aboutsummaryrefslogtreecommitdiff
path: root/src/argaze/DataStructures.py
blob: 2a8aed1f9830b39bdd7f0be1d2ad676ec29c110c (plain)
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
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
#!/usr/bin/env python

from typing import TypeVar, Tuple
import collections
import json
import bisect

import pandas
import matplotlib.pyplot as mpyplot
import matplotlib.patches as mpatches

TimeStampType = TypeVar('TimeStamp', int, float)
"""Type definition for timestamp as integer or float values."""

DataType = TypeVar('Data')
"""Type definition for data to store anything in time."""

TimeStampedBufferType = TypeVar('TimeStampedBuffer', bound="TimeStampedBuffer")
# Type definition for type annotation convenience

class TimeStampedBuffer(collections.OrderedDict):
    """Ordered dictionary to handle timestamped data.
    ```
        {
            timestamp1: data1,
            timestamp2: data2,
            ...
        }
    ```

    .. warning::
       Timestamps must be numbers.

    .. warning::
       Timestamps are not sorted by any order.
    """

    def __new__(cls, args = None):
        """Inheritance"""

        return super(TimeStampedBuffer, cls).__new__(cls)

    def __setitem__(self, ts: TimeStampType, data: DataType):
        """Store data at given timestamp."""

        assert(type(ts) == int or type(ts) == float)

        super().__setitem__(ts, data)

    def __str__(self):
        """String representation"""

        return json.dumps(self, default=vars)

    def append(self, timestamped_buffer: TimeStampedBufferType):
        """Append a timestamped buffer."""

        for ts, value in timestamped_buffer.items():
            self[ts] = value

    def get_first(self) -> Tuple[TimeStampType, DataType]:
        """Easing access to first item."""

        return list(self.items())[0]

    def pop_first(self) -> Tuple[TimeStampType, DataType]:
        """Easing FIFO access mode."""

        return self.popitem(last=False)

    def pop_first_until(self, ts: TimeStampType) -> Tuple[TimeStampType, DataType]:
        """Pop all item until a given timestamped value and return the last poped item."""

        # get last timestamp before given timestamp
        earliest_ts = self.get_last_before(ts)

        # when no timestamped have been found
        if earliest_ts == None:
            raise KeyError

        popep_ts, poped_value = self.pop_first()

        while popep_ts != earliest_ts:
            popep_ts, poped_value = self.pop_first()

        return popep_ts, poped_value

    def get_last(self) -> Tuple[TimeStampType, DataType]:
        """Easing access to last item."""

        return list(self.items())[-1]

    def pop_last(self) -> Tuple[TimeStampType, DataType]:
        """Easing FIFO access mode."""

        return self.popitem(last=True)

    def get_last_before(self, ts) -> Tuple[TimeStampType, DataType] | None:
        """Retreive last item timestamp before a given timestamp value."""

        ts_list = list(self.keys())
        last_before_index = bisect.bisect_left(ts_list, ts) - 1

        if last_before_index >= 0:

            return ts_list[last_before_index]
            
        else:
            
            return None

    def export_as_json(self, filepath):
        """Write buffer content into a json file."""

        try:
            with open(filepath, 'w', encoding='utf-8') as jsonfile:
                json.dump(self, jsonfile, ensure_ascii = False, default=vars)

        except:
            raise RuntimeError(f'Can\' write {filepath}')

    def as_dataframe(self, exclude=[], split={}) -> pandas.DataFrame:
        """Convert buffer as pandas dataframe. Timestamped values must be stored as dictionary where each keys will be related to a column."""

        df = pandas.DataFrame.from_dict(self.values())
        df.drop(exclude, inplace=True, axis=True)

        for key, columns in split.items():
            df[columns] = pandas.DataFrame(df[key].tolist(), index=df.index)
            df.drop(key, inplace=True, axis=True)

        df['timestamp'] = self.keys()
        df.set_index('timestamp', inplace=True)

        return df

    def export_as_csv(self, filepath, exclude=[]):
        """Write buffer content into a csv file."""

        try:
            self.as_dataframe(exclude=exclude).to_csv(filepath, index=True)

        except:
            raise RuntimeError(f'Can\' write {filepath}')

    def plot(self, names=[], colors=[], split={}, samples=None) -> list:
        """Plot data into time chart."""

        df = self.as_dataframe(split=split)
        legend_patches = []

        # decimate data
        if samples != None:

            if samples < len(df):

                step = int(len(df) / samples) + 1
                df = df.iloc[::step, :]

        for name, color in zip(names, colors):

            markerline, stemlines, baseline = mpyplot.stem(df.index, df[name])
            mpyplot.setp(markerline, color=color, linewidth=1, markersize = 1)
            mpyplot.setp(stemlines, color=color, linewidth=1)
            mpyplot.setp(baseline, color=color, linewidth=1)

            legend_patches.append(mpatches.Patch(color=color, label=name.upper()))

        return legend_patches