def test_tiffdata(): d = TiffData(rel_path("../data/flybrain.tif")) m = DataModel(d) print(m) for pos in range(m.sizeT()): print(pos) print((np.mean(m[pos])))
def test_numpydata(): d = NumpyData(np.ones((10, 100, 100, 100))) m = DataModel(d) print(m) for pos in range(m.sizeT()): print(pos) print(np.mean(m[pos]))
def test_spimdata(): d = SpimData(rel_path("../data/spimdata")) m = DataModel(d) print(m) for pos in range(m.sizeT()): print(pos) print(np.mean(m[pos])) return m
def test_tiffdata(): d = TiffData(rel_path("../data/flybrain.tif")) m = DataModel(d) print("thread is running: ", m.dataLoadThread.isRunning()) print(m) for pos in range(m.sizeT()): print(pos) print((np.mean(m[pos]))) time.sleep(.1)
def test_rawdata(): d = RawData(rel_path("../data/raw_64_65_66.raw"), shape=(1, 66, 65, 64), dtype=np.uint16) print(d.size()) m = DataModel(d) print(m) for pos in range(m.sizeT()): print(pos) print((np.mean(m[pos])))
def reset_dn(self, dn, size, simul_z=None, simul_xy=None): if simul_z is None: simul_z = 1 if simul_xy is None: simul_xy = dn.shape[1:][::-1] # simul_z = 2 # simul_xy = (1024,)*2 # simul_z = 2 # simul_xy = (512,)*2 self.bpm = Bpm3d_img(size=size, dn=dn, lam=.5, simul_z=simul_z, simul_xy=simul_xy) if not dn is None: self.dn_max = np.amax(dn) z = np.zeros_like(dn) z[0, 0, 0] = 1. units = [s / (n - 1.) for s, n in zip(size, dn.shape[::-1])] self.canvas.setModel(DataModel(NumpyData(z, stackUnits=units)))
def data_model(data): app = QtWidgets.QApplication(sys.argv) t = time.time() app.d = DataModel(NumpyData(data)) print("time to datamodel: ", time.time() - t) QtCore.QTimer.singleShot(100, app.quit) app.exec_()
def _with_glwidget(data): app = QtWidgets.QApplication(sys.argv) win = GLWidget() d = DataModel(NumpyData(data)) t = time.time() win.setModel(d) print("time to set model in glwidget: ", time.time() - t) win.show() win.raise_() app.win = win QtCore.QTimer.singleShot(200, app.quit) app.exec_()
def test_speed(): import time fName = rel_path("../data/spimdata") t = [] d = DataModel.fromPath(fName, 1) for i in range(100): print(i) if i % 10 == 0: a = d[i // 10] time.sleep(.01) t.append(time.time())
def test_frompaths(): from glob import glob fnames = glob(rel_path("../data/*")) if len(fnames) == 0: raise ValueError("could not find any test data!") print(fnames) for f in fnames: if os.path.splitext(f)[1] == ".raw": print("raw ...skipping") continue print(f) d = DataModel.fromPath(f) print(d) for i in np.random.randint(0, d.sizeT(), 10): print(i) a = d[i]
def test_folder(): d = DataModel.fromPath(rel_path("../data/tiffstacks")) print(d)
def test_folder(): print("test folder") d = DataModel.fromPath(rel_path("../data/tiffstacks")) print("thread is running: ", d.dataLoadThread.isRunning()) print(d) time.sleep(.1)
import numpy as np from PyQt5 import QtCore import logging from spimagine import volshow, volfig, logger, qt_exec, NumpyData, DataModel def single_data(data): w = volshow(data, raise_window=False) QtCore.QTimer.singleShot(1000, w.closeMe) qt_exec() def test_volumes(): d = np.random.uniform(0, 100, (100, ) * 3) for dtype in (np.float32, np.int8, np.uint16, np.int32): print("testing: %s" % dtype) single_data(d.astype(dtype)) if __name__ == '__main__': data = np.linspace(0, 255, 100**3).reshape((100, ) * 3).transpose( (1, 2, 0)) m = DataModel(NumpyData(data.astype(np.uint8))) w = volshow(m) QtCore.QTimer.singleShot(1000, w.closeMe) qt_exec()