如何通过每个lin中的值来分隔和绘制数组中的线

Question

我是Python新手，正在尝试从不断增长的CSV中提取数据，并创建一个实时更新的绘图。我想创建两个不同的x，y数组，这取决于数据通过哪个天线（每行数据中的一个值用逗号分隔）。数据文件如下所示：

TimeStamp, ReadCount, Antenna, Protocol, RSSI, EPC, Sensor 09/21/2016 15:24:40.560, 5499, 1, GEN2, -21, E036112D912508B3, 23.78,47.00,0.00,2.21, (Infinity%) 09/21/2016 15:24:41.138, 5506, 1, GEN2, -9, E036112D912508B3, 23.99,46.00,0.00,2.26, (Infinity%) 09/21/2016 15:24:41.623, 5513, 1, GEN2, -25, E036112D912508B3, 23.99,46.00,0.00,2.26, (Infinity%) 09/21/2016 15:24:42.120, 5520, 1, GEN2, -18, E036112D912508B3, 23.78,46.00,0.00,2.26, (Infinity%) 09/21/2016 15:24:42.633, 5527, 1, GEN2, -12, E036112D912508B3, 23.99,45.00,0.00,2.23, (Infinity%) 09/21/2016 15:24:43.211, 5534, 1, GEN2, -9, E036112D912508B3, 23.99,46.00,0.00,2.26, (Infinity%) 09/21/2016 15:24:43.744, 5541, 1, GEN2, -16, E036112D912508B3, 23.99,46.00,0.00,2.26, (Infinity%)

Answer 1

您可以简单地使用相同的轴绘制每个数据集。你知道吗

下面的方法使用Python csv.DictReader帮助读取数据，同时使用defaultdict(list)根据每行的天线自动将数据拆分为列表。你知道吗

这也会添加代码来处理您关于将数据点分组的注释，这些数据点之间的间隔不超过60秒，并且只显示最后5分钟的条目：

import matplotlib
import matplotlib.pyplot as plt
import matplotlib.animation as animation

from datetime import datetime, timedelta
import collections
import csv

offset = -7.4954
slope = 0.9548

def plot(ax, data, colour, width):
    if data:
        last_dt = data[0][0]
        sixty = timedelta(seconds=60)

        x = []
        y = []

        # Plot groups of data not more than 60 seconds apart
        for dt, ten in data:
            if dt <= last_dt + sixty:
                x.append(dt)
                y.append(ten)
            else:
                ax.plot(matplotlib.dates.date2num(x), y, colour, linewidth=width)
                x = [dt]
                y = [ten]

            last_dt = dt

        ax.plot(matplotlib.dates.date2num(x), y, colour, linewidth=width)


def animate(i, fig, ax):
    # Read in the CSV file
    data = collections.defaultdict(list)
    fields = ["TimeStamp", "ReadCount", "Antenna", "Protocol", "RSSI", "EPC", "Temp", "Ten", "Powr", "Unpowr", "Inf"]

    with open('SensorLog.csv') as f_input:
        csv_input = csv.DictReader(f_input, skipinitialspace=True, fieldnames=fields)
        header = next(csv_input)

        # Separate the rows based on the Antenna field
        for row in csv_input:
            try:
                data[row['Antenna']].append(
                    [datetime.strptime(row['TimeStamp'], '%m/%d/%Y %H:%M:%S.%f'), 
                    int(float(row['Ten']) * float(slope) + float(offset))])
            except TypeError as e:
                pass

    # Drop any data points more than 5 mins older than the last entry

    latest_dt = data[row['Antenna']][-1][0]     # Last entry
    not_before = latest_dt - timedelta(minutes=5)

    for antenna, entries in data.items():
        data[antenna] = [[dt, count] for dt, count in entries if dt >= not_before]

    # Redraw existing axis
    ax.clear()

    ax.spines['bottom'].set_color("#5998ff")
    ax.spines['top'].set_color("#5998ff")
    ax.spines['left'].set_color("#5998ff")
    ax.spines['right'].set_color("#5998ff")

    hfmt = matplotlib.dates.DateFormatter('%m/%d/%Y\n%I:%M:%S %p')
    ax.xaxis.set_major_formatter(hfmt)
    fig.autofmt_xdate()

    plot(ax, data['1'], 'c', 2)     # Antenna 1
    plot(ax, data['2'], 'r', 3)     # Antenna 2

    ax.grid(True, color='w')
    plt.ylabel('Tension (lb)', color='w', fontsize=20)
    plt.title('Spiral 1 Tension', color='w', fontsize=26)

    ax.tick_params(axis='y', colors='w')
    ax.tick_params(axis='x', colors='w')

fig = plt.figure(facecolor='#07000d')
ax = fig.add_subplot(111, axisbg='#07000d')

ani = animation.FuncAnimation(fig, animate, fargs=(fig, ax), interval=1000)
plt.show()

这将为您提供以下类型的输出：