piecewise-regression - pypi Package Compare versions

Comparing version 1.4.0 to 1.4.1

docs/README.rst

@@ -6,3 +6,3 @@ ==========================================================
 :Author: Charlie Pilgrim
-:Version: 1.4.0
+:Version: 1.4.1
 :Github: https://github.com/chasmani/piecewise-regression
@@ -51,3 +51,3 @@ :Documentation: https://piecewise-regression.readthedocs.io/en/master/index.html
 
-The package is tested on Python 3.7, 3.8 and 3.9.
+The package is tested on Python 3.7, 3.8, 3.9 and 3.10.
 
@@ -115,3 +115,2 @@ Getting started
 	====================================================================================================
-
 	Davies test for existence of at least 1 breakpoint: p=5.13032e-295 (e.g. p<0.05 means reject null hypothesis of no breakpoints at 5% significance)
@@ -118,0 +117,0 @@

piecewise_regression.egg-info/PKG-INFO

 Metadata-Version: 2.1
 Name: piecewise-regression
-Version: 1.4.0
+Version: 1.4.1
 Summary: piecewise (segmented) regression in python
@@ -15,2 +15,3 @@ Home-page: https://github.com/chasmani/piecewise-regression
 Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
 Description-Content-Type: text/markdown
@@ -17,0 +18,0 @@ License-File: LICENSE.txt

piecewise_regression/davies.py

@@ -7,51 +7,2 @@
 
-def get_test_statistic(xx_davies, yy_davies, theta):
-    """
-    Compute a test statistic for the Davies test for the p-value of existence
-    of a breakpoint. Based on Davies(1987) "Hypothesis Testing when a nuisance
-    parameter is present only under the alternative".
-    All the variables in this function are as named and described in that
-    paper.
-
-    :param xx_davies: Data series in x-axis (same axis as the breakpoints).
-    :type xx_davies: list of floats
-
-    :param yy_davies: Data series in y-axis.
-    :type yy_davies: list of floats
-
-    :param theta: A test value from within the range of data in xx
-    :type theta: float
-
-    """
-    n = len(xx_davies)
-    s_0 = 0
-    s_1 = 0
-    s_2 = 0
-    s_3 = 0
-    s_4 = 0
-
-    for x in xx_davies:
-        s_0 += x**2
-
-        if x > theta:
-            s_1 += x * (x - theta)
-            s_3 += x - theta
-
-        elif x < theta:
-            s_2 += x * (x - theta)
-            s_4 += x - theta
-
-    a_hat = np.sum(yy_davies) / n
-    b_hat = np.sum(xx_davies * yy_davies) / s_0
-    V = s_1 * s_2 / s_0 + s_3 * s_4 / n
-
-    S = 0
-    for i in range(n):
-        if xx_davies[i] > theta:
-            S += (yy_davies[i] - a_hat - b_hat * xx_davies[i]) * \
-                (xx_davies[i] - theta)
-    S = S / (np.sqrt(np.abs(V)))
-    return S
-
-
 def get_test_statistic_wald(xx, yy, theta):
@@ -58,0 +9,0 @@

PKG-INFO

 Metadata-Version: 2.1
 Name: piecewise-regression
-Version: 1.4.0
+Version: 1.4.1
 Summary: piecewise (segmented) regression in python
@@ -15,2 +15,3 @@ Home-page: https://github.com/chasmani/piecewise-regression
 Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
 Description-Content-Type: text/markdown
@@ -17,0 +18,0 @@ License-File: LICENSE.txt

setup.py

@@ -6,3 +6,3 @@ import setuptools
     name="piecewise-regression",
-    version="1.4.0",
+    version="1.4.1",
     description="piecewise (segmented) regression in python",
@@ -27,2 +27,3 @@ long_description=   "piecewise-regression provides tools for fitting "
         "Programming Language :: Python :: 3.9",
+        "Programming Language :: Python :: 3.10",
     ],
@@ -29,0 +30,0 @@ packages=setuptools.find_packages(),

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Worsened metrics

Total package byte prevSize

108589

-1.04%

Lines of code

2038

-1.78%