def setUp(self):
self.C = get_reference_composition("Chondrite_PON")
els = [i for i in REE() if not i == "Pm"]
vals = self.C[els]
self.df = pd.DataFrame({k: v for (k, v) in zip(els, vals)}, index=[0])
self.df.loc[1, :] = self.df.loc[0, :]
self.default_degree = 3
def setUp(self):
self.fromdir = temp_path() / ("testmelts" + self.__class__.__name__)
self.fromdir.mkdir(parents=True)
Gale_MORB = get_reference_composition("MORB_Gale2013")
majors = [
"SiO2",
"Al2O3",
"FeO",
"MnO",
"MgO",
"CaO",
"Na2O",
"TiO2",
"K2O",
"P2O5",
]
MORB = Gale_MORB.comp.loc[:, majors].apply(pd.to_numeric)
MORB = MORB.append(MORB).reset_index().drop(columns="index")
MORB["Title"] = [
"{}_{}".format(Gale_MORB.name, ix).replace("_", "")
for ix in MORB.index.values.astype(str)
]
MORB["Initial Temperature"] = 1300
MORB["Final Temperature"] = 800
MORB["Initial Pressure"] = 5000
MORB["Final Pressure"] = 5000
MORB["Log fO2 Path"] = "FMQ"
MORB["Increment Temperature"] = -5
MORB["Increment Pressure"] = 0
self.df = MORB
self.env = ENV
def isobaricGaleMORBexample(T0=1300, T1=800, P0=5000, P1=5000, fO2="FMQ", title=None):
Gale_MORB = get_reference_composition("MORB_Gale2013")
majors = [
"SiO2",
"Al2O3",
"FeO",
"MnO",
"MgO",
"CaO",
"Na2O",
"TiO2",
"K2O",
"P2O5",
]
MORB = Gale_MORB.comp[majors].reset_index(drop=True)
if title is not None:
MORB["Title"] = title
MORB["Initial Temperature"] = T0
MORB["Final Temperature"] = T1
MORB["Initial Pressure"] = P0
MORB["Final Pressure"] = P1
MORB["Log fO2 Path"] = fO2
MORB["Increment Temperature"] = -5
MORB["Increment Pressure"] = 0
return MORB
def setUp(self):
self.C = get_reference_composition("PM_PON")
self.C.set_units("ppm")
els = [i for i in REE() if not i == "Pm"]
vals = self.C[els]
self.df = pd.DataFrame({k: v for (k, v) in zip(els, vals)}, index=[0])
self.df = self.df.pyrochem.normalize_to("Chondrite_PON", units="ppm")
self.df.loc[1, :] = self.df.loc[0, :]
self.default_degree = 3
def test_norm_n_normto(self):
"""Check that norm indicator _n can be used with a specific norm."""
df = self.df.copy()
ratio = "Li/B_n"
for norm_to in [
"Chondrite_PON",
get_reference_composition("Chondrite_PON"),
(1.0, 2.0),
]:
with self.subTest(norm_to=norm_to):
r = get_ratio(df, ratio=ratio, norm_to=norm_to)
def test_norm_n_normto(self):
"""Check that norm indicator _n can be used with a specific norm."""
df = self.df.copy()
ratio = "Li/B_n"
values = df["Li"].values / df["B"].values
for norm_to in [
"Chondrite_PON",
get_reference_composition("Chondrite_PON"),
(1.0, 2.0),
4.5,
]:
with self.subTest(norm_to=norm_to):
r = get_ratio(df, ratio=ratio, norm_to=norm_to)
self.assertFalse(np.isclose(values, r.values).any())
def test_pyrochem_denormalize_from_composition(self):
obj = self.df.copy(deep=True).pyrochem.compositional
out = obj.pyrochem.denormalize_from(
get_reference_composition("Chondrite_PON"))
"""
Spiderplots & Density Spiderplots
==================================
"""
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
# sphinx_gallery_thumbnail_number = 4
########################################################################################
# Here we'll set up an example which uses EMORB as a starting point:
#
from pyrolite.geochem.norm import get_reference_composition
ref = get_reference_composition(
"EMORB_SM89") # EMORB composition as a starting point
ref.set_units("ppm")
df = ref.comp.pyrochem.compositional
########################################################################################
# Basic spider plots are straightforward to produce:
import pyrolite.plot
df.pyroplot.spider(color="k")
plt.show()
########################################################################################
# Typically we'll normalise trace element compositions to a reference composition
# to be able to link the diagram to 'relative enrichement' occuring during geological
# processes:
#
normdf = df.pyrochem.normalize_to("PM_PON", units="ppm")
normdf.pyroplot.spider(color="k", unity_line=True)
"""
Normalization
==============
A selection of reference compositions are included in pyrolite, and can be easily
accessed with :func:`pyrolite.geochem.norm.get_reference_composition` (see the list
at the bottom of the page for a complete list):
"""
import pandas as pd
import matplotlib.pyplot as plt
import pyrolite.plot
from pyrolite.geochem.ind import REE
from pyrolite.geochem.norm import get_reference_composition, all_reference_compositions
########################################################################################
chondrite = get_reference_composition("Chondrite_PON")
########################################################################################
# To use the compositions with a specific set of units, you can change them with
# :func:`~pyrolite.geochem.norm.Composition.set_units`:
#
CI = chondrite.set_units("ppm")
#########################################################################################
# The :func:`~pyrolite.geochem.pyrochem.normalize_to` method can be used to
# normalise DataFrames to a given reference (e.g. for spiderplots):
#
fig, ax = plt.subplots(1)
for name, ref in list(all_reference_compositions().items())[::2]:
if name != "Chondrite_PON":
ref.set_units("ppm")
df = ref.comp.pyrochem.REE.pyrochem.normalize_to(CI, units="ppm")
def test_default(self):
rc = "Chondrite_PON"
out = get_reference_composition(rc)
self.assertIsInstance(out, Composition)
def test_pyrochem_normalize_to_composition(self):
obj = self.df.copy(deep=True)
out = obj.pyrochem.normalize_to(
get_reference_composition("Chondrite_PON"))