Merge pull request #17 from pysat/pysat3_update

BUG/STY: update code to be compliant with numpy, pandas, and pysat development paths
pysat · Apr 27, 2020 · 74fa185 · 74fa185
2 parents 7b1c89c + 0687c7e
commit 74fa185
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diff --git a/.travis.yml b/.travis.yml
@@ -8,7 +8,6 @@ jobs:
     # Versions with latest numpy
     - python: 3.6
     - python: 3.7
-    - python: 3.8
 
 services: xvfb
 addons:
@@ -29,21 +28,30 @@ install:
   # Useful for debugging any issues with conda
   - conda info -a
   # Create conda test environment
-  - conda create -q -n test-environment python=$TRAVIS_PYTHON_VERSION numpy scipy pandas xarray requests beautifulsoup4 lxml netCDF4 nose pytest-cov pytest-ordering coveralls future
+  - conda create -q -n test-environment python=$TRAVIS_PYTHON_VERSION numpy scipy requests beautifulsoup4 lxml netCDF4 nose pytest-cov pytest-ordering coveralls future
   - conda activate test-environment
   # check for custom version of numpy
   - if [ -z ${NUMPY_VER} ]; then
       echo 'Using latest numpy';
     else
-      conda install -q numpy==$NUMPY_VER;
+      conda install numpy==$NUMPY_VER;
     fi
+  # Enforce version limits due to use of Panel
+  - conda install pandas==0.24.2
+  - conda install 'xarray<0.15'
   # Dependencies not available through conda, install through pip
   - pip install PyForecastTools
   - pip install pysatCDF >/dev/null
+  # Prepare pysat install from git
+  - cd ..
+  - git clone https://github.com/pysat/pysat.git >/dev/null
+  - cd ./pysat
   # set up data directory
   - mkdir /home/travis/build/pysatData
   # install pysat
-  - python setup.py install
+  - git checkout develop-3
+  - python setup.py install >/dev/null
+  - export PYTHONPATH=$PYTHONPATH:$(pwd)
   # install pysatSeasons
   - cd ../pysatSeasons
   - python setup.py install

diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -3,6 +3,8 @@ All notable changes to this project will be documented in this file.
 This project adheres to [Semantic Versioning](http://semver.org/).
 
 ## [0.1.2] - 2020-04-25
+- Updates demo codes to import objects from datetime and pandas for pysat 3.0.0 compatibility
+- Fixed a bug where test routines used float where numpy 1.18 expects an int
 - Import objects from datetime and pandas for pysat 3.0.0 compatibility
 - Use conda to manage Travis CI
 

diff --git a/demo/cosmic_and_ivm_demo.py b/demo/cosmic_and_ivm_demo.py
@@ -1,14 +1,16 @@
-import pysat
-import pysatSeasons
-import pandas as pds
+import datetime as dt
 import numpy as np
 import numpy.ma as ma
 import matplotlib.pyplot as plt
+import pandas as pds
+
+import pysat
+import pysatSeasons
 
 # dates for demo
 ssnDays = 67
-startDate = pds.datetime(2009, 12, 21) - pds.DateOffset(days=ssnDays)
-stopDate = pds.datetime(2009, 12, 21) + pds.DateOffset(days=ssnDays)
+startDate = dt.datetime(2009, 12, 21) - pds.DateOffset(days=ssnDays)
+stopDate = dt.datetime(2009, 12, 21) + pds.DateOffset(days=ssnDays)
 
 
 # define functions to customize data for application
@@ -176,7 +178,7 @@ def addTopsideScaleHeight(cosmic):
                        name='ivm', tag='',
                        clean_level='clean')
 # restrict meausurements to those near geomagnetic equator
-ivm.custom.add(restrictMLAT, 'modify', maxMLAT=25.)
+ivm.custom.attach(restrictMLAT, 'modify', maxMLAT=25.)
 # perform seasonal average
 ivm.bounds = (startDate, stopDate)
 ivmResults = pysatSeasons.avg.median2D(ivm, [0, 360, 24], 'alon',
@@ -189,13 +191,13 @@ def addTopsideScaleHeight(cosmic):
                           clean_level='clean',
                           altitude_bin=3)
 # apply custom functions to all data that is loaded through cosmic
-cosmic.custom.add(addApexLong, 'add')
+cosmic.custom.attach(addApexLong, 'add')
 # select locations near the magnetic equator
-cosmic.custom.add(filterMLAT, 'modify', mlatRange=(0., 10.))
+cosmic.custom.attach(filterMLAT, 'modify', mlatRange=(0., 10.))
 # take the log of NmF2 and add to the dataframe
-cosmic.custom.add(addlogNm, 'add')
+cosmic.custom.attach(addlogNm, 'add')
 # calculates the height above hmF2 to reach Ne < NmF2/e
-cosmic.custom.add(addTopsideScaleHeight, 'add')
+cosmic.custom.attach(addTopsideScaleHeight, 'add')
 
 # do an average of multiple COSMIC data products
 # from startDate through stopDate

diff --git a/demo/ssnl_occurrence_by_orbit.py b/demo/ssnl_occurrence_by_orbit.py
@@ -29,7 +29,7 @@ def filter_vefi(inst):
     return
 
 
-vefi.custom.add(filter_vefi, 'modify')
+vefi.custom.attach(filter_vefi, 'modify')
 # set limits on dates analysis will cover, inclusive
 start = dt.datetime(2010, 5, 9)
 stop = dt.datetime(2010, 5, 15)

diff --git a/pysatSeasons/tests/test_avg.py b/pysatSeasons/tests/test_avg.py
@@ -26,8 +26,8 @@ def teardown(self):
     def test_basic_seasonal_median2D(self):
         """ Test the basic seasonal 2D median"""
         self.testInst.bounds = self.bounds1
-        results = avg.median2D(self.testInst, [0., 360., 24.], 'longitude',
-                               [0., 24, 24], 'mlt',
+        results = avg.median2D(self.testInst, [0., 360., 24], 'longitude',
+                               [0., 24., 24], 'mlt',
                                ['dummy1', 'dummy2', 'dummy3'])
         dummy_val = results['dummy1']['median']
         dummy_dev = results['dummy1']['avg_abs_dev']
@@ -109,8 +109,8 @@ def teardown(self):
     def test_basic_seasonal_2Dmedian(self):
         """ Test the basic seasonal 2D median"""
 
-        results = avg.median2D(self.testInst, [0., 360., 24.], 'longitude',
-                               [0., 24, 24], 'mlt', [self.dname])
+        results = avg.median2D(self.testInst, [0., 360., 24], 'longitude',
+                               [0., 24., 24], 'mlt', [self.dname])
 
         # iterate over all
         # no variation in the median, all values should be the same
@@ -156,8 +156,8 @@ def teardown(self):
 
     def test_basic_seasonal_median2D(self):
         """ Test basic seasonal 2D median"""
-        results = avg.median2D(self.testInst, [0., 360., 24.], 'longitude',
-                               [0., 24, 24], 'mlt', [self.dname])
+        results = avg.median2D(self.testInst, [0., 360., 24], 'longitude',
+                               [0., 24., 24], 'mlt', [self.dname])
 
         # iterate over all
         # no variation in the median, all values should be the same
@@ -172,7 +172,7 @@ def test_basic_seasonal_median2D(self):
 
     def test_basic_seasonal_median1D(self):
         """ Test basic seasonal 1D median"""
-        results = avg.median1D(self.testInst, [0., 24, 24], 'mlt',
+        results = avg.median1D(self.testInst, [0., 24., 24], 'mlt',
                                [self.dname])
 
         # iterate over all
@@ -203,11 +203,11 @@ def test_constellation_median2D(self):
         for i in self.testC.instruments:
             i.bounds = self.bounds
         self.testI.bounds = self.bounds
-        resultsC = avg.median2D(self.testC, [0., 360., 24.], 'longitude',
-                                [0., 24, 24], 'mlt',
+        resultsC = avg.median2D(self.testC, [0., 360., 24], 'longitude',
+                                [0., 24., 24], 'mlt',
                                 ['dummy1', 'dummy2', 'dummy3'])
-        resultsI = avg.median2D(self.testI, [0., 360., 24.], 'longitude',
-                                [0., 24, 24], 'mlt',
+        resultsI = avg.median2D(self.testI, [0., 360., 24], 'longitude',
+                                [0., 24., 24], 'mlt',
                                 ['dummy1', 'dummy2', 'dummy3'])
         medC1 = resultsC['dummy1']['median']
         medI1 = resultsI['dummy1']['median']
@@ -259,8 +259,8 @@ def test_heterogenous_constellation_median2D(self):
         """ Test the seasonal 2D median of a heterogeneous constellation """
         for inst in self.testC:
             inst.bounds = self.bounds
-        results = avg.median2D(self.testC, [0., 360., 24.], 'longitude',
-                               [0., 24, 24], 'mlt',
+        results = avg.median2D(self.testC, [0., 360., 24], 'longitude',
+                               [0., 24., 24], 'mlt',
                                ['dummy1', 'dummy2', 'dummy3'])
         dummy_val = results['dummy1']['median']
         dummy_dev = results['dummy1']['avg_abs_dev']
@@ -462,7 +462,7 @@ def setup(self):
                                     112023., 111562., 112023., 111412.,
                                     111780., 111320., 111780., 111320.],
                           'avg_abs_dev': np.zeros(shape=24),
-                          'median': np.linspace(0.0, 23.0, 24.0)},
+                          'median': np.linspace(0.0, 23.0, 24)},
                          'dummy2':
                          {'count': [111780., 111320., 111780., 111320.,
                                     111780., 111320., 111780., 111320.,