Unidata /
MetPy
| Conditions | 4 |
| Total Lines | 55 |
| Lines | 0 |
| Ratio | 0 % |
| Changes | 1 | ||
| Bugs | 0 | Features | 0 |
Small methods make your code easier to understand, in particular if combined with a good name. Besides, if your method is small, finding a good name is usually much easier.
For example, if you find yourself adding comments to a method's body, this is usually a good sign to extract the commented part to a new method, and use the comment as a starting point when coming up with a good name for this new method.
Commonly applied refactorings include:
If many parameters/temporary variables are present:
| 1 | # Copyright (c) 2008-2015 MetPy Developers. |
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| 18 | def plot_vad(filelist,storm_relative=False,storm_motion=[0.,0.]): |
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| 19 | '''INPUT: list of NEXRAD VAD files |
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| 20 | OUTPUT: color-coded wind barbs plotted with height for |
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| 21 | the times given in the list of files |
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| 22 | |||
| 23 | plotting a storm-relative VAD is optional |
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| 24 | (requires a storm motion vector)''' |
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| 25 | vad_pd = pd.DataFrame() |
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| 26 | for files in filelist: |
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| 27 | vad_f = Level3File(files) |
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| 28 | vad_ft = vad_f.tab_pages |
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| 29 | vad = pd.concat([pd.read_table(StringIO(vad_ft[i]), sep='\s+',header=1,skiprows=[2]) for i in np.arange(0,len(vad_ft)-2)],axis=0) |
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| 30 | vad['TIME'] = vad_f.metadata['vol_time'] |
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| 31 | vad['AGL'] = ((vad['ALT']*100.)-vad_f.height)*0.3048 #convert from altitude in feet to AGL in meters |
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| 32 | vad_pd = pd.concat([vad_pd,vad],axis=0) |
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| 33 | |||
| 34 | # Begin Figure |
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| 35 | fig = plt.figure(figsize = (12,10)) |
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| 36 | ax = fig.add_subplot(111) |
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| 37 | |||
| 38 | uplot = vad_pd['U'] |
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| 39 | vplot = vad_pd['V'] |
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| 40 | altplot = vad_pd['AGL'] |
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| 41 | time_plot = mpl.dates.date2num(vad_pd['TIME'].astype(dt.datetime)) |
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| 42 | |||
| 43 | # Subtract storm motion vector from winds for storm-relative VAD |
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| 44 | if storm_relative == True: |
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| 45 | uplot,vplot = vad_pd['U']-storm_motion[0] , vad_pd['V']-storm_motion[1] |
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| 46 | |||
| 47 | # Set color params |
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| 48 | C = np.sqrt(uplot**2 + vplot**2) # color by speed |
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| 49 | bounds = np.arange(0,100,1) # min speed, max speed, interval |
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| 50 | |||
| 51 | # plot wind barbs |
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| 52 | cmap=plt.cm.gnuplot |
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| 53 | norm = mpl.colors.BoundaryNorm(bounds, cmap.N) |
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| 54 | m = 2 #plot every mth wind barb |
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| 55 | b = plt.barbs(time_plot[::m],vad_pd['AGL'].iloc[::m],uplot.iloc[::m],vplot.iloc[::m],C[::m],cmap=cmap,norm=norm) |
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| 56 | |||
| 57 | # Assign tick labels for x-axis |
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| 58 | starttime,endtime = vad_pd['TIME'].iloc[0],vad_pd['TIME'].iloc[-1] |
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| 59 | ax.xaxis.set_major_formatter(mpl.dates.DateFormatter('%d/%H:%M UTC')) |
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| 60 | ax.set_xlim(starttime-dt.timedelta(minutes=2),endtime+dt.timedelta(minutes=2)) |
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| 61 | |||
| 62 | # Plot asthetics |
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| 63 | fs = 14 |
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| 64 | cbar = plt.colorbar(b, cmap=cmap,boundaries=bounds,norm=norm) # Colorbar |
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| 65 | cbar.set_label('Wind Speed (m/s)', fontsize = fs) |
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| 66 | yticks = np.arange(0, 10500, 500) |
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| 67 | plt.yticks(yticks) |
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| 68 | plt.ylim(-500,10500) |
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| 69 | plt.xlabel('Time (UTC)',fontsize=fs) |
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| 70 | plt.ylabel('Altitude AGL (m)',fontsize=fs) |
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| 71 | plt.grid('on') |
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| 72 | plt.title(vad_f.siteID+' Velocity Azimuth Display',fontsize=fs+3) |
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| 73 |
