Merge pull request #418 from DataverseLabs/417-calculate-distances---revision-for-version-10

417 calculate distances   revision for version 10

Author: SimonMolinsky

.gitignore

@@ -174,6 +174,7 @@ venv/
 ENV/
 env.bak/
 venv.bak/
+venv-model/
 
 # Spyder project settings
 .spyderproject

readthedocs.yml .readthedocs.yamlreadthedocs.yml renamed to .readthedocs.yaml

@@ -1,10 +1,16 @@
-# .readthedocs.yml
+# ..readthedocs.yaml
 # Read the Docs configuration file
 # See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
 
 # Required
 version: 2
 
+# Set the version of Python and other tools you might need
+build:
+  os: ubuntu-22.04
+  tools:
+    python: "3.10"
+
 # Build documentation in the docs_oldies/ directory with Sphinx
 sphinx:
   configuration: docs/source/conf.py
@@ -19,7 +25,6 @@ formats:
 
 # Optionally set the version of Python and requirements required to build your docs_oldies
 python:
-  version: "3.8"
   install:
     - requirements: docs/requirements.txt
     - method: pip

README.md

@@ -4,7 +4,7 @@
 
 # Pyinterpolate
 
-**version 0.5** - *Mykolaiv*
+**version 0.5.1** - *Mykolaiv*
 
 ---
 

changelog.rst

@@ -6,12 +6,15 @@ Pyinterpolate is the Python library for **geostatistics** and **spatial statisti
 Changes by date
 ===============
 
-2023-XX-XX
+2024-02-19
 ----------
 
-**version 0.5.1**
+**version 0.5.1** (*pre production development*)
 
 * (enhancement) `interpolate_raster()` function takes `allow_approx_solutions` parameter, and it protects from `LinAlgError` that might occur if interpolation points are duplicated (due to the floating point number representation).
+* (refactoring) `calc_point_to_point_distance` function refactored to `point_distance`, changed input parameters' schema,
+* (refactoring) new selection method for unequally spaced bins: `select_values_between_lags`
+* (debug) `np.float` type casting has been changed to `float`
 
 2023-09-16
 ----------

developer/dev_checks/debug_sandbox/check_cent_pk/check.py

@@ -170,7 +170,7 @@ def centroid_poisson_kriging(semivariogram_model: TheoreticalVariogram,
 
     # Distances between known blocks
     coordinates = kriging_data[:, :values_column_index]
-    block_distances = calc_point_to_point_distance(coordinates).flatten()
+    block_distances = point_distance(coordinates, coordinates).flatten()
     known_blocks_semivars = semivariogram_model.predict(block_distances)
     predicted = np.array(known_blocks_semivars.reshape(n, n))
     predicted = sem_to_cov(predicted, sill)