version bump

pravirkr · Oct 27, 2023 · 0d11ef0 · 0d11ef0
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diff --git a/README.md b/README.md
@@ -7,7 +7,7 @@
 
 Python Implementation of the Kalman filter detector for detecting smoothly variying signals buried in gaussian noise (like Fast Radio Bursts).
 
-The detection statistic is designed to receive X(f), a sequence of observed "amplitudes" (where f is an arbitrary indexed parameter) and decide between:
+The detection statistic is designed to receive I(f), a sequence of observed "amplitudes" (where f is an arbitrary indexed parameter) and decide between:
 
 ```
 H0: I(f) = N(f)         Pure gaussian noise
@@ -31,6 +31,13 @@ kalman = KalmanDetector(spectrum_std)
 kalman.prepare_fits(ntrials=10000)
 kalman.get_significance(spectrum)
 ```
+
+### Efficiency
+
+```python
+python -m kalman_detector.efficiency
+```
+
 ## Citation
 Please cite [Kumar, Zackay & Law (2023)](https://ui.adsabs.harvard.edu/abs/2023arXiv230607914K) if you find this code useful in your research.
 The BibTeX entry for the paper is:

diff --git a/setup.cfg b/setup.cfg
@@ -1,6 +1,6 @@
 [metadata]
 name = kalman_detector
-version = 0.1.0
+version = 0.5.0
 author = "Pravir Kumar, Barak Zackay"
 author_email = pravirka@gmail.com
 description = Detecting Fast Radio Bursts with Spectral Structures
@@ -28,6 +28,7 @@ install_requires =
     matplotlib
     numba
     sympy
+    uncertainties
 
 [options.extras_require]
 tests =