8000 Merge pull request #26064 from saranti/fishbone · matplotlib/matplotlib@053e529 · GitHub
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Merge pull request #26064 from saranti/fishbone
add ishikawa diagram to examples
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‎galleries/examples/specialty_plots/ishikawa_diagram.py

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"""
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================
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Ishikawa Diagram
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================
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Ishikawa Diagrams, fishbone diagrams, herringbone diagrams, or cause-and-effect
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diagrams are used to identify problems in a system by showing how causes and
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effects are linked.
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Source: https://en.wikipedia.org/wiki/Ishikawa_diagram
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"""
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import matplotlib.pyplot as plt
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from matplotlib.patches import Polygon, Wedge
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# Create the fishbone diagram
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fig, ax = plt.subplots(figsize=(10, 6), layout='constrained')
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ax.set_xlim(-5, 5)
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ax.set_ylim(-5, 5)
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ax.axis('off')
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def problems(data: str,
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problem_x: float, problem_y: float,
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prob_angle_x: float, prob_angle_y: float):
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"""
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Draw each problem section of the Ishikawa plot.
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Parameters
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----------
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data : str
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The category name.
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problem_x, problem_y : float, optional
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The `X` and `Y` positions of the problem arrows (`Y` defaults to zero).
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prob_angle_x, prob_angle_y : float, optional
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The angle of the problem annotations. They are angled towards
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the tail of the plot.
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Returns
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-------
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None.
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"""
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ax.annotate(str.upper(data), xy=(problem_x, problem_y),
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xytext=(prob_angle_x, prob_angle_y),
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fontsize='10',
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color='white',
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weight='bold',
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xycoords='data',
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verticalalignment='center',
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horizontalalignment='center',
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textcoords='offset fontsize',
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arrowprops=dict(arrowstyle="->", facecolor='black'),
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bbox=dict(boxstyle='square',
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facecolor='tab:blue',
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pad=0.8))
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def causes(data: list, cause_x: float, cause_y: float,
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cause_xytext=(-9, -0.3), top: bool = True):
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"""
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Place each cause to a position relative to the problems
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annotations.
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Parameters
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----------
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data : indexable object
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The input data. IndexError is
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raised if more than six arguments are passed.
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cause_x, cause_y : float
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The `X` and `Y` position of the cause annotations.
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cause_xytext : tuple, optional
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Adjust to set the distance of the cause text from the problem
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arrow in fontsize units.
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top : bool
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Returns
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-------
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None.
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"""
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for index, cause in enumerate(data):
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# First cause annotation is placed in the middle of the problems arrow
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# and each subsequent cause is plotted above or below it in succession.
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# [<x pos>, [<y pos top>, <y pos bottom>]]
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coords = [[0, [0, 0]],
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[0.23, [0.5, -0.5]],
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[-0.46, [-1, 1]],
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[0.69, [1.5, -1.5]],
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[-0.92, [-2, 2]],
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[1.15, [2.5, -2.5]]]
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if top:
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cause_y += coords[index][1][0]
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else:
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cause_y += coords[index][1][1]
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cause_x -= coords[index][0]
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ax.annotate(cause, xy=(cause_x, cause_y),
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horizontalalignment='center',
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xytext=cause_xytext,
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fontsize='9',
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xycoords='data',
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textcoords='offset fontsize',
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arrowprops=dict(arrowstyle="->",
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facecolor='black'))
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def draw_body(data: dict):
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"""
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Place each section in its correct place by changing
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the coordinates on each loop.
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Parameters
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----------
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data : dict
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The input data (can be list or tuple). ValueError is
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raised if more than six arguments are passed.
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Returns
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-------
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None.
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"""
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second_sections = []
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third_sections = []
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# Resize diagram to automatically scale in response to the number
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# of problems in the input data.
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if len(data) == 1 or len(data) == 2:
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spine_length = (-2.1, 2)
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head_pos = (2, 0)
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tail_pos = ((-2.8, 0.8), (-2.8, -0.8), (-2.0, -0.01))
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first_section = [1.6, 0.8]
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elif len(data) == 3 or len(data) == 4:
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spine_length = (-3.1, 3)
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head_pos = (3, 0)
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tail_pos = ((-3.8, 0.8), (-3.8, -0.8), (-3.0, -0.01))
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first_section = [2.6, 1.8]
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second_sections = [-0.4, -1.2]
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else: # len(data) == 5 or 6
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spine_length = (-4.1, 4)
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head_pos = (4, 0)
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tail_pos = ((-4.8, 0.8), (-4.8, -0.8), (-4.0, -0.01))
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first_section = [3.5, 2.7]
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second_sections = [1, 0.2]
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third_sections = [-1.5, -2.3]
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# Change the coordinates of the annotations on each loop.
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for index, problem in enumerate(data.values()):
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top_row = True
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cause_arrow_y = 1.7
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if index % 2 != 0: # Plot problems below the spine.
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top_row = False
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y_prob_angle = -16
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cause_arrow_y = -1.7
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else: # Plot problems above the spine.
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y_prob_angle = 16
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# Plot the 3 sections in pairs along the main spine.
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if index in (0, 1):
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prob_arrow_x = first_section[0]
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cause_arrow_x = first_section[1]
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elif index in (2, 3):
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prob_arrow_x = second_sections[0]
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cause_arrow_x = second_sections[1]
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else:
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prob_arrow_x = third_sections[0]
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cause_arrow_x = third_sections[1]
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if index > 5:
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raise ValueError(f'Maximum number of problems is 6, you have entered '
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f'{len(data)}')
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# draw main spine
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ax.plot(spine_length, [0, 0], color='tab:blue', linewidth=2)
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# draw fish head
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ax.text(head_pos[0] + 0.1, head_pos[1] - 0.05, 'PROBLEM', fontsize=10,
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weight='bold', color='white')
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semicircle = Wedge(head_pos, 1, 270, 90, fc='tab:blue')
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ax.add_patch(semicircle)
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# draw fishtail
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triangle = Polygon(tail_pos, fc='tab:blue')
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ax.add_patch(triangle)
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# Pass each category name to the problems function as a string on each loop.
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problems(list(data.keys())[index], prob_arrow_x, 0, -12, y_prob_angle)
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# Start the cause function with the first annotation being plotted at
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# the cause_arrow_x, cause_arrow_y coordinates.
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causes(problem, cause_arrow_x, cause_arrow_y, top=top_row)
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# Input data
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categories = {
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'Method': ['Time consumption', 'Cost', 'Procedures', 'Inefficient process',
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'Sampling'],
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'Machine': ['Faulty equipment', 'Compatibility'],
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'Material': ['Poor-quality input', 'Raw materials', 'Supplier',
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'Shortage'],
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'Measurement': ['Calibration', 'Performance', 'Wrong measurements'],
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'Environment': ['Bad conditions'],
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'People': ['Lack of training', 'Managers', 'Labor shortage',
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'Procedures', 'Sales strategy']
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}
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draw_body(categories)
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plt.show()

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