importmathimportmatplotlib.pyplotaspltfrommatplotlib.patchesimportPolygon,Wedgefig,ax=plt.subplots(figsize=(10,6),layout='constrained')ax.set_xlim(-5,5)ax.set_ylim(-5,5)ax.axis('off')defproblems(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))defcauses(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.    """forindex,causeinenumerate(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]iftopelse-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'))defdraw_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))-1draw_spine(-2-length,2+length)# Change the coordinates of the 'problem' annotations after each one is rendered.offset=0prob_section=[1.55,0.8]forindex,probleminenumerate(data.values()):plot_above=index%2==0cause_arrow_y=1.7ifplot_aboveelse-1.7y_prob_angle=16ifplot_aboveelse-16# Plot each section in pairs along the main spine.prob_arrow_x=prob_section[0]+length+offsetcause_arrow_x=prob_section[1]+length+offsetifnotplot_above:offset-=2.5ifindex>5:raiseValueError(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)defdraw_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 spineax.plot([xmin-0.1,xmax],[0,0],color='tab:blue',linewidth=2)# draw fish headax.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 tailtail_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 datacategories={'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()

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