phm-plot.py

# coding=UTF-8

# Usage:
# python plot.py [end_record]
# python plot.py [start_record] [end_record]

import sys
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np

mpl.rcParams['agg.path.chunksize'] = 10000

FILES = []

LABEL = {
    'ForceX': 'ForceX',
    'ForceY': 'ForceY',
    'ForceZ': 'ForceZ',
    'VibrationX': 'VibrationX',
    'VibrationY': 'VibrationY',
    'VibrationZ': 'VibrationZ',
    'AE_RMS': 'AE_RMS',
}

FEATURES = [
    # {
    #     'label': LABEL['ForceX'],
    #     'color': 'r',
    #     's': 0.5,
    #     'alpha': 0.3,
    # },
    # {
    #     'label': LABEL['ForceY'],
    #     'color': 'g',
    #     's': 0.5,
    #     'alpha': 0.3,
    # },
    # {
    #     'label': LABEL['ForceZ'],
    #     'color': 'b',
    #     's': 0.5,
    #     'alpha': 0.3,
    # },
    # {
    #     'label': LABEL['VibrationX'],
    #     'color': 'r',
    #     's': 0.5,
    #     'alpha': 0.8,
    # },
    # {
    #     'label': LABEL['VibrationY'],
    #     'color': 'g',
    #     's': 0.5,
    #     'alpha': 0.8,
    # },
    # {
    #     'label': LABEL['VibrationZ'],
    #     'color': 'b',
    #     's': 0.5,
    #     'alpha': 0.8,
    # },
    {
        'label': LABEL['AE_RMS'],
        'color': 'y',
        's': 0.5,
        'alpha': 0.8,
    },
]
yLabel = ','.join(map(lambda f: f['label'], FEATURES))

CUTTERS = [1, 4, 6]
for cutter in CUTTERS:
    for cut in range(1, 316):
        cutNumber = '{0:0>3}'.format(cut)
        FILES.append('../data/training/c{cutter}/c_{cutter}_{cutNumber}.csv'.format(cutter=cutter, cutNumber=cutNumber))

skipRows = 0
maxRows = 250000
sums = {}

if len(sys.argv) > 1:
    maxRows = int(sys.argv[1])

if len(sys.argv) > 2:
    skipRows = int(sys.argv[1])
    maxRows = int(sys.argv[2])

for filename in FILES:
    # ref: <http://docs.scipy.org/doc/numpy/reference/generated/numpy.genfromtxt.html>
    data = np.genfromtxt(
        filename,
        delimiter=',',
        skip_header=skipRows,
        skip_footer=0,
        names=[
            LABEL['ForceX'],
            LABEL['ForceY'],
            LABEL['ForceZ'],
            LABEL['VibrationX'],
            LABEL['VibrationY'],
            LABEL['VibrationZ'],
            LABEL['AE_RMS'],
        ],
        max_rows=maxRows
    )

    rows = len(data[LABEL['ForceX']])

    # plt.plot(x,y)
    x = range(1 + skipRows, 1 + skipRows + rows)
    for f in FEATURES:
        y = data[f['label']]
        plt.scatter(x, y, color=f['color'], s=f['s'], alpha=f['alpha'])

    #
    # y = data[LABEL['ForceY']]
    # plt.scatter(x, y, color='g', s=0.5, alpha=0.8)
    #
    # y = data[LABEL['ForceZ']]
    # plt.scatter(x, y, color='b', s=0.5, alpha=0.8)

    # y = data[LABEL['VibrationX']]
    # plt.scatter(x, y, color='r', s=0.5, alpha=0.8)

    # y = data[LABEL['VibrationY']]
    # plt.scatter(x, y, color='g', s=0.5, alpha=0.8)
    #
    # y = data[LABEL['VibrationZ']]
    # plt.scatter(x, y, color='b', s=0.5, alpha=0.8)

    # 設定圖的範圍, 不設的話，系統會自行決定
    # rows = len(x)
    plt.xlim(1 + skipRows, 1 + skipRows + rows)
    # plt.ylim(-4, 4)
    #
    plt.xlabel('time(0.02s)')

plt.ylabel(yLabel)

cutterString = '{' + ','.join(map(lambda cutter: 'c' + str(cutter), CUTTERS)) + '}'
featureString = '{' + yLabel + '}'
rowString = '#{start}-#{end}'.format(start=skipRows + 1, end=rows)
displayTitle = '{0}.{1} ({2})'.format(cutterString, featureString, rowString)
fileName = '{0}.{1}_{2}'.format(cutterString, featureString, rowString)
plt.title(displayTitle)

plt.savefig('../plots/{0}.jpg'.format(fileName), dpi=300, format='jpg')
# plt.show()
# plt.clf()