Table of Contents
Name | Direction | Type | Default | Description |
---|---|---|---|---|
Workspace | InOut | Workspace | Mandatory | Workspace to add the log entry to |
LogName | Input | string | Mandatory | The name that will identify the log entry |
LogText | Input | string | The content of the log | |
LogType | Input | string | String | The type that the log data will be. Allowed values: [‘String’, ‘Number’, ‘Number Series’] |
LogUnit | Input | string | The units of the log |
Workspaces contain information in logs. Often these detail what happened to the sample during the experiment. This algorithm allows one named log to be entered.
The log can be either a String, a Number, or a Number Series. If you select Number Series, the workspace start time will be used as the time of the log entry, and the number in the text used as the (only) value.
If the LogText contains a numeric value, the created log will be of integer type if an integer is passed and floating point (double) otherwise. This applies to both the Number & Number Series options.
To add logs that vary over time (Time Series Logs) use AddTimeSeriesLog v1.
Example - Add Sample Logs in different ways
# Create a host workspace
demo_ws = CreateWorkspace(DataX=range(0,3), DataY=(0,2))
# Add sample logs
AddSampleLog(Workspace=demo_ws, LogName='x', LogText='hello world', LogType='String')
AddSampleLog(Workspace=demo_ws, LogName='y', LogText='1', LogType='Number')
AddSampleLog(Workspace=demo_ws, LogName='z', LogText='2', LogType='Number Series')
# Fetch the generated logs
run = demo_ws.getRun()
log_x = run.getLogData('x')
log_y = run.getLogData('y')
log_z = run.getLogData('z')
# Print the log values
print log_x.value
print log_y.value
print log_z.value
Output:
hello world
1
[2]
Categories: Algorithms | DataHandling | Logs