Graphs

Example 27 - graph plot

_images/fig27.png
import cf
import cfplot as cfp
f=cf.read('cfplot_data/ggap.nc')[1]
g=f.collapse('X: mean')
cfp.lineplot(g.subspace(pressure=100), marker='o', color='blue',\
             title='Zonal mean zonal wind at 100mb')

Other valid markers are:

'.' point
',' pixel
'o' circle
'v' triangle_down
'^' triangle_up
'<' triangle_left
'>' triangle_right
'1' tri_down
'2' tri_up
'3' tri_left
'4' tri_right
'8' octagon
's' square
'p' pentagon
'*' star
'h' hexagon1
'H' hexagon2
'+' plus
'x' x
'D' diamond
'd' thin_diamond

Example 28 - Line and legend plot

_images/fig28.png
import cf
import cfplot as cfp
f=cf.read('cfplot_data/ggap.nc')[1]
g=f.collapse('X: mean')
xticks=[-90,-75,-60,-45,-30,-15,0,15,30,45,60,75,90]
xticklabels=['90S','75S','60S','45S','30S','15S','0','15N','30N','45N','60N','75N','90N']
xpts=[-30, 30, 30, -30, -30]
ypts=[-8, -8, 5, 5, -8]

cfp.gset(xmin=-90, xmax=90, ymin=-10, ymax=50)
cfp.gopen()
cfp.lineplot(g.subspace(pressure=100), marker='o', color='blue',\
             title='Zonal mean zonal wind', label='100mb')
cfp.lineplot(g.subspace(pressure=200), marker='D', color='red',\
             label='200mb', xticks=xticks, xticklabels=xticklabels,\
             legend_location='upper right')
cfp.plotvars.plot.plot(xpts,ypts, linewidth=3.0, color='green')
cfp.plotvars.plot.text(35, -2, 'Region of interest', horizontalalignment='left')
cfp.gclose()
When making a multiple line plot:
a) Set the axis limits if required with cfp.gset before plotting the lines. Using cfp.gset after the last line has been plotted may give unexpected axis limits and / or labelling. This is a feature of Matplotlib.
b) The last call to lineplot is the one that any of the above
axis overrides should be placed in.
c) All calls to lineplot with the label attribute will appear in the legend.

The cfp.plotvars.plot object contains the Matplotlib plot and will accept normal Matplotlib plotting commands. As an example of this the following code within a cfp.gopen() cfp.gclose() construct will make a legend that is independent of any previously made lines and attached labels.

import matplotlib.lines as mlines
green_line = mlines.Line2D([], [], color='green', label='green')
black_line = mlines.Line2D([], [], color='black', ls='--' , label='black dashed')
cfp.plotvars.plot.legend(handles=[green_line, black_line])

Valid locations for the legend_location keyword are:

'right'
'center left'
'upper right'
'lower right'
'best'
'center'
'lower left'
'center right'
'upper left'
'upper center'
'lower center'

When making a call to lineplot the following parameters overide any predefined CF defaults:

title=None - plot title
xunits=None - x units
yunits=None - y units
xname=None - x name
yname=None - y name
xticks=None - x ticks
xticklabels=None - x tick labels
yticks=None - y ticks
yticklabels - y tick labels

Example 29 - Global average annual temperature

_images/fig29.png

In this example we subset a time data series of global temperature, area mean the data, convert to Celsius and plot a linegraph.

When using gset to set the limits on the plotting axes and a time axis pass time strings to give the limits i.e. cfp.gset(xmin = '1980-1-1', xmax = '1990-1-1', ymin = 285, ymax = 295)

The correct date format is 'YYYY-MM-DD' or 'YYYY-MM-DD HH:MM:SS' - anything else will give unexpected results.

import cf
import cfplot as cfp
f=cf.read('cfplot_data/tas_A1.nc')[0]
temp=f.subspace(time=cf.wi(cf.dt('1900-01-01'), cf.dt('1980-01-01')))
temp_annual=temp.collapse('T: mean', group=cf.Y())
temp_annual_global=temp_annual.collapse('area: mean', weights='area')
temp_annual_global.Units -= 273.15
cfp.lineplot(temp_annual_global, title='Global average annual temperature', color='blue')

Example 30 - Two axis plotting

_images/fig30.png

In this example we plot two x-axes, one with zonal mean zonal wind data and one with temperature data. Somewhat confusingly the option for a twin x-axis is twiny=True. This is a Matplotlib keyword which has been adopted within the cf-plot code.

import cf
import cfplot as cfp
tol=cf.RTOL(1e-5)
f=cf.read('cfplot_data/ggap.nc')[1]
u=f.collapse('X: mean')
u1=u.subspace(Y=-61.12099075)
u2=u.subspace(Y=0.56074494)

g=cf.read('cfplot_data/ggap.nc')[0]
t=g.collapse('X: mean')
t1=t.subspace(Y=-61.12099075)
t2=t.subspace(Y=0.56074494)

cfp.gopen()
cfp.gset(-30, 30, 1000, 0)
cfp.lineplot(u1,color='r')
cfp.lineplot(u2, color='r')

cfp.gset(190, 300, 1000, 0, twiny=True)
cfp.lineplot(t1,color='b')
cfp.lineplot(t2, color='b')

cfp.gclose()