Hi, I'm pretty new to sage and am currently trying it out with cloud.sagemath and sage on ubuntu. I'm trying to fit some data to an arrhenius equation of a continuous stirred tank reactor-model. So far, I've managed to import data from a .csv-file and convert it into a matrix:

```
import numpy as np
import csv
R = 8.314462 [J/mol/K]
yield = []
temp = []
t_res = [] #residence time
conc_init = [] #initial concentration
data2 = list(csv.reader(file('manuel2.csv'), delimiter=';'))
m = matrix([[ float(_) for _ in line] for line in data2])
n = np.vstack(m)
##now I'm converting the matrix into single numpy-arrays:
yield = n[:,0]
temp = n[:,1]
t_res = n[:,2]
conc_init = n[:,4]
conc = conc_init - yield/100*conc_init #calculate actual concentrations
```

from here I tried to use the find_fit function to fit my data to the arrhenius-equation

```
var('E_A,A')
model(conc)=conc_init - A*exp(-E_A/(R*temp))*conc*t_res
data=(conc,conc_init,temp,t_res)
fit=find_fit(data,model)
```

when I finally evaluate I get this error:

(E_A, k_inf) Error in lines 36-36 Traceback (most recent call last): File "/projects/b9085414-cff2-4e5a-9c3b-872f47d41a7c/.sagemathcloud/sage_server.py", line 736, in execute exec compile(block+'\n', '', 'single') in namespace, locals File "", line 1, in <module> File "/usr/local/sage/sage-6.3.beta6/local/lib/python2.7/site-packages/sage/calculus/all.py", line 96, in symbolic_expression return SR(x) File "parent.pyx", line 1083, in sage.structure.parent.Parent.__call__ (build/cythonized/sage/structure/parent.c:8902) File "coerce_maps.pyx", line 95, in sage.structure.coerce_maps.DefaultConvertMap_unique._call_ (build/cythonized/sage/structure/coerce_maps.c:4203) File "coerce_maps.pyx", line 90, in sage.structure.coerce_maps.DefaultConvertMap_unique._call_ (build/cythonized/sage/structure/coerce_maps.c:4110) File "ring.pyx", line 289, in sage.symbolic.ring.SymbolicRing._element_constructor_ (build/cythonized/sage/symbolic/ring.cpp:5332) TypeError

I actually don't have a clue what that means or how I can get this to work.