corrscope/ovgenpy/renderer.py

260 wiersze
8.1 KiB
Python

from typing import Optional, List, TYPE_CHECKING, TypeVar, Callable, Any
import matplotlib
import numpy as np
from ovgenpy.config import register_config
from ovgenpy.outputs import RGB_DEPTH
from ovgenpy.util import ceildiv, coalesce
matplotlib.use('agg')
from matplotlib import pyplot as plt
from matplotlib.backends.backend_agg import FigureCanvasAgg
if TYPE_CHECKING:
from matplotlib.axes import Axes
from matplotlib.figure import Figure
from matplotlib.lines import Line2D
from ovgenpy.channel import ChannelConfig
def default_color():
colors = np.array([int(x, 16) for x in '1f 77 b4'.split()], dtype=float)
colors /= np.amax(colors)
colors **= 1/3
return tuple(colors.tolist()) # tolist() converts np.float64 to float
@register_config(always_dump='bg_color init_line_color line_width')
class RendererConfig:
width: int
height: int
bg_color: Any = 'black'
init_line_color: Any = default_color()
line_width: Optional[float] = None # TODO
create_window: bool = False
class MatplotlibRenderer:
"""
Renderer backend which takes data and produces images.
Does not touch Wave or Channel.
If __init__ reads cfg, cfg cannot be hotswapped.
Reasons to hotswap cfg: RendererCfg:
- GUI preview size
- Changing layout
- Changing #smp drawn (samples_visible)
(see RendererCfg)
Original OVGen does not support hotswapping.
It disables changing options during rendering.
Reasons to hotswap trigger algorithms:
- changing scan_nsamp (cannot be hotswapped, since correlation buffer is incompatible)
So don't.
"""
DPI = 96
def __init__(self, cfg: RendererConfig, lcfg: 'LayoutConfig', nplots: int):
self.cfg = cfg
self.nplots = nplots
self.layout = RendererLayout(lcfg, nplots)
# Flat array of nrows*ncols elements, ordered by cfg.rows_first.
self._fig: 'Figure' = None
self._axes: List['Axes'] = None # set by set_layout()
self._lines: List['Line2D'] = None # set by render_frame() first call
self._line_colors: List = [None] * nplots
self._set_layout() # mutates self
def _set_layout(self) -> None:
"""
Creates a flat array of Matplotlib Axes, with the new layout.
Opens a window showing the Figure (and Axes).
Inputs: self.cfg, self.fig
Outputs: self.nrows, self.ncols, self.axes
"""
# Create Axes
# https://matplotlib.org/api/_as_gen/matplotlib.pyplot.subplots.html
if self._fig:
raise Exception("I don't currently expect to call set_layout() twice")
# plt.close(self.fig)
axes2d: np.ndarray['Axes']
self._fig, axes2d = plt.subplots(
self.layout.nrows, self.layout.ncols,
squeeze=False,
# Remove gaps between Axes
gridspec_kw=dict(left=0, bottom=0, right=1, top=1, wspace=0, hspace=0)
)
# remove Axis from Axes
for ax in axes2d.flatten():
ax.set_axis_off()
# Generate arrangement (using nplots, cfg.orientation)
self._axes = self.layout.arrange(lambda row, col: axes2d[row, col])
# Setup figure geometry
self._fig.set_dpi(self.DPI)
self._fig.set_size_inches(
self.cfg.width / self.DPI,
self.cfg.height / self.DPI
)
if self.cfg.create_window:
plt.show(block=False)
def set_colors(self, channel_cfgs: List['ChannelConfig']):
if len(channel_cfgs) != self.nplots:
raise ValueError(
f"cannot assign {len(channel_cfgs)} colors to {self.nplots} plots"
)
if self._lines is not None:
raise ValueError(
f'cannot set line colors after calling render_frame()'
)
self._line_colors = [cfg.line_color for cfg in channel_cfgs]
def render_frame(self, datas: List[np.ndarray]) -> None:
ndata = len(datas)
if self.nplots != ndata:
raise ValueError(
f'incorrect data to plot: {self.nplots} plots but {ndata} datas')
# Initialize axes and draw waveform data
if self._lines is None:
self._fig.set_facecolor(self.cfg.bg_color)
line_width = self.cfg.line_width
self._lines = []
for idx, data in enumerate(datas):
# Setup colors
line_color = coalesce(self._line_colors[idx], self.cfg.init_line_color)
# Setup axes
ax = self._axes[idx]
ax.set_xlim(0, len(data) - 1)
ax.set_ylim(-1, 1)
# Plot line
line = ax.plot(data, color=line_color, linewidth=line_width)[0]
self._lines.append(line)
# Draw waveform data
else:
for idx, data in enumerate(datas):
line = self._lines[idx]
line.set_ydata(data)
self._fig.canvas.draw()
self._fig.canvas.flush_events()
def get_frame(self) -> bytes:
""" Returns ndarray of shape w,h,3. """
canvas = self._fig.canvas
# Agg is the default noninteractive backend except on OSX.
# https://matplotlib.org/faq/usage_faq.html
if not isinstance(canvas, FigureCanvasAgg):
raise RuntimeError(
f'oh shit, cannot read data from {type(canvas)} != FigureCanvasAgg')
w = self.cfg.width
h = self.cfg.height
assert (w, h) == canvas.get_width_height()
buffer_rgb = canvas.tostring_rgb()
assert len(buffer_rgb) == w * h * RGB_DEPTH
return buffer_rgb
@register_config(always_dump='orientation')
class LayoutConfig:
nrows: Optional[int] = None
ncols: Optional[int] = None
orientation: str = 'h'
def __post_init__(self):
if not self.nrows:
self.nrows = None
if not self.ncols:
self.ncols = None
if self.nrows and self.ncols:
raise ValueError('cannot manually assign both nrows and ncols')
if not self.nrows and not self.ncols:
self.ncols = 1
Region = TypeVar('Region')
RegionFactory = Callable[[int, int], Region] # f(row, column) -> Region
class RendererLayout:
VALID_ORIENTATIONS = ['h', 'v']
def __init__(self, cfg: LayoutConfig, nplots: int):
self.cfg = cfg
self.nplots = nplots
# Setup layout
self.nrows, self.ncols = self._calc_layout()
self.orientation = cfg.orientation
if self.orientation not in self.VALID_ORIENTATIONS:
raise ValueError(f'Invalid orientation {self.orientation} not in '
f'{self.VALID_ORIENTATIONS}')
def _calc_layout(self):
"""
Inputs: self.cfg, self.waves
:return: (nrows, ncols)
"""
cfg = self.cfg
if cfg.nrows:
nrows = cfg.nrows
if nrows is None:
raise ValueError('invalid cfg: rows_first is True and nrows is None')
ncols = ceildiv(self.nplots, nrows)
else:
ncols = cfg.ncols
if ncols is None:
raise ValueError('invalid cfg: rows_first is False and ncols is None')
nrows = ceildiv(self.nplots, ncols)
return nrows, ncols
def arrange(self, region_factory: RegionFactory) -> List[Region]:
""" Generates an array of regions.
index, row, column are fed into region_factory in a row-major order [row][col].
The results are possibly reshaped into column-major order [col][row].
"""
nspaces = self.nrows * self.ncols
inds = np.arange(nspaces)
rows, cols = np.unravel_index(inds, (self.nrows, self.ncols))
row_col = np.array([rows, cols]).T
regions = np.array([region_factory(*rc) for rc in row_col]) # type: np.ndarray[Region]
regions2d = regions.reshape((self.nrows, self.ncols)) # type: np.ndarray[Region]
# if column major:
if self.orientation == 'v':
regions2d = regions2d.T
return regions2d.flatten()[:self.nplots].tolist()