Forward thermodynamic modelling is a commonly used tool for examining the thermobarometric history of a rock. Such models are being applied to a widening range of rock types using increasingly complex model systems. A useful aspect of phase equilibria modelling using pseudosections is the ability to calculate the modal abundance and compositions of phases, in addition to overall phase relations. However, calculating and plotting such data with thermocalc, a popular modelling program, is time consuming. In this article, we provide the methods and a description of a Matlab® computer program, TCInvestigator, which uses thermocalc 3.40 to automatically contour pre‐calculated pressure–temperature pseudosections with modal abundance and mineral composition parameters. The ability to calculate, plot and visualize these parameters automatically and rapidly, allows for a more in‐depth investigation into the metamorphic evolution of a rock. Data can be contoured for all minerals that are present in all fields on the pseudosection, rather than a selection of fields or phases that are a priori considered relevant. Examples of contoured pseudosections for pelitic and greywacke bulk compositions are presented, along with accompanying data sets, to illustrate the applications of this program. The software and example files are available from the CSIRO Data Access Portal at the following address: doi:.

Portable X-ray fluorescence (pXRF) technology can be used to collect large amounts of multi-element data rapidly at relatively low cost and has been widely embraced within the minerals industry. However, to date, it has been difficult to compare data-sets collected by different users or at different times because there is no standardized approach to the collection of these data. The absence of information on standardization and calibration procedures raises concerns about a lack of internal consistency within these data-sets and precludes comparison of different data-sets. This paper seeks to address this issue by developing a workflow for the collection of pXRF data in an exploration or mining setting. Two case studies highlight the robustness and possible applications of pXRF data collected following QA/QC protocols. A good correlation between conventional laboratory analyses and pXRF data is demonstrated through comparison of analysis methods for a drill-hole at the Plutonic Gold Mine, Western Australia, and fine-scale lithostratigraphic variation is recognized in pXRF data collected on grade control pulps from a drill fan at the Agnew Gold Mine, Western Australia. The Agnew data precision is sufficient to distinguish alteration signals from background lithology, and to discern which alteration signals are associated with gold mineralization.

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