140 lines
4.4 KiB
Python
140 lines
4.4 KiB
Python
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# -*- coding: utf-8 -*-
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import numpy as np
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import pyqtgraph as pg
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try:
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import cupy as cp
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pg.setConfigOption("useCupy", True)
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except ImportError:
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cp = None
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try:
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import numba
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except ImportError:
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numba = None
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def renderQImage(*args, **kwargs):
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imgitem = pg.ImageItem(axisOrder='row-major')
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if 'autoLevels' not in kwargs:
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kwargs['autoLevels'] = False
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imgitem.setImage(*args, **kwargs)
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imgitem.render()
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def prime_numba():
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shape = (64, 64)
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lut_small = np.random.randint(256, size=(256, 3), dtype=np.uint8)
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lut_big = np.random.randint(256, size=(512, 3), dtype=np.uint8)
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for lut in [lut_small, lut_big]:
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renderQImage(np.zeros(shape, dtype=np.uint8), levels=(20, 220), lut=lut)
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renderQImage(np.zeros(shape, dtype=np.uint16), levels=(250, 3000), lut=lut)
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renderQImage(np.zeros(shape, dtype=np.float32), levels=(-4.0, 4.0), lut=lut)
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class _TimeSuite(object):
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def __init__(self):
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super(_TimeSuite, self).__init__()
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self.size = None
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self.float_data = None
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self.uint8_data = None
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self.uint8_lut = None
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self.uint16_data = None
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self.uint16_lut = None
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self.cupy_uint16_lut = None
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self.cupy_uint8_lut = None
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def setup(self):
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size = (self.size, self.size)
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self.float_data, self.uint16_data, self.uint8_data, self.uint16_lut, self.uint8_lut = self._create_data(
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size, np
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)
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if numba is not None:
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# ensure JIT compilation
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pg.setConfigOption("useNumba", True)
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prime_numba()
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pg.setConfigOption("useNumba", False)
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if cp:
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_d1, _d2, _d3, self.cupy_uint16_lut, self.cupy_uint8_lut = self._create_data(size, cp)
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renderQImage(cp.asarray(self.uint16_data["data"])) # prime the gpu
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@property
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def numba_uint16_lut(self):
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return self.uint16_lut
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@property
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def numba_uint8_lut(self):
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return self.uint8_lut
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@property
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def numpy_uint16_lut(self):
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return self.uint16_lut
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@property
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def numpy_uint8_lut(self):
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return self.uint8_lut
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@staticmethod
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def _create_data(size, xp):
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float_data = {
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"data": xp.random.normal(size=size).astype("float32"),
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"levels": [-4.0, 4.0],
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}
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uint16_data = {
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"data": xp.random.randint(100, 4500, size=size).astype("uint16"),
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"levels": [250, 3000],
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}
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uint8_data = {
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"data": xp.random.randint(0, 255, size=size).astype("ubyte"),
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"levels": [20, 220],
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}
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c_map = xp.array([[-500.0, 255.0], [-255.0, 255.0], [0.0, 500.0]])
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uint8_lut = xp.zeros((256, 4), dtype="ubyte")
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for i in range(3):
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uint8_lut[:, i] = xp.clip(xp.linspace(c_map[i][0], c_map[i][1], 256), 0, 255)
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uint8_lut[:, 3] = 255
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uint16_lut = xp.zeros((2 ** 16, 4), dtype="ubyte")
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for i in range(3):
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uint16_lut[:, i] = xp.clip(xp.linspace(c_map[i][0], c_map[i][1], 2 ** 16), 0, 255)
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uint16_lut[:, 3] = 255
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return float_data, uint16_data, uint8_data, uint16_lut, uint8_lut
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def make_test(dtype, kind, use_levels, lut_name, func_name):
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def time_test(self):
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data = getattr(self, dtype + "_data")
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levels = data["levels"] if use_levels else None
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lut = getattr(self, f"{kind}_{lut_name}_lut", None) if lut_name is not None else None
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pg.setConfigOption("useNumba", kind == "numba")
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img_data = data["data"]
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if kind == "cupy":
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img_data = cp.asarray(img_data)
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renderQImage(img_data, lut=lut, levels=levels)
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time_test.__name__ = func_name
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return time_test
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for option in ["cupy", "numba", "numpy"]:
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if option == "cupy" and cp is None:
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continue
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if option == "numba" and numba is None:
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continue
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for data_type in ["float", "uint16", "uint8"]:
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for lvls in [True, False]:
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if data_type == "float" and not lvls:
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continue
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for lutname in [None, "uint8", "uint16"]:
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name = (
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f'time_1x_renderImageItem_{option}_{data_type}_{"" if lvls else "no"}levels_{lutname or "no"}lut'
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)
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setattr(_TimeSuite, name, make_test(data_type, option, lvls, lutname, name))
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class Time4096Suite(_TimeSuite):
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def __init__(self):
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super(Time4096Suite, self).__init__()
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self.size = 4096
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