In [1]:

    

import sys
sys.path.append('../')
sys.path.append('../../')

from errorpro.interactive import *
init(locals())


    

In [2]:

    

load_file('data')


    

In [3]:

    

E = assign([E1.value, E2.value, E3.value, E4.value, E5.value, E6.value, E7.value, E8.value, E9.value, E10.value],
           error='0.05', name='E', unit='V')
m, b = params('m b')
E0_m = mean(E0)
E_real = assign(E-mean(E0))
fit(m*(U) + b, U, E_real, [m, b])


    

    
Out[3]:





Results of fit
Results
 

	

		
$m \; \mathrm{\left[1\right]}$
		
$b \; \mathrm{\left[V\right]}$
	
	

		
$0.00081 \phantom{0} \pm 0.00005 \phantom{0}$
		
$1.0 \phantom{0} \pm 0.4 \phantom{0}$
	
	

		
$0.00066 \phantom{0} \pm 0.00005 \phantom{0}$
		
$0.83 \pm 0.26$
	
	

		
$0.00054 \phantom{0} \pm 0.00004 \phantom{0}$
		
$0.68 \pm 0.21$
	
	

		
$0.000457 \pm 0.000030$
		
$0.53 \pm 0.19$
	
	

		
$0.00036 \phantom{0} \pm 0.00004 \phantom{0}$
		
$0.50 \pm 0.22$
	
	

		
$0.000338 \pm 0.000019$
		
$0.28 \pm 0.12$
	
	

		
$0.000224 \pm 0.000012$
		
$0.17 \pm 0.08$
	
	

		
$0.000155 \pm 0.000008$
		
$0.07 \pm 0.05$
	
	

		
$0.000107 \pm 0.000008$
		
$0.02 \pm 0.05$
	
	

		
$0.000065 \pm 0.000009$
		
$0.01 \pm 0.06$
	
 

In [4]:

    

plot(U, slice(m,0,1)*U+slice(b,0,1),
     U, slice(m,1,2)*U+slice(b,1,2),
     U, slice(m,2,3)*U+slice(b,2,3),
     U, slice(m,3,4)*U+slice(b,3,4),
     U, slice(m,4,5)*U+slice(b,4,5),
     U, slice(m,5,6)*U+slice(b,5,6),
     U, slice(m,6,7)*U+slice(b,6,7),
     U, slice(m,7,8)*U+slice(b,7,8),
     U, slice(m,8,9)*U+slice(b,8,9),
     U, slice(m,9,10)*U+slice(b,9,10),
     U, assign(np.rollaxis(E_real.value,1)[0], unit='V'),
     U, assign(np.rollaxis(E_real.value,1)[1], unit='V'),
     U, assign(np.rollaxis(E_real.value,1)[2], unit='V'),
     U, assign(np.rollaxis(E_real.value,1)[3], unit='V'),
     U, assign(np.rollaxis(E_real.value,1)[4], unit='V'),
     U, assign(np.rollaxis(E_real.value,1)[5], unit='V'),
     U, assign(np.rollaxis(E_real.value,1)[6], unit='V'),
     U, assign(np.rollaxis(E_real.value,1)[7], unit='V'),
     U, assign(np.rollaxis(E_real.value,1)[8], unit='V'),
     U, assign(np.rollaxis(E_real.value,1)[9], unit='V'),
    legend=False, size=[8,5])


    

In [8]:

    

p, q = params('p q')
z = fit(p/s**q, s, m, [p,q], ignore_dim=True)
plot(s, m, {'marker':'x'},
     s, p/s**q, {'color':'blue'},
     xscale='log', yscale='log', xrange=[0.15,0.55], yrange=[4e-5,1e-3], size=[7,5], ignore_dim=True)


    

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