SDF-Python/src/sdf/dsres.py at a187a7fbe3b4bc39e4f34f7ef045458447cb0314 · ScientificDataFormat/SDF-Python · 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
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
170
171
172
173
from os import PathLike

import numpy as np
from sdf import Group, Dataset
import scipy.io


# extract strings from the matrix
def strMatNormal(a):
    return ["".join(s).rstrip() for s in a]


def strMatTrans(a):
    return ["".join(s).rstrip() for s in zip(*a)]


def _split_description(
    comment: str,
) -> tuple[str | None, str | None, str | None, dict[str, str]]:
    unit = None
    display_unit = None
    info = dict()

    if comment.endswith("]"):
        i = comment.rfind("[")
        unit = comment[i + 1 : -1]
        comment = comment[0:i].strip()

    if unit is not None:
        if ":#" in unit:
            segments = unit.split(":#")
            unit = segments[0]
            for segment in segments[1:]:
                key, value = segment[1:-1].split("=")
                info[key] = value

        if "|" in unit:
            unit, display_unit = unit.split("|")

    return unit, display_unit, comment, info


def load(filename: str | PathLike, objectname: str) -> Dataset | Group:
    g_root = _load_mat(filename)

    if objectname == "/":
        return g_root
    else:
        obj = g_root
        segments = objectname.split("/")
        for s in segments:
            if s:
                obj = obj[s]
        return obj


def _load_mat(filename: str) -> Group:
    mat = scipy.io.loadmat(filename, chars_as_strings=False)

    _vars = {}
    _blocks = []

    try:
        fileInfo = strMatNormal(mat["Aclass"])
    except KeyError:
        raise Exception("File structure not supported!")

    if fileInfo[1] == "1.1":
        if fileInfo[3] == "binTrans":
            # usually files from OpenModelica or Dymola auto saved,
            # all methods rely on this structure since this was the only
            # one understand by earlier versions
            names = strMatTrans(mat["name"])  # names
            descr = strMatTrans(mat["description"])  # descriptions

            cons = mat["data_1"]
            traj = mat["data_2"]

            d = mat["dataInfo"][0, :]
            x = mat["dataInfo"][1, :]

        elif fileInfo[3] == "binNormal":
            # usually files from dymola, save as...,
            # variables are mapped to the structure above ('binTrans')
            names = strMatNormal(mat["name"])  # names
            descr = strMatNormal(mat["description"])  # descriptions

            cons = mat["data_1"].T
            traj = mat["data_2"].T

            d = mat["dataInfo"][:, 0]
            x = mat["dataInfo"][:, 1]
        else:
            raise Exception("File structure not supported!")

        c = np.abs(x) - 1  # column
        s = np.sign(x)  # sign

        vars = zip(names, descr, d, c, s)
    elif fileInfo[1] == "1.0":
        # files generated with dymola, save as..., only plotted ...
        # fake the structure of a 1.1 transposed file
        names = strMatNormal(mat["names"])  # names
        _blocks.append(0)
        mat["data_0"] = mat["data"].transpose()
        del mat["data"]
        _absc = (names[0], "")
        for i in range(1, len(names)):
            _vars[names[i]] = ("", 0, i, 1)
    else:
        raise Exception("File structure not supported!")

    # build the SDF tree
    g_root = Group("/")

    ds_time = None

    for name, desc, d, c, s in vars:
        unit, display_unit, comment, info = _split_description(desc)

        path = name.split(".")

        g_parent = g_root

        for segment in path[:-1]:
            if segment in g_parent:
                g_parent = g_parent[segment]
            else:
                g_child = Group(segment)
                g_parent.groups.append(g_child)
                g_parent = g_child
            pass

        if d == 1:
            data = cons[c, 0] * s
        else:
            data = traj[c, :] * s

        if "type" in info:
            if info["type"] == "Integer" or "Boolean":
                data = np.asarray(data, dtype=np.int32)

        if d == 0:
            ds = Dataset(
                path[-1],
                comment="Simulation time",
                unit=unit,
                display_unit=display_unit,
                data=data,
                is_scale=True,
            )
            ds_time = ds
        elif d == 1:
            ds = Dataset(
                path[-1],
                comment=comment,
                unit=unit,
                display_unit=display_unit,
                data=data,
            )
        else:
            ds = Dataset(
                path[-1],
                comment=comment,
                unit=unit,
                display_unit=display_unit,
                data=data,
                scales=[ds_time],
            )

        g_parent.datasets.append(ds)

    return g_root