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Alternative way to initialize Obs to speed up error propagation

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This commit is contained in:
Fabian Joswig 2021-10-21 15:51:17 +01:00
parent 8ed1dac057
commit 369ee0a324
1 changed files with 18 additions and 7 deletions
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25
pyerrors/pyerrors.py
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@ -47,7 +47,7 @@ class Obs:
tau_exp_dict = {} tau_exp_dict = {}
N_sigma_global = 1.0 N_sigma_global = 1.0
def __init__(self, samples, names): def __init__(self, samples, names, **kwargs):
if len(samples) != len(names): if len(samples) != len(names):
raise Exception('Length of samples and names incompatible.') raise Exception('Length of samples and names incompatible.')
@ -62,10 +62,19 @@ class Obs:
self.shape = {} self.shape = {}
self.r_values = {} self.r_values = {}
self.deltas = {} self.deltas = {}
for name, sample in sorted(zip(names, samples)):
self.shape[name] = np.size(sample) if 'means' in kwargs:
self.r_values[name] = np.mean(sample) if len(samples) != len(kwargs.get('means')):
self.deltas[name] = sample - self.r_values[name] raise Exception('Length of samples and means incompatible.')
for name, sample, mean in sorted(zip(names, samples, kwargs.get('means'))):
self.shape[name] = np.size(sample)
self.r_values[name] = mean
self.deltas[name] = sample
else:
for name, sample in sorted(zip(names, samples)):
self.shape[name] = np.size(sample)
self.r_values[name] = np.mean(sample)
self.deltas[name] = sample - self.r_values[name]
self.N = sum(map(np.size, list(self.deltas.values()))) self.N = sum(map(np.size, list(self.deltas.values())))
@ -852,10 +861,12 @@ def derived_observable(func, data, **kwargs):
new_deltas[name] = new_deltas.get(name, 0) + deriv[i_val + j_obs] * obs.deltas[name] new_deltas[name] = new_deltas.get(name, 0) + deriv[i_val + j_obs] * obs.deltas[name]
new_samples = [] new_samples = []
new_means = []
for name in new_names: for name in new_names:
new_samples.append(new_deltas[name] + new_r_values[name][i_val]) new_samples.append(new_deltas[name])
new_means.append(new_r_values[name][i_val])
final_result[i_val] = Obs(new_samples, new_names) final_result[i_val] = Obs(new_samples, new_names, means=new_means)
final_result[i_val].value = new_val final_result[i_val].value = new_val
if multi == 0: if multi == 0: