295,36 +293,26 @@ class Obs:
else:
self.N_sigma = Obs.N_sigma_global
if max([len(x) for x in self.names]) <= e_tag_local:
for e, e_name in enumerate(self.e_names):
self.e_content[e_name] = [e_name]
else:
for e, e_name in enumerate(self.e_names):
if len(e_name) < e_tag_local:
self.e_content[e_name] = [e_name]
else:
self.e_content[e_name] = sorted(filter(lambda x: x.startswith(e_name), self.names))
for e, e_name in enumerate(self.e_names):
r_length = []
for r_name in self.e_content[e_name]:
for r_name in e_content[e_name]:
if self.idl[r_name] is range:
r_length.append(len(self.idl[r_name]))
else:
r_length.append((self.idl[r_name][-1] - self.idl[r_name][0] + 1))
e_N = np.sum([self.shape[r_name] for r_name in self.e_content[e_name]])
e_N = np.sum([self.shape[r_name] for r_name in e_content[e_name]])
w_max = max(r_length) // 2
e_gamma[e_name] = np.zeros(w_max)
self.e_rho[e_name] = np.zeros(w_max)
self.e_drho[e_name] = np.zeros(w_max)
for r_name in self.e_content[e_name]:
for r_name in e_content[e_name]:
e_gamma[e_name] += self.calc_gamma(self.deltas[r_name], self.idl[r_name], self.shape[r_name], w_max, fft)
gamma_div = np.zeros(w_max)
for r_name in self.e_content[e_name]:
for r_name in e_content[e_name]:
gamma_div += self.calc_gamma(np.ones((self.shape[r_name])), self.idl[r_name], self.shape[r_name], w_max, fft)
e_gamma[e_name] /= gamma_div[:w_max]
@ -384,11 +372,11 @@ class Obs:
self.ddvalue += (self.e_dvalue[e_name] * self.e_ddvalue[e_name]) ** 2
self._dvalue = np.sqrt(self.dvalue)
if self.dvalue == 0.0:
if self._dvalue == 0.0:
self.ddvalue = 0.0
else:
self.ddvalue = np.sqrt(self.ddvalue) / self.dvalue
return 0
return
def print(self, level=1):
"""Print basic properties of the Obs."""
@ -400,7 +388,7 @@ class Obs:
else:
percentage = np.abs(self.dvalue / self.value) * 100
print('Result\t %3.8e +/- %3.8e +/- %3.8e (%3.3f%%)' % (self.value, self.dvalue, self.ddvalue, percentage))
if hasattr(self, 'e_names'):
if hasattr(self, 'e_dvalue'):
if len(self.e_names) > 1:
print(' Ensemble errors:')
for e_name in self.e_names: