WiFi_CSI/batch_graph.py at master · CheChc/WiFi_CSI · GitHub

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# 将此文件覆盖到路径CSIKit中的CSIKit\CSIKit\tools,便于使用trans.py批量生成图片数据
import matplotlib.pyplot as plt
import numpy as np
from CSIKit.util import matlab

from CSIKit.util.csitools import get_CSI
from CSIKit.util.filters import bandpass, hampel, running_mean
from CSIKit.reader import get_reader, IWLBeamformReader

DEFAULT_PATH = "./data/intel/misc/log.all_csi.6.7.6.dat"


# DEFAULT_PATH = "./data/pi/walk_1597159475.pcap"

class BatchGraph:

    def __init__(self, path: str = DEFAULT_PATH, scaled: bool = False, filter_mac: str = None):
        reader = get_reader(path)
        self.csi_data = reader.read_file(path, scaled=scaled, filter_mac=filter_mac)
        self.path = path

    def prepostfilter(self):

        csi_trace = self.csi_data.frames
        finalEntry, no_frames, _ = get_CSI(self.csi_data)

        finalEntry = finalEntry[15]

        hampelData = hampel(finalEntry, 10)
        smoothedData = running_mean(hampelData.copy(), 10)

        y = finalEntry
        y2 = hampelData
        y3 = smoothedData

        x = list([x.timestamp for x in csi_trace])

        if sum(x) == 0:
            x = np.arange(0, no_frames, 1)

        plt.plot(x, y, label="Raw")
        plt.plot(x, y2, label="Hampel")
        plt.plot(x, y3, "r", label="Hampel + Running Mean")

        plt.xlabel("Time (s)")
        plt.ylabel("Amplitude (dBm)")
        plt.legend(loc="upper right")

        output_path = self.path.replace('.dat', '_prepostfilter.png')
        plt.savefig(output_path)
        plt.close()

    def plotAllSubcarriers(self):

        finalEntry, no_frames, _ = get_CSI(self.csi_data)

        for x in finalEntry:
            plt.plot(np.arange(no_frames) / 20, x)

        plt.xlabel("Time (s)")
        plt.ylabel("Amplitude (dBm)")
        plt.legend(loc="upper right")

        output_path = self.path.replace('.dat', '_all_subcarriers.png')
        plt.savefig(output_path)
        plt.close()

    def heatmap(self):

        finalEntry, no_frames, no_subcarriers = get_CSI(self.csi_data)
        if len(finalEntry.shape) == 4:
            finalEntry = finalEntry[:, :, 0, 0]

        finalEntry = np.transpose(finalEntry)

        x_label = "Time (s)"
        try:
            x = self.csi_data.timestamps
            x = [timestamp - x[0] for timestamp in x]
        except AttributeError:
            x = [0]

        if sum(x) == 0:
            xlim = no_frames
            x_label = "Frame No."
        else:
            xlim = max(x)

        limits = [0, xlim, 1, no_subcarriers]

        _, ax = plt.subplots()
        im = ax.imshow(finalEntry, cmap="jet", extent=limits, aspect="auto")

        cbar = ax.figure.colorbar(im, ax=ax)
        cbar.ax.set_ylabel("Amplitude (dBm)")

        plt.xlabel(x_label)
        plt.ylabel("Subcarrier Index")

        plt.title(self.csi_data.filename)

        output_path = self.path.replace('.dat', '_heatmap.png')
        plt.savefig(output_path)
        plt.close()

    @staticmethod
    def plot_heatmap(csi_matrix, timestamps, output_path):

        csi_matrix = np.transpose(csi_matrix)

        x_label = "Time (s)"
        try:
            x = timestamps
            x = [timestamp - x[0] for timestamp in x]
        except AttributeError:
            x = [0]

        if sum(x) == 0:
            xlim = csi_matrix.shape[1]
            x_label = "Frame No."
        else:
            xlim = max(x)

        limits = [0, xlim, 1, csi_matrix.shape[0]]

        _, ax = plt.subplots()
        im = ax.imshow(csi_matrix, cmap="jet", extent=limits, aspect="auto")

        cbar = ax.figure.colorbar(im, ax=ax)
        cbar.ax.set_ylabel("Amplitude (dBm)")

        plt.xlabel(x_label)
        plt.ylabel("Subcarrier Index")

        plt.title("CSI Amplitude Heatmap Plot")

        plt.savefig(output_path)
        plt.close()

    def sumsqrssi(self):
        finalEntry, no_frames, no_subcarriers = get_CSI(self.csi_data, extract_as_dBm=False)
        if len(finalEntry.shape) == 4:
            finalEntry = finalEntry[:, :, 0, 0]

        csi = finalEntry
        rss = [x.rssi for x in self.csi_data.frames]

        sumsq = np.sum(csi ** 2, axis=1)
        norm_sumsq = np.sqrt(sumsq) / no_subcarriers

        line = [matlab.db(sumsq_value) / rss_value for rss_value, sumsq_value in zip(rss, norm_sumsq)]

        plt.plot(self.csi_data.timestamps, line)

        plt.xlabel("Time (s)")
        plt.ylabel("RSSI / sumsq")

        plt.title(self.csi_data.filename)

        output_path = self.path.replace('.dat', '_sumsqrssi.png')
        plt.savefig(output_path)
        plt.close()


if __name__ == "__main__":
    bg = BatchGraph()
    bg.heatmap()