|
1
|
|
|
""" |
|
|
|
|
|
|
2
|
|
|
|
|
3
|
|
|
""" |
|
4
|
|
|
from __future__ import annotations |
|
5
|
|
|
|
|
6
|
|
|
import enum |
|
7
|
|
|
from pathlib import Path |
|
8
|
|
|
from typing import Union, Optional, Tuple, Mapping, Any, Generator, Sequence, Set |
|
9
|
|
|
|
|
10
|
|
|
import numpy as np |
|
|
|
|
|
|
11
|
|
|
import pandas as pd |
|
|
|
|
|
|
12
|
|
|
from matplotlib import pyplot as plt |
|
|
|
|
|
|
13
|
|
|
from matplotlib.colors import LinearSegmentedColormap, Colormap, ListedColormap, to_hex |
|
|
|
|
|
|
14
|
|
|
from matplotlib.figure import Figure |
|
|
|
|
|
|
15
|
|
|
from pocketutils.core.dot_dict import NestedDotDict |
|
|
|
|
|
|
16
|
|
|
from pocketutils.tools.common_tools import CommonTools |
|
|
|
|
|
|
17
|
|
|
|
|
18
|
|
|
# noinspection PyProtectedMember |
|
19
|
|
|
from seaborn.palettes import SEABORN_PALETTES |
|
|
|
|
|
|
20
|
|
|
from typeddfs import TypedDfs |
|
|
|
|
|
|
21
|
|
|
|
|
22
|
|
|
from mandos.model.utils.setup import logger |
|
|
|
|
|
|
23
|
|
|
from mandos.model.utils import CleverEnum |
|
24
|
|
|
from mandos.model.utils.misc_utils import MiscUtils |
|
25
|
|
|
from mandos.model.utils.resources import MandosResources |
|
26
|
|
|
|
|
27
|
|
|
try: |
|
28
|
|
|
import seaborn as sns |
|
29
|
|
|
from matplotlib.axes import Axes |
|
|
|
|
|
|
30
|
|
|
from matplotlib.figure import Figure |
|
|
|
|
|
|
31
|
|
|
except ImportError: |
|
32
|
|
|
sns = None |
|
33
|
|
|
Axes = None |
|
34
|
|
|
Figure = None |
|
35
|
|
|
|
|
36
|
|
|
|
|
37
|
|
|
class DataType(CleverEnum): |
|
|
|
|
|
|
38
|
|
|
qualitative = enum.auto() |
|
39
|
|
|
sequential = enum.auto() |
|
40
|
|
|
divergent = enum.auto() |
|
41
|
|
|
|
|
42
|
|
|
|
|
43
|
|
|
class VizResources: |
|
|
|
|
|
|
44
|
|
|
def __init__(self): |
|
45
|
|
|
self.override_settings = MandosResources.json_dict("viz", "style_override.json") |
|
46
|
|
|
self.dims = MandosResources.json_dict("viz", "page_dims.json") |
|
47
|
|
|
palettes = MandosResources.json_dict("viz", "palettes.json") |
|
48
|
|
|
self.named_palettes = palettes["named"] |
|
49
|
|
|
self.default_palettes = palettes["defaults"] |
|
50
|
|
|
self.named_cmaps = self._get_named_cmaps() |
|
51
|
|
|
|
|
52
|
|
|
def _get_named_cmaps(self) -> Mapping[str, Colormap]: |
|
53
|
|
|
cmaps = {} |
|
54
|
|
|
for name, cmap in self.named_palettes.items(): |
|
55
|
|
|
cmap = NestedDotDict(cmap) |
|
56
|
|
|
seq = cmap.req_list_as("sequence", str) |
|
57
|
|
|
seq = [to_hex(c) for c in seq] |
|
58
|
|
|
cat = cmap.req_as("categorical", bool) |
|
59
|
|
|
if cat: |
|
60
|
|
|
cmaps[name] = ListedColormap(seq) |
|
61
|
|
|
else: |
|
62
|
|
|
nan, under, over = cmap.get("nan"), cmap.get("under"), cmap.get("over") |
|
63
|
|
|
cmap = LinearSegmentedColormap.from_list(name, seq) |
|
64
|
|
|
cmap.set_extremes(bad=nan, under=under, over=over) |
|
65
|
|
|
return cmaps |
|
66
|
|
|
|
|
67
|
|
|
|
|
68
|
|
|
VIZ_RESOURCES = VizResources() |
|
69
|
|
|
|
|
70
|
|
|
|
|
71
|
|
|
class MandosPlotStyling: |
|
|
|
|
|
|
72
|
|
|
@classmethod |
|
73
|
|
|
def list_named_palettes(cls) -> Set[str]: |
|
|
|
|
|
|
74
|
|
|
return { |
|
75
|
|
|
*VIZ_RESOURCES.named_palettes.keys(), |
|
76
|
|
|
*SEABORN_PALETTES, |
|
77
|
|
|
*plt.colormaps(), |
|
78
|
|
|
} |
|
79
|
|
|
|
|
80
|
|
|
@classmethod |
|
81
|
|
|
def choose_palette( |
|
|
|
|
|
|
82
|
|
|
cls, |
|
|
|
|
|
|
83
|
|
|
data: pd.DataFrame, |
|
|
|
|
|
|
84
|
|
|
col: Optional[str], |
|
|
|
|
|
|
85
|
|
|
palette: Optional[str], |
|
|
|
|
|
|
86
|
|
|
) -> Union[None, Colormap, Mapping[str, str]]: |
|
87
|
|
|
if col is None: |
|
88
|
|
|
return None |
|
89
|
|
|
unique = data[col].unique() |
|
90
|
|
|
dtype = cls.guess_data_type(data) |
|
91
|
|
|
if palette is None: |
|
92
|
|
|
palette = cls.get_palette(None, dtype) |
|
93
|
|
|
if dtype is DataType.qualitative: |
|
94
|
|
|
if not isinstance(palette, ListedColormap): |
|
95
|
|
|
raise TypeError(f"{palette} is not a valid choice for {dtype}") |
|
96
|
|
|
if len(unique) > len(palette.colors): |
|
97
|
|
|
raise ValueError( |
|
98
|
|
|
f"Palette (N={len(palette.colors)}) too small for {len(unique)} items" |
|
99
|
|
|
) |
|
100
|
|
|
return {i: j for i, j in CommonTools.zip_strict(unique, map(to_hex, palette.colors))} |
|
|
|
|
|
|
101
|
|
|
return palette |
|
102
|
|
|
|
|
103
|
|
|
@classmethod |
|
104
|
|
|
def get_palette(cls, name: Optional[str], data_type: Union[DataType, str]) -> Colormap: |
|
|
|
|
|
|
105
|
|
|
data_type = DataType.of(data_type) |
|
106
|
|
|
if name is None: |
|
107
|
|
|
name = VIZ_RESOURCES.default_palettes[data_type.name] |
|
108
|
|
|
if name in VIZ_RESOURCES.named_cmaps: |
|
109
|
|
|
return VIZ_RESOURCES.named_cmaps[name] |
|
110
|
|
|
return sns.color_palette(name, as_cmap=True) |
|
111
|
|
|
|
|
112
|
|
|
@classmethod |
|
113
|
|
|
def guess_data_type(cls, data: Sequence[Union[str, float]]) -> DataType: |
|
|
|
|
|
|
114
|
|
|
numerical = cls._to_numerical(data) |
|
115
|
|
|
if numerical is None: |
|
116
|
|
|
return DataType.qualitative |
|
117
|
|
|
is_divergent = cls._are_floats_divergent(data) |
|
118
|
|
|
if is_divergent: |
|
119
|
|
|
return DataType.divergent |
|
120
|
|
|
return DataType.sequential |
|
121
|
|
|
|
|
122
|
|
|
@classmethod |
|
123
|
|
|
def _to_colors(cls, data: Sequence[Union[float, str]]) -> Optional[Sequence[str]]: |
|
124
|
|
|
if not all((isinstance(d, str)) for d in data): |
|
125
|
|
|
return None |
|
126
|
|
|
try: |
|
127
|
|
|
return [to_hex(c) for c in data] |
|
128
|
|
|
except ValueError: |
|
129
|
|
|
return None |
|
130
|
|
|
|
|
131
|
|
|
@classmethod |
|
132
|
|
|
def _to_numerical(cls, data: Sequence[Union[str, float]]) -> Optional[Sequence[float]]: |
|
|
|
|
|
|
133
|
|
|
try: |
|
134
|
|
|
[float(d) for d in data] |
|
135
|
|
|
except ValueError: |
|
136
|
|
|
return None |
|
137
|
|
|
|
|
138
|
|
|
@classmethod |
|
139
|
|
|
def _are_floats_divergent(cls, data: Sequence[float]): |
|
140
|
|
|
signs = {np.sign(d) for d in data if d != 0 and not np.isnan(d) and not np.isinf(d)} |
|
141
|
|
|
return len(signs) == 2 |
|
142
|
|
|
|
|
143
|
|
|
@classmethod |
|
144
|
|
|
def context( |
|
145
|
|
|
cls, style: Union[None, str, Path], kwargs: Optional[Mapping[str, Any]] |
|
|
|
|
|
|
146
|
|
|
) -> Generator[None, None, None]: |
|
147
|
|
|
""" |
|
148
|
|
|
Override these from the default style. |
|
149
|
|
|
This will be called once, at startup. |
|
150
|
|
|
""" |
|
151
|
|
|
new_kwargs = dict(VIZ_RESOURCES.override_settings["allow_change"]) |
|
152
|
|
|
if kwargs is not None: |
|
153
|
|
|
new_kwargs.update(kwargs) |
|
154
|
|
|
with plt.rc_context(new_kwargs, style): |
|
155
|
|
|
yield |
|
156
|
|
|
|
|
157
|
|
|
@classmethod |
|
158
|
|
|
def fig_width_and_height(cls, size: str) -> Tuple[float, float]: |
|
|
|
|
|
|
159
|
|
|
if size is None: |
|
160
|
|
|
return plt.rcParams["figure.figsize"] |
|
161
|
|
|
axis_to_str = { |
|
162
|
|
|
i: d.strip() for i, d in enumerate(size.replace(" × ", " by ").split(" by ")) |
|
163
|
|
|
} |
|
164
|
|
|
try: |
|
165
|
|
|
default_inch = plt.rcParams["figure.figsize"] |
|
166
|
|
|
width = cls._to_inch(axis_to_str.get(0), VIZ_RESOURCES.dims["widths"], default_inch[0]) |
|
167
|
|
|
height = cls._to_inch( |
|
168
|
|
|
axis_to_str.get(1), VIZ_RESOURCES.dims["heights"], default_inch[1] |
|
169
|
|
|
) |
|
170
|
|
|
except ValueError: |
|
171
|
|
|
raise ValueError(f"Strange --size format in '{size}'") |
|
172
|
|
|
return width, height |
|
173
|
|
|
|
|
174
|
|
|
@classmethod |
|
175
|
|
|
def _to_inch( |
|
|
|
|
|
|
176
|
|
|
cls, s: Optional[str], standards: Mapping[str, float], default_inch: float |
|
|
|
|
|
|
177
|
|
|
) -> float: |
|
178
|
|
|
if s is None or len(s) == "": |
|
179
|
|
|
return default_inch |
|
180
|
|
|
try: |
|
181
|
|
|
return float(s) |
|
182
|
|
|
except ValueError: |
|
183
|
|
|
pass |
|
184
|
|
|
x = standards.get(s, s) |
|
|
|
|
|
|
185
|
|
|
return MiscUtils.canonicalize_quantity(x, "[length]").to("inch").magnitude |
|
186
|
|
|
|
|
187
|
|
|
|
|
188
|
|
|
class MandosPlotUtils: |
|
|
|
|
|
|
189
|
|
|
@classmethod |
|
190
|
|
|
def save(cls, figure: Figure, path: Path) -> None: |
|
|
|
|
|
|
191
|
|
|
path.parent.mkdir(parents=True, exist_ok=True) |
|
192
|
|
|
figure.savefig(str(path)) |
|
193
|
|
|
figure.clear() |
|
194
|
|
|
|
|
195
|
|
|
|
|
196
|
|
|
CompoundStyleDf = ( |
|
197
|
|
|
TypedDfs.typed("CompoundStyleDf").require("inchikey", dtype=str).strict(cols=False).secure() |
|
198
|
|
|
).build() |
|
199
|
|
|
|
|
200
|
|
|
PredicateObjectStyleDf = ( |
|
201
|
|
|
TypedDfs.typed("PredicateObjectStyleDf") |
|
202
|
|
|
.require("predicate", "object", dtype=str) |
|
203
|
|
|
.strict(cols=False) |
|
204
|
|
|
.secure() |
|
205
|
|
|
).build() |
|
206
|
|
|
|
|
207
|
|
|
PhiPsiStyleDf = ( |
|
208
|
|
|
TypedDfs.typed("PhiPsiStyleDf").require("phi", "psi", dtype=str).strict(cols=False).secure() |
|
209
|
|
|
).build() |
|
210
|
|
|
|
|
211
|
|
|
|
|
212
|
|
|
__all__ = [ |
|
213
|
|
|
"sns", |
|
214
|
|
|
"plt", |
|
215
|
|
|
"Figure", |
|
216
|
|
|
"Axes", |
|
217
|
|
|
"MandosPlotStyling", |
|
218
|
|
|
"MandosPlotUtils", |
|
219
|
|
|
"CompoundStyleDf", |
|
220
|
|
|
"PredicateObjectStyleDf", |
|
221
|
|
|
"VIZ_RESOURCES", |
|
222
|
|
|
] |
|
223
|
|
|
|