Merge pull request #137 from fjosw/feat/gamma_method_alias

Alias gm for gamma_method

CHANGELOG.md

@@ -2,6 +2,17 @@
 
 All notable changes to this project will be documented in this file.
 
+## [2.5.0] - 2023-xx-xx
+### Added
+- Hotelling t-squared p-value added for correlated fits.
+- String conversion of numpy arrays containing `Obs` improved.
+- Alias `gm` for `Obs.gamma_method` added.
+- Input routine for xSF measurement program added.
+
+### Fixed
+- Complex valued `Corr` objects fixed.
+- Small bug in `qtop_projection` fixed.
+
 ## [2.4.0] - 2022-12-01
 ### Added
 - Log-derivatives and symmetric log-effective mass added.
@@ -13,8 +24,6 @@ All notable changes to this project will be documented in this file.
 - Bug in `input.json` export in connection with `numpy.int64` fixed.
 - Small bug fixes in `input.openQCD`.
 
-
-
 ## [2.3.1] - 2022-10-19
 ### Fixed
 - Integrated autocorrelation times are now correctly estimated for gapped irregular Monte Carlo chains.

pyerrors/obs.py

@@ -349,6 +349,8 @@ class Obs:
             self.ddvalue = np.sqrt(self.ddvalue) / self._dvalue
         return
 
+    gm = gamma_method
+
     def _calc_gamma(self, deltas, idx, shape, w_max, fft):
         """Calculate Gamma_{AA} from the deltas, which are defined on idx.
            idx is assumed to be a contiguous range (possibly with a stepsize != 1)

tests/obs_test.py

@@ -1015,3 +1015,15 @@ def test_hash():
         assert hash(i_obs) != hash((1 + 1e-7) * i_obs)
     assert hash(obs) != hash(o1)
     assert hash(o1) != hash(o2)
+
+def test_gm_alias():
+    samples = np.random.rand(500)
+
+    tt1 = pe.Obs([samples], ["ens"])
+    tt1.gamma_method()
+
+    tt2 = pe.Obs([samples], ["ens"])
+    tt2.gm()
+
+    assert np.isclose(tt1.dvalue, tt2.dvalue)
+