In [4]:

    

# Import Packages
from SimPEG import *
from IPython.html.widgets import interactive
import numpy as np
%pylab inline


    

    




Populating the interactive namespace from numpy and matplotlib






    




WARNING: pylab import has clobbered these variables: ['interactive', 'beta']
`%matplotlib` prevents importing * from pylab and numpy

In [5]:

    

beta_0=1000000 
beta=beta_0
m = np.array([1., 1])*beta
phid = np.dot(m.T,m)**0.5
phi_dstar=20
phid_mid = []
tol = 0.000000000000001
i=1

while np.absolute(phid - phi_dstar)>tol:  
    m = np.array([1., 1])*beta                      #put fcn for m here
    phid = np.dot(m.T,m)**0.5                       #put fcn for phid here
    if phid>phi_dstar:
        beta = beta_0*0.5**i
    if phid<phi_dstar:
        beta_abv = beta_0*0.5**(i-2)
        beta_bel = beta_0*0.5**(i-1)
        beta_mid = 0.5*(beta_abv+beta_bel)
        mmid = np.array([1., 1])*beta_mid              #put fcn for m here
        phidmid = np.dot(mmid.T,mmid)**0.5             #put fcn for phid here
        while np.absolute(phidmid - phi_dstar)>tol:
            if phidmid<phi_dstar:
                beta_abv = beta_0*0.5**(i-2)
                beta_bel = beta_mid
                beta_mid = 0.5*(beta_abv+beta_bel)
                beta=beta_mid
                mmid = np.array([1., 1])*beta_mid      #put fcn for m here
                phidmid = np.dot(mmid.T,mmid)**0.5     #put fcn for phi here     
            if phidmid>phi_dstar:
                beta_abv = beta_mid
                beta_bel = beta_bel
                beta_mid = 0.5*(beta_abv+beta_bel)
                beta=beta_mid
                mmid = np.array([1., 1])*beta_mid      #put fcn for m here
                phidmid = np.dot(mmid.T,mmid)**0.5     #put fcn for phi here            
                if phidmid<phi_dstar:
                    beta_abv = beta_abv
                    beta_bel = beta_mid
                    beta_mid = 0.5*(beta_abv+beta_bel)
                    beta=beta_mid
                    mmid = np.array([1., 1])*beta_mid   #put fcn for m here
                    phidmid = np.dot(mmid.T,mmid)**0.5  #put fcn for phi here
            phid=phidmid
            m=mmid
    i=i+1   
print("At end beta=", beta,"phid=", phid)


    

    




('At end beta=', 14.142135623730951, 'phid=', 20.0)

In [1]:

    

beta_0=1000000 
beta=beta_0
m = np.array([1., 1])*beta
phid = np.dot(m.T,m)**0.5
phi_dstar=20
phid_mid = []
tol = 0.0001
i=1

while np.absolute(phid - phi_dstar)>tol:  
    print("At start beta=", beta)
    m = np.array([1., 1])*beta
    phid = np.dot(m.T,m)**0.5
    print("Start Itn",j, "beta=", beta, "phid=", phid)
    if phid>phi_dstar:
        beta = beta_0*0.5**i
    if phid<phi_dstar:
        beta_abv = beta_0*0.5**(i-2)
        beta_bel = beta_0*0.5**(i-1)
        beta_mid = 0.5*(beta_abv+beta_bel)
        mabv= np.array([1., 1])*beta_abv
        mbel= np.array([1., 1])*beta_bel
        mmid = np.array([1., 1])*beta_mid
        phidabv = np.dot(mabv.T,mabv)**0.5
        phidbel = np.dot(mbel.T,mbel)**0.5
        phidmid = np.dot(mmid.T,mmid)**0.5
        print("Itn # is:",j, "below threshold", "beta above=", beta_abv, "beta below=", beta_bel, "beta mid=",beta_mid)
        print("Itn # is:",j, "below threshold", "phi above=",  phidabv, "phi below=",  phidbel, "phi mid=", phidmid)   
        while np.absolute(phidmid - phi_dstar)>tol:
            if phidmid<phi_dstar:
                beta_abv = beta_0*0.5**(i-2)
                beta_bel = beta_mid
                beta_mid = 0.5*(beta_abv+beta_bel)
                beta=beta_mid
                mabv= np.array([1., 1])*beta_abv
                mbel= np.array([1., 1])*beta_bel
                mmid = np.array([1., 1])*beta_mid
                phidabv = np.dot(mabv.T,mabv)**0.5
                phidbel = np.dot(mbel.T,mbel)**0.5
                phidmid = np.dot(mmid.T,mmid)**0.5
                print("Itn # is:",j, "in R1", "beta above=", beta_abv, "beta below=", beta_bel, "beta mid=",beta_mid)
                print("Itn # is:",j, "in R1", "phi above=",  phidabv, "phi below=",  phidbel, "phi mid=", phidmid)         
            if phidmid>phi_dstar:
                beta_abv = beta_mid
                beta_bel = beta_bel
                beta_mid = 0.5*(beta_abv+beta_bel)
                beta=beta_mid
                mabv= np.array([1., 1])*beta_abv
                mbel= np.array([1., 1])*beta_bel
                mmid = np.array([1., 1])*beta_mid
                phidabv = np.dot(mabv.T,mabv)**0.5
                phidbel = np.dot(mbel.T,mbel)**0.5
                phidmid = np.dot(mmid.T,mmid)**0.5                
                print("Itn # is:",j, "in R2", "beta above=", beta_abv, "beta below=", beta_bel, "beta mid=",beta_mid)
                print("Itn # is:",j, "in R2", "phi above=",  phidabv, "phi below=",  phidbel, "phi mid=", phidmid)
                if phidmid<phi_dstar:
                    beta_abv = beta_abv
                    beta_bel = beta_mid
                    beta_mid = 0.5*(beta_abv+beta_bel)
                    beta=beta_mid
                    mabv= np.array([1., 1])*beta_abv
                    mbel= np.array([1., 1])*beta_bel
                    mmid = np.array([1., 1])*beta_mid
                    phidabv = np.dot(mabv.T,mabv)**0.5
                    phidbel = np.dot(mbel.T,mbel)**0.5
                    phidmid = np.dot(mmid.T,mmid)**0.5
                    print("Itn # is:",j, "in R3", "beta above=", beta_abv, "beta below=", beta_bel, "beta mid=",beta_mid)
                    print("Itn # is:",j, "in R3", "phi above=",  phidabv, "phi below=",  phidbel, "phi mid=", phidmid)  
            phid=phidmid
    print("At end beta=", beta,"phid=", phid)
    i=i+1


    

    




---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-1-2a89a7e084bf> in <module>()
      1 beta_0=1000000
      2 beta=beta_0
----> 3 m = np.array([1., 1])*beta
      4 phid = np.dot(m.T,m)**0.5
      5 phi_dstar=20

NameError: name 'np' is not defined

In [29]:

    

beta=14.142075087875128
m = np.array([1., 1])*beta
phid = np.dot(m.T,m)**0.5
phi_dstar=20
print phid


    

    




19.9999143894

In [ ]: