Observable Plotting Tutorial

Basic plotting

For any Palantir Observable, there are some basic ways to plot data.

Throughout this part of the tutorial, we will use a E2EObservable

>>> import palantir.structures as structures

>>> startDate = '231102'
>>> endDate = '231102'
>>> startTime = '000000'
>>> endTime = '100000'

>>> infraID = 1
>>> REFIMEVE = structures.Infrastructure(infraID, startDate, endDate, startTime, endTime, 'UTC')

>>> freq_transfer = REFIMEVE.processE2E(1)
>>> observable = freq_transfer.e2e

Using the plotTrace() Trace

>>> observable.plotTrace(stageKey="stage1")

Using the plotDistribution() Density Distribution

>>> observable.plotDistribution(stageKey="stage1")

Using the plotDeviation() Plot Allan deviation

>>> observable.plotDeviation(method="mdev", stageKey="stage1")

Using the plotPhase() Plot Phase

>>> observable.plotPhase(stageKey="stage1")

Using the plotQuickview() Plot Quickview

>>> observable.plotQuickview(stages=[2,3,4])

Using the plotFilters() Plot filters

>>> observable.plotFilters(stages=[2,3,4])

Using the plotTemplatePage() Plot template

>>> observable.plotTemplatePage(stageKey="stage1")

Using the plotAllTemplates() Plot All Templates

>>> observable.plotAllTemplates()

Measuring Instrument timestamps drift

TODO

Clock comparison specific plots

Throughout this part of the tutorial, we will use a ClockComparison object of two Strontium clocks as follow :

>>> import palantir.clock_comparisons as clock_comparisons

>>> startDate = '230331'
>>> endDate = '230402'
>>> startTime = '000000'
>>> endTime = '000000'

>>> campaignID = 6
>>> CAMPAIGN_2023 = clock_comparisons.Campaign(campaignID, startDate, endDate, startTime, endTime, timezone='UTC')

>>> module0 = 184
>>> moduleN = 79

>>> PTB_Sr3_CombKnoten_NPL_Sr1 = CAMPAIGN_2023.processClockComparison(module0, moduleN, fetch_local=True)

Plot all the comparators and the comparison in a single plot.

Plot the published frequencies

>>> PTB_Sr3_CombKnoten_NPL_Sr1.plotComparators()

Plot the quality factors

>>> PTB_Sr3_CombKnoten_NPL_Sr1.plotComparators(quality=True)