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feat!: Implemented improved first and second derivatives for the
corresponding methods of the Corr class. The parameter which distinguishes between the variant is now a string instead of a bool which may break current analyses.
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fbb98e05f6
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2 changed files with 75 additions and 30 deletions
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@ -460,25 +460,16 @@ class Corr:
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return (self + T_partner) / 2
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def deriv(self, symmetric=True):
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def deriv(self, variant="symmetric"):
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"""Return the first derivative of the correlator with respect to x0.
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Parameters
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----------
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symmetric : bool
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decides whether symmetric of simple finite differences are used. Default: True
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variant : str
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decides which definition of the finite differences derivative is used.
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Available choice: symmetric, forward, improved, default: symmetric
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"""
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if not symmetric:
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newcontent = []
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for t in range(self.T - 1):
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if (self.content[t] is None) or (self.content[t + 1] is None):
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newcontent.append(None)
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else:
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newcontent.append(self.content[t + 1] - self.content[t])
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if(all([x is None for x in newcontent])):
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raise Exception("Derivative is undefined at all timeslices")
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return Corr(newcontent, padding=[0, 1])
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if symmetric:
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if variant == "symmetric":
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newcontent = []
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for t in range(1, self.T - 1):
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if (self.content[t - 1] is None) or (self.content[t + 1] is None):
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@ -488,9 +479,39 @@ class Corr:
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if(all([x is None for x in newcontent])):
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raise Exception('Derivative is undefined at all timeslices')
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return Corr(newcontent, padding=[1, 1])
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elif variant == "forward":
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newcontent = []
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for t in range(self.T - 1):
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if (self.content[t] is None) or (self.content[t + 1] is None):
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newcontent.append(None)
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else:
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newcontent.append(self.content[t + 1] - self.content[t])
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if(all([x is None for x in newcontent])):
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raise Exception("Derivative is undefined at all timeslices")
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return Corr(newcontent, padding=[0, 1])
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elif variant == "improved":
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newcontent = []
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for t in range(2, self.T - 2):
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if (self.content[t - 2] is None) or (self.content[t - 1] is None) or (self.content[t + 1] is None) or (self.content[t + 2] is None):
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newcontent.append(None)
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else:
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newcontent.append((1 / 12) * (self.content[t - 2] - 8 * self.content[t - 1] + 8 * self.content[t + 1] - self.content[t + 2]))
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if(all([x is None for x in newcontent])):
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raise Exception('Derivative is undefined at all timeslices')
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return Corr(newcontent, padding=[2, 2])
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else:
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raise Exception("Unknown variant.")
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def second_deriv(self):
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"""Return the second derivative of the correlator with respect to x0."""
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def second_deriv(self, variant="symmetric"):
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"""Return the second derivative of the correlator with respect to x0.
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Parameters
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----------
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variant : str
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decides which definition of the finite differences derivative is used.
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Available choice: symmetric, improved, default: symmetric
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"""
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if variant == "symmetric":
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newcontent = []
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for t in range(1, self.T - 1):
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if (self.content[t - 1] is None) or (self.content[t + 1] is None):
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@ -500,6 +521,18 @@ class Corr:
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if(all([x is None for x in newcontent])):
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raise Exception("Derivative is undefined at all timeslices")
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return Corr(newcontent, padding=[1, 1])
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elif variant == "improved":
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newcontent = []
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for t in range(2, self.T - 2):
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if (self.content[t - 2] is None) or (self.content[t - 1] is None) or (self.content[t] is None) or (self.content[t + 1] is None) or (self.content[t + 2] is None):
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newcontent.append(None)
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else:
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newcontent.append((1 / 12) * (-self.content[t + 2] + 16 * self.content[t + 1] - 30 * self.content[t] + 16 * self.content[t - 1] - self.content[t - 2]))
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if(all([x is None for x in newcontent])):
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raise Exception("Derivative is undefined at all timeslices")
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return Corr(newcontent, padding=[2, 2])
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else:
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raise Exception("Unknown variant.")
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def m_eff(self, variant='log', guess=1.0):
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"""Returns the effective mass of the correlator as correlator object
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@ -45,7 +45,7 @@ def test_modify_correlator():
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exponent = np.random.normal(3, 5)
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corr_content.append(pe.pseudo_Obs(2 + 10 ** exponent, 10 ** (exponent - 1), 't'))
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corr = pe.correlators.Corr(corr_content)
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corr = pe.Corr(corr_content)
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with pytest.warns(RuntimeWarning):
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corr.symmetric()
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@ -53,14 +53,26 @@ def test_modify_correlator():
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corr.anti_symmetric()
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for pad in [0, 2]:
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corr = pe.correlators.Corr(corr_content, padding=[pad, pad])
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corr = pe.Corr(corr_content, padding=[pad, pad])
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corr.roll(np.random.randint(100))
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corr.deriv(symmetric=True)
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corr.deriv(symmetric=False)
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corr.deriv(variant="forward")
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corr.deriv(variant="symmetric")
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corr.deriv(variant="improved")
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corr.deriv().deriv()
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corr.second_deriv()
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corr.second_deriv(variant="symmetric")
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corr.second_deriv(variant="improved")
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corr.second_deriv().second_deriv()
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for i, e in enumerate(corr.content):
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corr.content[i] = None
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for func in [pe.Corr.deriv, pe.Corr.second_deriv]:
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for variant in ["symmetric", "improved", "forward", "gibberish", None]:
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with pytest.raises(Exception):
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func(corr, variant=variant)
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def test_m_eff():
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for padding in [0, 4]:
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