AIOCG plots

pyrolite/data/models/AIOCG/config.json

@@ -0,0 +1 @@
+{"name":"AIOCG","axes":{"x":"(2Ca+5Fe+2Mn)+(2Ca+5Fe+2Mn+Mg+Si) molar","y":"K/(K+Na+0.5Ca) molar"},"fields":{"K":{"name":["K"],"poly":[[0,405.2],[103.2,405.2],[109.4,244.1],[51.6,235.0],[39.6,222.8],[45.6,194.4],[0,194.4]]},"KintNa":{"name":[""],"poly":[[0,194.4],[0,121.5],[145.7,121.5],[54.7,176.2],[45.6,194.4]]},"Na":{"name":["Na"],"poly":[[0,121.5],[145.7,121.5],[145.7,32.4],[157.9,0.0],[0,0.0]]},"NotAltered1":{"name":[""],"poly":[[291.6,145.9],[221.7,72.5],[294.7,30.5],[346.3,44.6],[352.3,54.7],[346.3,73.0],[334.1,101.3],[315.8,117.6]]},"NotAltered2":{"name":[""],"poly":[[291.6,145.9],[221.7,72.5],[294.7,30.5],[346.3,44.6],[352.3,54.7],[346.3,73.0],[334.1,101.3],[315.8,117.6]]},"Na-Ca-Fe-(Mg)":{"name":["Na-Ca-Fe-(Mg)"],"poly":[[145.7,121.5],[145.7,32.4],[157.9,0.0],[413,0.0],[400.8,48.7],[367.4,77.1],[352.3,117.6],[315.8,117.6],[334.1,101.3],[346.3,73.0],[352.3,54.7],[346.3,44.6],[294.7,30.5],[206.6,81.1]]},"KintK-Fe":{"name":[""],"poly":[[103.2,405.2],[109.4,244.1],[115.4,245.1],[197.5,223.5],[200.4,275.6],[194.4,405.2]]},"K-Fe":{"name":["K-Fe"],"poly":[[194.4,405.2],[200.4,275.6],[197.5,223.5],[200.4,222.8],[437.2,222.8],[431.2,328.1],[413,364.6],[413,405.2]]},"Ca-K-Fe":{"name":["Ca-K-Fe"],"poly":[[200.4,222.8],[291.6,145.9],[315.8,117.6],[352.3,117.6],[443.5,117.6],[437.2,222.8]]},"Ca-Fe-(Mg)":{"name":["Ca-Fe-(Mg)"],"poly":[[352.3,117.6],[367.4,77.1],[400.8,48.7],[413,0.0],[461.7,0.0],[445.4,70.8],[443.5,117.6]]},"Fe-rich_Ca-Fe":{"name":["Fe-rich Ca-Fe"],"poly":[[443.5,117.6],[445.4,70.8],[461.7,0.0],[607.4,0.0],[607.4,117.6]]},"Fe-rich_Ca-K-Fe":{"name":["Fe-rich Ca-K-Fe"],"poly":[[437.2,222.8],[443.5,117.6],[607.4,117.6],[607.4,222.8]]},"Fe-rich_K-Fe":{"name":["Fe-rich K-Fe"],"poly":[[413,405.2],[413,364.6],[431.2,328.1],[437.2,222.8],[607.4,222.8],[607.4,405.2]]}}}

pyrolite/geochem/alteration.py

@@ -127,3 +127,26 @@ def WIP(df: pd.DataFrame):
 
     """
     return 2 * df.Na2O / 0.35 + df.MgO / 0.9 + 2 * df.K2O / 0.25 + df.CaO / 0.7
+
+def AIOCG_xy(df: pd.DataFrame):
+    """
+
+    Alteration diagram coordinates for iron oxide-copper-gold mineralisation 
+    system. (molecular) [#ref_1]_
+    Returns X,Y coordinates to plot in discriminant diagram scaled to the 
+    400x600 dimension of the background
+
+    References
+    ----------
+    .. [#ref_1] Montreuil J F, Corriveau L, Grunsky E C (2013). Compositional 
+            data analysis of hydrothermal alteration in IOCG systems, Great 
+            Bear magmatic zone, Canada: to each alteration type its own 
+            geochemical signature. Geochemistry: Exploration, Environment, 
+            Analysis 13:229-247.
+            doi:`<http://dx.doi.org/10.1144/geochem2011-101>`__
+    """
+    x = (2*df.Ca+5*df.Fe+2*df.Mn)/(2*df.Ca+5*df.Fe+2*df.Mn+df.Mg+df.Si)*600
+    y = df.K/(df.K+df.Na+0.5*df.Ca)*400
+    return x, y
+
+

pyrolite/plot/templates/AIOCG.py

@@ -0,0 +1,61 @@
+import matplotlib.pyplot as plt
+import numpy as np
+from ...util.plot.axes import init_axes
+from ...util.classification import AIOCG as AIOCGclassifier
+from ...util.meta import sphinx_doi_link, update_docstring_references, subkwargs
+from ...util.log import Handle
+
+logger = Handle(__name__)
+
+
+@update_docstring_references
+def AIOCG(ax=None, relim=True, color="k", **kwargs):
+    """
+    Adds the AIOCG diagram from Montreuil et al. (2013) [#ref_1]_ to an axes.
+    NOTE to user:
+    x:y are scaled from 1:1 to 600:400 to account for plot dimension
+
+
+    Parameters
+    ----------
+    ax : :class:`matplotlib.axes.Axes`
+        Axes to add the template on to.
+    relim : :class:`bool`
+        Whether to relimit axes to fit the built in ranges for this diagram.
+    color : :class:`str`
+        Line color for the diagram.
+
+    Returns
+    -------
+    ax : :class:`matplotlib.axes.Axes`
+
+    References
+    -----------
+    .. [#ref_1] Montreuil J F, Corriveau L, and Potter E G (2015). Formation of 
+            albitite-hosted uranium within IOCG systems: the Southern Breccia, 
+            Great Bear magmatic zone, Northwest Territories, Canada. 
+            Mineralium Deposita, 50:293-325.
+            doi:`<https://doi.org/10.1007/s00126-014-0530-7>`__
+    """
+    AIOCG_xlim, AIOCG_ylim = (0, 607.4), (0, 405.2)
+    if ax is None:
+        xlim, ylim = AIOCG_xlim, AIOCG_ylim
+    else:
+        # if the axes limits are not defaults, update to reflect the axes
+        ax_defaults = (0, 1)
+        ax_xlim, ax_ylim = ax.get_xlim(), ax.get_ylim()
+        xlim, ylim = (
+            [ax_xlim, AIOCG_xlim][np.allclose(ax_xlim, ax_defaults)],
+            [ax_ylim, AIOCG_ylim][np.allclose(ax_ylim, ax_defaults)],
+        )
+    ax = init_axes(ax=ax, **kwargs)
+
+    aiocg = AIOCGclassifier()
+    aiocg.add_to_axes(ax=ax, **kwargs)
+    if relim:
+        ax.set_xlim(xlim)
+        ax.set_ylim(ylim)
+    return ax
+
+
+AIOCG.__doc__ = AIOCG.__doc__.format(Montreuil2013=sphinx_doi_link("10.1007/s00126-014-0530-7"))

pyrolite/util/classification.py

@@ -289,6 +289,110 @@ def add_to_axes(self, ax=None, fill=False, axes_scale=100.0, labels=None, **kwar
         ax.set_xlabel("$SiO_2$")
         return ax
 
+class AIOCG(PolygonClassifier):
+    """
+    AIOCG Diagram classifier from Montreuil et al. (2013) [#ref_1]_.
+
+    Parameters
+    -----------
+    name : :class:`str`
+        A name for the classifier model.
+    axes : :class:`list` | :class:`tuple`
+        Names of the axes corresponding to the polygon coordinates.
+    fields : :class:`dict`
+        Dictionary describing indiviudal polygons, with identifiers as keys and
+        dictionaries containing 'name' and 'fields' items.
+    scale : :class:`float`
+        Default maximum scale for the axes. Typically 100 (wt%) or 1 (fractional).
+    xlim : :class:`tuple`
+        Default x-limits for this classifier for plotting.
+    ylim : :class:`tuple`
+        Default y-limits for this classifier for plotting.
+
+    References
+    -----------
+    .. [#ref_1] Montreuil J F, Corriveau L, and Potter E G (2015). Formation of 
+            albitite-hosted uranium within IOCG systems: the Southern Breccia, 
+            Great Bear magmatic zone, Northwest Territories, Canada. 
+            Mineralium Deposita, 50:293-325.
+            doi:`<https://doi.org/10.1007/s00126-014-0530-7>`__
+    """
+
+    @update_docstring_references
+    def __init__(self, **kwargs):
+        src = pyrolite_datafolder(subfolder="models") / "AIOCG" / "config.json"
+
+        with open(src, "r") as f:
+            config = json.load(f)
+        kw = dict(scale=100.0, xlim=[0, 607.4], ylim=[0, 405.2])
+        kw.update(kwargs)
+        poly_config = {**config, **kw}
+        super().__init__(**poly_config)
+
+    def add_to_axes(self, ax=None, fill=False, axes_scale=100.0, labels=None, **kwargs):
+        """
+        Add the AIOCG fields from the classifier to an axis.
+
+        Parameters
+        ----------
+        ax : :class:`matplotlib.axes.Axes`
+            Axis to add the polygons to.
+        fill : :class:`bool`
+            Whether to fill the polygons.
+        axes_scale : :class:`float`
+            Maximum scale for the axes. Typically 100 (for wt%) or 1 (fractional).
+        labels : :class:`str`
+            Which labels to add to the polygons (e.g. for TAS, 'volcanic', 'intrusive'
+            or the field 'ID').
+
+        Returns
+        --------
+        ax : :class:`matplotlib.axes.Axes`
+        """
+        # use and override the default add_to_axes
+        ax = self._add_polygons_to_axes(
+            ax=ax, fill=fill, axes_scale=axes_scale, **kwargs
+        )
+        rescale_by = 1.0
+        if axes_scale is not None:  # rescale polygons to fit ax
+            if not np.isclose(self.default_scale, axes_scale):
+                rescale_by = axes_scale / self.default_scale
+        if labels is not None:
+            for k, cfg in self.fields.items():
+                if cfg["poly"]:
+                    verts = np.array(cfg["poly"]) * rescale_by
+                    x, y = get_centroid(matplotlib.patches.Polygon(verts))
+                    label = cfg["name"][0]
+                    ax.annotate(
+                        "\n".join(label.split()),
+                        xy=(x, y),
+                        ha="center",
+                        va="center",
+                        **subkwargs(kwargs, ax.annotate, matplotlib.text.Text)
+                    )
+
+
+                    #  if cfg["poly"]:
+                    # verts = np.array(cfg["poly"]) * rescale_by
+                    # x, y = get_centroid(matplotlib.patches.Polygon(verts))
+                    # if "volc" in labels:  # use the volcanic name
+                    #     label = cfg["name"][0]
+                    # elif "intr" in labels:  # use the intrusive name
+                    #     label = cfg["name"][-1]
+                    # else:  # use the field identifier
+                    #     label = k
+                    # ax.annotate(
+                    #     "\n".join(label.split()),
+                    #     xy=(x, y),
+                    #     ha="center",
+                    #     va="center",
+                    #     **subkwargs(kwargs, ax.annotate, matplotlib.text.Text)
+                    # )
+
+
+        ax.set_ylabel("$K/(K+Na+0.5Ca) molar$")
+        ax.set_xlabel("$(2Ca+5Fe+2Mn)+(2Ca+5Fe+2Mn+Mg+Si) molar$")
+        return ax
 
 class PeralkalinityClassifier(object):
     def __init__(self):

test/geochem/geochem_alteration.py

@@ -87,5 +87,19 @@ def test_WIP(self):
         df.loc[:, "WIP"] = WIP(df)
 
 
+
+class TestAIOCG_xy(unittest.TestCase):
+    """Tests the AIOCG coordinate calculation."""
+
+    def setUp(self):
+        self.cols = ["Si", "Ca", "Mg", "Mn", "Fe", "Ti", "Na", "K", "Al"]
+        self.df = pd.DataFrame(
+            {k: v for k, v in zip(self.cols, np.random.rand(len(self.cols), 10))}
+        )
+
+    def test_AIOCG_xy(self):
+        df = self.df
+        df.loc[:, "AIOCG_x"], df.loc[:, "AIOCG_y"] = AIOCG_xy(df)
+
 if __name__ == "__main__":
     unittest.main()

test/plot/templates/plot_templates_AIOCG.py

@@ -0,0 +1,26 @@
+import unittest
+import matplotlib.pyplot as plt
+from pyrolite.plot.templates.AIOCG import AIOCG
+
+
+class TestAIOCGPlot(unittest.TestCase):
+    def setUp(self):
+        pass
+
+    def test_TAS_default(self):
+        fig, axes = plt.subplots(1)
+        for ax in [None, axes]:
+            with self.subTest(ax=ax):
+                ax = AIOCG(ax)
+
+    def test_TAS_relim(self):
+        for relim in [True, False]:
+            with self.subTest(relim=relim):
+                ax = AIOCG(relim=relim)
+
+    def tearDown(self):
+        plt.close("all")
+
+
+if __name__ == "__main__":
+    unittest.main()