13486214877

Committed 23 Feb 2025 07:30PM UTC coverage: 84.783% (-2.9%) from 87.727%

Build # 13486214877

Build Type

Pull #9

github

Committed by

BestLocation

Commit Message

fix errors with files

Pull Request Pull Request #9: Added boxplot and tests

Run Details

58 of 69 new or added lines in 2 files covered. (84.06%)

273 of 322 relevant lines covered (84.78%)

6.97 hits per line

Source File
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66.67

/MatPlus/BoxPlot.py

import matplotlib.pyplot as plt
import numpy as np


class BoxPlot:
    def __init__(self, data, notch=False, sym="b", vert=True, whis=1.5):
        """Initializes Boxplot object with the following parameters:
        data: data to be plotted
        notch: notch shape of the box
        sym: symbol for outliers
        vert: vertical orientation (deprecated, use orientation instead)
        whis: whisker length in number of IQR
        """
        if not data or len(data) == 0:
            raise ValueError("Data array cannot be empty")

        self.data = data
        self.notch = notch
        self.sym = sym
        self.vert = vert
        self.whis = whis

    def median(self):
        """Calculate median of the data"""
        return float(np.median(self.data))

    def quartiles(self):
        """Calculate first and third quartiles"""
        q1 = float(np.percentile(self.data, 25))
        q3 = float(np.percentile(self.data, 75))
        return (q1, q3)

    def outliers(self):
        """Identify outliers using whis*IQR rule"""
        q1, q3 = self.quartiles()
        iqr = q3 - q1
        lower_bound = q1 - (self.whis * iqr)
        upper_bound = q3 + (self.whis * iqr)
        return [x for x in self.data if x < lower_bound or x > upper_bound]

    def plot(self):
        """Generate box plot"""
        plt.style.use("_mpl-gallery")
        fig, ax = plt.subplots()

        # Set orientation using new parameter name
        orientation = "vertical" if self.vert else "horizontal"

        # Set ticks properly
        if orientation == "vertical":
            ax.set_xticks([1])
            ax.set_xticklabels(["Data"])
        else:
            ax.set_yticks([1])
            ax.set_yticklabels(["Data"])

        plt.show()

1	import matplotlib.pyplot as plt	6✔
2	import numpy as np	6✔
3
4
5	class BoxPlot:	6✔
6	def __init__(self, data, notch=False, sym="b", vert=True, whis=1.5):	6✔
7	"""Initializes Boxplot object with the following parameters:
8	data: data to be plotted
9	notch: notch shape of the box
10	sym: symbol for outliers
11	vert: vertical orientation (deprecated, use orientation instead)
12	whis: whisker length in number of IQR
13	"""
14	if not data or len(data) == 0:	6✔
15	raise ValueError("Data array cannot be empty")	6✔
16
17	self.data = data	6✔
18	self.notch = notch	6✔
19	self.sym = sym	6✔
20	self.vert = vert	6✔
21	self.whis = whis	6✔
22
23	def median(self):	6✔
24	"""Calculate median of the data"""
NEW 25	return float(np.median(self.data))	×
26
27	def quartiles(self):	6✔
28	"""Calculate first and third quartiles"""
NEW 29	q1 = float(np.percentile(self.data, 25))	×
NEW 30	q3 = float(np.percentile(self.data, 75))	×
NEW 31	return (q1, q3)	×
32
33	def outliers(self):	6✔
34	"""Identify outliers using whis*IQR rule"""
NEW 35	q1, q3 = self.quartiles()	×
NEW 36	iqr = q3 - q1	×
NEW 37	lower_bound = q1 - (self.whis * iqr)	×
NEW 38	upper_bound = q3 + (self.whis * iqr)	×
NEW 39	return [x for x in self.data if x < lower_bound or x > upper_bound]	×
40
41	def plot(self):	6✔
42	"""Generate box plot"""
43	plt.style.use("_mpl-gallery")	6✔
44	fig, ax = plt.subplots()	6✔
45
46	# Set orientation using new parameter name
47	orientation = "vertical" if self.vert else "horizontal"	6✔
48
49	# Set ticks properly
50	if orientation == "vertical":	6✔
51	ax.set_xticks([1])	6✔
52	ax.set_xticklabels(["Data"])	6✔
53	else:
NEW 54	ax.set_yticks([1])	×
NEW 55	ax.set_yticklabels(["Data"])	×
56
57	plt.show()	6✔

ac-i2i-engineering / MatPlus / 13486214877

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