model of DCN pyramidal neuron
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# -*- coding: utf-8 -*-
from pyqtgraph.Qt import QtGui, QtCore
from pyqtgraph.pgcollections import OrderedDict
from .DataTreeWidget import DataTreeWidget
import pyqtgraph.functions as fn
import types, traceback
import numpy as np
__all__ = ["DiffTreeWidget"]
class DiffTreeWidget(QtGui.QWidget):
"""
Widget for displaying differences between hierarchical python data structures
(eg, nested dicts, lists, and arrays)
"""
def __init__(self, parent=None, a=None, b=None):
QtGui.QWidget.__init__(self, parent)
self.layout = QtGui.QHBoxLayout()
self.setLayout(self.layout)
self.trees = [DataTreeWidget(self), DataTreeWidget(self)]
for t in self.trees:
self.layout.addWidget(t)
if a is not None:
self.setData(a, b)
def setData(self, a, b):
"""
Set the data to be compared in this widget.
"""
self.data = (a, b)
self.trees[0].setData(a)
self.trees[1].setData(b)
return self.compare(a, b)
def compare(self, a, b, path=()):
"""
Compare data structure *a* to structure *b*.
Return True if the objects match completely.
Otherwise, return a structure that describes the differences:
{ 'type': bool
'len': bool,
'str': bool,
'shape': bool,
'dtype': bool,
'mask': array,
}
"""
bad = (255, 200, 200)
diff = []
# generate typestr, desc, childs for each object
typeA, descA, childsA, _ = self.trees[0].parse(a)
typeB, descB, childsB, _ = self.trees[1].parse(b)
if typeA != typeB:
self.setColor(path, 1, bad)
if descA != descB:
self.setColor(path, 2, bad)
if isinstance(a, dict) and isinstance(b, dict):
keysA = set(a.keys())
keysB = set(b.keys())
for key in keysA - keysB:
self.setColor(path + (key,), 0, bad, tree=0)
for key in keysB - keysA:
self.setColor(path + (key,), 0, bad, tree=1)
for key in keysA & keysB:
self.compare(a[key], b[key], path + (key,))
elif isinstance(a, (list, tuple)) and isinstance(b, (list, tuple)):
for i in range(max(len(a), len(b))):
if len(a) <= i:
self.setColor(path + (i,), 0, bad, tree=1)
elif len(b) <= i:
self.setColor(path + (i,), 0, bad, tree=0)
else:
self.compare(a[i], b[i], path + (i,))
elif (
isinstance(a, np.ndarray)
and isinstance(b, np.ndarray)
and a.shape == b.shape
):
tableNodes = [tree.nodes[path].child(0) for tree in self.trees]
if a.dtype.fields is None and b.dtype.fields is None:
eq = self.compareArrays(a, b)
if not np.all(eq):
for n in tableNodes:
n.setBackground(0, fn.mkBrush(bad))
# for i in np.argwhere(~eq):
else:
if a.dtype == b.dtype:
for i, k in enumerate(a.dtype.fields.keys()):
eq = self.compareArrays(a[k], b[k])
if not np.all(eq):
for n in tableNodes:
n.setBackground(0, fn.mkBrush(bad))
# for j in np.argwhere(~eq):
# dict: compare keys, then values where keys match
# list:
# array: compare elementwise for same shape
def compareArrays(self, a, b):
intnan = -9223372036854775808 # happens when np.nan is cast to int
anans = np.isnan(a) | (a == intnan)
bnans = np.isnan(b) | (b == intnan)
eq = anans == bnans
mask = ~anans
eq[mask] = np.allclose(a[mask], b[mask])
return eq
def setColor(self, path, column, color, tree=None):
brush = fn.mkBrush(color)
# Color only one tree if specified.
if tree is None:
trees = self.trees
else:
trees = [self.trees[tree]]
for tree in trees:
item = tree.nodes[path]
item.setBackground(column, brush)
def _compare(self, a, b):
"""
Compare data structure *a* to structure *b*.
"""
# Check test structures are the same
assert type(info) is type(expect)
if hasattr(info, "__len__"):
assert len(info) == len(expect)
if isinstance(info, dict):
for k in info:
assert k in expect
for k in expect:
assert k in info
self.compare_results(info[k], expect[k])
elif isinstance(info, list):
for i in range(len(info)):
self.compare_results(info[i], expect[i])
elif isinstance(info, np.ndarray):
assert info.shape == expect.shape
assert info.dtype == expect.dtype
if info.dtype.fields is None:
intnan = -9223372036854775808 # happens when np.nan is cast to int
inans = np.isnan(info) | (info == intnan)
enans = np.isnan(expect) | (expect == intnan)
assert np.all(inans == enans)
mask = ~inans
assert np.allclose(info[mask], expect[mask])
else:
for k in info.dtype.fields.keys():
self.compare_results(info[k], expect[k])
else:
try:
assert info == expect
except Exception:
raise NotImplementedError(
"Cannot compare objects of type %s" % type(info)
)