Le jeudi 28 mai 2009 20:57:50 Vicente Sole, vous avez écrit :
Hello,
I am writing a generic data handling application in which I need to be
able to show the contents of a numpy array in a sort of
table/spreadsheet. The array can be big (1024 x 1024 floats or may be
even more).
Is there a faster way of filling a table than looping through all the
array elements and introducing them in the table cells one by one?
You should use a QTableView with a model you write (which should derivate from
QAbstractTableModel) like the file attached.
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David DouardLOGILAB, Paris (France), +33 1 45 32 03 12
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import numpy
from PyQt4 import QtCore, QtGui
Qt = QtCore.Qt
class NumpyModel(QtCore.QAbstractTableModel):
def __init__(self, narray, parent=None):
QtCore.QAbstractTableModel.__init__(self, parent)
self._array = narray
def rowCount(self, parent=None):
return self._array.shape[0]
def columnCount(self, parent=None):
return self._array.shape[1]
def data(self, index, role=Qt.DisplayRole):
if index.isValid():
if role == Qt.DisplayRole:
row = index.row()
col = index.column()
return QtCore.QVariant(%.5f%self._array[row, col])
return QtCore.QVariant()
if __name__ == __main__:
a = QtGui.QApplication([])
w = QtGui.QTableView()
d = numpy.random.normal(0,1, (1000,1000))
m = NumpyModel(d)
w.setModel(m)
w.show()
a.exec_()
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