Merge branch 'release/0.1.5'

README.md

@@ -1,6 +1,6 @@
 # `pyrolite`
 
-<img src="https://raw.githubusercontent.com/morganjwilliams/pyrolite/develop/docs/source/_static/icon.png" alt="pyrolite Logo" width="30%" align="right">
+<img src="https://raw.githubusercontent.com/morganjwilliams/pyrolite/develop/docs/source/_static/icon.jpg" alt="pyrolite Logo" width="30%" align="right">
 
 <p align="left">
   <a href="https://pypi.python.org/pypi/pyrolite/">

docs/examples/plotting/REE_v_radii.py

@@ -70,8 +70,8 @@
 fig, ax = plt.subplots(1, 2, sharey=True, figsize=(12, 4))
 
 df1.pyroplot.REE(ax=ax[0])
-# we can also change the mode of the second figure
-ax1 = df2.pyroplot.REE(ax=ax[1], color='k', mode='elements')
+# we can also change the index of the second figure
+ax1 = df2.pyroplot.REE(ax=ax[1], color='k', index='elements')
 plt.tight_layout()
 
 # %% Save Figure

docs/examples/plotting/conditionalspider.py

@@ -0,0 +1,69 @@
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+from pyrolite.geochem.norm import ReferenceCompositions
+from pyrolite.geochem.ind import REE
+from pyrolite.plot.spider import spider
+import logging
+
+rc = ReferenceCompositions()
+rn = rc["EMORB_SM89"]  # emorb composition as a starting point
+components = [i for i in rn.data.index if i in REE()]
+data = rn[components]["value"]
+nindex, nobs = data.index.size, 200
+ss = [0.1, 0.2, 0.5]  # sigmas for noise
+
+modes = [
+    ("plot", "plot", [], dict(color="k", alpha=0.01)),
+    ("fill", "fill", [], dict()),
+    ("binkde", "binkde", [], dict(resolution=5)),
+    (
+        "binkde",
+        "binkde percentiles specified",
+        [],
+        dict(percentiles=[0.95, 0.5], resolution=5),
+    ),
+    ("ckde", "ckde", [], dict(resolution=5)),
+    ("kde", "kde", [], dict(resolution=5)),
+    ("histogram", "histogram", [], dict(resolution=5)),
+]
+
+fig, ax = plt.subplots(
+    len(modes), len(ss), sharey=True, figsize=(len(ss) * 3, 2 * len(modes))
+)
+ax[0, 0].set_ylim((0.1, 100))
+
+for a, (m, name, args, kwargs) in zip(ax, modes):
+    a[0].annotate(  # label the axes rows
+        "Mode: {}".format(name),
+        xy=(0.1, 1.05),
+        xycoords=a[0].transAxes,
+        fontsize=8,
+        ha="left",
+        va="bottom",
+    )
+for ix, s in enumerate(ss):
+    x = np.arange(nindex)
+    y = rc["PM_PON"].normalize(data).applymap(np.log)
+    y = np.tile(y, nobs).reshape(nobs, nindex)
+    y += np.random.normal(0, s / 2, size=(nobs, nindex))  # noise
+    y += np.random.normal(0, s, size=(1, nobs)).T  # random pattern offset
+    df = pd.DataFrame(y, columns=components)
+    df["Eu"] += 1.0  # significant offset
+    df = df.applymap(np.exp)
+    for mix, (m, name, args, kwargs) in enumerate(modes):
+        df.pyroplot.spider(
+            indexes=x,
+            mode=m,
+            ax=ax[mix, ix],
+            cmap="viridis",
+            vmin=0.05,
+            *args,
+            **kwargs
+        )
+
+plt.tight_layout()
+# %% save figure
+from pyrolite.util.plot import save_figure, save_axes
+
+save_figure(fig, save_at="../../source/_static", name="spider_modes")

docs/examples/plotting/logo.py

@@ -70,8 +70,8 @@
 for ix, sample in enumerate(df.Sample.unique()):
     comp = df.query("Sample == {}".format(sample)).loc[:, ["SiO2", "MgO", "FeO"]]
     tcomp = to_log(comp)
-    plot_stdev_ellipses(tcomp, color=t10b3[ix], **kwargs)
-    plot_pca_vectors(tcomp, ls="-", lw=0.5, color="k", **kwargs)
+    plot_stdev_ellipses(tcomp.values, color=t10b3[ix], **kwargs)
+    plot_pca_vectors(tcomp.values, ls="-", lw=0.5, color="k", **kwargs)
 # %% individual density diagrams ------------------------------------------------------
 kwargs = dict(ax=ax[-2], bins=100, no_ticks=True, axlabels=False)
 for ix, sample in enumerate(df.Sample.unique()):
@@ -95,25 +95,29 @@
     a.patch.set_facecolor(None)
     a.patch.set_visible(False)
     a.set_aspect("equal")
-plt.tight_layout()
+
 # %% Save Figure
 from pyrolite.util.plot import save_axes, save_figure
 from pathlib import Path
 import svgutils
+
 dpi = 600
 save_at = Path("./../../source/_static/")
 fmts = ["png", "jpg"]
-save_axes(ax[1], name="icon", save_at=save_at, save_fmts=fmts+['svg'], dpi=dpi)
+save_axes(ax[1], name="icon", save_at=save_at, save_fmts=fmts, dpi=dpi)
 
 ax[0].set_title("Synthetic Data")
 ax[1].set_title("Covariance Ellipses and PCA Vectors")
 ax[-2].set_title("Individual Density, with Contours")
 ax[-1].set_title("Overall Density")
-save_figure(fig, name="logo_eg_all", save_at=save_at, save_fmts=fmts, dpi=dpi)
+
 save_axes(ax[0], name="logo_eg_points", save_at=save_at, save_fmts=fmts, dpi=dpi)
 save_axes(ax[1], name="logo_eg_ellipses", save_at=save_at, save_fmts=fmts, dpi=dpi)
 save_axes(ax[2], name="logo_eg_contours", save_at=save_at, save_fmts=fmts, dpi=dpi)
 save_axes(ax[3], name="logo_eg_density", save_at=save_at, save_fmts=fmts, dpi=dpi)
+plt.tight_layout()
+save_figure(fig, name="logo_eg_all", save_at=save_at, save_fmts=fmts, dpi=dpi)
+
 """
 svg = svgutils.transform.fromfile(save_at / "logo_eg_points.svg")
 originalSVG = svgutils.compose.SVG(save_at / "logo_eg_points.svg")

docs/examples/plotting/spider.py

@@ -22,9 +22,9 @@
 
 # %% Fill Plot -------------------------------------------------------------------------
 # This behaviour can be modified (see spider docs) to provide filled ranges:
-ax = spider(df.values, fill=True, plot=False, color="k", alpha=0.5)
+ax = spider(df.values, mode='fill', color="k", alpha=0.5)
 # or, alternatively directly from the dataframe:
-ax = df.pyroplot.spider(fill=True, plot=False, color="k", alpha=0.5)
+ax = df.pyroplot.spider(mode='fill', color="k", alpha=0.5)
 ax.set_ylabel('Abundance')
 # %% Save Figure
 save_figure(ax.figure, save_at="../../source/_static", name="spider_fill")

docs/source/future.rst

@@ -46,8 +46,8 @@ planned be integrated over the longer term.
 
 :code:`pyrolite.comp.impute`
 
-  Compositional data imputation algorithms (including EMCOMP,
-  `Issue #6 <https://github.com/morganjwilliams/pyrolite/issues/6>`__)
+  Expansion of compositional data imputation algorithms beyond EMCOMP
+  (`Issue #6 <https://github.com/morganjwilliams/pyrolite/issues/6>`__).
 
 :code:`pyrolite.geochem.isotope`
 
@@ -56,11 +56,8 @@ planned be integrated over the longer term.
 
 :code:`pyrolite.plot`
 
-  A few improvements to plotting functionality are on the horizon:
-    * Native integration of a ternary projection for :code:`matplotlib`.
-    * Conditional probability density plot for :code:`scatterplot` like diagrams with a
-      non-continuous index on the x-axis (
-      `Issue #10 <https://github.com/morganjwilliams/pyrolite/issues/10>`__)
+  A few improvements to plotting functionality are on the horizon, including native
+  integration of a ternary projection for :code:`matplotlib`.
 
 :code:`pyrolite.geochem.magma`
 

docs/source/index.rst

@@ -4,8 +4,8 @@
 `Pyrolite`
 ====================================
 
-.. image:: ./_static/icon.svg
-   :width: 70%
+.. image:: ./_static/icon.png
+   :width: 40%
    :align: right
 
 .. toctree::

docs/source/usage/eg/plotting/REE_v_radii.rst

@@ -47,4 +47,5 @@ REE Radii Plots
    :align: center
 
 .. seealso:: `Visualising Orthogonal Polynomials <../lambdas/lambdavis.html>`__,
-             `Dimensional Reduction <../lambdas/lambdadimreduction.html>`__
+             `Dimensional Reduction <../lambdas/lambdadimreduction.html>`__,
+             `Spider Density Diagrams <conditionaldensity.html>`__,

docs/source/usage/eg/plotting/conditionaldensity.rst

@@ -0,0 +1,16 @@
+Conditional Density Spiderplots
+==================================
+
+The spiderplot can be extended to provide visualisations of ranges and density via the
+various modes:
+
+.. literalinclude:: ../../../../examples/plotting/conditionalspider.py
+   :language: python
+   :end-before: # %% save figure
+
+.. image:: ../../../_static/spider_modes.png
+   :width: 100%
+   :align: center
+
+.. seealso:: `Density Plots <density.html>`__,
+             `Spiderplots <spider.html>`__

docs/source/usage/eg/plotting/density.rst

@@ -116,4 +116,5 @@ are specified:
           where the edges of bins within a ``pcolormesh`` image (used for plotting the
           KDE estimate) are over-emphasized, giving a gridded look.
 
-.. seealso:: `Ternary Plots <../plotting/ternary.html>`__
+.. seealso:: `Ternary Plots <../plotting/ternary.html>`__,
+             `Spider Density Diagrams <conditionaldensity.html>`__,

docs/source/usage/eg/plotting/spider.rst

@@ -42,5 +42,6 @@ Spider Plots
    :align: center
 
 .. seealso:: `Dimensional Reduction <lambdadimreduction.html>`__,
-  `REE Radii Plot <../plotting/REE_v_radii.html>`__,
-  `Normalisation <../normalisation/normalisation.html>`__
+             `REE Radii Plot <REE_v_radii.html>`__,
+             `Spider Density Diagrams <conditionaldensity.html>`__,
+             `Normalisation <../normalisation/normalisation.html>`__

pyrolite/__init__.py

@@ -1,13 +1,12 @@
 import sys
 import logging
-from ._version import get_versions
-from .plot import pyroplot
-
-__version__ = get_versions()["version"]
-del get_versions
-
 # http://docs.python-guide.org/en/latest/writing/logging/
 logging.getLogger(__name__).addHandler(logging.NullHandler())
 logging.captureWarnings(True)
 
+from ._version import get_versions
+from .plot import pyroplot # import after logger setup to suppress numpydoc warnings
+__version__ = get_versions()["version"]
+del get_versions
+
 __all__ = ['plot', 'comp', 'geochem', 'mineral', 'util']

pyrolite/comp/codata.py

@@ -28,7 +28,7 @@ def close(X: np.ndarray, sumf=np.sum):
     :class:`numpy.ndarray`
         Closed array.
 
-    Note
+    Notes
     ------
         * Does not check for non-positive entries.
     """

pyrolite/comp/impute.py

@@ -33,7 +33,7 @@ def _little_sweep(G, k: int = 0, verify=False):
         Little R. J. A. and Rubin D. B. (2014).
         Statistical analysis with missing data. 2nd ed., Wiley, Hoboken, N.J.
 
-    Note
+    Notes
     ------
         The sweep operator is defined for symmetric matrices as follows. A p x p
         symmetric matrix G is said to be swept on row and column k if it is replaced by

pyrolite/geochem/ind.py

@@ -42,8 +42,8 @@ def common_elements(cutoff=92, output="string", order=None, as_set=False):
     :class:`list` | :class:`set`
         List of elements.
 
-    Note
-    -----
+    Notes
+    ------
         Formulae cannot be used as members of a set, and hence sets returned will
         instead consist only of strings.
 
@@ -130,8 +130,8 @@ def common_oxides(
     :class:`list` | :class:`set`
         List of oxides.
 
-    Note
-    -----
+    Notes
+    ------
         Formulae cannot be used as members of a set, and hence sets returned will
         instead consist only of strings.
 

pyrolite/geochem/norm.py

@@ -25,8 +25,6 @@ def scale_multiplier(in_unit, target_unit="ppm"):
     """
     Provides the scale difference between to mass units.
 
-    Todo: implement different inputs - string, list, pandas series
-
     Parameters
     ----------
     in_unit: current units

pyrolite/geochem/transform.py

@@ -464,9 +464,10 @@ def convert_chemistry(input_df, to=[], logdata=False, renorm=False):
         # can't deal with more than one component/component speciation
         if len(get_fe) > 1:
             raise NotImplementedError
-        get_fe = get_fe[0]
-        df = recalculate_Fe(df, to=get_fe, renorm=False, logdata=logdata)
-        logger.info("Reducing {} to {}.".format(c_fe_str, get_fe))
+        else:
+            get_fe = get_fe[0]
+            df = recalculate_Fe(df, to=get_fe, renorm=False, logdata=logdata)
+            logger.info("Transforming {} to {}.".format(c_fe_str, get_fe))
 
     # Try to get some ratios -----------------------------------------------------------
     ratios = [i for i in to if "/" in i and i in get]
@@ -479,12 +480,14 @@ def convert_chemistry(input_df, to=[], logdata=False, renorm=False):
 
     # Last Minute Checks ---------------------------------------------------------------
     remaining = [i for i in to if i not in df.columns]
+    df_comp_c = [i for i in df.columns if i in c_components]
     assert not len(remaining), "Columns not attained: {}".format(", ".join(remaining))
     if renorm:
-        logger.info("Recalculation Done, Renormalising")
-        return renormalise(df.loc[:, to])
+        logger.info("Recalculation Done, Renormalising compositional components.")
+        df.loc[:, df_comp_c] = renormalise(df.loc[:, df_comp_c])
+        return df.loc[:, to]
     else:
-        logger.info("Recalculation Done.")
+        logger.info("Recalculation Done. Data not renormalised.")
         return df.loc[:, to]