Rename prcp_fac

docs/_code/prepare_climate.py

@@ -36,8 +36,8 @@
 tasks.catchment_width_correction(gdir)
 cfg.PARAMS['baseline_climate'] = 'HISTALP'
 cfg.PARAMS['use_tstar_calibration'] = True
-cfg.PARAMS['use_winter_prcp_factor'] = False
-cfg.PARAMS['prcp_scaling_factor'] = 2.5
+cfg.PARAMS['use_winter_prcp_fac'] = False
+cfg.PARAMS['prcp_fac'] = 2.5
 tasks.process_histalp_data(gdir)
 with warnings.catch_warnings():
     warnings.filterwarnings("ignore", category=FutureWarning)

oggm/cfg.py

@@ -531,11 +531,11 @@ def initialize_minimal(file=None, logging_level='INFO', params=None,
     PARAMS['hydro_month_nh'] = cp.as_int('hydro_month_nh')
     PARAMS['hydro_month_sh'] = cp.as_int('hydro_month_sh')
     PARAMS['geodetic_mb_period'] = cp['geodetic_mb_period']
-    PARAMS['use_winter_prcp_factor'] = cp.as_bool('use_winter_prcp_factor')
+    PARAMS['use_winter_prcp_fac'] = cp.as_bool('use_winter_prcp_fac')
 
-    k = 'winter_prcp_factor_ab'
+    k = 'winter_prcp_fac_ab'
     PARAMS[k] = [float(vk) for vk in cp.as_list(k)]
-    k = 'winter_prcp_factor_range'
+    k = 'winter_prcp_fac_range'
     PARAMS[k] = [float(vk) for vk in cp.as_list(k)]
     k = 'ref_mb_valid_window'
     PARAMS[k] = [int(vk) for vk in cp.as_list(k)]
@@ -561,9 +561,9 @@ def initialize_minimal(file=None, logging_level='INFO', params=None,
 
     # Precip factor can be none
     try:
-        PARAMS['prcp_scaling_factor'] = cp.as_float('prcp_scaling_factor')
+        PARAMS['prcp_fac'] = cp.as_float('prcp_fac')
     except ValueError:
-        PARAMS['prcp_scaling_factor'] = None
+        PARAMS['prcp_fac'] = None
 
     # Delete non-floats
     ltr = ['working_dir', 'dem_file', 'climate_file', 'use_tar_shapefiles',
@@ -582,11 +582,10 @@ def initialize_minimal(file=None, logging_level='INFO', params=None,
            'free_board_marine_terminating', 'use_kcalving_for_inversion',
            'error_when_glacier_reaches_boundaries', 'glacier_length_method',
            'use_inversion_params_for_run',
-           'tidewater_type', 'store_model_geometry', 'use_winter_prcp_factor',
+           'tidewater_type', 'store_model_geometry', 'use_winter_prcp_fac',
            'store_diagnostic_variables', 'store_fl_diagnostic_variables',
-           'geodetic_mb_period', 'store_fl_diagnostics', 'winter_prcp_factor_ab',
-           'winter_prcp_factor_range', 'prcp_scaling_factor',
-           'downstream_line_shape']
+           'geodetic_mb_period', 'store_fl_diagnostics', 'winter_prcp_fac_ab',
+           'winter_prcp_fac_range', 'prcp_fac', 'downstream_line_shape']
     for k in ltr:
         cp.pop(k, None)
 

oggm/core/massbalance.py

@@ -65,10 +65,10 @@ def decide_winter_precip_factor(gdir):
 
     # from MB sandbox calibration to winter MB
     # using t_melt=-1, cte lapse rate, monthly resolution
-    a, b = cfg.PARAMS['winter_prcp_factor_ab']
+    a, b = cfg.PARAMS['winter_prcp_fac_ab']
     prcp_fac = a * np.log(w_prcp) + b
     # don't allow extremely low/high prcp. factors!!!
-    r0, r1 = cfg.PARAMS['winter_prcp_factor_range']
+    r0, r1 = cfg.PARAMS['winter_prcp_fac_range']
     return clip_scalar(prcp_fac, r0, r1)
 
 
@@ -545,7 +545,7 @@ def monthly_melt_f(self):
     # after instantiation with properly changing the prcp time series
     @property
     def prcp_fac(self):
-        """Precipitation factor (default: cfg.PARAMS['prcp_scaling_factor'])
+        """Precipitation factor (default: cfg.PARAMS['prcp_fac'])
 
         Called factor to make clear that it is a multiplicative factor in
         contrast to the additive temperature bias
@@ -1448,9 +1448,9 @@ def mb_calibration_from_scalar_mb(gdir,
                                   melt_f=None,
                                   melt_f_min=None,
                                   melt_f_max=None,
-                                  prcp_scaling_factor=None,
-                                  prcp_scaling_factor_min=None,
-                                  prcp_scaling_factor_max=None,
+                                  prcp_fac=None,
+                                  prcp_fac_min=None,
+                                  prcp_fac_max=None,
                                   temp_bias=0,
                                   temp_bias_min=None,
                                   temp_bias_max=None,
@@ -1539,16 +1539,16 @@ def mb_calibration_from_scalar_mb(gdir,
     melt_f_max: float
         the maximum accepted value for the melt factor during optimisation.
         Defaults to cfg.PARAMS['melt_f_max'].
-    prcp_scaling_factor: float
+    prcp_fac: float
         the default value to use as precipitation scaling factor
         (or the starting value when optimizing MB). Defaults to the method
         chosen in `params.cfg` (winter prcp or global factor).
-    prcp_scaling_factor_min: float
+    prcp_fac_min: float
         the minimum accepted value for the precipitation scaling factor during
-        optimisation. Defaults to cfg.PARAMS['prcp_scaling_factor_min'].
-    prcp_scaling_factor_max: float
+        optimisation. Defaults to cfg.PARAMS['prcp_fac_min'].
+    prcp_fac_max: float
         the maximum accepted value for the precipitation scaling factor during
-        optimisation. Defaults to cfg.PARAMS['prcp_scaling_factor_max'].
+        optimisation. Defaults to cfg.PARAMS['prcp_fac_max'].
     temp_bias: float
         the default value to use as temperature bias (or the starting value when
         optimizing MB). Defaults to 0.
@@ -1565,10 +1565,10 @@ def mb_calibration_from_scalar_mb(gdir,
         melt_f_min = cfg.PARAMS['melt_f_min']
     if melt_f_max is None:
         melt_f_max = cfg.PARAMS['melt_f_max']
-    if prcp_scaling_factor_min is None:
-        prcp_scaling_factor_min = cfg.PARAMS['prcp_scaling_factor_min']
-    if prcp_scaling_factor_max is None:
-        prcp_scaling_factor_max = cfg.PARAMS['prcp_scaling_factor_max']
+    if prcp_fac_min is None:
+        prcp_fac_min = cfg.PARAMS['prcp_fac_min']
+    if prcp_fac_max is None:
+        prcp_fac_max = cfg.PARAMS['prcp_fac_max']
     if melt_f is None:
         melt_f = cfg.PARAMS['melt_f']
     if temp_bias_min is None:
@@ -1620,21 +1620,21 @@ def mb_calibration_from_scalar_mb(gdir,
                                   'you posted!')
 
     # Ok, regardless on how we want to calibrate, we start with defaults
-    if prcp_scaling_factor is None:
-        if cfg.PARAMS['use_winter_prcp_factor']:
+    if prcp_fac is None:
+        if cfg.PARAMS['use_winter_prcp_fac']:
             # Some sanity check
-            if cfg.PARAMS['prcp_scaling_factor'] is not None:
-                raise InvalidWorkflowError("Set PARAMS['prcp_scaling_factor'] "
+            if cfg.PARAMS['prcp_fac'] is not None:
+                raise InvalidWorkflowError("Set PARAMS['prcp_fac'] "
                                            "to None if using winter_prcp_factor")
             prcp_fac = decide_winter_precip_factor(gdir)
         else:
-            prcp_fac = cfg.PARAMS['prcp_scaling_factor']
+            prcp_fac = cfg.PARAMS['prcp_fac']
             if prcp_fac is None:
-                raise InvalidWorkflowError("Set either PARAMS['use_winter_prcp_factor'] "
+                raise InvalidWorkflowError("Set either PARAMS['use_winter_prcp_fac'] "
                                            "or PARAMS['winter_prcp_factor'].")
     else:
-        # if a prcp_scaling_factor is set, we will use it instead of the default option
-        prcp_fac = prcp_scaling_factor    
+        # if a prcp_fac is set, we will use it instead of the default option
+        prcp_fac = prcp_fac
 
     # Create the MB model we will calibrate
     mb_mod = mb_model_class(gdir,
@@ -1652,7 +1652,7 @@ def mb_calibration_from_scalar_mb(gdir,
     if calibrate_param1 == 'melt_f':
         min_range, max_range = melt_f_min, melt_f_max
     elif calibrate_param1 == 'prcp_fac':
-        min_range, max_range = prcp_scaling_factor_min, prcp_scaling_factor_max
+        min_range, max_range = prcp_fac_min, prcp_fac_max
     elif calibrate_param1 == 'temp_bias':
         min_range, max_range = temp_bias_min, temp_bias_max
     else:
@@ -1685,7 +1685,7 @@ def to_minimize(x, model_attr):
         if calibrate_param2 == 'melt_f':
             min_range, max_range = melt_f_min, melt_f_max
         elif calibrate_param2 == 'prcp_fac':
-            min_range, max_range = prcp_scaling_factor_min, prcp_scaling_factor_max
+            min_range, max_range = prcp_fac_min, prcp_fac_max
         elif calibrate_param2 == 'temp_bias':
             min_range, max_range = temp_bias_min, temp_bias_max
         else:
@@ -1712,7 +1712,7 @@ def to_minimize(x, model_attr):
             if calibrate_param3 == 'melt_f':
                 min_range, max_range = melt_f_min, melt_f_max
             elif calibrate_param3 == 'prcp_fac':
-                min_range, max_range = prcp_scaling_factor_min, prcp_scaling_factor_max
+                min_range, max_range = prcp_fac_min, prcp_fac_max
             elif calibrate_param3 == 'temp_bias':
                 min_range, max_range = temp_bias_min, temp_bias_max
             else:
@@ -1964,7 +1964,7 @@ def fixed_geometry_mass_balance(gdir, ys=None, ye=None, years=None,
     precipitation_factor: float
         multiply a factor to the precipitation time series
         default is None and means that the precipitation factor from the
-        calibration is applied which is cfg.PARAMS['prcp_scaling_factor']
+        calibration is applied which is cfg.PARAMS['prcp_fac']
     mb_model_class : MassBalanceModel class
         the MassBalanceModel class to use, default is MonthlyTIModel
     """
@@ -2021,7 +2021,7 @@ def compute_ela(gdir, ys=None, ye=None, years=None, climate_filename='climate_hi
     precipitation_factor: float
         multiply a factor to the precipitation time series
         default is None and means that the precipitation factor from the
-        calibration is applied which is cfg.PARAMS['prcp_scaling_factor']
+        calibration is applied which is cfg.PARAMS['prcp_fac']
     mb_model_class : MassBalanceModel class
         the MassBalanceModel class to use, default is MonthlyTIModel
     """

oggm/params.cfg

@@ -209,19 +209,19 @@ temp_bias_min = -10
 temp_bias_max = 10
 
 # precipitation correction: set to a float for a constant scaling factor
-# Needs to be set empty if use_winter_prcp_factor is True
-prcp_scaling_factor =
+# Needs to be set empty if use_winter_prcp_fac is True
+prcp_fac =
 # For calibration - set a range
-prcp_scaling_factor_min = 0.1
-prcp_scaling_factor_max = 5
+prcp_fac_min = 0.1
+prcp_fac_max = 5
 
 # Use a precipitation dependent factor (unique per glacier)
 # The values below have been calibrated on W5E5 data - they will work
 # less well on other datasets (but should be fine since it only corrects
 # total precipitation and should be less affected by temperature).
-use_winter_prcp_factor = True
-winter_prcp_factor_ab = -1.0614, 3.9200
-winter_prcp_factor_range = 0.1, 10
+use_winter_prcp_fac = True
+winter_prcp_fac_ab = -1.0614, 3.9200
+winter_prcp_fac_range = 0.1, 10
 
 
 # When matching geodetic MB on a glacier per glacier basis, which period

oggm/tests/funcs.py

@@ -399,8 +399,8 @@ def init_hef(reset=False, border=40, logging_level='INFO', rgi_id=None,
     cfg.PATHS['working_dir'] = testdir
     cfg.PARAMS['trapezoid_lambdas'] = 1
     cfg.PARAMS['border'] = border
-    cfg.PARAMS['use_winter_prcp_factor'] = False
-    cfg.PARAMS['prcp_scaling_factor'] = 2.5
+    cfg.PARAMS['use_winter_prcp_fac'] = False
+    cfg.PARAMS['prcp_fac'] = 2.5
 
     hef_file = get_demo_file('Hintereisferner_RGI5.shp')
     entity = gpd.read_file(hef_file).iloc[0]
@@ -503,8 +503,8 @@ def init_columbia(reset=False):
     cfg.PARAMS['border'] = 10
     cfg.PARAMS['use_kcalving_for_inversion'] = True
     cfg.PARAMS['use_kcalving_for_run'] = True
-    cfg.PARAMS['use_winter_prcp_factor'] = False
-    cfg.PARAMS['prcp_scaling_factor'] = 2.5
+    cfg.PARAMS['use_winter_prcp_fac'] = False
+    cfg.PARAMS['prcp_fac'] = 2.5
     cfg.PARAMS['baseline_climate'] = 'CRU'
 
     entity = gpd.read_file(get_demo_file('01_rgi60_Columbia.shp')).iloc[0]
@@ -542,8 +542,8 @@ def init_columbia_eb(dir_name, reset=False):
     cfg.PARAMS['border'] = 10
     cfg.PARAMS['use_kcalving_for_inversion'] = True
     cfg.PARAMS['use_kcalving_for_run'] = True
-    cfg.PARAMS['use_winter_prcp_factor'] = False
-    cfg.PARAMS['prcp_scaling_factor'] = 2.5
+    cfg.PARAMS['use_winter_prcp_fac'] = False
+    cfg.PARAMS['prcp_fac'] = 2.5
     cfg.PARAMS['baseline_climate'] = 'CRU'
 
     entity = gpd.read_file(get_demo_file('01_rgi60_Columbia.shp')).iloc[0]

oggm/tests/test_benchmarks.py

@@ -50,8 +50,8 @@ def setUp(self):
         cfg.PATHS['working_dir'] = self.testdir
         cfg.PATHS['dem_file'] = get_demo_file('dem_SouthGlacier.tif')
         cfg.PARAMS['border'] = 10
-        cfg.PARAMS['use_winter_prcp_factor'] = False
-        cfg.PARAMS['prcp_scaling_factor'] = 2.5
+        cfg.PARAMS['use_winter_prcp_fac'] = False
+        cfg.PARAMS['prcp_fac'] = 2.5
         cfg.PARAMS['baseline_climate'] = 'CRU'
 
         self.tf = get_demo_file('cru_ts4.01.1901.2016.SouthGlacier.tmp.dat.nc')
@@ -474,8 +474,8 @@ def setUp(self):
         cfg.PATHS['working_dir'] = self.testdir
         cfg.PARAMS['use_kcalving_for_inversion'] = True
         cfg.PARAMS['use_kcalving_for_run'] = True
-        cfg.PARAMS['use_winter_prcp_factor'] = False
-        cfg.PARAMS['prcp_scaling_factor'] = 2.5
+        cfg.PARAMS['use_winter_prcp_fac'] = False
+        cfg.PARAMS['prcp_fac'] = 2.5
         cfg.PARAMS['baseline_climate'] = 'CRU'
 
     def tearDown(self):

oggm/tests/test_graphics.py

@@ -177,8 +177,8 @@ def test_multiple_inversion():
     cfg.PARAMS['border'] = 40
     cfg.PARAMS['baseline_climate'] = 'CUSTOM'
     cfg.PARAMS['trapezoid_lambdas'] = 1
-    cfg.PARAMS['use_winter_prcp_factor'] = False
-    cfg.PARAMS['prcp_scaling_factor'] = 2.5
+    cfg.PARAMS['use_winter_prcp_fac'] = False
+    cfg.PARAMS['prcp_fac'] = 2.5
     cfg.PATHS['working_dir'] = testdir
 
     # Get the RGI ID
@@ -262,8 +262,8 @@ def test_multiple_models():
     cfg.PATHS['working_dir'] = testdir
     cfg.PARAMS['baseline_climate'] = 'CUSTOM'
     cfg.PARAMS['trapezoid_lambdas'] = 1
-    cfg.PARAMS['use_winter_prcp_factor'] = False
-    cfg.PARAMS['prcp_scaling_factor'] = 2.5
+    cfg.PARAMS['use_winter_prcp_fac'] = False
+    cfg.PARAMS['prcp_fac'] = 2.5
     cfg.PARAMS['border'] = 40
 
     # Get the RGI ID
@@ -352,8 +352,8 @@ def test_chhota_shigri():
     cfg.PARAMS['use_intersects'] = False
     cfg.PATHS['working_dir'] = testdir
     cfg.PARAMS['trapezoid_lambdas'] = 1
-    cfg.PARAMS['use_winter_prcp_factor'] = False
-    cfg.PARAMS['prcp_scaling_factor'] = 2.5
+    cfg.PARAMS['use_winter_prcp_fac'] = False
+    cfg.PARAMS['prcp_fac'] = 2.5
 
     hef_file = get_demo_file('divides_RGI50-14.15990.shp')
     df = gpd.read_file(hef_file)
@@ -396,8 +396,8 @@ def test_ice_cap():
     cfg.PARAMS['border'] = 60
     cfg.PATHS['working_dir'] = testdir
     cfg.PARAMS['trapezoid_lambdas'] = 1
-    cfg.PARAMS['use_winter_prcp_factor'] = False
-    cfg.PARAMS['prcp_scaling_factor'] = 2.5
+    cfg.PARAMS['use_winter_prcp_fac'] = False
+    cfg.PARAMS['prcp_fac'] = 2.5
 
     df = gpd.read_file(get_demo_file('divides_RGI50-05.08389.shp'))
     df['Area'] = df.Area * 1e-6  # cause it was in m2
@@ -438,8 +438,8 @@ def test_coxe():
     cfg.PARAMS['use_kcalving_for_inversion'] = True
     cfg.PARAMS['use_kcalving_for_run'] = True
     cfg.PARAMS['trapezoid_lambdas'] = 1
-    cfg.PARAMS['use_winter_prcp_factor'] = False
-    cfg.PARAMS['prcp_scaling_factor'] = 2.5
+    cfg.PARAMS['use_winter_prcp_fac'] = False
+    cfg.PARAMS['prcp_fac'] = 2.5
 
     hef_file = get_demo_file('rgi_RGI50-01.10299.shp')
     entity = gpd.read_file(hef_file).iloc[0]