Merge pull request #160 from wpreimes/master

Change naming convention for Intercomparison metrics calculator results. Use kdtree from pykdtree instead of scipy (faster). Add MetadataMetrics to metrics calculator. Remove pybufr-ecmwf, use generic test data for testing spatial resampling.

.gitignore

@@ -48,3 +48,5 @@ MANIFEST
 
 # ignore ISMN metadata files as they are different on win/linux
 */python_metadata/*
+
+local_scripts/*

.travis.yml

@@ -36,13 +36,9 @@ install:
   # Useful for debugging any issues with conda
   - conda info -a
 
-  - conda create -q -n test-environment -c conda-forge python=$TRAVIS_PYTHON_VERSION numpy scipy pandas netCDF4 cython pytest pip matplotlib pykdtree pyresample cartopy xarray
+  - conda create -q -n test-environment -c conda-forge python=$TRAVIS_PYTHON_VERSION
+  - conda env update -n test-environment -f environment.yml
   - source activate test-environment
-  - pip install pybufr-ecmwf
-  - pip install pygeogrids
-  - pip install pygeobase
-  - pip install ascat
-  - pip install ismn
   - python setup.py install
   - pip list
   - which pip

CHANGES.rst

@@ -1,5 +1,16 @@
-v0.7.0, 2019-05-15 
-===================
+unreleased
+==========
+-
+
+v0.7.1, 2019-09-03
+==================
+- Change naming convention for Intercomparison metrics calculator results
+- Use kdtree from pykdtree instead of scipy (faster)
+- Add MetadataMetrics to metrics calculator
+- Remove pybufr-ecmwf, use generic test data for testing spatial resampling
+
+v0.7.0, 2019-05-15
+==================
 
 - Add option for filling no data values to moving average
 - Add option for minimum observations to moving average

environment.yml

@@ -0,0 +1,27 @@
+# List of conda and pip packages that are should be install when developing the packages
+# To create the full conda environment: conda env create -f environment.yml
+name: pytesmo
+channels:
+  - conda-forge
+  - defaults
+dependencies:
+  - numpy
+  - scipy
+  - pandas
+  - netCDF4
+  - cython
+  - matplotlib
+  - pykdtree
+  - pyresample
+  - cartopy
+  - pip
+  - pip:
+    - pynetcf
+    - pygeogrids
+    - pynetcf
+    - pygeobase
+    - ascat
+    - ismn
+    - pytest
+    - configparser
+    - more_itertools

optional_requirements.txt

@@ -1,4 +1,3 @@
-pybufr-ecmwf>=0.80
 pygrib>=1.9.9
 pykdtree>=0.2
 pyresample>=1.0

pytesmo/temporal_matching.py

@@ -3,7 +3,7 @@
 """
 
 import numpy as np
-from scipy.spatial import cKDTree
+from pykdtree.kdtree import KDTree
 
 import pandas as pd
 
@@ -60,11 +60,11 @@ def df_match(reference, *args, **kwds):
         values = np.arange(comp_step.size)
         # setup kdtree which must get 2D input
         try:
-            tree = cKDTree(np.atleast_2d(comp_step).T, balanced_tree=False)
+            tree = KDTree(np.atleast_2d(comp_step).T, balanced_tree=False)
         except TypeError:
             # scipy before version 0.16 does not have the balanced_tree kw
             # but is fast in this case also without it
-            tree = cKDTree(np.atleast_2d(comp_step).T)
+            tree = KDTree(np.atleast_2d(comp_step).T)
 
         dist, i = tree.query(np.atleast_2d(ref_step).T)
         matched = values[i]