Start of tidy up and transition to Python3

pynemo/nemo_bogadons_gauntlet.py

-#
-# The loop from nemo_bdy_extr_tm3
-#
-# 
-#
-
-from calendar import monthrange
-from datetime import datetime
-
-from netCDF4 import Dataset, netcdftime
-
-
-class Enter:
-
-    def __init__(self, settings, sc_time, dir_list, dst_cal_type, year, month):
-
-        var_nam = ['votemper', 'vosaline']
-        sc_fields = source_fields
-
-        #self.setup = settings # dict
-        # define src/dst cals
-        sf, ed = cal_trans(sc_time, dst_cal_type, year, month)
-        # W
-        DstCal = utime('seconds since %d-1-1' %year, dst_cal_type)
-        dst_start = DstCal.date2num(datetime(year, month, 1))
-        dst_end = DstCal.date2num(datetime(year, month, ed, 23, 59, 59))
-
-        self.S_cal = utime(sc_time[0]['units'], sc_time[0]['calendar'])
-        self.D_cal = utime('seconds since %d-1-1' %settings['year_000'], 
-                           settings['dst_calendar'])
-
-        for date in sc_time:
-            date['date_num'] = DstCal.date2num(date['date']) * sf
-
-        # Get first and last date within range
-        first_date, last_date = None, None
-        rev_seq = range(len_sc_time)
-        rev_seq.reverse()
-        # Multiple values.. might be broken.. 
-        for date in rev_seq:
-            if sc_time[date]['date_num'] < dst_start:
-                first_date = date #number..
-                break
-        for date in range(len_sc_time):
-            if sc_time[date]['date_num'] > dst_end:
-                last_date = date
-                break
-
-        for date in range(first_date, last_date + 1):
-            nc = Dataset(sc_time[date], 'r')
-            if key_vec:
-                pass
-                #nc_2 = Dataset
-                # FIX ME
-
-            # We shouldnt have to worry about counters
-            sc_bdy = np.zeros(nvar, sc_z_len, source_ind['ind'].shape[0],
-                                  source_ind['ind'].shape[1])
-            ind_vec = {}
-            # distinctive variable name since it gets lost in the huge loop
-            for shoggoth in range(nvar):
-                varid = nc.variables[var_nam[shoggoth]]
-                i, ii = source_ind['imin'], source_ind['imax']
-                j, jj = source_ind['jmin'], source_ind['jmax']
-                sc_arrays = []
-                col_sc_arrays = []
-                if key_vec:
-                    varid_2 = nc_2.variables[var_nam[shoggoth + 1]]
-                if not isslab and not key_vec:
-                    # NOTE: 0 v 1 indexing may problemate
-                    sc_arrays.append(varid[i-1:ii, j-1:jj, :sc_z_len, :1])
-                elif key_vec:
-                    sc_arrays.append(varid[i-2:ii, j-1:jj, :sc_z_len, :1])
-                    sc_arrays.append(varid_2[i-1:ii, j-2:jj, :sc_z_len, :1])
-                    for x in 0,1:
-                        # tidy up src array - replace missing val
-                        for y in 'mv', 'fv':
-                            if not np.isnan(sc_fields[y][x]):
-                                ind_vec[y] = sc_arrays[x] == sc_fields[y][x]
-                                sc_arrays[x][ind_vec[y]] = 0
-                            else:
-                                sc_arrays[x][np.isnan(scarr)] = 0
-                        # Adjust for scaling or offsets
-                        if not np.isnan(sc_fields['sf'][x]):
-                            sc_arrays[x] *= sc_fields['sf'][x]
-                        if not np.isnan(sc_fields['os'][x]):
-                            sc_arrays[x] += sc_fields['os'][x]
-                
-                        # Colocate velocity points on T grid prior to rotation
-                        axis = [1, None]
-                        col = 0.5 * (sc_arrays[x][:-axis[0],:-axis[1],:] + 
-                                     sc_arrays[x][axis[0]:,axis[1]:,:])
-                        col[col == 0] = np.NaN
-                        col_sc_arrays.append(col)
-                        axis.reverse()
-                
-                # This is a slab
-                else:
-                    sc_arrays.append(varid[i-1:ii, j-1:jj, :1])
-                    #query var names
-                    if msk and first and shoggoth==0:
-                        pass
-                        # Open another magic file and do stuff
-                        nc3 = Dataset(source_mask, 'r')
-                        varid_3 = nc3.variables['tmaskutil']
-                        msk_array = varid_3[i-1:ii, j-1:jj, :1]
-                    if msk: #must be true for msk array ??...
-                        sc_arrays[0][msk_array == 0] = np.NaN
-
-        
-            # Finished reading Source data
-
-            #for depth_val in range(sc_z_len):
-            #    tmp_arrays = []
-            #    if not key_vec:
-            #        tmp_arrays.append(sc_arrays[0][:,:depth_val]
-
-
-    def _fv_mv_to_zero(self, scarr, indvec, sc_fields, pos):
-        
-        for x in 'mv', 'fv':
-            if not np.isnan(sc_fields[x][pos]):
-                ind_vec[x] = scarr == sc_fields[x][pos]
-                scarr[ind_vec[x]] = 0
-            else:
-                scarr[np.isnan(scarr)] = 0
-        return scarr, indvec
-
-    # Convert numeric date from source to dest
-    def convert_date(self, date):
-        
-        val = self.S_cal.num2date(date)
-        return self.D_cal.date2num(val)
-
-    def cal_trans(self, source, dest, year, month):
-        vals = {'gregorian': [monthrange(year, month)[1], 31], 'noleap': 
-                [365., 31],'360_day': [360., 30]}
-        if source not in vals.keys():
-            raise ValueError('Unknown calendar type: %s' %source)
-        
-        sf = val[source][0] / val[dest][0]
-        
-        return sf, vals[dest][1]
-
-
-
-
-