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678a0d5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 | import matplotlib.pyplot as plt
import numpy as np
from scipy import stats
class plotting():
def quick_plot(self, scatter=None, line=None, columns=["X","Y"], output=None, hline=None):
"""
Plot the data along with the best fit line and its associated confidence band.
Parameters:
data (list): List of data to plot
columns (list): Axes labels (default is "X","Y")
Returns:
None: Displays a matplotlib plot with data, fit line, and confidence band
Example:
>>> quick_plot(x_data, y_data)
"""
if scatter is None and line is None:
raise ValueError("Either scatter or line should be provided")
if not isinstance(scatter,list):
scatter = [scatter]
if not isinstance(line,list):
line = [line]
# Plot the observed data points as a scatter plot
for ds in scatter:
plt.scatter(ds[:,0],ds[:,1], color='blue', label='Data')
# Add labels and title to the plot
plt.xlabel(columns[0])
plt.ylabel(columns[1])
if hline is not None:
plt.axhline(hline, color='black', linestyle='--')
# Display the legend
plt.legend()
# Show the plot
if output is None:
plt.show()
else:
plt.savefig(output)
plt.close()
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