def volumina_flexible_layer(data, layer_types, labels=None):
assert len(layer_types) == len(data)
app = QApplication (sys.argv)
import volumina
from volumina.api import Viewer
v = Viewer ()
v.title = " Volumina Demo "
v.showMaximized ()
for i, d in enumerate(data):
layer_name = "layer_" + str(i)
if labels is not None:
layer_name = labels[i]
# get data type of the elements d, to determine
# if we use a grayscale overlay (float32) or a randomcolors overlay (uint) for labels
data_type = d.dtype
if layer_types[i] == 'Grayscale':
v.addGrayscaleLayer(d , name = layer_name)
elif layer_types[i] == 'RandomColors':
v.addRandomColorsLayer(d.astype(np.uint32), name=layer_name)
elif layer_types[i] == 'Red':
v.addAlphaModulatedLayer(d , name=layer_name, tintColor=QColor(255,0,0))
elif layer_types[i] == 'Green':
v.addAlphaModulatedLayer(d , name=layer_name, tintColor=QColor(0,255,0))
elif layer_types[i] == 'Blue':
v.addAlphaModulatedLayer(d , name=layer_name, tintColor=QColor(0,0,255))
else:
raise KeyError("Invalid Layer Type, %s!" % layer_types[i])
app.exec_()
def volumina_n_layer(data, labels = None):
app = QApplication(sys.argv)
import volumina
from volumina.api import Viewer
v = Viewer ()
v.title = " Volumina Demo "
v.showMaximized ()
for ind, d in enumerate(data):
layer_name = "layer_" + str(ind)
if labels is not None:
layer_name = labels[ind]
# get data type of the elements d, to determine
# if we use a grayscale overlay (float32) or a randomcolors overlay (uint) for labels
data_type = d.dtype
if data_type == np.float32 or data_type == np.float64:
v.addGrayscaleLayer(d , name = layer_name)
else:
v.addRandomColorsLayer(d.astype(np.uint32), name = layer_name)
app.exec_()
def view(data, labels=None, layer_types=None):
"""
"""
if labels is not None:
assert len(labels) == len(data)
if layer_types is not None:
assert len(layer_types) == len(data)
assert all(ltype in ('Grayscale', 'RandomColors', 'Red', 'Green', 'Blue')
for ltype in layer_types)
app = QApplication(sys.argv)
from volumina.api import Viewer
v = Viewer()
v.title = "Volumina Viewer"
v.showMaximized()
for i, d in enumerate(data):
layer_name = layer_name = "layer_" + str(i) if labels is None else labels[i]
if layer_types is None:
_dtype_to_layer(v, d, layer_name)
else:
_name_to_layer(v, d, layer_types[i], layer_name)
app.exec_()
def show():
import numpy as np
import sys , h5py ; from numpy import float32 , uint8
from vigra.filters import hessianOfGaussianEigenvalues , gaussianSmoothing
from vigra.analysis import watersheds
from vigra.analysis import labelVolumeWithBackground, extendedLocalMinima3D
from PyQt4.QtCore import QTimer ; from PyQt4 . QtGui import QApplication
app = QApplication ( sys.argv )
from volumina.api import Viewer
v = Viewer ()
v . title = " Volumina Demo "
v . showMaximized ()
print "blubb"
print a
data = np.random.random((50,50,50))
v . addGrayscaleLayer ( data , name =" raw data ")
t = QTimer ()
t.setInterval (200)
app.exec_ ()
def volumina_single_layer(data): app = QApplication (sys.argv) from volumina.api import Viewer v = Viewer () v.title = " Volumina Demo " v.showMaximized () v.addGrayscaleLayer (data , name =" raw data ") app . exec_ ()
def volumina_double_layer(data, overlay): # get data type of the elements of overlay, to determine # if we use a grayscale overlay (float32) or a randomcolors overlay (uint) for labels mask = [] for i in range( len(overlay.shape) ): mask.append(0) mask = tuple(mask) data_type = type(overlay[mask]) app = QApplication (sys.argv) from volumina.api import Viewer v = Viewer () v.title = " Volumina Demo " v.showMaximized () v.addGrayscaleLayer(data , name = " raw data ") if data_type == np.float32: v.addGrayscaleLayer(overlay , name = " overlay ") else: v.addRandomColorsLayer(overlay, name = " overlay ") app . exec_ ()
