Merge pull request #25 from JannisHoch/dev

major additions

.vscode/settings.json

@@ -1,4 +1,3 @@
 {
-    "python.pythonPath": "C:\\Users\\hoch0001\\AppData\\Local\\Continuum\\anaconda3\\envs\\conflict_model\\python.exe",
     "restructuredtext.confPath": "${workspaceFolder}\\docs"
 }

conflict_model/__init__.py

@@ -7,4 +7,4 @@
 
 __author__ = """Jannis M. Hoch"""
 __email__ = '[email protected]'
-__version__ = '0.0.1'
+__version__ = '0.0.2b3'

conflict_model/get_var_from_nc.py

@@ -7,7 +7,7 @@
 import matplotlib.pyplot as plt
 import os, sys
 
-def nc_with_integer_timestamp(extent_gdf, config, var_name, sim_year, stat_func='mean'):
+def nc_with_float_timestamp(extent_gdf, config, var_name, sim_year, stat_func='mean'):
     """This function extracts a statistical value from a netCDF-file (specified in the config-file) for each polygon specified in extent_gdf for a given year.
     By default, the mean value of all cells within a polygon is computed.
     The resulting list does not contain additional meta-information about the files or polygons and is mostly intended for data-driven approaches such as machine learning.
@@ -35,7 +35,7 @@ def nc_with_integer_timestamp(extent_gdf, config, var_name, sim_year, stat_func=
         list: list containing statistical value per polygon, i.e. with same length as extent_gdf
     """   
     # get path to netCDF-file.
-    nc_fo = os.path.join(config.get('general', 'input_dir'), 
+    nc_fo = os.path.join(os.path.abspath(config.get('general', 'input_dir')), 
                          config.get('env_vars', var_name))
 
     print('calculating mean {0} per aggregation unit from file {1} for year {2}'.format(var_name, nc_fo, sim_year))
@@ -66,7 +66,7 @@ def nc_with_integer_timestamp(extent_gdf, config, var_name, sim_year, stat_func=
 
     return list_out
 
-def nc_with_continous_regular_timestamp(extent_gdf, config, var_name, sim_year, stat_func='mean'):
+def nc_with_continous_datetime_timestamp(extent_gdf, config, var_name, sim_year, stat_func='mean'):
     """This function extracts a statistical value from a netCDF-file (specified in the config-file) for each polygon specified in extent_gdf for a given year.
     By default, the mean value of all cells within a polygon is computed.
     The resulting list does not contain additional meta-information about the files or polygons and is mostly intended for data-driven approaches such as machine learning.

conflict_model/selection.py

@@ -73,7 +73,7 @@ def clip_to_extent(gdf, config):
         geodataframe: geodataframe containing country polygons of selected continent
     """    
 
-    shp_fo = os.path.join(config.get('general', 'input_dir'), 
+    shp_fo = os.path.join(os.path.abspath(config.get('general', 'input_dir')), 
                           config.get('extent', 'shp'))
 
     print('reading extent and spatial aggregation level from file {}'.format(shp_fo))
@@ -97,10 +97,10 @@ def climate_zoning(gdf, config):
         geodataframe: geodataframe containing filtered entries
     """    
 
-    Koeppen_Geiger_fo = os.path.join(config.get('general', 'input_dir'),
+    Koeppen_Geiger_fo = os.path.join(os.path.abspath(config.get('general', 'input_dir')),
                                      config.get('climate', 'shp')) 
 
-    code2class_fo = os.path.join(config.get('general', 'input_dir'),
+    code2class_fo = os.path.join(os.path.abspath(config.get('general', 'input_dir')),
                                  config.get('climate', 'code2class'))
 
     look_up_classes = config.get('climate', 'zones').rsplit(',')

conflict_model/utils.py

@@ -18,7 +18,7 @@ def get_geodataframe(config, longitude='longitude', latitude='latitude', crs='EP
     """    
 
     # construct path to file with conflict data
-    conflict_fo = os.path.join(config.get('general', 'input_dir'), 
+    conflict_fo = os.path.join(os.path.abspath(config.get('general', 'input_dir')), 
                                config.get('conflict', 'conflict_file'))
 
     # read file to pandas dataframe