In [1]:

    

CURRENT_SAMPLE="S1W7D21_15_09_11"
# import helper functions including automated setup
from agilentpyvisa.reram_helpers_B1500 import *

# display images in the notebook %matplotlib notebook makes them interactive!
%matplotlib inline

import os
import os.path
today=datetime.today().strftime("%Y-%m-%d")
already_in = today in os.path.abspath(".")
if not already_in and not os.path.exists(today):
    os.mkdir(today)
if not already_in:
    os.chdir(today)
print("Working directory:")
print(os.path.abspath("."))

form_data={}
annealing_data={}


    

    




C:\Users\krawczuk\Desktop\agilentpyvisa\agilentpyvisa\reram_helpers_B1500\__init__.py:332: SyntaxWarning: assertion is always true, perhaps remove parentheses?
  assert(all([k in form_data for k in form_keys]),"Ensure that form_data has keys {}".format(form_keys))
C:\Users\krawczuk\Desktop\agilentpyvisa\agilentpyvisa\reram_helpers_B1500\__init__.py:335: SyntaxWarning: assertion is always true, perhaps remove parentheses?
  assert(all([isinstance(k,int) for k in annealing_data.keys()]),"Ensure annealing data is a dict with only int as keys")
C:\Users\krawczuk\Desktop\agilentpyvisa\agilentpyvisa\reram_helpers_B1500\__init__.py:336: SyntaxWarning: assertion is always true, perhaps remove parentheses?
  assert(all(






    




('GPIB1::17::INSTR', 'ASRL1::INSTR', 'ASRL10::INSTR')
Setting 'tester_id' to GPIB1::17::INSTR and creating test_object b15 to be used in tests.If you want to change this, set 'tester_id' globally and either reimport or recreate the b15 object
101 HVSPGU
102 HVSPGU
2 HRSMU
3 HRSMU
4 HRSMU
5 HRSMU
6 MFCFMU
Setting SMU2 to 3
Setting SMU1 to 3
Setting SMU3 to 3
Setting SMU4 to 3
Working directory:
C:\Users\krawczuk\Desktop\agilentpyvisa\2016-07-26

In [2]:

    

form_sweep= plt.figure(figsize=[10,5])
f=form(3,100,10e-3, mrange=MeasureRanges_I.uA10_limited,gate=1.9)
f.to_csv("{}_form_3V.csv".format(datetime.now().strftime('%Y-%m-%d_%H-%M-%S')))
plt.autoscale()
form_data={}
form_data['FORM_GATE']=1.9
print(checkR(CURRENT_SAMPLE))
form_data['FORM_V']=find_set_V(f)
print("Forming Voltage:",form_data['FORM_V'])


    

    




                 EI             ET          EV  cumulative_energy  \
count  2.000000e+02     200.000000  200.000000       2.000000e+02   
mean   8.683061e-05  331980.607000    1.500000       5.524041e-05   
std    9.228324e-05       0.308263    0.876928       6.300931e-05   
min   -1.750000e-08  331980.100000    0.000000      -3.454375e-10   
25%    0.000000e+00  331980.300000    0.749937      -2.393750e-10   
50%    5.376000e-06  331980.600000    1.500000       8.595856e-08   
75%    1.913000e-04  331980.900000    2.250063       1.304572e-04   
max    1.939000e-04  331981.100000    3.000000       1.546074e-04   

                  R  
count  2.000000e+02  
mean            inf  
std             NaN  
min   -4.242500e+09  
25%    3.038044e+03  
50%    8.786068e+03  
75%    4.359622e+06  
max             inf  
3680.0901581434264
3.0






    






<matplotlib.figure.Figure at 0x45e2208>






    













    

In [5]:

    

print(checkR(CURRENT_SAMPLE))
r=reset_sweep(-1.5,100,5e-3, mrange=MeasureRanges_I.uA10_limited,gate=1.9,plot=True)
r.to_csv("{}_reset_{}.csv".format(datetime.now().strftime('%Y-%m-%d_%H-%M-%S'), CURRENT_SAMPLE))
print(checkR(CURRENT_SAMPLE))


    

    




3912.6420082359355
                 EI             ET          EV  cumulative_energy  \
count  2.000000e+02     200.000000  200.000000         200.000000   
mean  -1.761234e-04  332097.103500   -0.750000           0.000086   
std    1.095591e-04       0.277892    0.438458           0.000064   
min   -3.752000e-04  332096.600000   -1.500000          -0.000000   
25%   -2.766500e-04  332096.900000   -1.125000           0.000023   
50%   -1.840000e-04  332097.100000   -0.750000           0.000091   
75%   -7.163750e-05  332097.300000   -0.375000           0.000151   
max   -3.000000e-09  332097.600000    0.000000           0.000161   

                  R  
count    200.000000  
mean    4940.963811  
std     2134.773661  
min       -0.000000  
25%     3253.118569  
50%     4417.567422  
75%     6125.562375  
max    10336.620197  
11817.71570014144






    













    

In [6]:

    

print(checkR(CURRENT_SAMPLE))
s=set_sweep(1.0,100,5e-3, mrange=MeasureRanges_I.uA10_limited,gate=1.9,plot=True)
s.to_csv("{}_set_{}.csv".format(datetime.now().strftime('%Y-%m-%d_%H-%M-%S'), CURRENT_SAMPLE))
print("Set Voltage:", find_set_V(s))
print(checkR(CURRENT_SAMPLE))


    

    




11894.199346405227
                 EI             ET          EV  cumulative_energy  \
count  2.000000e+02     200.000000  200.000000         200.000000   
mean   1.235078e-04  332102.075500    0.500001           0.000039   
std    7.194625e-05       0.282753    0.292322           0.000031   
min    7.500000e-09  332101.600000    0.000000           0.000000   
25%    4.938750e-05  332101.800000    0.249975           0.000001   
50%    1.690250e-04  332102.100000    0.500050           0.000043   
75%    1.880000e-04  332102.300000    0.750025           0.000071   
max    1.903000e-04  332102.600000    1.000000           0.000080   

                  R  
count    200.000000  
mean    4894.913316  
std     2647.232400  
min        0.000000  
25%     2769.241653  
50%     4102.715521  
75%     5701.830296  
max    10813.704497  
Set Voltage: 0.5556
2974.5158531891893






    













    

In [7]:

    

rh=get_hist(r)
plt.plot(rh['EV'],rh['R'])


    

    
Out[7]:





[<matplotlib.lines.Line2D at 0xa798b00>]






    

In [8]:

    

sh=get_hist(s)
plt.plot(sh['EV'],sh['R'])


    

    
Out[8]:





[<matplotlib.lines.Line2D at 0xa9fb7b8>]






    

In [10]:

    

frames,annealing_data=anneal(CURRENT_SAMPLE,setV=1.0,resetV=-1.5,gateV=1.9,steps=100,times=3, plot=True,sleep_between=1)


    

    




Reset with Peak -1.5V, 100 steps, gate 1.9V
                 EI             ET          EV  cumulative_energy  \
count  2.000000e+02     200.000000  200.000000         200.000000   
mean  -1.857727e-04  332207.353500   -0.750000           0.000097   
std    1.125651e-04       0.284945    0.438458           0.000070   
min   -3.736500e-04  332206.800000   -1.500000           0.000000   
25%   -2.787375e-04  332207.100000   -1.125000           0.000017   
50%   -2.021500e-04  332207.400000   -0.750000           0.000128   
75%   -7.915375e-05  332207.600000   -0.375000           0.000171   
max    6.000000e-09  332207.800000    0.000000           0.000177   

                  R  
count    200.000000  
mean    4826.190171  
std     2419.541078  
min        0.000000  
25%     2371.160550  
50%     4610.690568  
75%     6031.510461  
max    10493.614084  
Histmax 8217.313072677334
HRS 11756.364922206505
Set with Peak 1.0V, 100 steps, gate 1.9V
                 EI             ET          EV  cumulative_energy            R
count  2.000000e+02     200.000000  200.000000         200.000000   200.000000
mean   3.386764e-04  332211.716000    0.500001           0.000110  1671.396667
std    2.386038e-04       0.289938    0.292322           0.000093   501.452176
min   -5.500000e-09  332211.200000    0.000000          -0.000000    -0.000000
25%    1.328750e-04  332211.500000    0.249975           0.000013  1308.938078
50%    2.886250e-04  332211.700000    0.500050           0.000089  1391.502863
75%    5.356750e-04  332212.000000    0.750025           0.000219  2212.257037
max    8.078500e-04  332212.200000    1.000000           0.000228  2568.014238
Histmax 1154.9673016760562
Set V 0.6465
LRS 1931.8858890273311
Reset with Peak -1.5V, 100 steps, gate 1.9V
                 EI             ET          EV  cumulative_energy  \
count  2.000000e+02     200.000000  200.000000         200.000000   
mean  -2.959762e-04  332216.138000   -0.750000           0.000172   
std    3.010121e-04       0.286121    0.438458           0.000117   
min   -9.933500e-04  332215.600000   -1.500000          -0.000000   
25%   -4.752875e-04  332215.900000   -1.125000           0.000036   
50%   -1.770500e-04  332216.100000   -0.750000           0.000222   
75%   -6.577875e-05  332216.400000   -0.375000           0.000282   
max   -1.500000e-09  332216.600000    0.000000           0.000285   

                  R  
count    200.000000  
mean    5864.869768  
std     4814.117754  
min       -0.000000  
25%     1325.183792  
50%     6393.066100  
75%     9055.495891  
max    16405.264107  
Histmax 14998.989960533656
HRS 18173.955296404278
Set with Peak 1.0V, 100 steps, gate 1.9V
                 EI             ET          EV  cumulative_energy            R
count  2.000000e+02     200.000000  200.000000         200.000000   200.000000
mean   2.536467e-04  332220.524500    0.500001           0.000081  2483.660481
std    1.965618e-04       0.287687    0.292322           0.000072  1102.955504
min   -7.500000e-09  332220.000000    0.000000          -0.000000    -0.000000
25%    8.736250e-05  332220.300000    0.249975           0.000007  1606.371989
50%    1.907250e-04  332220.500000    0.500050           0.000053  1734.362291
75%    4.223875e-04  332220.800000    0.750025           0.000166  3796.039106
max    6.635500e-04  332221.000000    1.000000           0.000174  4375.609228
Histmax 2665.194325145061
Set V 1.0
LRS 2219.058287677223
Reset with Peak -1.5V, 100 steps, gate 1.9V
                 EI             ET          EV  cumulative_energy  \
count  2.000000e+02     200.000000  200.000000         200.000000   
mean  -2.117619e-04  332224.903000   -0.750000           0.000111   
std    1.968741e-04       0.287584    0.438458           0.000072   
min   -6.528000e-04  332224.400000   -1.500000          -0.000000   
25%   -3.289000e-04  332224.700000   -1.125000           0.000045   
50%   -1.499500e-04  332224.900000   -0.750000           0.000141   
75%   -5.224750e-05  332225.125000   -0.375000           0.000177   
max    2.500000e-09  332225.400000    0.000000           0.000182   

                  R  
count    200.000000  
mean    7552.700577  
std     6303.705016  
min       -0.000000  
25%     1675.489835  
50%     7449.897410  
75%    11396.402079  
max    23090.586146  
Histmax 21351.289509562685
HRS 20992.857142857145
Set with Peak 1.0V, 100 steps, gate 1.9V
                 EI             ET          EV  cumulative_energy            R
count  2.000000e+02     200.000000  200.000000         200.000000   200.000000
mean   2.566703e-04  332229.115500    0.500001           0.000081  2425.768389
std    1.964236e-04       0.289185    0.292322           0.000072  1046.326631
min   -8.500000e-09  332228.600000    0.000000          -0.000000    -0.000000
25%    8.868625e-05  332228.900000    0.249975           0.000008  1601.426693
50%    1.949250e-04  332229.100000    0.500050           0.000059  1721.346712
75%    4.188750e-04  332229.400000    0.750025           0.000167  3617.679708
max    6.657500e-04  332229.600000    1.000000           0.000174  4086.587093
Histmax 2434.570485123048
Set V 0.798
LRS 2273.9185614062194






    













    













    













    













    













    













    













    













    

In [ ]:

    

pat = get_pyramid_pattern