1 from pylab import *
   2 import Nio
   3 
   4 '''
   5 a remark in advance. When importing a module, best practice is actually
   6 to import always into a variable
   7 
   8 e.g. import numpy as np
   9 from matplotlib import pylab as pl
  10 ...
  11 
  12 reason: some functions are available in different modules with different
  13 implementation. If you want to be sure that you work with the same
  14 routine always, then you can e.g. call np.cos() for the cosine function
  15 and you know where it comes from.
  16 '''
  17 
  18 
  19 '''
  20 Best start for plotting is to always look for examples
  21 in the matplotlib gallery: http://matplotlib.sourceforge.net/gallery.html
  22 '''
  23 close('all')
  24 
  25 #simple plotting with different labels
  26 x=arange(100)/100. *6*pi
  27 
  28 plot(x,sin(x))
  29 plot(x,cos(x))
  30 
  31 plot(x,sin(x),label='test1')
  32 plot(x,cos(x),label='test2')
  33 legend()
  34 
  35 
  36 
  37 #explicit specifications of styles
  38 
  39 #... the dirty way
  40 close('all')
  41 plot(x,sin(x),'r--')
  42 plot(x,cos(x),'go-.')
  43 title('quick & dirty')
  44 
  45 figure()
  46 #... the "clean" way
  47 plot(x,sin(x),color='red',linestyle='--')
  48 plot(x,cos(x),color='green',linestyle='-.',marker='o')
  49 title('the cleaner way')
  50 xlabel('x-label here')
  51 ylabel('y-label here')
  52 
  53 ########################################################################
  54 
  55 '''
  56 It is recommended to NOT follow the previous examples, but to use always
  57 figure and axis objects to work with, as this always allows allows a
  58 proper handling of different axes. This is of particular importance
  59 when working with multiple axes or subplots
  60 '''
  61 
  62 f=figure(figsize=(12,3))
  63 ax1 = f.add_subplot(111) #<<< subplot
  64 
  65 ax1.plot(x,sin(x),'r')
  66 ax2=twinx()
  67 ax2.plot(x,100*cos(x),'g')
  68 ax1.set_ylabel('This is the one label')
  69 ax2.set_ylabel('This is the other label')
  70 
  71 
  72 
  73 '''
  74 for interactive working, this also helps a lot as it allows
  75 to synchronize different axes
  76 
  77 try the sharex option!
  78 '''
  79 close('all')
  80 f = figure()
  81 ax1=f.add_subplot(1,2,1)
  82 ax2=f.add_subplot(1,2,2,sharex=ax1)
  83 
  84 ax1.plot(x,sin(x) )
  85 ax2.plot(x,cos(x) )
  86 ax1.set_title('Axis synchronization rocks ...')
  87 
  88 
  89 
  90 '''
  91 cheating with subplots
  92 '''
  93 close('all')
  94 f = figure()
  95 ax1 = f.add_subplot(221)
  96 ax2 = f.add_subplot(222)
  97 ax3 = f.add_subplot(212)
  98 
  99 ax1.plot(x,sin(x))
 100 ax2.plot(x,sin(x))
 101 ax3.plot(x,sin(x)); ax3.plot(x,cos(x))
 102 
 103 '''
 104 a more sophisticated approach to handle subplots
 105 is provided by gridspec
 106 
 107 for more detailed documentation see http://matplotlib.sourceforge.net/users/gridspec.html
 108 '''
 109 import matplotlib.gridspec as gs
 110 
 111 f= figure()
 112 grid = gs.GridSpec(2, 1, height_ratios=[3,1])
 113 
 114 ax1 = f.add_subplot(grid[0])
 115 ax2 = f.add_subplot(grid[1])
 116 ax1.plot(x,sin(x))
 117 ax2.plot(x,x**2)
 118 
 119 
 120 stop
 121 
 122 
 123 
 124 ########################################################################
 125 # 2D plotting
 126 ########################################################################
 127 close('all')
 128 fname='/home/m300028/shared/data/SEP/data_sources/LSMASK/jsbach_T63_GR15_4tiles_1992.nc'
 129 F=Nio.open_file(fname,'r')
 130 z=F.variables['elevation'].get_value()
 131 
 132 #... again dirty
 133 figure()
 134 imshow(z)
 135 colorbar() #shrink=0.5
 136 
 137 #... better
 138 f=figure()
 139 ax=f.add_subplot(111)
 140 im=ax.imshow(z)
 141 colorbar(im,ax=ax,shrink=0.5)
 142 
 143 #... changing colorbar
 144 figure()
 145 imshow(z,cmap='RdBu')
 146 colorbar(shrink=0.75,orientation='horizontal')
 147 
 148 
 149 mycmap = cm.get_cmap('RdBu_r', 11)
 150 
 151 figure()
 152 imshow(z,cmap=mycmap)
 153 colorbar(shrink=0.75,orientation='horizontal')
 154 
 155 
 156 
 157 
 158 #--- another way to get a nice colorbar ---
 159 def add_nice_legend(ax,im,cmap,cticks=None):
 160     '''
 161     add a nice looking legend
 162 
 163     @param ax: major axis with plot
 164     @type ax: matpltlib axis object
 165 
 166     @param im: result from command like imshow
 167     @param im: matplotlib im object (???)
 168 
 169     #http://old.nabble.com/manual-placement-of-a-colorbar-td28112662.html
 170 
 171 
 172 
 173     '''
 174     from mpl_toolkits.axes_grid import make_axes_locatable
 175     import  matplotlib.axes as maxes
 176 
 177     #set legend aligned with plot (nice looking)
 178     divider = make_axes_locatable(ax)
 179     cax = divider.new_horizontal("5%", pad=0.05, axes_class=maxes.Axes)
 180     ax.figure.add_axes(cax)
 181     norm = mpl.colors.Normalize(vmin=im.get_clim()[0], vmax=im.get_clim()[1])
 182     cb   = mpl.colorbar.ColorbarBase(cax, cmap=cmap, norm=norm,ticks=cticks)
 183 
 184 
 185 
 186 close('all')
 187 
 188 f=figure(); ax=f.add_subplot(111)
 189 im=ax.imshow(z,cmap=mycmap)
 190 add_nice_legend(ax,im,mycmap)
 191 
 192 #----
 193 
 194 stop
 195 
 196 
 197 
 198 
 199 
 200 '''
 201 contourplots are generated with
 202 
 203 contour() or contourf() function
 204 '''
 205 
 206 
 207 '''
 208 saving a figure ...
 209 '''
 210 f=figure(); ax=f.add_subplot(111)
 211 ax.imshow(z); ax.set_title('global topography [m]')
 212 f.savefig('elevation1.png')
 213 f.savefig('elevation1.pdf')
 214 f.savefig('elevation2.pdf',bbox_inches='tight')
 215 
 216 
 217 '''
 218 ... one of my favorites
 219 '''
 220 close('all')
 221 f=figure(); ax1=f.add_subplot(211); ax2=f.add_subplot(212)
 222 ax1.fill_between(x,sin(x))
 223 ax2.fill_between(x,sin(x),y2=cos(x),color='red')