如何根据数字符号更改matplotlib中的标记 [英] How to change marker in matplotlib based on sign of number

问题描述

概述

我有一些类似的数据:

• X值:频率范围
• Y值:float可以为正或负的值
  • 如果您好奇，则Y值为电抗
  • X values: range of frequencies
  • Y values: float value that can be positive or negative
    • The Y-value is electrical reactance, if you're curious

    我用对数-对数图表示数据.由于您只能取正数的对数，因此我绘制abs(Y-value).

    I represent the data in a log-log plot. Since you can only take the logarithm of a positive number, I plot abs(Y-value).

    在对数-对数图上，我想通过更改标记符号来表示原始数字的符号:

    On the log-log plot, I would like to represent the original number's sign by changing the marker symbol:

    • +标记(如果符号为+
    )
    • -标记(如果符号为-
    )
    • + marker if sign was +
    • - marker if sign was -

    通常:下面，我放置了当前的方法.我想做得更好".希望matplotlib有更标准的方法来实现这一点.

    Generally: below I have placed my current method. I would like to "do it better". Hopefully matplotlib has a more standard way of doing this.

    详细信息

    目前，这是我的情节:

    这是我当前代码的相似之处(请注意:数据是从设备中提取的，因此在这种情况下，我只使用了random.uniform):

    Here is some semblance of my current code (note: the data was pulled from equipment, so I just used random.uniform in this case):

    import numpy as np
    import matplotlib.pyplot as plt
    from random import uniform
    
    
    # Generating data
    num_pts = 150
    freq_arr = np.logspace(start=2, stop=6, num=num_pts, base=10)
    reactance_arr = [uniform(-1000,1000) for i in range(num_pts)]
    abs_reactance_arr = [abs(i) for i in reactance_arr]
    reactance_signed_marker = [1 if reactance_arr[i] >= 0 else -1 for i in range(len(reactance_arr))]
    
    # Taken from here: https://stackoverflow.com/questions/28706115/how-to-use-different-marker-for-different-point-in-scatter-plot-pylab
    x = np.array(freq_arr)
    y = np.array(abs_reactance_arr)
    grouping = np.array(reactance_signed_marker)
    
    # Plotting
    fig1, ax1 = plt.subplots()
    
    positives_line = ax1.scatter(
        x[grouping == 1], 
        y[grouping == 1], 
        s=16, 
        marker="+", 
        label="Reactance",
    )
    
    # Match color between the two plots
    col = positives_line.get_facecolors()[0].tolist()
    
    ax1.scatter(
        x[grouping == -1],
        y[grouping == -1],
        s=16,
        marker="_",
        label="Reactance",
        color=col,
    )
    
    ax1.set_xlim([freq_arr[0], freq_arr[-1]])
    ax1.set_xscale("log")
    ax1.set_xlabel("Frequency (Hz)")
    ax1.set_yscale("log")
    ax1.set_ylabel("Value (Ohm)")
    ax1.legend()
    ax1.set_title("Reactance")
    

    我该如何做得更好?目前，这感觉非常手动.我想知道:

    How can I do this better? Currently, this feels very manual. I am wondering:

    • 是否有更好的方法将-和+值解析为标记?
      • 当前方法非常麻烦:1.绘制+，2.提取颜色，3.绘制具有相同颜色的-
      • Is there a better way to parse - and + values into markers?
        • The current way is quite cumbersome with 1. plotting +, 2. extracting color, 3. plotting - with the same color

        推荐答案

        我在

        I proposed a scatter with multiple markers in iterating markers in plots. Applying it here would look like:

        import numpy as np
        import matplotlib.pyplot as plt
        
        def mscatter(x, y, ax=None, m=None, **kw):
            import matplotlib.markers as mmarkers
            if not ax: ax=plt.gca()
            sc = ax.scatter(x,y,**kw)
            if (m is not None) and (len(m)==len(x)):
                paths = []
                for marker in m:
                    if isinstance(marker, mmarkers.MarkerStyle):
                        marker_obj = marker
                    else:
                        marker_obj = mmarkers.MarkerStyle(marker)
                    path = marker_obj.get_path().transformed(
                                marker_obj.get_transform())
                    paths.append(path)
                sc.set_paths(paths)
            return sc
        
        # Generating data
        num_pts = 150
        freq_arr = np.logspace(start=2, stop=6, num=num_pts, base=10)
        reactance_arr = np.random.uniform(-1000,1000,num_pts)
        
        x = np.array(freq_arr)
        y = np.abs(reactance_arr)
        markers = np.array(["_", "+"])[(reactance_arr >= 0).astype(int)]
        
        # Plotting
        fig1, ax1 = plt.subplots()
        
        mscatter(x, y, ax=ax1, s=16, m = markers, label="Reactance")
        
        ax1.set_xlim([freq_arr[0], freq_arr[-1]])
        ax1.set_xscale("log")
        ax1.set_xlabel("Frequency (Hz)")
        ax1.set_yscale("log")
        ax1.set_ylabel("Value (Ohm)")
        ax1.legend()
        ax1.set_title("Reactance")
        
        plt.show()
        

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