DOC: Add example plotting fronts on a map

examples/plots/Front_Analysis.py

@@ -0,0 +1,147 @@
+import cartopy.crs as ccrs
+import cartopy.feature as cfeature
+import matplotlib.pyplot as plt
+
+from metpy.plots import ColdFront, WarmFront, OccludedFront, StationaryFront
+
+def str_to_lonlat(s):
+    return -int(s[3:]) / 10, int(s[:3]) / 10
+
+def parse_points(strs):
+    for mag_str, loc_str in zip(strs[:-1:2], strs[1::2]):
+        mag = int(mag_str)
+        yield *str_to_lonlat(loc_str), mag
+
+def parse_path(strs):
+    return [str_to_lonlat(s) for s in strs]
+
+def decode(fobj):
+    ret = dict()
+    last_field = ''
+    for line in fobj:
+        try:
+            field, *info = line.split()
+        except ValueError:  # Not a good report line
+            continue
+
+        continuing = False
+        if field not in ('VALID', 'HIGHS', 'LOWS', 'WARM', 'COLD', 'OCFNT', 'STNRY', 'TROF'):
+            info = [field] + info
+            field = last_field
+            continuing = True
+        if field == 'VALID':
+            ret['VALID'] = info[0]
+        elif field in ('HIGHS', 'LOWS'):
+            ret.setdefault(field, []).extend(parse_points(info))
+        elif field in ('WARM', 'COLD', 'OCFNT', 'STNRY', 'TROF'):
+            dest = ret.setdefault(field, [])
+            vals = parse_path(info)
+            if continuing:
+                dest[-1].extend(vals)
+            else:
+                dest.append(vals)
+        last_field = field
+    return ret
+
+
+from io import StringIO
+
+data = StringIO("""870 
+ASUS02 KWBC 161500
+CODSUS
+
+CODED SURFACE FRONTAL POSITIONS
+NWS WEATHER PREDICTION CENTER COLLEGE PARK MD
+1148 AM EST THU JAN 16 2020
+
+VALID 011615Z
+HIGHS 1042 3861066 1047 4330965 1031 4051097 1043 5611072 1048 6381359 1027
+2830840 1047 4760967 1018 2711238 1018 3511169 1029 4441105
+LOWS 1004 4240707 1024 3090952 992 6600543 993 6010464 994 6270370 997 5960564
+1001 4111212 1003 4371271 992 5131279 1003 4591186 1020 4471060 1017 4691101
+OCFNT 4240707 4230701 4200697 4160694 4080692 3980694 3880701
+WARM 3880701 3670692 3550676 3490655
+COLD 3880701 3740718 3660736 3570760 3470790 3370814 3210850 3140883 3120907
+3130925 3130932
+TROF 6110627 6040668 5960723 5870777 5820829 5770871 5710939 5520985 5401016
+TROF 7170861 7060959 6971059 6861166
+TROF 3610946 3460947 3270952 3140953
+COLD 3070954 3040960 3000973 2960985 2901004 2871023 2891048 2931066 2991080
+3071092 3181100 3271103 3361108 3421116
+STNRY 3130933 3110943 3070953
+STNRY 6260372 6200373 6080385 5990416 6000439 6020454 6000466
+COLD 6010464 5760448 5440444 5170477 5060528
+STNRY 6170333 6240354 6250371
+OCFNT 6600544 6510522 6340495 6210480 6010464
+STNRY 5060526 5010553 4930577 4740605 4670621 4670642 4710686 4650709
+COLD 4660708 4560722 4490736 4430758 4430786 4480817 4560847 4650870
+TROF 4040687 3990674 4000653 3990640 3980625
+COLD 4101212 4021216 3931223 3771234 3631244 3511257 3381275 3251299 3151319
+TROF 5081274 5021265 4861245 4661238 4481239
+STNRY 4941280 4931291 4961318 5141345 5371366 5521371 5721374 5861382 5921407
+5951437 5921455
+OCFNT 5121279 5091263 5051249 4991237 4921229 4721218 4621214 4531212
+TROF 4341180 4261159 4271132 4321116
+COLD 4531212 4461211 4371210 4251210
+STNRY 4261210 4151211 4091212
+STNRY 4311002 4341022 4411036 4471047 4461059
+STNRY 4591186 4541189 4521199 4501207 4531212
+WARM 7951527 7781482 7581465 7421461
+TROF 7960731 7690701 7490642 7260577 6960544 6710536
+STNRY 3421115 3471123 3551135
+TROF 2801099 2671091 2391071 2071059 1821057
+TROF 5401072 5271088 5061097 4831096 4711100
+STNRY 4461059 4461067 4491079 4581086 4671093 4691102
+TROF 4451059 4371058 4261058 4131052 3991041 3841043 3721041
+STNRY 4691100 4681107 4701122 4711135 4771145 4901153 4951162 4951174 4901178
+4761179 4641180 4581188
+TROF 4661099 4541093 4391092 4301090 4201083 4111082
+TROF 4191204 4011198 3861186 3701159 3571144 3401137 3231138 3071134
+TROF 4131113 4041129 3911137 3831151
+TROF 5471329 5331315 5231301 5131283
+TROF 4501270 4271271 4011265 3811266
+TROF 6121522 6321518 6411495 6481463 6561438
+""")
+
+bull = decode(data)
+
+from metpy.plots._mpl import TextCollection
+def plot_bulletin(ax, data, style=None):
+    size = 5
+    fontsize = 16
+    complete_style = {'HIGHS':{'color':'blue', 'fontsize':fontsize},
+                      'LOWS':{'color':'red', 'fontsize':fontsize},
+                      'WARM':{'linewidth':1, 'path_effects':[WarmFront(size=size)]},
+                      'COLD':{'linewidth':1, 'path_effects':[ColdFront(size=size)]},
+                      'OCFNT':{'linewidth':1, 'path_effects':[OccludedFront(size=size)]},
+                      'STNRY':{'linewidth':1, 'path_effects':[StationaryFront(size=size)]},
+                      'TROF':{'linewidth':2, 'linestyle':'dashed', 'color':'darkorange'}}
+    if style:
+        complete_style.update(style)
+    for field in ('HIGHS', 'LOWS'):
+        if field in data:
+            x, y, vals = zip(*data[field])
+            tc = TextCollection(x, y, [field[0]] * len(x), ha='center',
+                                **complete_style[field], transform=ccrs.PlateCarree())
+            ax.add_collection(tc)
+            tc = TextCollection(x, y, [str(v) for v in vals], offset=(0, -15), ha='center',
+                                **complete_style[field], transform=ccrs.PlateCarree())
+            ax.add_collection(tc)
+    for field in ('WARM', 'COLD', 'STNRY', 'OCFNT', 'TROF'):
+        for front in data[field]:
+            if field == 'STNRY':
+                front = reversed(front)
+            x, y = zip(*front)
+            plt.plot(x, y, **complete_style.get(field, {}), transform=ccrs.PlateCarree())
+
+
+fig = plt.figure(figsize=(18, 18), dpi=300)
+ax = fig.add_subplot(1, 1, 1, projection=ccrs.LambertConformal(central_longitude=-103))
+ax.add_feature(cfeature.COASTLINE)
+ax.add_feature(cfeature.OCEAN)
+ax.add_feature(cfeature.LAND)
+ax.add_feature(cfeature.BORDERS)
+ax.add_feature(cfeature.STATES)
+ax.add_feature(cfeature.LAKES)
+plot_bulletin(ax, bull)
+ax.set_extent((-125, -70, 20, 55))