

In [3]:

    
import papermill as pm
from pyCHX.chx_packages import *
%matplotlib notebook
plt.rcParams.update({'figure.max_open_warning': 0})
plt.rcParams.update({ 'image.origin': 'lower'   })
plt.rcParams.update({ 'image.interpolation': 'none'   })
import pickle as cpk
from pyCHX.chx_xpcs_xsvs_jupyter_V1 import *
import itertools

For test purpose



In [2]:

    
if False:
    a= 10
    b= 20
    Xm=1 
    pm.execute_notebook(
   '/home/yuzhang/analysis/2018_3/commissioning/Test_papermill.ipynb',
   '/home/yuzhang/analysis/2018_3/commissioning/Test_papermill_res2.ipynb',
   parameters = dict( a=a,b=b,Xm=Xm ),
        kernel_name= None, report_mode=True
)



In [8]:

    
get_last_uids( -1)









    Out[8]:





"   uid = 'e01b4e' #(scan num: 24785 (Measurement: Series 0.00134s x 2000 - sample:  CNC 7%         "



In [ ]:

For run XPCS



In [10]:

    
if True:

    uid = '109db9' #(scan num: 24784 (Measurement: Series 0.00134s x 2000 - sample:  CNC 7%         "
     
    pm.execute_notebook(
   '/home/yuzhang/analysis/2018_3/commissioning/XPCS_Single_2018_V13.ipynb',
   '/home/yuzhang/analysis/2018_3/commissioning/XPCS_Single_2018_V13_uid=%s.ipynb'%uid,
   parameters = dict( uid = uid, ), kernel_name= None, report_mode=True 
    
    )









    



Input Notebook:  /home/yuzhang/analysis/2018_3/commissioning/XPCS_Single_2018_V13.ipynb
Output Notebook: /home/yuzhang/analysis/2018_3/commissioning/XPCS_Single_2018_V13_uid=109db9.ipynb
100%|██████████| 190/190 [04:55<00:00,  1.55s/it]



In [ ]:

    
#nbs = pm.read_notebooks('.')
#nbs.display_output('Test_papermill_res.ipynb')



In [16]:

    
#  jupyter nbconvert ResPipes/*.ipynb --to html



In [ ]: