Geopy/metadata.py at master · HouseJaay/Geopy · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
import distaz
import matplotlib.pyplot as plt
import numpy as np
import pandas
from obspy.core import UTCDateTime


# cut every seismogram in a stream
def cut(st, start, end):
    delta = st[0].stats.delta
    width = end - start
    npts = int(width/delta)
    # check
    if(start > end):
        raise ValueError('starttime must be smaller than endtime')
    for i in range(len(st)):
        if(st[i].stats.delta != delta):
            raise ValueError('all data must have same delta')
        if(st[i].stats.starttime > start or st[i].stats.endtime < end):
            raise ValueError('invalid time range')
    for i in range(len(st)):
        n = int((start - st[i].stats.starttime)/delta)
        st[i].data = st[i].data[n:n+npts]
        st[i].stats.starttime = start

# plot seismogram in a stream
def plot(st):
    n = st[0].stats.npts
    delta = st[0].stats.delta
    t = np.arange(n)*delta
    rows = len(st)
    fig,axes = plt.subplots(nrows=rows,ncols=1)
    for i in range(rows):
        axes[i].plot(t,st[i].data,color='black')
    plt.show()

# input file is bqmail output format
def read_station(filename):
    """
    input file format:
    net station lat lon start end
    """
    col_name = ['net','station','lat','lon','start','end']
    sta = pandas.read_table(filename,sep='\s+',names=col_name)
    sta['start'] = sta['start'].map(read_date)
    sta['end'] = sta['end'].map(read_date)
    return sta

# read date in year/month/day to UTCDateTime format
def read_date(date):
    """
    read date year/month/day
    return UTCDateTime
    """
    temp = date.split('/')
    year = int(temp[0])
    month = int(temp[1])
    day = int(temp[2])
    return UTCDateTime(year,month,day)

def merge_date(start1,end1,start2,end2):
    if(start1 > start2):
        start = start1
    else:
        start = start2
    if(end1 > end2):
        end = end2
    else:
        end = end1
    if(end < start):
        raise ValueError('station pair must have common work date')
    else:
        return start,end

# input value is output of read_table
def mk_sta_pairs(sta):
    col_name = ['net1','station1','lat1','lon1','net2','station2','lat2','lon2','start','end']
    pair = pandas.DataFrame(columns=col_name)
    row = 0
    for i in range(len(sta)-1):
        for j in range(i+1,len(sta)):
            temp1 = [sta['net'][i],sta['station'][i],sta['lat'][i],sta['lon'][i]]
            temp2 = [sta['net'][j],sta['station'][j],sta['lat'][j],sta['lon'][j]]
            try:
                start,end = merge_date(sta['start'][i],sta['end'][i],sta['start'][j],sta['end'][j])
            except ValueError:
                print("date error:%s %s and %s %s" % (sta['net'][i],sta['station'][i],sta['net'][j],sta['station'][j]))
                continue
            pair.loc[row] = temp1 + temp2 + [start,end]
            row += 1
    return pair

def cal_dist(row):
    d = distaz.distaz(row['lat1'],row['lon1'],row['lat2'],row['lon2']).getDelta()
    return d

# input file in bqmail output format
def read_event(filename):
    """
    input file format:
    year month day jday hour min sec lat lon dep mw
    """
    col_name = ['year','month','day','jday','hour','min','sec','lat','lon','dep','mw']
    evt = pandas.read_table(filename, sep='\s+', names=col_name)
    time = lambda x : UTCDateTime(int(x['year']),int(x['month']),int(x['day']),int(x['hour']),int(x['min']),int(x['sec']))
    evt['time'] = evt.apply(time,axis='columns')
    del evt['year'], evt['month'], evt['day'], evt['jday'], evt['hour'], evt['min'], evt['sec']
    return evt

# input list of filenames
def read_data(filelist):
    pass
def plot_data(data):
    pass