Ternary plotting but specifically aimed at those working in geology who want to plot petrograpic data. Quartz, feldspar and lithic data derived from petrographic analysis can be plotted on a QFL diagram as per Pettijohn (1977) to gain an idea of their petrographic classification. Recently added the Dickenson (1983) classification diagram.
This repo includes a notebook to demonstrate the use of the QFL ternary as well as the file to run the plotting.
classified_data, makefig.plot = plot_qfl(data, top=quartz, left=fsp, right=lithic, matrix=matrix, plottype='Pettijohn_1977' , toplab='Q', leftlab='F', rightlab='L', grid=True, color='r', size=15)
Parameters:
data: dataframe
pandas data frame containing the data to which classifications can be appended
top, left, right: str or array-like
the three paramaters to plot. Commonly these will be 1D arrays, but can also be strings referencing columns in the
dataframe
matrix: str or array-like, optional, default=None
if plotting petrographic data clay matrix values can be included. Commonly this will be a 1D array, but can also be
a string referencing a column in the dataframe
plottype: str, optional, default='blank'
The background on which to plot the data, options are 'Dickinson_1983', 'Pettijohn_1977' or 'blank'.
toplab, leftlab, rightlab: str, optional
The apex labels as strings
grid: bool, optional, default=False
To plot grid and axis ticks
color: color, optional
The marker color
size: scaler, optional
The marker size
Returns:
final_data: dataframe
The original dataframe with classifications column added, returns None if blank backgound
fig: pyploy figure
Shown with plt.show()
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