Merge a1c49c2 into 91719ae

.gitignore

@@ -10,6 +10,9 @@ __pycache__
 # coverage stuffs
 .coverage
 
+# OS generated files
+.DS_Store
+
 # Notebook stuffs
 examples/*checkpoints
 .ipynb_checkpoints
@@ -24,6 +27,7 @@ result_images
 *.egg
 *.egg-info
 eggs
+*.eggs
 
 # specific
 *.cache

.travis.yml

@@ -29,6 +29,7 @@ matrix:
     - env: TEST_CONTAINER=py37 OGGM_TEST_ENV=models MPL=
     - env: TEST_CONTAINER=py37 OGGM_TEST_ENV=benchmark MPL=
     - env: TEST_CONTAINER=py37 OGGM_TEST_ENV=utils MPL=
+    - env: TEST_CONTAINER=py37 OGGM_TEST_ENV=vascaling MPL=
     - env: TEST_CONTAINER=py37 OGGM_TEST_ENV=workflow MPL=--mpl OGGM_TEST_MULTIPROC=True
     - env: TEST_CONTAINER=py37 OGGM_TEST_ENV=workflow MPL=--mpl OGGM_TEST_MULTIPROC=False
     - env: TEST_CONTAINER=py37 OGGM_TEST_ENV=graphics MPL=--mpl
@@ -43,6 +44,8 @@ matrix:
       os: linux
     - env: TEST_CONTAINER=20190409 OGGM_TEST_ENV=utils MPL=
       os: linux
+    - env: TEST_CONTAINER=20190409 OGGM_TEST_ENV=vascaling MPL=
+      os: linux
     - env: TEST_CONTAINER=20190409 OGGM_TEST_ENV=workflow MPL=--mpl OGGM_TEST_MULTIPROC=True
       os: linux
     - env: TEST_CONTAINER=20190409 OGGM_TEST_ENV=workflow MPL=--mpl OGGM_TEST_MULTIPROC=False
@@ -59,6 +62,8 @@ matrix:
       os: linux
     - env: TEST_CONTAINER=py37 OGGM_TEST_ENV=utils MPL=
       os: linux
+    - env: TEST_CONTAINER=py37 OGGM_TEST_ENV=vascaling MPL=
+      os: linux
     - env: TEST_CONTAINER=py37 OGGM_TEST_ENV=workflow MPL=--mpl OGGM_TEST_MULTIPROC=True
       os: linux
     - env: TEST_CONTAINER=py37 OGGM_TEST_ENV=workflow MPL=--mpl OGGM_TEST_MULTIPROC=False

docs/whats-new.rst

@@ -33,6 +33,11 @@ Enhancements
   By `Fabien Maussion <https://github.com/fmaussion>`_.
 - Added an option to pre-process all DEMs at once (:pull:`771`).
   By `Fabien Maussion <https://github.com/fmaussion>`_.
+- Added support for another evolution model: the volume-area-scaling based
+  model of Marzeion et al., 2012 (:pull:`662`). This is a major enhancement
+  to the code base as it increases the number of choices available to users
+  and demonstrates the modularity of the model.
+  By `Moritz Oberrauch <https://github.com/oberrauch>`_.
 
 
 Bug fixes

oggm/cfg.py

@@ -210,6 +210,10 @@ def __setitem__(self, key, value):
 _doc = 'Calving output (deprecated).'
 BASENAMES['calving_output'] = ('calving_output.pkl', _doc)
 
+_doc = "A dict containing the glacier's t*, bias, mu*. Analogous " \
+       "to 'local_mustar.json', but for the volume/area scaling model."
+BASENAMES['vascaling_mustar'] = ('vascaling_mustar.json', _doc)
+
 
 def set_logging_config(logging_level='INFO'):
     """Set the global logger parameters.
@@ -385,15 +389,18 @@ def initialize(file=None, logging_level='INFO'):
     for k in cp:
         PARAMS[k] = cp.as_float(k)
 
-    # Read-in the reference t* data - maybe it will be used, maybe not
-    fns = ['ref_tstars_rgi5_cru4', 'ref_tstars_rgi6_cru4',
-           'ref_tstars_rgi5_histalp', 'ref_tstars_rgi6_histalp']
-    for fn in fns:
-        PARAMS[fn] = pd.read_csv(get_demo_file('oggm_' + fn + '.csv'))
-        fpath = get_demo_file('oggm_' + fn + '_calib_params.json')
-        with open(fpath, 'r') as fp:
-            mbpar = json.load(fp)
-        PARAMS[fn+'_calib_params'] = mbpar
+    # Read-in the reference t* data for all available models types (oggm, vas)
+    model_prefixes = ['oggm_', 'vas_']
+    for prefix in model_prefixes:
+        fns = ['ref_tstars_rgi5_cru4', 'ref_tstars_rgi6_cru4',
+               'ref_tstars_rgi5_histalp', 'ref_tstars_rgi6_histalp']
+        for fn in fns:
+            fpath = get_demo_file(prefix + fn + '.csv')
+            PARAMS[prefix + fn] = pd.read_csv(fpath)
+            fpath = get_demo_file(prefix + fn + '_calib_params.json')
+            with open(fpath, 'r') as fp:
+                mbpar = json.load(fp)
+            PARAMS[prefix + fn + '_calib_params'] = mbpar
 
     # Empty defaults
     set_intersects_db()

oggm/core/climate.py

@@ -1038,15 +1038,15 @@ def local_t_star(gdir, *, ref_df=None, tstar=None, bias=None):
                 v = gdir.rgi_version[0]  # major version relevant
 
                 # Check that the params are fine
-                str_s = 'cru4' if 'CRU' in source else 'histalp'
-                vn = 'ref_tstars_rgi{}_{}_calib_params'.format(v, str_s)
+                s = 'cru4' if 'CRU' in source else 'histalp'
+                vn = 'oggm_ref_tstars_rgi{}_{}_calib_params'.format(v, s)
                 for k in params:
                     if cfg.PARAMS[k] != cfg.PARAMS[vn][k]:
                         msg = ('The reference t* you are trying to use was '
                                'calibrated with different MB parameters. You '
                                'might have to run the calibration manually.')
                         raise MassBalanceCalibrationError(msg)
-                ref_df = cfg.PARAMS['ref_tstars_rgi{}_{}'.format(v, str_s)]
+                ref_df = cfg.PARAMS['oggm_ref_tstars_rgi{}_{}'.format(v, s)]
             else:
                 # Use the the local calibration
                 fp = os.path.join(cfg.PATHS['working_dir'], 'ref_tstars.csv')

oggm/core/flowline.py

@@ -399,7 +399,7 @@ def __init__(self, flowlines, mb_model=None, y0=0., glen_a=None,
         mb_model : MassBalanceModel
             the MB model to use
         y0 : int
-            the starting year of the simultation
+            the starting year of the simulation
         glen_a : float
             glen's parameter A
         fs: float

oggm/core/massbalance.py

@@ -856,7 +856,7 @@ def get_annual_mb(self, heights, year=None, fl_id=None):
 class MultipleFlowlineMassBalance(MassBalanceModel):
     """Handle mass-balance at the glacier level instead of flowline level.
 
-    Convenience class doing not much more than wraping a list of mass-balance
+    Convenience class doing not much more than wrapping a list of mass-balance
     models, one for each flowline.
 
     This is useful for real-case studies, where each flowline might have a