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Advanced Access to Sample Logs

Sample Log Properties

It can be useful to access different properties from the Sample Logs, or add to them:

from mantid.simpleapi import *

# Standard Sample Log set-up
ws = Load('CNCS_7860_event')
run = ws.getRun()
chopper = run.getLogData('ChopperStatus1')

print('\n### Original Sample Logs ###')
print('Number of Entries:',chopper.size())
print('Chopper Values:',chopper.value)
print('Chopper Timestamps:',chopper.times)
print('First Value:',chopper.firstValue())
print('First Time:',chopper.firstTime())
print('Second Value:',chopper.value[1])
print('Second Time:',chopper.times[1])

chopper.addValue('2010-Mar-26 00:00:00.00',5)
print('\n--- Sample Logs with Addition ---')
print('Number of Entries:',chopper.size())
print('Chopper Values:',chopper.value)
print('Chopper Timestamps:',chopper.times)

# Also very nice is valueAsPrettyStr()
print('\n# ', chopper.name)
print(chopper.valueAsPrettyStr())

Output:

### Original Sample Logs ###
Number of Entries: 2
Chopper Values: [ 4.  4.]
Chopper Timestamps: ['2010-03-25T16:09:27.930000000' '2010-03-25T16:11:05.000000000']
First Value: 4.0
First Time: 2010-03-25T16:09:27.930000000
Second Value: 4.0
Second Time: 2010-03-25T16:11:05.000000000

--- Sample Logs with Addition ---
Number of Entries: 3
Chopper Values: [ 4.  4.  5.]
Chopper Timestamps: ['2010-03-25T16:09:27.930000000' '2010-03-25T16:11:05.000000000'
 '2010-03-26T00:00:00.000000000']

#  ChopperStatus1
2010-Mar-25 16:09:27.930000000  4
2010-Mar-25 16:11:05  4
2010-Mar-26 00:00:00  5

Auto-filtered Access

Sample Logs can be automatically filtered. If so, they will have been filtered by run_status and also by period_log if the data has been captured in multiple separate periods. While it is easy to view a plot of the un/filtered logs with the Filtered tickbox, here’s how to access such values in a script:

# Only access filtered properties
print(chopper.filtered_value)
print(chopper.filtered_times)

# Access all values
print(chopper.unfiltered().value)
print(chopper.unfiltered().times)

Invalid Values

The same access to values filtered by run_status or period_log, also applies to those filtered for bad or invalid values. Whether entries are invalid values is marked in a hidden log called LOGNAME_invalid_values, which can be found with ` model.get_hidden_logs()`.

# import mantid algorithms and SampleLogsModel
from mantid.simpleapi import *
from mantidqt.widgets.samplelogs.model import SampleLogsModel

ws = Load('ENGINX00228061_log_alarm_data.nxs')
model = SampleLogsModel(ws)

invalid_logs = model.get_logs_with_invalid_data()
# -1:Fully Invalid, 1:Partially Invalid
print("Dictionary of Invalid Logs:",invalid_logs)

for count,key in enumerate(invalid_logs.keys()):
    log_data = ws.getRun().getLogData(key)
    invalid_entries = ws.getRun().getLogData(key + '_invalid_values').value
    filtered_entries = log_data.filtered_value
    unfiltered_entries = log_data.unfiltered().value
    print("\nInvalid Log {}:".format(count+1), log_data.name )
    print("Unfiltered Values:",unfiltered_entries)
    print('Which entries are good:',invalid_entries)
    print("Filtered Values:",filtered_entries)

log_data_CT1 = ws.getRun().getLogData('cryo_temp1')
status = ws.getRun().getLogData('Status')

print('\n# ', log_data_CT1.name)
print(log_data_CT1.valueAsPrettyStr())
print('# ', status.name)
print(status.valueAsPrettyStr())

In the output below, you will notice that all entries for cryo_temp2 are invalid and so there is no filter applied. For cryo_temp1, the value 5.0 is filtered out for being marked invalid, but the value 3.0 is also filtered out as it occurred before the status log was set to RUNNING. For more information, see: Invalid Sample Logs.

Output:

Dictionary of Invalid Logs: {'cryo_temp1': 1, 'cryo_temp2': -1}
Invalid Log 1: cryo_temp1
Unfiltered Values: [ 3.  5.  7.]
Which entries are good: [ True False  True]
Filtered Values: [ 7.]

Invalid Log 2: cryo_temp2
Unfiltered Values: [ 3.  5.  7.]
Which entries are good: [False False False]
Filtered Values: [ 3.  5.  7.]

#  cryo_temp1
2015-Mar-17 12:55:12  3
2015-Mar-17 12:55:17  5
2015-Mar-17 12:55:32  7

#  Status
2015-Mar-17 12:55:11  SETUP
2015-Mar-17 12:55:17  RUNNING

Plotting Sample Logs

Mantid helps you plot Sample Logs from a workspace, without formally accessing them.

• Produce a plot from the “Show Sample Logs” interface, by right-clicking on the log entry or double-clicking on the plot. Next, look for plot toolbar button to generate a script for producing this plot for some inspiration!

• Check out the source code for the tiled plot in Sample Logs, which plots using something similar to:

axes.plot(CNCS_7860_event, ExperimentInfo=0, Filtered=True, LogName='SampleTemp')