Plotting Raw Data with Pyleoclim

This notebook lays out the details of how we plot raw data using Pyleoclim objects that we loaded in the Load Data notebook.

The notebook is structured as follows:

1. Load and plot the raw records

# Importing relevant packages

import pickle

import pyleoclim as pyleo
import matplotlib.pyplot as plt

# Importing the data

with open("../../data/plotting_series_dict.pkl", "rb") as handle:
    plotting_series_dict = pickle.load(handle)

with open("../../data/cmap_grouped.pkl", "rb") as handle:
    cmap_grouped = pickle.load(handle)

with open("../../data/marker_dict.pkl", "rb") as handle:
    marker_dict = pickle.load(handle)

Pyleoclim has some built-in plotting functionalities for multiple records (e.g. stackplot), but we’re going to do something slightly more bespoke as we want to have multiple columns:

# Plotting the data

plot_order = [
    "Kesang.China.2012",
    "Linzhu.China.2009",
    "Bittoo.India.2016",
    "Dongge.China.2004",
    "Sanbao.China.2016",
    "CuevadelDiamante.Peru.2013",
    "Botuvera.Brazil.2005",
    "Leviathan.Nevada.2017",
    "DevilsHole.Nevada.2017",
    "BuckeyeCreek.WestVirginia.2019",
    "Peqiin.Israel.2003",
    "JerusalemWest.Jerusalem.1999",
    "Soreq.Israel.2003",
    "Clearwater.Borneo.2016",
]

fig = plt.figure(figsize=(16, 22))
gs = fig.add_gridspec(7, 2)

for idx, label in enumerate(plot_order):
    ts = plotting_series_dict[label]
    if idx <= 6:
        gs_slot = gs[idx, 0]
    else:
        gs_slot = gs[idx - 7, 1]

    ts.value_name = r"$\delta^{18}O$"
    ts.value_unit = "‰"
    ax = fig.add_subplot(gs_slot)
    ts.plot(ax=ax, color=cmap_grouped[ts.label])
    ax.legend(
        handles=[
            plt.Line2D(
                [0],
                [0],
                marker=marker_dict[label],
                color=cmap_grouped[label],
                label=label,
                markersize=10,
                linestyle="None",
            )
        ]
    ).set_visible(True)
    ax.invert_xaxis()
    if idx in [6, 13]:
        pass
    else:
        ax.set_xlabel("")
    if idx in [0, 1, 2, 3, 4, 5, 6]:
        pass
    else:
        ax.set_ylabel("")