- Background
- Installation
- Graphical interface
- Functions to support batch processing
- Further information
In order to address several shortcomings with ensuring similitude in examining the output from commercial hydrogen analysers, a modest suite of tools written with freely available Python 3 libraries has been developed to perform basic analyses. This consists of several high-level functions that can be accessed directly from interactive Python, as well as a Graphical User Interface (GUI) to use/demonstrate them.
Analysis requires two data files with the format exemplified, one stemming from a temperature data acquisition device and the second exported from Agilent gas chromotographer data aquisition software, ChemStation. HydroTrace has been specifically developed to merge these records along with other experimental settings to provide:
- Calculate the total hydrogen content;
- Provide desorbtion versus temperature records; and
- Enable extentions to batch processing of hydrogren desorbtion curves and modelling efforts.
Using pip, either install directly from the *.tar.gz archive available in ~/dist (potentially for local installations to Anaconda), or from PyPI directly:
>pip install HydroTrace
Once installed, the graphical interface can be launched with:
>python -m HydroTrace.main
Under the 'basic' tab of the user interface (Fig. 1), parameters stemming from the run are entered along with the relevant chromatography record and the final content is calculated. Apparatus constants can be accessed/updated via the Settings button (Fig. 2), which are resilient and are installation specific.
Overview of the HydroTrace GUI
Configuration settings accessed by pressing 'Settings' on the main screen.
Once the relevant entries have been entered under the 'basic' tab, then temperature data can be loaded in the 'Temperature' tab (Fig. 3). Desorbtion vs. time as well as the temperature timeseries can also be examined by selecting the appropriate radio button.
Desorbtion vs. temperature plot
The temperature vs. time plot will show raw data from the datalogger and points interpolated for the GC timebase with the delay imposed. This delay is necessary to account for 'time of flight' of hydrogen from the location where the sample is being heated to arriving at the chromatographer.
Temperature vs. time, showing the imposed delay between the GC and temperature data records.
The merged records can be exported by clicking the Export button, whereby the data will be written in a comma separated format file, with a single header line describing the columns.
To access the underlying functions employed by the GUI, import them from HydroTrace according to:
>>>from HydroTrace.common import *
where * is one or more of the following, described below:
- read_cs_file
- read_pico_csv
- interp_datetime
- calc_total
- calc_desorbtion_rate
| Function | Description |
|---|---|
int_run, area, dt = read_cs_file(fname) |
Parameters: full path and file name to the Chem Station file formatted in the same way as provided in the exampledata. Returns: int_run: numpy array, area: numpy array, dt list of datetime objects. While dt is a datetime array of all injection times, int_run provides an index of these where there area could be measured. All are returned as None if unsuccessful. |
temp, dt = read_pico_csv(fname) |
Parameters: full path and file name to the temperature record formatted in the same way as provided in the exampledata. Returns: temp: numpy array, dt: list of datetime objects. dt is a datetime array of all temperature measurement points, temp is the temperature at these datetimes, both are returned as None if unsuccessful. |
fdtl, dtl_mdates = interp_datetime(dt0,d0,dt1) |
Parameters: dt0 and d0 are incoming list of datetime objects and values, respectively. dtl is a list of datetimes within the range captured by dt0.Returns: fdtl: numpy array, dtl_mdates: numpy array. fdtl is interpolated values corresponding to input datetimes dt1, dtl_mdates is an array of matplotlib mdate values corresponding to dtl for plotting purposes. |
content = calc_total(hsc,std_pa,w,cgas,frate,ctime,area) |
Parameters: H std content in ppm (hsc), H std peak area (std_pa), weight in g (w), carrier gas µmol/s (cgas), flow rate in mL/min (frate), cycle time in min (ctime) - all float values and area (numpy array from read_cs_file).Returns: content as float. |
rates = calc_desorbtion_rate(hsc,std_pa,w,cgas,frate,area) |
Parameters: H std content in ppm (hsc), H std peak area (std_pa), weight in g (w), carrier gas µmol/s (cgas), flow rate in mL/min (frate), - all float values and area (numpy array from read_cs_file).Returns: rates as numpy array. |
This application has been developed in support of activities conducted at the University of Manchester made available by the Henry Royce Institute. Please see LICENSE for further details.