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
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
|
"""
================
Ishikawa Diagram
================
Ishikawa Diagrams, fishbone diagrams, herringbone diagrams, or cause-and-effect
diagrams are used to identify problems in a system by showing how causes and
effects are linked.
Source: https://en.wikipedia.org/wiki/Ishikawa_diagram
"""
import math
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon, Wedge
fig, ax = plt.subplots(figsize=(10, 6), layout='constrained')
ax.set_xlim(-5, 5)
ax.set_ylim(-5, 5)
ax.axis('off')
def problems(data: str,
problem_x: float, problem_y: float,
angle_x: float, angle_y: float):
"""
Draw each problem section of the Ishikawa plot.
Parameters
----------
data : str
The name of the problem category.
problem_x, problem_y : float, optional
The `X` and `Y` positions of the problem arrows (`Y` defaults to zero).
angle_x, angle_y : float, optional
The angle of the problem annotations. They are always angled towards
the tail of the plot.
Returns
-------
None.
"""
ax.annotate(str.upper(data), xy=(problem_x, problem_y),
xytext=(angle_x, angle_y),
fontsize=10,
color='white',
weight='bold',
xycoords='data',
verticalalignment='center',
horizontalalignment='center',
textcoords='offset fontsize',
arrowprops=dict(arrowstyle="->", facecolor='black'),
bbox=dict(boxstyle='square',
facecolor='tab:blue',
pad=0.8))
def causes(data: list,
cause_x: float, cause_y: float,
cause_xytext=(-9, -0.3), top: bool = True):
"""
Place each cause to a position relative to the problems
annotations.
Parameters
----------
data : indexable object
The input data. IndexError is
raised if more than six arguments are passed.
cause_x, cause_y : float
The `X` and `Y` position of the cause annotations.
cause_xytext : tuple, optional
Adjust to set the distance of the cause text from the problem
arrow in fontsize units.
top : bool, default: True
Determines whether the next cause annotation will be
plotted above or below the previous one.
Returns
-------
None.
"""
for index, cause in enumerate(data):
# [<x pos>, <y pos>]
coords = [[0.02, 0],
[0.23, 0.5],
[-0.46, -1],
[0.69, 1.5],
[-0.92, -2],
[1.15, 2.5]]
# First 'cause' annotation is placed in the middle of the 'problems' arrow
# and each subsequent cause is plotted above or below it in succession.
cause_x -= coords[index][0]
cause_y += coords[index][1] if top else -coords[index][1]
ax.annotate(cause, xy=(cause_x, cause_y),
horizontalalignment='center',
xytext=cause_xytext,
fontsize=9,
xycoords='data',
textcoords='offset fontsize',
arrowprops=dict(arrowstyle="->",
facecolor='black'))
def draw_body(data: dict):
"""
Place each problem section in its correct place by changing
the coordinates on each loop.
Parameters
----------
data : dict
The input data (can be a dict of lists or tuples). ValueError
is raised if more than six arguments are passed.
Returns
-------
None.
"""
# Set the length of the spine according to the number of 'problem' categories.
length = (math.ceil(len(data) / 2)) - 1
draw_spine(-2 - length, 2 + length)
# Change the coordinates of the 'problem' annotations after each one is rendered.
offset = 0
prob_section = [1.55, 0.8]
for index, problem in enumerate(data.values()):
plot_above = index % 2 == 0
cause_arrow_y = 1.7 if plot_above else -1.7
y_prob_angle = 16 if plot_above else -16
# Plot each section in pairs along the main spine.
prob_arrow_x = prob_section[0] + length + offset
cause_arrow_x = prob_section[1] + length + offset
if not plot_above:
offset -= 2.5
if index > 5:
raise ValueError(f'Maximum number of problems is 6, you have entered '
f'{len(data)}')
problems(list(data.keys())[index], prob_arrow_x, 0, -12, y_prob_angle)
causes(problem, cause_arrow_x, cause_arrow_y, top=plot_above)
def draw_spine(xmin: int, xmax: int):
"""
Draw main spine, head and tail.
Parameters
----------
xmin : int
The default position of the head of the spine's
x-coordinate.
xmax : int
The default position of the tail of the spine's
x-coordinate.
Returns
-------
None.
"""
# draw main spine
ax.plot([xmin - 0.1, xmax], [0, 0], color='tab:blue', linewidth=2)
# draw fish head
ax.text(xmax + 0.1, - 0.05, 'PROBLEM', fontsize=10,
weight='bold', color='white')
semicircle = Wedge((xmax, 0), 1, 270, 90, fc='tab:blue')
ax.add_patch(semicircle)
# draw fish tail
tail_pos = [[xmin - 0.8, 0.8], [xmin - 0.8, -0.8], [xmin, -0.01]]
triangle = Polygon(tail_pos, fc='tab:blue')
ax.add_patch(triangle)
# Input data
categories = {
'Method': ['Time consumption', 'Cost', 'Procedures', 'Inefficient process',
'Sampling'],
'Machine': ['Faulty equipment', 'Compatibility'],
'Material': ['Poor-quality input', 'Raw materials', 'Supplier',
'Shortage'],
'Measurement': ['Calibration', 'Performance', 'Wrong measurements'],
'Environment': ['Bad conditions'],
'People': ['Lack of training', 'Managers', 'Labor shortage',
'Procedures', 'Sales strategy']
}
draw_body(categories)
plt.show()
|
