G 3. AN ELECTRONIC JOURNAL OF THE EARTH SCIENCES Published by AGU and the Geochemical Society

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1 Geosystems G 3 AN ELECTRONIC JOURNAL OF THE EARTH SCIENCES Published by AGU and the Geochemical Society Technical Brief Volume 6, Number 7 26 July 2005 Q07011, doi: /2005gc ISSN: PetroGraph: A new software to visualize, model, and present geochemical data in igneous petrology M. Petrelli, G. Poli, D. Perugini, and A. Peccerillo Department of Earth Sciences, University of Perugia, Piazza Università, 1, Perugia, Italy (maurip@unipg.it) [1] A new software, PetroGraph, has been developed to visualize, elaborate, and model geochemical data for igneous petrology purposes. The software is able to plot data on several different diagrams, including a large number of classification and petrotectonic plots. PetroGraph gives the opportunity to handle large geochemical data sets in a single program without the need of passing from one software to the other as usually happens in petrologic data handling. Along with these basic functions, PetroGraph contains a wide choice of modeling possibilities, from major element mass balance calculations to the most common partial melting and magma evolution models based on trace element and isotopic data. Results and graphs can be exported as vector graphics in publication-quality form, or they can be copied and pasted within the most common graphics programs for further modifications. All these features make PetroGraph one of the most complete software presently available for igneous petrology research. Components: 4646 words, 10 figures, 4 tables. Keywords: data management; data plotting; geochemical modeling; petrology; software. Index Terms: 3610 Mineralogy and Petrology: Geochemical modeling (1009, 8410); 1065 Geochemistry: Major and trace element geochemistry; 1094 Geochemistry: Instruments and techniques. Received 3 February 2005; Revised 5 May 2005; Accepted 11 May 2005; Published 26 July Petrelli, M., G. Poli, D. Perugini, and A. Peccerillo (2005), PetroGraph: A new software to visualize, model, and present geochemical data in igneous petrology, Geochem. Geophys. Geosyst., 6, Q07011, doi: /2005gc Introduction [2] Handling, visualization, and modeling of geochemical data are of fundamental importance in igneous petrology. Most of these operations can be performed using a variety of software packages such as spreadsheet programs (e.g., MS Excel 1 or Microcal Origin 1 ), interpreted scientific computer languages (e.g., R 1 or Matlab 1 ), or software specifically developed for igneous petrology such as MinPet 1 (MinPet 1 Geological Software Inc. Web site: GCDKit [Janousek et al., 2003], IgPet 1 (IgPet 1 RockWare Web site: and PetroPlot [Su et al., 2003]. Moreover, a large number of codes have been developed [e.g., Wright and Doherty, 1970; Stormer and Nicholls, 1978; Woussen and Côté, 1987; Conrad, 1987; Holm, 1988, 1990; Nielsen, 1988; Defant and Nielsen, 1990; Harnois, 1991; Benito and López- Ruiz, 1992; D Orazio, 1993; Verma et al., 1998; Keskin, 2002; Spera and Bohrson, 2001] to help researchers in performing specific geochemical models. All these software allowed users to greatly speed up modeling of geochemical data, but some of them are designed for old MS-DOS operating systems and cause problems when loaded into modern MS Windows systems. Other programs have limited possibility of geochemical modeling (e.g., MinPet, GCDKit and PetroPlot). Moreover, problems can arise when trying to run algorithms available only as source codes; for example, the mass balance algorithm by Stormer and Nicholls [1978] requires a FORTRAN compiler to be loaded, and this may cause difficulties for the user if Copyright 2005 by the American Geophysical Union 1 of 15

2 Figure 1. General screen shot of PetroGraph showing some types of graphs performed by the software. (a) Total Alkali-Silica, TAS diagram [Le Bas et al., 1986], (b) TiO 2 versus SiO 2 binary plot, (c) AFM ternary plot [Kuno, 1968], and (d) Condrite normalized REE diagram [Haskin et al., 1968]. Displayed data are from Peccerillo et al. [2003]. compared to modern object-oriented, user-friendly software. [3] In this contribution we present a new program, PetroGraph (Figure 1), developed with the aim of giving a complete platform to handle, visualize and model geochemical data in a user friendly environment. The program runs under Windows 98/2000/XP 1 platforms as a standalone application. The source code is written in MS Visual Basic and is distributed together with the program. The code is open source and we invite all users to contribute to the development of the software by proposing improvement or developing new codes. To download the software and the tutorial, please go to unipg.it/maurip/software.htm (see also ancillary material). [4] In the following sections we present the main features and potentialities of PetroGraph. The paper is divided into five main sections (Figure 2), including (1) input of geochemical data, (2) data visualization, (3) development of geochemical models, (4) data management, and (5) additional features. 2. Data Input [5] Geochemical data can be imported into Petro- Graph in three file formats (Figure 2a): (1) MS Excel 1 worksheets, (2) IgPetWin 1 formatted files, and (3) PetroGraph (.peg) files. [6] MS Excel 1 worksheets need little formatting before imported to PetroGraph, as reported in Figure 2. The arrangement of the worksheet, however, is not much different from common analytical outputs. In particular, the first column must contain the sample name, whereas the following three columns are dedicated to symbol and color management and to the choice to show (1) or not to show (0) the sample in the diagrams (see the tutorial for a detailed explanation of the arrangement of the MS Excel 1 file). 2of15

3 Geosystems G 3 petrelli et al.: petrograph software /2005GC Figure 2. PetroGraph block diagram explaining the main features of the program. [7] A specific code has been written to import IgPet 1 files (.roc format) without modifications of the original file format. [8] PetroGraph can save data into text files by applying the.peg extension. These files can be opened by the software much faster than MS Excel formatted spreadsheets. 3. Visualization [9] Once data have been imported, the user can visualize them (Figure 2b) using three different types of diagrams commonly used in igneous petrology: binary, ternary, and spider diagrams (Figure 1). All diagrams can be easily generated in few steps. For example, a binary or a ternary diagram can be created in only 3 steps as described in Figure 3. Several options are presented to the user for each type of diagram. For instance, data can be plotted in binary diagrams by using linear and logarithmic scaling; maximum and minimum values of the axis can be rearranged to zoom into specific areas of the graphs. In addition, a large number of symbols and colors can be selected to visualize data. The most common 3of15

4 Figure 3. Screen shot of the program showing the procedure to plot a binary and ternary diagram. (a) Button of the control bar that opens the binary plot window, (b) window that allows the user to customize and plot a binary diagram, (c) button that allows the user to open (f) the windows in which elements can be easily selected, (d) example of binary plot, (e) note that name and the coordinate of samples can be displayed on the lower part of the main windows by tracking on them with the pointer, (g) button of the control bar that opens the triangular plot window, (h) window that allows the user to customize and plot a triangular diagram, and (i) example of a triangular plot. normalizations can be chosen for rare earth elements (REE) normalized diagrams (Figure 4a; Table 1). For example, REE data can be normalized by Condrite or NASC values by selecting the relative normalization values in the REE spiders window (arrow in the REE spiders window; Figure 4a). [10] Additional spider diagrams can be also performed using several normalizations (Figure 4b; Table 1). For example, data can be normalized by primordial mantle [Wood et al., 1979a], mid-ocean ridge basalts (MORB) [Bevins et al., 1984], and continental crust [Taylor and McLennan, 1981; Weaver and Tarney, 1984] by selecting them in 4of15

5 Figure 4. Screen shot of the program showing the procedure to plot a spider diagram. (a) Procedure to plot a REE spider diagram. (b) Procedure to plot a general spider diagram. Arrow in the REE spiders window: possible normalizations for REE spiders. Arrow in the general spiders window: possible normalizations for general spiders. the relative spider window (arrow in the general spider window; Figure 4b). An important feature of PetroGraph is the possibility to generate normalization files that can be used to generate custom spider diagrams. [11] One of the major tasks in igneous petrology is rock classification and this can be easily done with PetroGraph by using a wide choice of classification diagrams (e.g., Q -ANOR, TAS, etc.; Table 2); several petrotectonic diagrams (e.g., Nb-Y, Ti- Zr-Y, etc.; Table 2) can be also generated [Rollison, 1993]. For example, the Total Alkali versus Silica diagram (TAS) [Le Bas et al., 1986] can be created simply selecting it from the Diagram section of the Plot menu (Figure 5). [12] All diagrams can be easily modified by a mouse double click (Figure 6b) and a cascade menu containing several options can be opened by a right click (Figure 6a). All these options allow the user to generate high-quality graphs that can be saved to file in publication-ready form in Microsoft 1 metafile format or copied to the clipboard to 5of15

6 Table 1. Normalizations Available in PetroGraph for REE and General Spider Diagrams Normalization Source REE Spiders Chondrite Haskin et al. [1968] Chondrite Masuda et al. [1973] Chondrite Nakamura [1974] Chondrite Boynton [1984] Chondrite Sun and McDonough [1989] NASC Haskin and Frey [1966] NASC Haskin and Haskin [1966] General Spiders Primordial mantle Wood et al. [1979a] Primordial mantle McDonough et al. [1992] Primordial mantle Taylor and McLennan [1985] Condrite Wood et al. [1979b] MORB Bevins et al. [1984] Upper cont. crust Taylor and McLennan [1981] Lower cont. crust Weaver and Tarney [1984] Average cont. crust Weaver and Tarney [1984] Average N-type MORB Saunders and Tarney [1984], Sun [1980] Average OIB Sun [1980] Custom spider allows user to generate custom normalization file be further elaborated in the major vector-graphic applications (e.g., MS Office 1, Corel 1 ). 4. Modeling of Geochemical Data 4.1. Major Element Modeling [13] Several modeling approaches by using major and trace elements, and isotopes are implemented in PetroGraph (Figure 2c). [14] Major elements are modeled by the mass balance algorithm [Stormer and Nicholls, 1978]. This approach involves a least squares solution to a set of linear mass balance equations (one for each oxide) and the calculations are performed on data consisting of chemical analyses of igneous rocks, assumed to represent the composition of parent and daughter magmas. This computational approach can be used to test fractional crystallization, assimilation, fractional melting, and magma mixing [e.g., Stormer and Nicholls, 1978]. Mass balance computations are performed in a user friendly environment (Figure 7) by selecting magmas and phases among the samples belonging to the geochemical data set. Figure 7 shows the procedure to develop a Mass Balance computation using PetroGraph: first select the oxides (Figures 7b 7e), successively select the initial and final magmas (Figures 7c 7f), then select the phases and finally calculate results (Figure 7h) Trace Element and Isotope Modeling [15] Trace elements models are divided into three main sections, involving (1) magma crystallization processes (Table 3), (2) partial melting (Table 4, top), and (3) magma mixing (Table 4, bottom). PetroGraph can model mixing [Langmuir et al., 1978] and Assimilation plus Fractional Crystallization (AFC) [DePaolo, 1981] processes, using isotopic data. [16] Trace element and isotope models can be performed by choosing the model end-members directly from the plotted samples; this strongly simplifies the modeling procedure and allows the user to immediately evaluate if the selected model is suitable or not for the studied data set. Once a model has been plotted on a graph, model parameters can be readily modified in the appropriate window that will pop up with a single click of the mouse directly on the graph. Different models can be displayed simultaneously either in a single graph or in different graph windows. [17] Figure 8 reproduces two diagrams extracted from Peccerillo et al. [2003] and shows, as an example, how to perform trace element and isotope models with PetroGraph. The models refer to the origin of peralkaline silicic magmas at Gedemsa volcano (Central Ethiopian Rift), which can be generated either by batch melting of a basaltic rock or by fractional crystallization of a basaltic parental melt. Trace element and isotope models reported in Figure 8 show that fractional crystallization accompanied by little assimilation of the Precambrian crust is more suitable than batch-melting to explain sample variability in the Gedemsa magmatic system (see Peccerillo et al. [2003] for a detailed discussion of these data) and these models can be easily developed using PetroGraph. 5. Data Management [18] Data management (Figure 2d) can be performed by using four principal types of operation: (1) algebraic operations, (2) determination of geochemical parameters or indexes, (3) operation related to rare earth elements, and (4) operation on isotopes (Figure 9a). [19] Algebraic operations are the sum, subtraction, division, multiplication, the elevation to an expo- 6of15

7 Table 2. Classification and Discriminating Diagrams Performed by PetroGraph Diagram Source General Classification Diagrams Binary [Q 0 (F 0 ) - ANOR] volcanic after Streckeisen and Le Maitre [1979] [K 2 O-SiO 2 ] after Peccerillo and Taylor [1976] [K 2 O-SiO 2 ] after Middlemost [1975] [TAS Alkalis - Silica] volcanic after Le Bas et al. [1986] [TAS Alkalis - Silica] volcanic after Cox et al. [1979] [TAS Alkalis - Silica] plutonic after Cox et al. [1979] [SiO 2 -K 2 O Andesite Types] after Gill [1981] [SiO 2 - F/M] after Miyashiro [1974] Triangular AFM after Kuno [1968] AFM after Irvine and Baragar [1971] Diagrams for Basalts Binary [Ta/Yb - Tb/Yb] after Pearce [1982] [Y - Cr] after Pearce [1982] [Ti - Zr] after Pearce and Cann [1973] Triangular [Ti - Zr - Y] after Pearce and Cann [1973] [Ti - Zr - Sr] after Pearce and Cann [1973] [Nb - Zr - Y] after Meschede [1986] [Th - Hf - Ta] after Wood [1980] Diagrams for Granites [Nb - Y] after Pearce et al. [1984] [Ta - Yb] after Pearce et al. [1984] [Rb - (Y + Nb)] after Pearce et al. [1984] [Rb - (Yb + Ta)] after Pearce et al. [1984] Mantle End-Members [ 87 Sr/ 86 Sr Nd/ 144 Nd] data from Hart et al. [1992] [ 206 Pb/ 204 Pb Nd/ 144 Nd] data from Hart et al. [1992] [ 206 Pb/ 204 Pb - 87 Sr/ 86 Sr] data from Hart et al. [1992] nent, and the square root. In addition, it is possible to convert parts per million (PPM) values to weight percent (wt%) and vice versa. These operations allow the user to generate new variables that can be plotted and elaborated analogously to the original ones. [20] Geochemical parameters and indexes that can be determined by PetroGraph are Total Iron (FeO tot ), Larsen Index, Solidification Index (SI), CIPW norm, Magnesium Number (Mg#), Aluminium Saturation Index (ASI), and Fe/Mg Ratio. [21] Regarding operations related to REE, Petro- Graph can calculate the Europium anomaly (Eu/ Eu*), three different normalized REE ratios (La n / Sm n,la n /Yb n,tb n /Yb n ) and the total sum of REE (SREE). [22] Regarding isotopes, PetroGraph offers the opportunity to use the epsilon notation for Nd and Hf isotopes and to calculate the percent deviation from present-day chondritic value for 187 Os/ 188 Os. 6. Additional Features [23] Among additional features (Figure 2e), Petro- Graph offers the opportunity to filter data sets by applying several kinds of constraints and allows the user to consult a solid/liquid partition coefficient database, a useful option when developing trace element geochemical models. [24] Filters (Figures 9b and 9c) are useful when only samples with specific compositional characteristics (e.g., only samples with a content of SiO 2 higher than 50 wt%) are to be selected for plotting (Figure 9c). [25] A complete data set of partition coefficients is stored in PetroGraph (Figure 10). Data for the 7of15

8 Figure 5. Screen shot of the program showing the procedure to plot classification or petrotectonic diagrams. (a) Procedure to select a diagram; (b) example of a TAS diagram. 8of15

9 Figure 6. Screen shot of the program showing options to customize a binary plot. (a) Cascade menu generated by click of the right mouse button on the diagram; (b) window opened by a double click of the left mouse button on the diagram to change axis properties. 9of15

10 Figure 7. (a) Mass Balance window and results of the mass balance calculation. (b, c, and d) On the upper part of the Mass Balance window are reported buttons that open the windows to select (e) oxides, (f) magmas, and (g) phases. The computation can be performed by clicking (h) the Calculate button. The output is displayed in the lower part of the window. Results can be also exported into the clipboard or saved as text files. Data and results reported in the presented example are the same as in the original paper by Stormer and Nicholls [1978]. Detailed information on step-by-step procedures to perform mass balance computations is reported in the software tutorial. partition coefficient database are from Earth Reference Data and Models Web site (EarthRef; Summary [26] PetroGraph is a program specifically developed to visualize, elaborate, and model geochemical data. It runs on Microsoft 1 Windows 98/2000/ XP platforms and it is written in Visual Basic With its user friendly design, it is able to plot data within binary, triangular and spider diagrams with minimum effort. A large number of classification and discriminating diagrams can be easily plotted; several operations can be performed on the original variables in order to obtain new variables and geochemical parameters. A large number of geochemical models can be calculated from major and trace elements, and isotopes. Moreover, Petro- Table 3. Trace Element Models Involving Crystallization Processes Model Equilibrium Crystallization [Wood and Fraser, 1976] Fractional Crystallization [Neuman et al., 1954] Assimilation plus Fractional Crystallization [DePaolo, 1981] In Situ Crystallization [Langmuir, 1989] Zone Refining [Richter, 1986] Abbreviation EC FC AFC In Situ C ZR 10 of 15

11 Table 4. Trace Element Models Involving Melting and Mixing Processes Model Batch Melting [Wood and Fraser, 1976] Non Modal Batch Melting [Wood and Fraser, 1976] Fractional Melting [Wood and Fraser, 1976] Melting Models Abbreviation BM nmbm FM Mixing [Langmuir et al., 1978] Mixing Model Mix Figure 8. Screen shot of the program explaining the potentialities of PetroGraph in performing trace element modeling. (a) Window that allows the user to customize trace element models. (b) V versus Zr plot in which Fractional Crystallization (D V =4.0,D Zr = 0.1) and Batch Melting (D V =4.0,D Zr = 0.1) models are reported. It is clear that Gedemsa rocks behavior can be well explained by fractional crystallization, whereas batch melting fails in accounting for the sample variability. (c) Sr versus 87 Sr/ 86 Sr plot reporting the Assimilation and Fractional Crystallization (AFC) model. Isotopic modeling corroborates the hypothesis indicating that fractional crystallization couples with moderate assimilation of Precambrian crust can suitably account for Sr isotopic signature of Gedemsa rocks; model parameters are reported in the graph. Data are from Peccerillo et al. [2003]. Detailed information on step-by-step procedures to perform geochemical models is reported in the software tutorial. 11 of 15

12 Figure 9. Screen shot of the program showing potentialities of PetroGraph in (a) data management and (b and c) the data filtering window. 12 of 15

13 Figure 10. Screen shot of the program showing the solid/liquid partition coefficient database. (a) Option of the Windows menu that allows the user to open the solid/liquid partition coefficient database. (b) Window with the periodic table of elements. (c) By clicking an element on the table, the solid/liquid partition coefficients for that element appears. Graph produces high-quality graphic outputs which can be directly used for publication. Acknowledgments [27] We acknowledge the useful suggestions and criticisms of Yoshiyuki Tatsumi (Associate Editor) and two anonymous referees. The editorial handling of W. M. White is gratefully acknowledged. This work was funded by MIUR (G.P., A.P.) and GNV grants. References Benito, R., and J. López-Ruiz (1992), ANATEX.BAS: A program for calculating the mineralogy of the residual solid and trace element fractionation in partial melting, Comput. Geosci., 18(5), Bevins, R. E., B. P. Kokelaar, and P. N. Dunkley (1984), Petrology and geochemistry for lower to middle Ordovician igneous rocks in Wales: A volcanic arc to marginal basin transition, Proc. Geol. Assoc., 95, Boynton, W. V. (1984), Geochemistry of the rare earth elements: Meteorite studies, in Rare Earth Element Geochemistry, edited by P. Henderson, pp , Elsevier, New York. Conrad, W. R. (1987), A FORTRAN program for simulating major- and trace-element variations during Rayleigh fractionation with melt replenishment or assimilation, Comput. Geosci., 13(1), Cox, K. J., J. D. Bell, and R. J. Pankhurst (1979), The Interpretation of Igneous Rocks, 450 pp, Allen and Unwin, St Leonards, NSW, Australia. Defant, M. J., and R. L. Nielsen (1990), Interpretation of open system petrogenetic process: Phase equilibria constrains on magma evolution, Geochim. Cosmochim. Acta, 54(1), DePaolo, D. J. (1981), Trace element and isotopic effects of combined wallrock assimilation and fractional crystallization, Earth Planet. Sci. Lett., 53, D Orazio, M. (1993), A Macintosh BASIC program for the interactive testing of combined assimilation and fractional crystallization, Comput. Geosci., 19(4), Gill, J. B. (1981), Orogenic Andesites and Plate Tectonics, 358 pp., Springer, New York. Harnois, L. (1991), TEA: A computer program in BASIC to calculate trace-element abundances in silicate rocks and magmas during melting and crystallization processes, Comput. Geosci., 17(5), of 15

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15 the nature of crustal contamination of basaltic lavas of the British Tertiary volcanic province, Earth Planet. Sci. Lett., 50, Wood, D. A., J. L. Joron, M. Treuil, M. Norry, and J. Tarney (1979a), Elemental and Sr isotope variations in basic lavas from Iceland and the surrounding ocean floor, Contrib. Mineral. Petrol., 70, Wood, D. A., J. Tarney, J. Varet, A. D. Saunders, Y. Bougault, J. L. Joron, M. Treuil, and J. R. Cann (1979b), Geochemistry of basalts drilled in the North Atlantic by IPOD Leg 49: Implications for mantle heterogeneity, Earth Planet. Sci. Lett., 42, Woussen, G., and D. Côté (1987), HYPERFUNC: BASIC program to calculate hyperbolic magna-mixing curves for geochemical data, Comput. Geosci., 13(4), Wright, T. L., and P. C. Doherty (1970), A linear programming and least squares computer method for solving petrologic mixing problems, Bull. Geol. Soc. Am., 81, of 15