meteogram: refactor

1 files changed, 61 insertions, 44 deletions

diff --git a/plotter/meteogram.py b/plotter/meteogram.py
index a04fe34..7fca360 100755
--- a/plotter/meteogram.py
+++ b/plotter/meteogram.py
@@ -24,22 +24,12 @@ def run(data, plots, output='.'):
 
     return index
 
-def _plot(data, output, name, lat, lon):
-    index = []
-
-    data = data.sel(latitude=lat, longitude = lon, method='nearest')
-
-    init = misc.np_time_convert(data.time.values)
-
-    init_str = init.strftime('%d %b %Y - %HUTC')
-    init_for_filename = init.strftime('%Y-%m-%d-%HUTC')
-
-    fig = plt.figure(figsize=(12, 10), layout="constrained")
-
-
-    # start figure and set axis
-    ax = fig.add_subplot(HEIGHT,1,(1,4))
+def _get_next_subplot(size, counter=0):
+    ret = (counter + 1, counter + size)
+    counter += size
+    return counter, ret
 
+def _add_cloudcov(ax, data):
     ax.set_ylabel('Pressure level [hPa]')
 
     clc = ax.contourf(data.valid_time, data.isobaricInhPa, data.ccl.transpose(), cmap='clcov', vmin=0, vmax=100, levels=9)
@@ -47,63 +37,89 @@ def _plot(data, output, name, lat, lon):
     # use Format parameter for n/8
     plt.colorbar(clc, label='cloudcov', extendfrac=None, ticks=[100*n/8 for n in range(9)], format=lambda x,_: f'{int(x/12.5)}/8', pad=0.0, fraction=0.015)
 
-
     cf = ax.contour(data.valid_time, data.isobaricInhPa, data.t.metpy.convert_units('degC').transpose())
     ax.clabel(cf, inline=True, fontsize=10)
 
+    # TODO convert to knots?
     barbs = ax.barbs(data.valid_time, data.isobaricInhPa, data.u.transpose(), data.v.transpose())
 
     ax.invert_yaxis()
 
+def _add_temp_dewpoint(ax, data):
     ### Temp + Dewpoint
-    ax2 = fig.add_subplot(HEIGHT,1,(5,6),sharex=ax)
-    ax2.plot(data.valid_time, data.t2m.metpy.convert_units('degC').transpose(), color='red', label='Temperature (2m)')
-    ax2.plot(data.valid_time, mpcalc.dewpoint_from_relative_humidity(data.t2m, data.r2).transpose(), color='blue', label='Dewpoint (2m)')
-    ax2.plot(data.valid_time, data.sel(isobaricInhPa=850.0).t.metpy.convert_units('degC').transpose(), color='grey', label='Tempreature (850hPa)')
-    ax2.set_ylabel('Temperature [degC]')
-    ax2.legend(loc='lower right')
-
-
-    ## MSLP
-    ax3 = fig.add_subplot(HEIGHT,1,(7,8),sharex=ax)
-    ax3.plot(data.valid_time, data.prmsl.metpy.convert_units('hPa').transpose(), color='black', label='Temperature (2m)')
-    ax3.set_ylabel('Mean Sea Level Pressure [hPa]')
-    #ax3.legend(loc='lower right')
+    ax.plot(data.valid_time, data.t2m.metpy.convert_units('degC').transpose(), color='red', label='Temperature (2m)')
+    ax.plot(data.valid_time, mpcalc.dewpoint_from_relative_humidity(data.t2m, data.r2).transpose(), color='blue', label='Dewpoint (2m)')
+    ax.plot(data.valid_time, data.sel(isobaricInhPa=850.0).t.metpy.convert_units('degC').transpose(), color='grey', label='Tempreature (850hPa)')
+    ax.set_ylabel('Temperature [degC]')
+    ax.legend(loc='lower right')
+
+def _add_mslp(ax, data):
+    ax.plot(data.valid_time, data.prmsl.metpy.convert_units('hPa').transpose(), color='black', label='Temperature (2m)')
+    ax.set_ylabel('Mean Sea Level Pressure [hPa]')
+
+def _add_convective_clouds(ax, data):
     # TODO: ADD HBAS_CON, HTOP_CON
     # If none: -500m
-
-    ax4 = ax3.twinx()
-    ax4.set_ylim(0, 14)
-    ax4.set_ylabel('Convective Clouds Height [km]')
-    ax4.bar(data.valid_time, alpha=0.5,
+    ax.set_ylim(0, 14)
+    ax.set_ylabel('Convective Clouds Height [km]')
+    ax.bar(data.valid_time, alpha=0.5,
             bottom=data.HBAS_CON.metpy.convert_units('km').transpose(),
             height=(data.hcct.metpy.convert_units('km')-data.HBAS_CON.metpy.convert_units('km')).transpose(),
             align='edge', width=np.timedelta64(3, 'h'))
 
-    # Precip
-    ax5 = fig.add_subplot(HEIGHT,1,(9,10),sharex=ax)
-    ax5.set_ylabel('Total precipitation [mm]')
-    ax5.set_ylim(0, 30)
-    ax5.bar(data.valid_time[:-1], data.tp.diff('step').transpose(), width=np.timedelta64(3, 'h'),
+def _add_precip(ax, data):
+    ax.set_ylabel('Total precipitation [mm]')
+    ax.set_ylim(0, 30)
+    ax.bar(data.valid_time[:-1], data.tp.diff('step').transpose(), width=np.timedelta64(3, 'h'),
             align='edge', alpha=0.7, color='green')
 
-    ax6 = ax5.twinx()
-    ax6.set_ylabel('Snow depth [m]')
-    ax6.set_ylim(bottom=0)
-    ax6.plot(data.valid_time, data.sde.transpose(), color='blue')
+    ax_p = ax.twinx()
+    ax_p.set_ylabel('Snow depth [m]')
+    ax_p.set_ylim(bottom=0)
+    ax_p.plot(data.valid_time, data.sde.transpose(), color='blue')
+
+
+def _plot(data, output, name, lat, lon):
+    data = data.sel(latitude=lat, longitude = lon, method='nearest')
+
+    fig = plt.figure(figsize=(12, 10), layout="constrained")
+
+    sp_cnt, spec = _get_next_subplot(4)
+    ax = fig.add_subplot(HEIGHT,1,spec)
+    _add_cloudcov(ax, data)
+
+    sp_cnt, spec2 = _get_next_subplot(2,sp_cnt)
+    ax2 = fig.add_subplot(HEIGHT,1,spec2,sharex=ax)
+    _add_temp_dewpoint(ax2, data)
+
+    sp_cnt, spec3 = _get_next_subplot(2,sp_cnt)
+    ax3 = fig.add_subplot(HEIGHT,1,spec3,sharex=ax)
+    #ax3.legend(loc='lower right')
+    _add_mslp(ax3, data)
+
+    ax4 = ax3.twinx()
+    _add_convective_clouds(ax4, data)
+
+    sp_cnt, spec4 = _get_next_subplot(2,sp_cnt)
+    ax5 = fig.add_subplot(HEIGHT,1,spec4,sharex=ax)
+    _add_precip(ax5, data)
 
     ### Info Lines
+    sp_cnt, spec5 = _get_next_subplot(1,sp_cnt)
+    ax_text = fig.add_subplot(HEIGHT, 1, spec5)
+
     info_lines = []
     init = misc.np_time_convert(data.time.values)
     init_str = init.strftime('%d %b %Y - %HUTC')
+    init_for_filename = init.strftime('%Y-%m-%d-%HUTC')
 
     info_lines.append(f'{name}')
     info_lines.append(f"INIT : {init_str}")
     info_lines.append(f"LAT {lat} LON {lon}")
+
     if '_description' in data.attrs:
         info_lines.append(data.attrs['_description'])
 
-    ax_text = fig.add_subplot(HEIGHT, 1, 11)
     ax_text.text(0, 0, '\n'.join(info_lines), ha='left', va='center',
             size=10, fontfamily='monospace')
     ax_text.axis("off")
@@ -114,6 +130,7 @@ def _plot(data, output, name, lat, lon):
     plt.savefig(os.path.join(output, outname))
     plt.close('all')
 
+    index = []
     index.append(
         {
             'file': outname,