Tutorial 02

Intro

This tutorial outlines the workflow from data import to the definition of an interpolation function and its application.

The data come from the following article:
Terrigenous input off northern South America driven by changes in Amazonian climate and the North Brazil Current retroflection during the last 250 ka.
Clim. Past, 10, 843–862, 2014
www.clim-past.net/10/843/2014/
doi:10.5194/cp-10-843-2014

-- Prepared by Aline Govin (LSCE)

flowchart LR
A["Import data"] --> B["Define interpolation"] --> C["Apply interpolation"]

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Data import

Import Cibicides data (δ18O and δ13C) from tutorial_02/GeoB3938-1_Data.xlsx, sheet 3938-1 data.

Copy using Ctrl+C (use the down arrow to select all rows). Note that the format used is X, Y1, Y2.
Open the Import Data window in PyAnalySeries, paste the data, and click Import series.

Repeat the same process with the XRF data.

Visual checks

At this stage, you should have a worksheet (WS) as follows:

Rename the worksheet as WS_GeoB3938.xlsx.

You can plot the series individually. It may also be convenient to plot them stacked using Edit / Display Stacked.
Note: a maximum of 8 series can be displayed in the same window.

Import data from tutorial_02/MD95-2042_Ref_Data.xlsx as WS_MD2042.xlsx and from tutorial_02/LR04_Ref_Data.xlsx as WS_LR04.xlsx.

Click on Y axis inverted for δ18O series.

You should now have PyAnalySeries displayed as follows:

Define the interpolation

Import pointers

Import pointers (14C dates) from tutorial_02/GeoB3938-1_Data.xlsx, sheet Dating Data.

From the Import Data window in PyAnalySeries, import them as pointers.

Rename the interpolation as 14C dates and display the imported pointers.

Add more pointers

Now select 14C dates and the relevant series to define new matches between peaks or transitions.
These define additional pointers that will be used for the interpolation function.

Define new pointers using:

• δ18O Cib as the reference serie and δ18O from MD95-2042 as the distorted serie

• δ13C Cib as the reference and δ13C from MD95-2042 as the distorted serie

• and finally δ18O Cib against δ18O LR04

For comparison, you can import all pointers from tutorial_02/GeoB3938-1_Data.xlsx, sheet Dating Data, and check against those you created.

Here are the initial pointers and those created.

Place a pointer on a transition

or hold the Ctrl key to display the data points and position the pointer precisely.

Here is an animated GIF showing the placement of two pointers.

Have a look to the final interpolation function and its gradient.

Apply the interpolation

Now apply the interpolation to the XRF series.

All series are now interpolated.

Visualization

Select the interpolated series and display them with Edit / Display Stacked.

Sampling vs Interpolation

You can compare different approach to smooth the interpolated serie. By applying a moving average :

or by sampling with integration for example :