create 20 lines of databroker code

[prjemian]

image analysis using data from previous session packed and unpacked with databroker-pack

[prjemian]

See this notebook for some example.

[prjemian]

Use print() instead of a pretty table like pyRestTable.

[prjemian]

this is a minimal example:

(class_2021_03) jemian@vm:~$ ipython
Python 3.8.8 (default, Feb 24 2021, 21:46:12) 
Type 'copyright', 'credits' or 'license' for more information
IPython 7.21.0 -- An enhanced Interactive Python. Type '?' for help.

In [1]: import databroker
   ...: from scipy import ndimage
   ...: from apstools.utils import listruns
   ...: 
   ...: cat = databroker.catalog["class_data_examples"]
   ...: print(f"{len(cat) = }")
   ...: listruns(db=cat.v1)
   ...: 
len(cat) = 59
catalog name: class_data_examples
========= ========================== ======= ======= ========================================
short_uid date/time                  exit    scan_id command                                 
========= ========================== ======= ======= ========================================
f7b96eb   2021-02-26 15:53:08.941444 unknown 65      count(detectors=['adsimdet'], num=1)    
e693870   2021-02-22 19:04:06.141078 success 39      scan(detectors=['temperature_setpoin ...
4fe01dd   2021-02-22 18:29:28.631949 success 32      count(detectors=['temperature'], num=20)
1dbed4f   2021-02-26 15:30:24.568066 unknown 61      count(detectors=['adsimdet'], num=1)    
361400d   2021-02-26 15:44:16.602373 unknown 64      count(detectors=['adsimdet'], num=1)    
56c2dae   2021-02-23 10:34:00.034502 success 45      scan(detectors=['temperature_setpoin ...
6bb9a4b   2021-02-22 18:38:24.851409 abort   37      scan(detectors=['temperature_setpoin ...
0eca468   2021-03-03 10:40:35.430278 success 76      count(detectors=['adsimdet'], num=1)    
2befeb8   2021-02-26 15:38:32.784263 unknown 62      count(detectors=['adsimdet'], num=1)    
c49f204   2021-02-26 00:21:35.750333 unknown 52      count(detectors=['adsimdet'], num=1)    
daaebeb   2021-02-27 16:24:52.777810 success 73      count(detectors=['adsimdet'], num=1)    
4705e97   2021-02-22 18:59:06.562506 success 38      scan(detectors=['temperature_setpoin ...
75b01ca   2021-03-03 10:48:19.682975 success 80      count(detectors=['adsimdet'], num=1)    
01013b8   2021-02-23 00:16:12.899690 success 42      scan(detectors=['temperature_setpoin ...
7e309ce   2021-02-22 18:33:49.130694 success 34      count(detectors=['temperature'], num=20)
37d2c3b   2021-02-23 10:35:02.214576 success 46      scan(detectors=['temperature_setpoin ...
0401c91   2021-03-06 15:10:19.356874 success 83      rel_scan(detectors=['noisy'], num=23 ...
a8bcac2   2021-03-06 15:16:41.614573 success 90      scan(detectors=['noisy'], num=21, ar ...
1219f70   2021-02-26 16:04:30.688444 unknown 68      count(detectors=['adsimdet'], num=1)    
6255bc8   2021-03-03 10:45:35.730732 success 79      count(detectors=['adsimdet'], num=1)    
========= ========================== ======= ======= ========================================

Out[1]: <pyRestTable.rest_table.Table at 0x7ff735871f40>

In [2]: run = cat.search({"scan_id": 44})[-1]
   ...: ds = run.primary.read()
   ...: np_arr = ds["temperature_readback"]
   ...: print(f"{np_arr.mean().values = }")
   ...: print(f"{np_arr.std().values  = }")
   ...: 
np_arr.mean().values = array(78.30275489)
np_arr.std().values  = array(76.86473889)

In [3]: # TODO: repeat for scan_id = 57
   ...: 

In [4]: run = cat.search({"scan_id": 80})[-1]
   ...: ds = run.primary.read()
   ...: np_frame = ds["adsimdet_image"][0][0].to_masked_array()
   ...: print(f"{ndimage.measurements.center_of_mass(np_frame)   = }")
   ...: print(f"{ndimage.measurements.maximum_position(np_frame) = }")
   ...: print(f"{np_frame.max() = }")
   ...: print(f"{np_frame.min() = }")
   ...: 
ndimage.measurements.center_of_mass(np_frame)   = (443.4099839785622, 444.8162751497467)
ndimage.measurements.maximum_position(np_frame) = (101, 108)
np_frame.max() = 190
np_frame.min() = 7

In [5]: 

[prjemian]

the extra TODO:

In [5]: run = cat.search({"scan_id": 57})[-1]
   ...: ds = run.primary.read()
   ...: np_arr = ds["temperature_readback"]
   ...: print(f"{np_arr.mean().values = }")
   ...: print(f"{np_arr.std().values  = }")
   ...: 
np_arr.mean().values = array(24.99790311)
np_arr.std().values  = array(0.28447621)