Taylor diagram sample gallery


See below a list of examples, with the command issued to generate each diagram.

Each command generates a PostScript file that is easily converted into PDF format or any other format on a Unix system using the utilitiy programs respectively ps2pdf (based on ghostscript, GNU free PostScript interpreter) and convert (availlable freely at ImageMagick Studio)

You can download a PDF version of each diagram by clicking on it.


Annual mean spatial anomaly to zonal mean

command:

>>> python plot_taylor_diagrams.py -C8 -p -t "Deep Pacific water C14 Taylor diagram" -o annual_mean_spatial_anomaly.ps C14/comp_stat.nc

Option '-C8' selects the 8th component (over 8): that is, Annual mean spatial anomaly to zonal mean

Option '-p' selects PostScript output format.

Option '-t' defines the diagram title.

Option '-o' defines the output file name.

C-14/comp_stat.nc is the input file containing the comparison statistics



 Sample 1
Sample 2


Zonal annual mean with color



command:

>>> python plot_taylor_diagrams.py -i38 -t "Model/Takahashi Sea-Air CO2 flux comparison" -c -C2 -o zonal_annual_mean.ps TAKA_FCO2_comp_stat.nc

Option '-C2' selects the second component: that is, Zonal annual mean

Option '-c' requests color to be added

Option '-i' sets the marker size for each point on the diagram. (Allowed size ranges from 1 to 100, default is 50)


Total space-time field component with bias

bias color scale is discrete, zero-centered blue-to-red.

command:

>>> python plot_taylor_diagrams.py -i38 -C1 -pbrd -t "CFC-11 inventory Taylor diagram" -o total_w_bias_red_blue.ps CFC11/comp_stat/comp_stat.nc

Option '-C1' selects the first component: that is, total space-time field (8 components in total)

Option '-b' requests the bias to be shown

Option '-r' selects the red-to-blue color palette

Option '-d' requests the colors scale to be discrete


 Sample 3

Sample 4


Total space-time field component with bias

bias color scale is discrete, rainbow-colored.


command:

>>> python plot_taylor_diagrams.py -i38 -C1 -pbd -t "CFC-11 inventory Taylor diagram" -o total_w_bias_red_blue.ps CFC11/comp_stat/comp_stat.nc

Option '-C1' selects the first component: that is, total space-time field (8 components in total)

Option '-b' requests the bias to be shown

Option '-d' requests the colors scale to be discrete





Total space-time field component with bias

bias color scale is continuous, rainbow-colored.

command:

>>> python plot_taylor_diagrams.py -i50 -C1 -pb -t "Deep Pacific water C14 Taylor diagram" -o total_w_bias_continuous.ps C-14/comp_stat/comp_stat.nc

Option '-i50': markers have the default size

Option '-b' requests the bias to be shown



 Sample 5
Sample 6


Multi-component

Four statistical components are shown on this diagram

command:

>>> python plot_taylor_diagrams.py -i32 -t "Model/World Ocean Atlas phosphate comparison" -sp -C1,7,2,4 -o multi-component.ps WOA_PO4_comp_stat.nc

Option '-C1,7,2,4' selects four components: 

  1. Total space-time field
  2. Spatial anomaly to zonal monthly mean
  3. Zonal annual mean
  4. Monthly anomaly to zonal annual mean

Option '-s' requests components to be superimposed on the same diagram.
Otherwise, four diagram in four different files would have been generated