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SF.net SVN: matplotlib:[5793] trunk/matplotlib/lib/matplotlib/contour.py
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From: <ef...@us...> - 2008-07-20 00:57:47
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Revision: 5793
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5793&view=rev
Author: efiring
Date: 2008-07-20 00:57:41 +0000 (Sun, 20 Jul 2008)
Log Message:
-----------
Reverting clabel-related change in contour.py to 5689.
contour_demo.py was broken.
Modified Paths:
--------------
trunk/matplotlib/lib/matplotlib/contour.py
Modified: trunk/matplotlib/lib/matplotlib/contour.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/contour.py 2008-07-19 07:05:43 UTC (rev 5792)
+++ trunk/matplotlib/lib/matplotlib/contour.py 2008-07-20 00:57:41 UTC (rev 5793)
@@ -17,9 +17,6 @@
import matplotlib.text as text
import matplotlib.cbook as cbook
-# Import needed for adding manual selection capability to clabel
-from matplotlib.blocking_input import BlockingContourLabeler
-
# We can't use a single line collection for contour because a line
# collection can have only a single line style, and we want to be able to have
# dashed negative contours, for example, and solid positive contours.
@@ -71,17 +68,7 @@
*fmt*:
a format string for the label. Default is '%1.3f'
- Alternatively, this can be a dictionary matching contour
- levels with arbitrary strings to use for each contour level
- (i.e., fmt[level]=string)
- *manual*:
- if *True*, contour labels will be placed manually using
- mouse clicks. Click the first button near a contour to
- add a label, click the second button (or potentially both
- mouse buttons at once) to finish adding labels. The third
- button can be used to remove the last label added, but
- only if labels are not inline.
"""
fontsize = kwargs.get('fontsize', None)
@@ -89,9 +76,8 @@
self.fmt = kwargs.get('fmt', '%1.3f')
_colors = kwargs.get('colors', None)
- # Detect if manual selection is desired and remove from argument list
- self.manual_select=kwargs.get('manual',False)
+
if len(args) == 0:
levels = self.levels
indices = range(len(self.levels))
@@ -140,16 +126,10 @@
#self.cl_cvalues = [] # same
self.cl_xy = []
- if self.manual_select:
- print 'Select label locations manually using first mouse button.'
- print 'End manual selection with second mouse button.'
- if not inline:
- print 'Remove last label by clicking third mouse button.'
+ self.labels(inline)
- blocking_contour_labeler = BlockingContourLabeler(self)
- blocking_contour_labeler(inline)
- else:
- self.labels(inline)
+ for label in self.cl:
+ self.ax.add_artist(label)
self.label_list = cbook.silent_list('text.Text', self.cl)
return self.label_list
@@ -161,10 +141,10 @@
if lcsize > 10 * labelwidth:
return 1
- xmax = np.amax(linecontour[:,0])
- xmin = np.amin(linecontour[:,0])
- ymax = np.amax(linecontour[:,1])
- ymin = np.amin(linecontour[:,1])
+ xmax = np.amax(np.array(linecontour)[:,0])
+ xmin = np.amin(np.array(linecontour)[:,0])
+ ymax = np.amax(np.array(linecontour)[:,1])
+ ymin = np.amin(np.array(linecontour)[:,1])
lw = labelwidth
if (xmax - xmin) > 1.2* lw or (ymax - ymin) > 1.2 * lw:
@@ -213,7 +193,7 @@
if cbook.is_string_like(lev):
lw = (len(lev)) * fsize
else:
- lw = (len(self.get_text(lev,fmt))) * fsize
+ lw = (len(fmt%lev)) * fsize
return lw
@@ -230,11 +210,9 @@
if cbook.is_string_like(lev):
return lev
else:
- if isinstance(fmt,dict):
- return fmt[lev]
- else:
- return fmt%lev
+ return fmt%lev
+
def break_linecontour(self, linecontour, rot, labelwidth, ind):
"break a contour in two contours at the location of the label"
lcsize = len(linecontour)
@@ -248,8 +226,8 @@
slc = trans.transform(linecontour)
x,y = slc[ind]
- xx=slc[:,0].copy()
- yy=slc[:,1].copy()
+ xx= np.asarray(slc)[:,0].copy()
+ yy=np.asarray(slc)[:,1].copy()
#indices which are under the label
inds, = np.nonzero(((xx < x+xlabel) & (xx > x-xlabel)) &
@@ -330,8 +308,8 @@
else:
ysize = labelwidth
- XX = np.resize(linecontour[:,0],(xsize, ysize))
- YY = np.resize(linecontour[:,1],(xsize, ysize))
+ XX = np.resize(np.asarray(linecontour)[:,0],(xsize, ysize))
+ YY = np.resize(np.asarray(linecontour)[:,1],(xsize, ysize))
#I might have fouled up the following:
yfirst = YY[:,0].reshape(xsize, 1)
ylast = YY[:,-1].reshape(xsize, 1)
@@ -357,85 +335,19 @@
return x,y, rotation, dind
- def add_label(self,x,y,rotation,icon):
- dx,dy = self.ax.transData.inverted().transform_point((x,y))
- t = text.Text(dx, dy, rotation = rotation,
- horizontalalignment='center',
- verticalalignment='center')
-
- color = self.label_mappable.to_rgba(self.label_cvalues[icon],
- alpha=self.alpha)
-
- _text = self.get_text(self.label_levels[icon],self.fmt)
- self.set_label_props(t, _text, color)
- self.cl.append(t)
- self.cl_cvalues.append(self.label_cvalues[icon])
-
- # Add label to plot here - useful for manual mode label selection
- self.ax.add_artist(t)
-
- def pop_label(self,index=-1):
- '''Defaults to removing last label, but any index can be supplied'''
- self.cl_cvalues.pop(index)
- t = self.cl.pop(index)
- t.remove()
-
- def find_nearest_contour( self, x, y, pixel=True ):
- """
- Finds contour that is closest to a point. Defaults to
- measuring distance in pixels (screen space - useful for manual
- contour labeling), but this can be controlled via a keyword
- argument.
-
- Returns a tuple containing the contour, segment, index of
- segment, x & y of segment point and distance to minimum point.
- """
-
- # This function uses a method that is probably quite
- # inefficient based on converting each contour segment to
- # pixel coordinates and then comparing the given point to
- # those coordinates for each contour. This will probably be
- # quite slow for complex contours, but for normal use it works
- # sufficiently well that the time is not noticeable.
- # Nonetheless, improvements could probably be made.
-
- dmin = 1e10
- conmin = None
- segmin = None
- xmin = None
- ymin = None
-
- for icon in self.label_indices:
- con = self.collections[icon]
- paths = con.get_paths()
- for segNum, linepath in enumerate(paths):
- lc = linepath.vertices
-
- # transfer all data points to screen coordinates if desired
- if pixel:
- lc = self.ax.transData.transform(lc)
-
- ds = (lc[:,0]-x)**2 + (lc[:,1]-y)**2
- d = min( ds )
- if d < dmin:
- dmin = d
- conmin = icon
- segmin = segNum
- imin = mpl.mlab.find( ds == d )[0]
- xmin = lc[imin,0]
- ymin = lc[imin,1]
-
- return (conmin,segmin,imin,xmin,ymin,dmin)
-
def labels(self, inline):
levels = self.label_levels
fslist = self.fslist
trans = self.ax.transData
-
- for icon, lev, fsize in zip(self.label_indices,
- self.label_levels, fslist):
+ _colors = self.label_mappable.to_rgba(self.label_cvalues,
+ alpha=self.alpha)
+ fmt = self.fmt
+ for icon, lev, color, cvalue, fsize in zip(self.label_indices,
+ self.label_levels,
+ _colors,
+ self.label_cvalues, fslist):
con = self.collections[icon]
- lw = self.get_label_width(lev, self.fmt, fsize)
+ lw = self.get_label_width(lev, fmt, fsize)
additions = []
paths = con.get_paths()
for segNum, linepath in enumerate(paths):
@@ -450,8 +362,16 @@
slc = trans.transform(linecontour)
if self.print_label(slc,lw):
x,y, rotation, ind = self.locate_label(slc, lw)
- self.add_label(x,y,rotation,icon)
-
+ # transfer the location of the label back to
+ # data coordinates
+ dx,dy = trans.inverted().transform_point((x,y))
+ t = text.Text(dx, dy, rotation = rotation,
+ horizontalalignment='center',
+ verticalalignment='center')
+ _text = self.get_text(lev,fmt)
+ self.set_label_props(t, _text, color)
+ self.cl.append(t)
+ self.cl_cvalues.append(cvalue)
if inline:
new = self.break_linecontour(linecontour, rotation, lw, ind)
if len(new[0]):
@@ -882,8 +802,19 @@
Use keyword args to control colors, linewidth, origin, cmap ... see
below for more details.
- *X*, *Y*, and *Z* must be arrays with the same dimensions.
+ *X*, *Y*, and *Z* may be arrays all with the same 2-D shape, or
+ *X* and *Y* can be 1-D while *Z* is 2-D. In the latter
+ case, the following must be true:
+ ::
+
+ Z.shape == len(Y), len(X)
+
+ Note that the first index of *Z*, the row number, corresponds
+ to the vertical coordinate on the page, while the second
+ index, the column number, corresponds to the horizontal
+ coordinate on the page.
+
*Z* may be a masked array, but filled contouring may not
handle internal masked regions correctly.
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