In [1]:
import sys
sys.path.append('../')
sys.path.append('../../')

%matplotlib inline

from errorpro.default import *
p = default_project

In [2]:
load("teil1.dat")

In [3]:
fit("a4*p**4 + a3*p**3 + a2*p**2 + a1*p + a0", ["p","B"], ["a0","a1","a2","a3","a4"])


Out[3]:
Displaying: $a_{0}$, $a_{1}$, $a_{2}$, $a_{3}$, $a_{4}$



In [4]:
# differentiate fit function
from sympy import diff
from errorpro.quantities import parse_expr
fit_function = parse_expr("a4*p**4 + a2*p**2 + a1*p + a0",p.data)
ableitung = diff(fit_function, p.data["p"])
BdBdh = fit_function*ableitung

# save values of B*dB/dh at certain positions
Bi = BdBdh.subs(p["p"],p.data["p_Bi_m"])
assign("BdBdh_Bi", value=Bi, unit="T**2/m")
Mn = BdBdh.subs(p.data["p"],p.data["p_Mn_m"])
assign("BdBdh_Mn", value=Mn, unit="T**2/m")
Ta = BdBdh.subs(p.data["p"],p.data["p_Ta_m"])
assign("BdBdh_Ta", value=Ta, unit="T**2/m")

In [5]:
%%calc
chi_Bi = F_Bi*mu0/(m_Bi/rho_Bi)/BdBdh_Bi
chi_Mn = F_Mn*mu0/(m_Mn/rho_Mn)/BdBdh_Mn
chi_Ta = F_Ta*mu0/(m_Ta/rho_Ta)/BdBdh_Ta

In [6]:
table("chi_Bi","chi_Mn","chi_Ta")


Out[6]:
Displaying: $\chi_{Bi}$, $\chi_{Mn}$, $\chi_{Ta}$



In [7]:
load("teil2.dat")

In [ ]: