Added features from meganbkratz:

- isocurves
 - array processing through gradientwidget

flowchart/library/Filters.py

@@ -187,7 +187,7 @@ class HistogramDetrend(CtrlNode):
     """Removes baseline from data by computing mode (from histogram) of beginning and end of data."""
     nodeName = 'HistogramDetrend'
     uiTemplate = [
-        ('windowSize', 'intSpin', {'value': 500, 'min': 10, 'max': 1000000}),
+        ('windowSize', 'intSpin', {'value': 500, 'min': 10, 'max': 1000000, 'suffix': 'pts'}),
         ('numBins', 'intSpin', {'value': 50, 'min': 3, 'max': 1000000})
     ]
     

functions.py

@@ -409,12 +409,12 @@ def affineSlice(data, shape, origin, vectors, axes, **kargs):
 
 
 
-def makeARGB(data, lut=None, levels=None):
+def makeARGB(data, lut=None, levels=None, useRGBA=False): 
     """
     Convert a 2D or 3D array into an ARGB array suitable for building QImages
     Will optionally do scaling and/or table lookups to determine final colors.
     
-    Returns the ARGB array and a boolean indicating whether there is alpha channel data.
+    Returns the ARGB array (values 0-255) and a boolean indicating whether there is alpha channel data.
     
     Arguments:
         data  - 2D or 3D numpy array of int/float types
@@ -433,6 +433,8 @@ def makeARGB(data, lut=None, levels=None):
                 Lookup tables can be built using GradientWidget.
         levels - List [min, max]; optionally rescale data before converting through the
                 lookup table.   rescaled = (data-min) * len(lut) / (max-min)
+        useRGBA - If True, the data is returned in RGBA order. The default is 
+                  False, which returns in BGRA order for use with QImage.
                 
     """
     
@@ -580,8 +582,11 @@ def makeARGB(data, lut=None, levels=None):
 
     prof.mark('4')
 
-
+    if useRGBA:
+        order = [0,1,2,3] ## array comes out RGBA
+    else:
         order = [2,1,0,3] ## for some reason, the colors line up as BGR in the final image.
+        
     if data.shape[2] == 1:
         for i in xrange(3):
             imgData[..., order[i]] = data[..., 0]    
@@ -732,6 +737,84 @@ def rescaleData(data, scale, offset):
     #return facets
     
 
+def isocurve(data, level):
+    """
+        Generate isocurve from 2D data using marching squares algorithm.
+        
+        *data*   2D numpy array of scalar values
+        *level*  The level at which to generate an isosurface
+        
+        This function is SLOW; plenty of room for optimization here.
+        """    
+    
+    sideTable = [
+    [],
+    [0,1],
+    [1,2],
+    [0,2],
+    [0,3],
+    [1,3],
+    [0,1,2,3],
+    [2,3],
+    [2,3],
+    [0,1,2,3],
+    [1,3],
+    [0,3],
+    [0,2],
+    [1,2],
+    [0,1],
+    []
+    ]
+    
+    edgeKey=[
+    [(0,1),(0,0)],
+    [(0,0), (1,0)],
+    [(1,0), (1,1)],
+    [(1,1), (0,1)]
+    ]
+    
+    
+    lines = []
+    
+    ## mark everything below the isosurface level
+    mask = data < level
+    
+    ### make four sub-fields and compute indexes for grid cells
+    index = np.zeros([x-1 for x in data.shape], dtype=np.ubyte)
+    fields = np.empty((2,2), dtype=object)
+    slices = [slice(0,-1), slice(1,None)]
+    for i in [0,1]:
+        for j in [0,1]:
+            fields[i,j] = mask[slices[i], slices[j]]
+            #vertIndex = i - 2*j*i + 3*j + 4*k  ## this is just to match Bourk's vertex numbering scheme
+            vertIndex = i+2*j
+            #print i,j,k," : ", fields[i,j,k], 2**vertIndex
+            index += fields[i,j] * 2**vertIndex
+            #print index
+    #print index
+    
+    ## add lines
+    for i in xrange(index.shape[0]):                 # data x-axis
+        for j in xrange(index.shape[1]):             # data y-axis     
+            sides = sideTable[index[i,j]]
+            for l in range(0, len(sides), 2):     ## faces for this grid cell
+                edges = sides[l:l+2]
+                pts = []
+                for m in [0,1]:      # points in this face
+                    p1 = edgeKey[edges[m]][0] # p1, p2 are points at either side of an edge
+                    p2 = edgeKey[edges[m]][1]
+                    v1 = data[i+p1[0], j+p1[1]] # v1 and v2 are the values at p1 and p2
+                    v2 = data[i+p2[0], j+p2[1]]
+                    f = (level-v1) / (v2-v1)
+                    fi = 1.0 - f
+                    p = (    ## interpolate between corners
+                        p1[0]*fi + p2[0]*f + i + 0.5, 
+                        p1[1]*fi + p2[1]*f + j + 0.5
+                        )
+                    pts.append(p)
+                lines.append(pts)
+
+    return lines ## a list of pairs of points
 
     
 def isosurface(data, level):

graphicsItems/IsocurveItem.py

@@ -0,0 +1,38 @@
+
+
+from GraphicsObject import *
+import pyqtgraph.functions as fn
+from pyqtgraph.Qt import QtGui
+
+
+class IsocurveItem(GraphicsObject):
+    """
+    Item displaying an isocurve of a 2D array.
+    
+    To align this item correctly with an ImageItem,
+    call isocurve.setParentItem(image)
+    """
+    
+    def __init__(self, data, level, pen='w'):
+        GraphicsObject.__init__(self)
+        
+        lines = fn.isocurve(data, level)
+        
+        self.path = QtGui.QPainterPath()
+        self.setPen(pen)
+        
+        for line in lines:
+            self.path.moveTo(*line[0])
+            self.path.lineTo(*line[1])
+            
+    def setPen(self, *args, **kwargs):
+        self.pen = fn.mkPen(*args, **kwargs)
+        self.update()
+
+    def boundingRect(self):
+        return self.path.boundingRect()
+    
+    def paint(self, p, *args):
+        p.setPen(self.pen)
+        p.drawPath(self.path)
+        

widgets/GradientWidget.py

@@ -55,6 +55,7 @@ class GradientWidget(GraphicsView):
             self.setMaximumHeight(16777215)
         
     def __getattr__(self, attr):
+        ### wrap methods from GradientEditorItem
         return getattr(self.item, attr)