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Adding R squared value to scatter plot

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  Adding R squared value to scatter plot Jamie Mitchell <jamiemitchell1604@gmail.com> - 2014-05-21 04:59 -0700
    Re: Adding R squared value to scatter plot Jason Swails <jason.swails@gmail.com> - 2014-05-21 08:30 -0400
      Re: Adding R squared value to scatter plot Jamie Mitchell <jamiemitchell1604@gmail.com> - 2014-06-05 08:55 -0700

#71852 — Adding R squared value to scatter plot

I have made a plot using the following code:

python2.7
import netCDF4
import matplotlib.pyplot as plt
import numpy as np

swh_Q0_con_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q0/swh/controlperiod/south_west/swhcontrol_swest_annavg1D.nc','r')
hs_Q0_con_sw=swh_Q0_con_sw.variables['hs'][:]
swh_Q3_con_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q3/swh/controlperiod/south_west/swhcontrol_swest_annavg1D.nc','r')
hs_Q3_con_sw=swh_Q3_con_sw.variables['hs'][:]
swh_Q4_con_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q4/swh/controlperiod/south_west/swhcontrol_swest_annavg1D.nc','r')
hs_Q4_con_sw=swh_Q4_con_sw.variables['hs'][:]
swh_Q14_con_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q14/swh/controlperiod/south_west/swhcontrol_swest_annavg1D.nc','r')
hs_Q14_con_sw=swh_Q14_con_sw.variables['hs'][:]
swh_Q16_con_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q16/swh/controlperiod/south_west/swhcontrol_swest_annavg1D.nc','r')
hs_Q16_con_sw=swh_Q16_con_sw.variables['hs'][:]
swh_Q0_fut_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q0/swh/2050s/south_west/swh2050s_swest_annavg1D.nc','r')
hs_Q0_fut_sw=swh_Q0_fut_sw.variables['hs'][:]
swh_Q3_fut_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q3/swh/2050s/south_west/swh2050s_swest_annavg1D.nc','r')
hs_Q3_fut_sw=swh_Q3_fut_sw.variables['hs'][:]
swh_Q4_fut_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q4/swh/2050s/south_west/swh2050s_swest_annavg1D.nc','r')
hs_Q4_fut_sw=swh_Q4_fut_sw.variables['hs'][:]
swh_Q14_fut_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q14/swh/2050s/south_west/swh2050s_swest_annavg1D.nc','r')
hs_Q14_fut_sw=swh_Q14_fut_sw.variables['hs'][:]
swh_Q16_fut_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q16/swh/2050s/south_west/swh2050s_swest_annavg1D.nc','r')
hs_Q16_fut_sw=swh_Q16_fut_sw.variables['hs'][:]

fit_Q0_sw=np.polyfit(hs_Q0_con_sw,hs_Q0_fut_sw,1)
fit_fn_Q0_sw=np.poly1d(fit_Q0_sw)

plt.plot(hs_Q0_con_sw,hs_Q0_fut_sw,'g.')
plt.plot(hs_Q0_con_sw,fit_fn_Q0_sw(hs_Q0_con_sw),'g',label='Q0 no pert')

fit_Q3_sw=np.polyfit(hs_Q3_con_sw,hs_Q3_fut_sw,1)
fit_fn_Q3_sw=np.poly1d(fit_Q3_sw)

plt.plot(hs_Q3_con_sw,hs_Q3_fut_sw,'b.')
plt.plot(hs_Q3_con_sw,fit_fn_Q3_sw(hs_Q3_con_sw),'b',label='Q3 low sens')

fit_Q4_sw=np.polyfit(hs_Q4_con_sw,hs_Q4_fut_sw,1)
fit_fn_Q4_sw=np.poly1d(fit_Q4_sw)

plt.plot(hs_Q4_con_sw,hs_Q4_fut_sw,'y.')
plt.plot(hs_Q4_con_sw,fit_fn_Q4_sw(hs_Q4_con_sw),'y',label='Q4 low sens')

fit_Q14_sw=np.polyfit(hs_Q14_con_sw,hs_Q14_fut_sw,1)
fit_fn_Q14_sw=np.poly1d(fit_Q14_sw)

plt.plot(hs_Q14_con_sw,hs_Q14_fut_sw,'r.')
plt.plot(hs_Q14_con_sw,fit_fn_Q14_sw(hs_Q14_con_sw),'r',label='Q14 high sens')

fit_Q16_sw=np.polyfit(hs_Q16_con_sw,hs_Q16_fut_sw,1)
fit_fn_Q16_sw=np.poly1d(fit_Q16_sw)

plt.plot(hs_Q16_con_sw,hs_Q16_fut_sw,'c.')
plt.plot(hs_Q16_con_sw,fit_fn_Q16_sw(hs_Q16_con_sw),'c',label='Q16 high sens')

plt.legend(loc='best')
plt.xlabel('Significant Wave Height annual averages NW Scotland 1981-2010')
plt.ylabel('Significant Wave Height annual averages NW Scotland 2040-2069')
plt.title('Scatter plot of Significant Wave Height')
plt.show()

--

What I would like to do is display the R squared value next to the line of best fits that I have made. 

Does anyone know how to do this with matplotlib?

Thanks,

Jamie

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#71853

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​​



On Wed, May 21, 2014 at 7:59 AM, Jamie Mitchell <jamiemitchell1604@gmail.com
> wrote:

> I have made a plot using the following code:
>
> python2.7
> import netCDF4
> import matplotlib.pyplot as plt
> import numpy as np
>
>
> swh_Q0_con_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q0/swh/controlperiod/south_west/swhcontrol_swest_annavg1D.nc','r')
> hs_Q0_con_sw=swh_Q0_con_sw.variables['hs'][:]
>
> swh_Q3_con_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q3/swh/controlperiod/south_west/swhcontrol_swest_annavg1D.nc','r')
> hs_Q3_con_sw=swh_Q3_con_sw.variables['hs'][:]
>
> swh_Q4_con_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q4/swh/controlperiod/south_west/swhcontrol_swest_annavg1D.nc','r')
> hs_Q4_con_sw=swh_Q4_con_sw.variables['hs'][:]
>
> swh_Q14_con_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q14/swh/controlperiod/south_west/swhcontrol_swest_annavg1D.nc','r')
> hs_Q14_con_sw=swh_Q14_con_sw.variables['hs'][:]
>
> swh_Q16_con_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q16/swh/controlperiod/south_west/swhcontrol_swest_annavg1D.nc','r')
> hs_Q16_con_sw=swh_Q16_con_sw.variables['hs'][:]
>
> swh_Q0_fut_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q0/swh/2050s/south_west/swh2050s_swest_annavg1D.nc','r')
> hs_Q0_fut_sw=swh_Q0_fut_sw.variables['hs'][:]
>
> swh_Q3_fut_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q3/swh/2050s/south_west/swh2050s_swest_annavg1D.nc','r')
> hs_Q3_fut_sw=swh_Q3_fut_sw.variables['hs'][:]
>
> swh_Q4_fut_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q4/swh/2050s/south_west/swh2050s_swest_annavg1D.nc','r')
> hs_Q4_fut_sw=swh_Q4_fut_sw.variables['hs'][:]
>
> swh_Q14_fut_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q14/swh/2050s/south_west/swh2050s_swest_annavg1D.nc','r')
> hs_Q14_fut_sw=swh_Q14_fut_sw.variables['hs'][:]
>
> swh_Q16_fut_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q16/swh/2050s/south_west/swh2050s_swest_annavg1D.nc','r')
> hs_Q16_fut_sw=swh_Q16_fut_sw.variables['hs'][:]
>
> fit_Q0_sw=np.polyfit(hs_Q0_con_sw,hs_Q0_fut_sw,1)
> fit_fn_Q0_sw=np.poly1d(fit_Q0_sw)
>
> plt.plot(hs_Q0_con_sw,hs_Q0_fut_sw,'g.')
> plt.plot(hs_Q0_con_sw,fit_fn_Q0_sw(hs_Q0_con_sw),'g',label='Q0 no pert')
>
> fit_Q3_sw=np.polyfit(hs_Q3_con_sw,hs_Q3_fut_sw,1)
> fit_fn_Q3_sw=np.poly1d(fit_Q3_sw)
>
> plt.plot(hs_Q3_con_sw,hs_Q3_fut_sw,'b.')
> plt.plot(hs_Q3_con_sw,fit_fn_Q3_sw(hs_Q3_con_sw),'b',label='Q3 low sens')
>
> fit_Q4_sw=np.polyfit(hs_Q4_con_sw,hs_Q4_fut_sw,1)
> fit_fn_Q4_sw=np.poly1d(fit_Q4_sw)
>
> plt.plot(hs_Q4_con_sw,hs_Q4_fut_sw,'y.')
> plt.plot(hs_Q4_con_sw,fit_fn_Q4_sw(hs_Q4_con_sw),'y',label='Q4 low sens')
>
> fit_Q14_sw=np.polyfit(hs_Q14_con_sw,hs_Q14_fut_sw,1)
> fit_fn_Q14_sw=np.poly1d(fit_Q14_sw)
>
> plt.plot(hs_Q14_con_sw,hs_Q14_fut_sw,'r.')
> plt.plot(hs_Q14_con_sw,fit_fn_Q14_sw(hs_Q14_con_sw),'r',label='Q14 high
> sens')
>
> fit_Q16_sw=np.polyfit(hs_Q16_con_sw,hs_Q16_fut_sw,1)
> fit_fn_Q16_sw=np.poly1d(fit_Q16_sw)
>
> plt.plot(hs_Q16_con_sw,hs_Q16_fut_sw,'c.')
> plt.plot(hs_Q16_con_sw,fit_fn_Q16_sw(hs_Q16_con_sw),'c',label='Q16 high
> sens')
>
> plt.legend(loc='best')
> plt.xlabel('Significant Wave Height annual averages NW Scotland 1981-2010')
> plt.ylabel('Significant Wave Height annual averages NW Scotland 2040-2069')
> plt.title('Scatter plot of Significant Wave Height')
> plt.show()
>
> --
>
> What I would like to do is display the R squared value next to the line of
> best fits that I have made.
>
> Does anyone know how to do this with matplotlib?
>

​You can add plain text or annotations with arrows using any of the API
functions described here:
http://matplotlib.org/1.3.1/users/text_intro.html(information
specifically regarding the text call is here:
http://matplotlib.org/1.3.1/api/pyplot_api.html#matplotlib.pyplot.text)

You can also use LaTeX typesetting here, so you can make the text something
like r'$R^2$' to display R^2 with "nice" typesetting. (I typically use raw
strings for matplotlib text strings with LaTeX formulas in them since LaTeX
makes extensive use of the \ character.)

The onus is on you, the programmer, to determine _where_ on the plot you
want the text to appear.  Since you know what you are plotting, you can
write a quick helper function that will compute the optimal (to you)
location for the label to occur based on where things are drawn on the
canvas.  There is a _lot_ of flexibility here so you should be able to get
your text looking exactly how (and where) you want it.

Hope this helps,
Jason

-- 
Jason M. Swails
BioMaPS,
Rutgers University
Postdoctoral Researcher

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#72719

On Wednesday, May 21, 2014 1:30:16 PM UTC+1, Jason Swails wrote:
> 
> 
> 
> 
> 
> 
> On Wed, May 21, 2014 at 7:59 AM, Jamie Mitchell <jamiemit...@gmail.com> wrote:
> 
> I have made a plot using the following code:
> 
> 
> 
> python2.7
> 
> import netCDF4
> 
> import matplotlib.pyplot as plt
> 
> import numpy as np
> 
> 
> 
> swh_Q0_con_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q0/swh/controlperiod/south_west/swhcontrol_swest_annavg1D.nc','r')
> 
> hs_Q0_con_sw=swh_Q0_con_sw.variables['hs'][:]
> 
> swh_Q3_con_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q3/swh/controlperiod/south_west/swhcontrol_swest_annavg1D.nc','r')
> 
> hs_Q3_con_sw=swh_Q3_con_sw.variables['hs'][:]
> 
> swh_Q4_con_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q4/swh/controlperiod/south_west/swhcontrol_swest_annavg1D.nc','r')
> 
> hs_Q4_con_sw=swh_Q4_con_sw.variables['hs'][:]
> 
> swh_Q14_con_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q14/swh/controlperiod/south_west/swhcontrol_swest_annavg1D.nc','r')
> 
> hs_Q14_con_sw=swh_Q14_con_sw.variables['hs'][:]
> 
> swh_Q16_con_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q16/swh/controlperiod/south_west/swhcontrol_swest_annavg1D.nc','r')
> 
> hs_Q16_con_sw=swh_Q16_con_sw.variables['hs'][:]
> 
> swh_Q0_fut_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q0/swh/2050s/south_west/swh2050s_swest_annavg1D.nc','r')
> 
> hs_Q0_fut_sw=swh_Q0_fut_sw.variables['hs'][:]
> 
> swh_Q3_fut_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q3/swh/2050s/south_west/swh2050s_swest_annavg1D.nc','r')
> 
> hs_Q3_fut_sw=swh_Q3_fut_sw.variables['hs'][:]
> 
> swh_Q4_fut_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q4/swh/2050s/south_west/swh2050s_swest_annavg1D.nc','r')
> 
> hs_Q4_fut_sw=swh_Q4_fut_sw.variables['hs'][:]
> 
> swh_Q14_fut_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q14/swh/2050s/south_west/swh2050s_swest_annavg1D.nc','r')
> 
> hs_Q14_fut_sw=swh_Q14_fut_sw.variables['hs'][:]
> 
> swh_Q16_fut_sw=netCDF4.Dataset('/data/cr1/jmitchel/Q16/swh/2050s/south_west/swh2050s_swest_annavg1D.nc','r')
> 
> hs_Q16_fut_sw=swh_Q16_fut_sw.variables['hs'][:]
> 
> 
> 
> fit_Q0_sw=np.polyfit(hs_Q0_con_sw,hs_Q0_fut_sw,1)
> 
> fit_fn_Q0_sw=np.poly1d(fit_Q0_sw)
> 
> 
> 
> plt.plot(hs_Q0_con_sw,hs_Q0_fut_sw,'g.')
> 
> plt.plot(hs_Q0_con_sw,fit_fn_Q0_sw(hs_Q0_con_sw),'g',label='Q0 no pert')
> 
> 
> 
> fit_Q3_sw=np.polyfit(hs_Q3_con_sw,hs_Q3_fut_sw,1)
> 
> fit_fn_Q3_sw=np.poly1d(fit_Q3_sw)
> 
> 
> 
> plt.plot(hs_Q3_con_sw,hs_Q3_fut_sw,'b.')
> 
> plt.plot(hs_Q3_con_sw,fit_fn_Q3_sw(hs_Q3_con_sw),'b',label='Q3 low sens')
> 
> 
> 
> fit_Q4_sw=np.polyfit(hs_Q4_con_sw,hs_Q4_fut_sw,1)
> 
> fit_fn_Q4_sw=np.poly1d(fit_Q4_sw)
> 
> 
> 
> plt.plot(hs_Q4_con_sw,hs_Q4_fut_sw,'y.')
> 
> plt.plot(hs_Q4_con_sw,fit_fn_Q4_sw(hs_Q4_con_sw),'y',label='Q4 low sens')
> 
> 
> 
> fit_Q14_sw=np.polyfit(hs_Q14_con_sw,hs_Q14_fut_sw,1)
> 
> fit_fn_Q14_sw=np.poly1d(fit_Q14_sw)
> 
> 
> 
> plt.plot(hs_Q14_con_sw,hs_Q14_fut_sw,'r.')
> 
> plt.plot(hs_Q14_con_sw,fit_fn_Q14_sw(hs_Q14_con_sw),'r',label='Q14 high sens')
> 
> 
> 
> fit_Q16_sw=np.polyfit(hs_Q16_con_sw,hs_Q16_fut_sw,1)
> 
> fit_fn_Q16_sw=np.poly1d(fit_Q16_sw)
> 
> 
> 
> plt.plot(hs_Q16_con_sw,hs_Q16_fut_sw,'c.')
> 
> plt.plot(hs_Q16_con_sw,fit_fn_Q16_sw(hs_Q16_con_sw),'c',label='Q16 high sens')
> 
> 
> 
> plt.legend(loc='best')
> 
> plt.xlabel('Significant Wave Height annual averages NW Scotland 1981-2010')
> 
> plt.ylabel('Significant Wave Height annual averages NW Scotland 2040-2069')
> 
> plt.title('Scatter plot of Significant Wave Height')
> 
> plt.show()
> 
> 
> 
> --
> 
> 
> 
> What I would like to do is display the R squared value next to the line of best fits that I have made.
> 
> 
> 
> Does anyone know how to do this with matplotlib?
> 
> 
> 
> You can add plain text or annotations with arrows using any of the API functions described here: http://matplotlib.org/1.3.1/users/text_intro.html (information specifically regarding the text call is here: http://matplotlib.org/1.3.1/api/pyplot_api.html#matplotlib.pyplot.text)
> 
> 
> 
> You can also use LaTeX typesetting here, so you can make the text something like r'$R^2$' to display R^2 with "nice" typesetting. (I typically use raw strings for matplotlib text strings with LaTeX formulas in them since LaTeX makes extensive use of the \ character.)
> 
> 
> 
> The onus is on you, the programmer, to determine _where_ on the plot you want the text to appear.  Since you know what you are plotting, you can write a quick helper function that will compute the optimal (to you) location for the label to occur based on where things are drawn on the canvas.  There is a _lot_ of flexibility here so you should be able to get your text looking exactly how (and where) you want it.
> 
> 
> 
> Hope this helps,
> Jason
> 
> 
> -- 
> 
> Jason M. Swails
> BioMaPS,
> Rutgers University
> Postdoctoral Researcher

Hi Jason,

Thank you for your swift response - you solved my problem!

Sorry I took a while to get back to you.

Thanks again,

Jamie

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