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From: aishwarya s. <ais...@gm...> - 2018-05-16 14:21:28
|
Dear all,
I wanted to reciprocate the effect of :
import matplotlib.pyplot as plt}
plt.imshow(image1)
plt.pause(0.7)
plt.imshow(image2)
in a code making use of Tkinter and FigureCanvastkAgg;
Which lookes something like this :
f = Figure(figsize=(6,6))
a = f.add_subplot(111)
image = np.array(np.random.random((1024,1024))*100,dtype=int)
a.imshow(image)
canvas = FigureCanvasTkAgg(f, self)
canvas.show()
canvas.get_tk_widget().pack(side=tk.BOTTOM, fill=tk.BOTH, expand=True)`
If I want to plot another image2 in the same graph. How could I do it?
I tried another method but was not able to obtain the desired output:
>
>
self.i = 0
def Plot():
print self.i
self.f = Figure(figsize=(6,6))
self.a = self.f.add_subplot(111)
image = np.array(np.random.random((1024,1024))*100,dtype=int)
>
> if self.i <20:
self.i = self.i+1
self.a.imshow(image)
self.canvas = FigureCanvasTkAgg(self.f, self)
self.canvas.show()
self.parent.after(500,Plot)
Plot()
>
>
self.canvas.get_tk_widget().pack(side=tk.BOTTOM, fill=tk.BOTH,
> expand=True)
toolbar = NavigationToolbar2TkAgg(self.canvas, self)
toolbar.update()
self.canvas._tkcanvas.pack(side=tk.TOP, fill=tk.BOTH, expand=True)
>
>
Awaiting your reply.
--
Regards,
Aishwarya Selvaraj
|
|
From: <fer...@us...> - 2011-12-17 21:49:43
|
Revision: 8989
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8989&view=rev
Author: fer_perez
Date: 2011-12-17 21:49:36 +0000 (Sat, 17 Dec 2011)
Log Message:
-----------
Sync SVN repo with contents in current git repo
Modified Paths:
--------------
trunk/sample_data/setup.py
Added Paths:
-----------
trunk/sample_data/moonlanding.png
trunk/sample_data/screenshots/
trunk/sample_data/screenshots/500hgtdata.gz
trunk/sample_data/screenshots/500hgtlats.gz
trunk/sample_data/screenshots/500hgtlons.gz
trunk/sample_data/screenshots/chandra.dat
trunk/sample_data/screenshots/eeg.dat
trunk/sample_data/screenshots/etopo20data.gz
trunk/sample_data/screenshots/etopo20lats.gz
trunk/sample_data/screenshots/etopo20lons.gz
trunk/sample_data/screenshots/hst.zdat
trunk/sample_data/screenshots/intc.csv
trunk/sample_data/screenshots/msft.csv
trunk/sample_data/screenshots/s1045.ima
trunk/sample_data/stinkbug.png
Added: trunk/sample_data/moonlanding.png
===================================================================
(Binary files differ)
Property changes on: trunk/sample_data/moonlanding.png
___________________________________________________________________
Added: svn:mime-type
+ application/octet-stream
Added: trunk/sample_data/screenshots/500hgtdata.gz
===================================================================
(Binary files differ)
Property changes on: trunk/sample_data/screenshots/500hgtdata.gz
___________________________________________________________________
Added: svn:mime-type
+ application/octet-stream
Added: trunk/sample_data/screenshots/500hgtlats.gz
===================================================================
(Binary files differ)
Property changes on: trunk/sample_data/screenshots/500hgtlats.gz
___________________________________________________________________
Added: svn:mime-type
+ application/octet-stream
Added: trunk/sample_data/screenshots/500hgtlons.gz
===================================================================
(Binary files differ)
Property changes on: trunk/sample_data/screenshots/500hgtlons.gz
___________________________________________________________________
Added: svn:mime-type
+ application/octet-stream
Added: trunk/sample_data/screenshots/chandra.dat
===================================================================
(Binary files differ)
Property changes on: trunk/sample_data/screenshots/chandra.dat
___________________________________________________________________
Added: svn:mime-type
+ application/octet-stream
Added: trunk/sample_data/screenshots/eeg.dat
===================================================================
(Binary files differ)
Property changes on: trunk/sample_data/screenshots/eeg.dat
___________________________________________________________________
Added: svn:mime-type
+ application/octet-stream
Added: trunk/sample_data/screenshots/etopo20data.gz
===================================================================
(Binary files differ)
Property changes on: trunk/sample_data/screenshots/etopo20data.gz
___________________________________________________________________
Added: svn:mime-type
+ application/octet-stream
Added: trunk/sample_data/screenshots/etopo20lats.gz
===================================================================
(Binary files differ)
Property changes on: trunk/sample_data/screenshots/etopo20lats.gz
___________________________________________________________________
Added: svn:mime-type
+ application/octet-stream
Added: trunk/sample_data/screenshots/etopo20lons.gz
===================================================================
(Binary files differ)
Property changes on: trunk/sample_data/screenshots/etopo20lons.gz
___________________________________________________________________
Added: svn:mime-type
+ application/octet-stream
Added: trunk/sample_data/screenshots/hst.zdat
===================================================================
(Binary files differ)
Property changes on: trunk/sample_data/screenshots/hst.zdat
___________________________________________________________________
Added: svn:mime-type
+ application/octet-stream
Added: trunk/sample_data/screenshots/intc.csv
===================================================================
--- trunk/sample_data/screenshots/intc.csv (rev 0)
+++ trunk/sample_data/screenshots/intc.csv 2011-12-17 21:49:36 UTC (rev 8989)
@@ -0,0 +1,66 @@
+Date,Open,High,Low,Close,Volume,Adj. Close*
+19-Sep-03,29.30,29.36,28.83,29.17,53550300,29.15
+18-Sep-03,28.69,29.28,28.46,29.16,46619000,29.14
+17-Sep-03,28.94,29.38,28.77,28.88,52827300,28.86
+16-Sep-03,28.08,28.99,28.02,28.91,48748000,28.89
+15-Sep-03,28.33,28.45,27.91,27.99,36350400,27.97
+12-Sep-03,27.81,28.39,27.55,28.34,51931600,28.32
+11-Sep-03,27.62,28.35,27.29,28.03,56654900,28.01
+10-Sep-03,28.44,28.49,27.63,27.66,57999300,27.64
+9-Sep-03,29.00,29.13,28.66,28.79,49792900,28.77
+8-Sep-03,28.88,29.20,28.80,29.18,52154000,29.16
+5-Sep-03,28.83,29.10,28.37,28.71,68429904,28.69
+4-Sep-03,28.32,28.74,28.04,28.60,63744700,28.58
+3-Sep-03,28.94,28.97,28.04,28.22,60714800,28.20
+2-Sep-03,28.77,28.84,28.17,28.74,58841200,28.72
+29-Aug-03,28.18,28.65,28.04,28.59,41986600,28.57
+28-Aug-03,28.10,28.35,27.85,28.30,48631600,28.28
+27-Aug-03,27.61,28.08,27.42,28.02,58217200,28.00
+26-Aug-03,26.96,27.74,26.68,27.71,65213400,27.69
+25-Aug-03,27.56,27.76,27.07,27.24,52037500,27.22
+22-Aug-03,28.16,29.04,27.32,27.39,120604096,27.37
+21-Aug-03,26.69,26.78,26.01,26.39,66434900,26.37
+20-Aug-03,26.14,26.74,26.13,26.36,47210300,26.34
+19-Aug-03,26.37,26.54,25.92,26.47,55966300,26.45
+18-Aug-03,25.10,26.23,25.05,26.19,59081000,26.17
+15-Aug-03,25.09,25.25,24.81,25.05,21622800,25.04
+14-Aug-03,24.80,25.17,24.55,25.14,51830000,25.13
+13-Aug-03,24.50,25.00,24.30,24.71,51882500,24.70
+12-Aug-03,24.09,24.40,23.82,24.37,48475100,24.36
+11-Aug-03,23.62,24.13,23.58,23.90,41624600,23.89
+8-Aug-03,24.15,24.22,23.33,23.58,57453600,23.57
+7-Aug-03,23.94,24.30,23.86,23.99,48517800,23.98
+6-Aug-03,24.10,24.55,23.81,24.14,57799000,24.13
+5-Aug-03,25.12,25.12,24.23,24.27,51979800,24.26
+4-Aug-03,24.91,25.23,24.39,25.13,53570000,25.10
+1-Aug-03,24.78,25.07,24.73,25.02,48494900,24.99
+31-Jul-03,24.80,25.35,24.68,24.89,68692096,24.86
+30-Jul-03,24.86,24.87,24.28,24.49,40786200,24.46
+29-Jul-03,24.81,25.23,24.70,24.90,68217600,24.87
+28-Jul-03,24.92,25.13,24.61,24.76,45462200,24.73
+25-Jul-03,24.17,24.94,23.73,24.91,52627700,24.88
+24-Jul-03,25.15,25.17,23.95,23.97,58119100,23.94
+23-Jul-03,24.37,24.90,24.26,24.81,49058200,24.78
+22-Jul-03,24.39,24.53,24.05,24.42,61074300,24.39
+21-Jul-03,24.60,24.63,23.95,24.06,52851200,24.03
+18-Jul-03,25.10,25.15,24.15,24.66,65296900,24.63
+17-Jul-03,24.69,25.10,24.60,24.93,71736800,24.90
+16-Jul-03,25.24,25.50,24.82,25.31,128925696,25.27
+15-Jul-03,24.44,24.77,23.67,24.10,102323696,24.07
+14-Jul-03,24.27,24.58,23.85,24.02,76909400,23.99
+11-Jul-03,23.29,23.50,23.07,23.34,46535400,23.31
+10-Jul-03,23.07,23.30,22.61,22.91,63261600,22.88
+9-Jul-03,23.30,23.99,23.25,23.48,78521904,23.45
+8-Jul-03,22.83,23.40,22.67,23.15,64980800,23.12
+7-Jul-03,22.24,22.98,22.17,22.91,56553100,22.88
+3-Jul-03,21.97,22.31,21.71,21.72,40502400,21.69
+2-Jul-03,21.66,22.32,21.47,22.21,74291504,22.18
+1-Jul-03,20.87,21.50,20.51,21.41,64496600,21.38
+30-Jun-03,21.14,21.30,20.59,20.81,51457500,20.78
+27-Jun-03,20.70,21.13,20.53,20.57,63348200,20.54
+26-Jun-03,20.30,20.76,20.15,20.63,52904900,20.60
+25-Jun-03,20.53,20.83,19.99,20.04,61250600,20.01
+24-Jun-03,20.11,20.74,20.04,20.45,63799700,20.42
+23-Jun-03,20.70,20.97,20.05,20.36,59628100,20.33
+20-Jun-03,21.34,21.42,20.64,20.67,78909400,20.64
+19-Jun-03,21.66,21.92,21.12,21.12,69563696,21.09
Added: trunk/sample_data/screenshots/msft.csv
===================================================================
--- trunk/sample_data/screenshots/msft.csv (rev 0)
+++ trunk/sample_data/screenshots/msft.csv 2011-12-17 21:49:36 UTC (rev 8989)
@@ -0,0 +1,66 @@
+Date,Open,High,Low,Close,Volume,Adj. Close*
+19-Sep-03,29.76,29.97,29.52,29.96,92433800,29.79
+18-Sep-03,28.49,29.51,28.42,29.50,67268096,29.34
+17-Sep-03,28.76,28.95,28.47,28.50,47221600,28.34
+16-Sep-03,28.41,28.95,28.32,28.90,52060600,28.74
+15-Sep-03,28.37,28.61,28.33,28.36,41432300,28.20
+12-Sep-03,27.48,28.40,27.45,28.34,55777200,28.18
+11-Sep-03,27.66,28.11,27.59,27.84,37813300,27.68
+10-Sep-03,28.03,28.18,27.48,27.55,54763500,27.40
+9-Sep-03,28.65,28.71,28.31,28.37,44315200,28.21
+8-Sep-03,28.39,28.92,28.34,28.84,46105300,28.68
+5-Sep-03,28.23,28.75,28.17,28.38,64024500,28.22
+4-Sep-03,28.10,28.47,27.99,28.43,59840800,28.27
+3-Sep-03,27.42,28.40,27.38,28.30,109437800,28.14
+2-Sep-03,26.70,27.30,26.47,27.26,74168896,27.11
+29-Aug-03,26.46,26.55,26.35,26.52,34503000,26.37
+28-Aug-03,26.50,26.58,26.24,26.51,46211200,26.36
+27-Aug-03,26.51,26.58,26.30,26.42,30633900,26.27
+26-Aug-03,26.31,26.67,25.96,26.57,47546000,26.42
+25-Aug-03,26.31,26.54,26.23,26.50,36132900,26.35
+22-Aug-03,26.78,26.95,26.21,26.22,65846300,26.07
+21-Aug-03,26.65,26.73,26.13,26.24,63802700,26.09
+20-Aug-03,26.30,26.53,26.00,26.45,56739300,26.30
+19-Aug-03,25.85,26.65,25.77,26.62,72952896,26.47
+18-Aug-03,25.56,25.83,25.46,25.70,45817400,25.56
+15-Aug-03,25.61,25.66,25.43,25.54,27607900,25.40
+14-Aug-03,25.66,25.71,25.52,25.63,37338300,25.49
+13-Aug-03,25.79,25.89,25.50,25.60,39636900,25.46
+12-Aug-03,25.71,25.77,25.45,25.73,38208400,25.59
+11-Aug-03,25.61,25.99,25.54,25.61,36433900,25.47
+8-Aug-03,25.88,25.98,25.50,25.58,33241400,25.44
+7-Aug-03,25.72,25.81,25.45,25.71,44258500,25.57
+6-Aug-03,25.54,26.19,25.43,25.65,56294900,25.51
+5-Aug-03,26.31,26.54,25.60,25.66,58825800,25.52
+4-Aug-03,26.15,26.41,25.75,26.18,51825600,26.03
+1-Aug-03,26.33,26.51,26.12,26.17,42649700,26.02
+31-Jul-03,26.60,26.99,26.31,26.41,64504800,26.26
+30-Jul-03,26.46,26.57,26.17,26.23,41240300,26.08
+29-Jul-03,26.88,26.90,26.24,26.47,62391100,26.32
+28-Jul-03,26.94,27.00,26.49,26.61,52658300,26.46
+25-Jul-03,26.28,26.95,26.07,26.89,54173000,26.74
+24-Jul-03,26.78,26.92,25.98,26.00,53556600,25.85
+23-Jul-03,26.42,26.65,26.14,26.45,49828200,26.30
+22-Jul-03,26.28,26.56,26.13,26.38,51791000,26.23
+21-Jul-03,26.87,26.91,26.00,26.04,48480800,25.89
+18-Jul-03,27.11,27.23,26.75,26.89,63388400,26.74
+17-Jul-03,27.14,27.27,26.54,26.69,72805000,26.54
+16-Jul-03,27.56,27.62,27.20,27.52,49838900,27.37
+15-Jul-03,27.47,27.53,27.10,27.27,53567600,27.12
+14-Jul-03,27.63,27.81,27.05,27.40,60464400,27.25
+11-Jul-03,26.95,27.45,26.89,27.31,50377300,27.16
+10-Jul-03,27.25,27.42,26.59,26.91,55350800,26.76
+9-Jul-03,27.56,27.70,27.25,27.47,62300700,27.32
+8-Jul-03,27.26,27.80,27.25,27.70,61896800,27.55
+7-Jul-03,27.02,27.55,26.95,27.42,88960800,27.27
+3-Jul-03,26.69,26.95,26.41,26.50,39440900,26.35
+2-Jul-03,26.50,26.93,26.45,26.88,94069296,26.73
+1-Jul-03,25.59,26.20,25.39,26.15,60926000,26.00
+30-Jun-03,25.94,26.12,25.50,25.64,48073100,25.50
+27-Jun-03,25.95,26.34,25.53,25.63,76040304,25.49
+26-Jun-03,25.39,26.51,25.21,25.75,51758100,25.61
+25-Jun-03,25.64,25.99,25.14,25.26,60483500,25.12
+24-Jun-03,25.65,26.04,25.52,25.70,51820300,25.56
+23-Jun-03,26.14,26.24,25.49,25.78,52584500,25.64
+20-Jun-03,26.34,26.38,26.01,26.33,86048896,26.18
+19-Jun-03,26.09,26.39,26.01,26.07,63626900,25.92
Added: trunk/sample_data/screenshots/s1045.ima
===================================================================
(Binary files differ)
Property changes on: trunk/sample_data/screenshots/s1045.ima
___________________________________________________________________
Added: svn:mime-type
+ application/octet-stream
Modified: trunk/sample_data/setup.py
===================================================================
--- trunk/sample_data/setup.py 2011-02-18 19:28:29 UTC (rev 8988)
+++ trunk/sample_data/setup.py 2011-12-17 21:49:36 UTC (rev 8989)
@@ -1,7 +1,7 @@
from distutils.core import setup
setup(name='mpl_sampledata',
- version='1.0.1',
+ version='1.1.0',
description='matplotlib sample data',
author='John Hunter',
author_email='jd...@gm...',
Added: trunk/sample_data/stinkbug.png
===================================================================
(Binary files differ)
Property changes on: trunk/sample_data/stinkbug.png
___________________________________________________________________
Added: svn:mime-type
+ application/octet-stream
This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.
|
|
From: <wea...@us...> - 2011-02-18 19:28:35
|
Revision: 8988
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8988&view=rev
Author: weathergod
Date: 2011-02-18 19:28:29 +0000 (Fri, 18 Feb 2011)
Log Message:
-----------
scatter() now supports empty arrays as input (i.e., scatter([], []) is now valid).
Enabling this required fixes in both scatter() and in collections.py.
Collections now support empty versions of themselves more correctly due to these fixes.
Modified Paths:
--------------
trunk/matplotlib/CHANGELOG
trunk/matplotlib/lib/matplotlib/axes.py
trunk/matplotlib/lib/matplotlib/collections.py
Modified: trunk/matplotlib/CHANGELOG
===================================================================
--- trunk/matplotlib/CHANGELOG 2011-02-17 16:44:28 UTC (rev 8987)
+++ trunk/matplotlib/CHANGELOG 2011-02-18 19:28:29 UTC (rev 8988)
@@ -1,3 +1,6 @@
+2011-02-18 scatter([], []) is now valid. Also fixed issues
+ with empty collections - BVR
+
2011-02-07 Quick workaround for dviread bug #3175113 - JKS
2011-02-05 Add cbook memory monitoring for Windows, using
Modified: trunk/matplotlib/lib/matplotlib/axes.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/axes.py 2011-02-17 16:44:28 UTC (rev 8987)
+++ trunk/matplotlib/lib/matplotlib/axes.py 2011-02-18 19:28:29 UTC (rev 8988)
@@ -5832,24 +5832,17 @@
else:
collection.autoscale_None()
- temp_x = x
- temp_y = y
-
- minx = np.amin(temp_x)
- maxx = np.amax(temp_x)
- miny = np.amin(temp_y)
- maxy = np.amax(temp_y)
-
- w = maxx-minx
- h = maxy-miny
-
# the pad is a little hack to deal with the fact that we don't
# want to transform all the symbols whose scales are in points
# to data coords to get the exact bounding box for efficiency
# reasons. It can be done right if this is deemed important
- padx, pady = 0.05*w, 0.05*h
- corners = (minx-padx, miny-pady), (maxx+padx, maxy+pady)
- self.update_datalim( corners)
+ # Also, only bother with this padding if there is anything to draw.
+ if self._xmargin < 0.05 and x.size > 0 :
+ self.set_xmargin(0.05)
+
+ if self._ymargin < 0.05 and x.size > 0 :
+ self.set_ymargin(0.05)
+
self.autoscale_view()
# add the collection last
Modified: trunk/matplotlib/lib/matplotlib/collections.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/collections.py 2011-02-17 16:44:28 UTC (rev 8987)
+++ trunk/matplotlib/lib/matplotlib/collections.py 2011-02-18 19:28:29 UTC (rev 8988)
@@ -59,6 +59,8 @@
scalar mappable will be made to set the face colors.
"""
_offsets = np.array([], np.float_)
+ # _offsets must be a Nx2 array!
+ _offsets.shape = (0, 2)
_transOffset = transforms.IdentityTransform()
_transforms = []
@@ -95,10 +97,11 @@
self._uniform_offsets = None
self._offsets = np.array([], np.float_)
+ # Force _offsets to be Nx2
+ self._offsets.shape = (0, 2)
if offsets is not None:
offsets = np.asarray(offsets)
- if len(offsets.shape) == 1:
- offsets = offsets[np.newaxis,:] # Make it Nx2.
+ offsets.shape = (-1, 2) # Make it Nx2
if transOffset is not None:
self._offsets = offsets
self._transOffset = transOffset
@@ -148,13 +151,17 @@
transOffset = self._transOffset
offsets = self._offsets
paths = self.get_paths()
+
+
if not transform.is_affine:
paths = [transform.transform_path_non_affine(p) for p in paths]
transform = transform.get_affine()
if not transOffset.is_affine:
offsets = transOffset.transform_non_affine(offsets)
transOffset = transOffset.get_affine()
+
offsets = np.asarray(offsets, np.float_)
+ offsets.shape = (-1, 2) # Make it Nx2
result = mpath.get_path_collection_extents(
transform.frozen(), paths, self.get_transforms(),
@@ -176,6 +183,7 @@
offsets = self._offsets
paths = self.get_paths()
+
if self.have_units():
paths = []
for path in self.get_paths():
@@ -184,17 +192,19 @@
xs = self.convert_xunits(xs)
ys = self.convert_yunits(ys)
paths.append(mpath.Path(zip(xs, ys), path.codes))
- if len(self._offsets):
- xs = self.convert_xunits(self._offsets[:,0])
- ys = self.convert_yunits(self._offsets[:,1])
+
+ if offsets.size > 0:
+ xs = self.convert_xunits(offsets[:,0])
+ ys = self.convert_yunits(offsets[:,1])
offsets = zip(xs, ys)
offsets = np.asarray(offsets, np.float_)
+ offsets.shape = (-1, 2) # Make it Nx2
if not transform.is_affine:
paths = [transform.transform_path_non_affine(path) for path in paths]
transform = transform.get_affine()
- if not transOffset.is_affine:
+ if not transOffset.is_affine :
offsets = transOffset.transform_non_affine(offsets)
transOffset = transOffset.get_affine()
@@ -258,8 +268,7 @@
ACCEPTS: float or sequence of floats
"""
offsets = np.asarray(offsets, np.float_)
- if len(offsets.shape) == 1:
- offsets = offsets[np.newaxis,:] # Make it Nx2.
+ offsets.shape = (-1, 2) # Make it Nx2
#This decision is based on how they are initialized above
if self._uniform_offsets is None:
self._offsets = offsets
@@ -1221,6 +1230,7 @@
offsets = zip(xs, ys)
offsets = np.asarray(offsets, np.float_)
+ offsets.shape = (-1, 2) # Make it Nx2
self.update_scalarmappable()
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|
|
From: <js...@us...> - 2011-02-17 16:44:34
|
Revision: 8987
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8987&view=rev
Author: jswhit
Date: 2011-02-17 16:44:28 +0000 (Thu, 17 Feb 2011)
Log Message:
-----------
update
Modified Paths:
--------------
trunk/toolkits/basemap/Changelog
Modified: trunk/toolkits/basemap/Changelog
===================================================================
--- trunk/toolkits/basemap/Changelog 2011-02-17 15:51:17 UTC (rev 8986)
+++ trunk/toolkits/basemap/Changelog 2011-02-17 16:44:28 UTC (rev 8987)
@@ -2,6 +2,7 @@
* added lic_demo.py to examples (line integral convolution,
requires scikit.vectorplot).
* removed deprecated NetCDFFile.
+ * added zorder keyword to drawmapscale.
version 1.0.1 (svn revision 8967)
* regenerated C source with cython 0.14.1.
* added new "allsky" example from Tom Loredo.
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|
|
From: <md...@us...> - 2011-02-17 15:51:23
|
Revision: 8986
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8986&view=rev
Author: mdboom
Date: 2011-02-17 15:51:17 +0000 (Thu, 17 Feb 2011)
Log Message:
-----------
Fix long Unicode characters in SVG backend (fixes mathtext_stixsans test on narrow Python builds.)
Modified Paths:
--------------
trunk/matplotlib/lib/matplotlib/backends/backend_svg.py
trunk/matplotlib/lib/matplotlib/mathtext.py
Modified: trunk/matplotlib/lib/matplotlib/backends/backend_svg.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/backends/backend_svg.py 2011-02-17 15:50:47 UTC (rev 8985)
+++ trunk/matplotlib/lib/matplotlib/backends/backend_svg.py 2011-02-17 15:51:17 UTC (rev 8986)
@@ -603,7 +603,7 @@
if rcParams['svg.embed_char_paths']:
new_chars = []
for c in s:
- path = self._add_char_def(prop, c)
+ path = self._add_char_def(prop, ord(c))
if path is not None:
new_chars.append(path)
if len(new_chars):
@@ -628,7 +628,7 @@
lastgind = None
currx = 0
for c in s:
- charnum = self._get_char_def_id(prop, c)
+ charnum = self._get_char_def_id(prop, ord(c))
ccode = ord(c)
gind = cmap.get(ccode)
if gind is None:
@@ -680,13 +680,13 @@
font = prop
font.set_size(self.FONT_SCALE, 72)
ps_name = font.get_sfnt()[(1,0,0,6)]
- char_id = urllib.quote('%s-%d' % (ps_name, ord(char)))
+ char_id = urllib.quote('%s-%d' % (ps_name, char))
char_num = self._char_defs.get(char_id, None)
if char_num is not None:
return None
path_data = []
- glyph = font.load_char(ord(char), flags=LOAD_NO_HINTING)
+ glyph = font.load_char(char, flags=LOAD_NO_HINTING)
currx, curry = 0.0, 0.0
for step in glyph.path:
if step[0] == 0: # MOVE_TO
@@ -724,7 +724,7 @@
font = prop
font.set_size(self.FONT_SCALE, 72)
ps_name = font.get_sfnt()[(1,0,0,6)]
- char_id = urllib.quote('%s-%d' % (ps_name, ord(char)))
+ char_id = urllib.quote('%s-%d' % (ps_name, char))
return self._char_defs[char_id]
def _draw_mathtext(self, gc, x, y, s, prop, angle):
@@ -742,8 +742,8 @@
if rcParams['svg.embed_char_paths']:
new_chars = []
- for font, fontsize, thetext, new_x, new_y_mtc, metrics in svg_glyphs:
- path = self._add_char_def(font, thetext)
+ for font, fontsize, char, new_x, new_y_mtc, metrics in svg_glyphs:
+ path = self._add_char_def(font, char)
if path is not None:
new_chars.append(path)
if len(new_chars):
@@ -760,8 +760,8 @@
svg.append('translate(%f,%f)' % (x, y))
svg.append('">\n')
- for font, fontsize, thetext, new_x, new_y_mtc, metrics in svg_glyphs:
- charid = self._get_char_def_id(font, thetext)
+ for font, fontsize, char, new_x, new_y_mtc, metrics in svg_glyphs:
+ charid = self._get_char_def_id(font, char)
svg.append('<use xlink:href="#%s" transform="translate(%f,%f)scale(%f)"/>\n' %
(charid, new_x, -new_y_mtc, fontsize / self.FONT_SCALE))
Modified: trunk/matplotlib/lib/matplotlib/mathtext.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/mathtext.py 2011-02-17 15:50:47 UTC (rev 8985)
+++ trunk/matplotlib/lib/matplotlib/mathtext.py 2011-02-17 15:51:17 UTC (rev 8986)
@@ -329,10 +329,9 @@
def render_glyph(self, ox, oy, info):
oy = self.height - oy + info.offset
- thetext = unichr_safe(info.num)
self.svg_glyphs.append(
- (info.font, info.fontsize, thetext, ox, oy, info.metrics))
+ (info.font, info.fontsize, info.num, ox, oy, info.metrics))
def render_rect_filled(self, x1, y1, x2, y2):
self.svg_rects.append(
This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.
|
|
From: <md...@us...> - 2011-02-17 15:50:53
|
Revision: 8985
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8985&view=rev
Author: mdboom
Date: 2011-02-17 15:50:47 +0000 (Thu, 17 Feb 2011)
Log Message:
-----------
Update image_interps.pdf baseline image.
Modified Paths:
--------------
trunk/matplotlib/lib/matplotlib/tests/baseline_images/test_image/image_interps.pdf
Modified: trunk/matplotlib/lib/matplotlib/tests/baseline_images/test_image/image_interps.pdf
===================================================================
(Binary files differ)
This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.
|
|
From: <md...@us...> - 2011-02-17 15:50:16
|
Revision: 8984
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8984&view=rev
Author: mdboom
Date: 2011-02-17 15:50:10 +0000 (Thu, 17 Feb 2011)
Log Message:
-----------
Adding canonical baseline images
Added Paths:
-----------
trunk/matplotlib/lib/matplotlib/tests/baseline_images/test_axes/canonical.pdf
trunk/matplotlib/lib/matplotlib/tests/baseline_images/test_axes/canonical.png
trunk/matplotlib/lib/matplotlib/tests/baseline_images/test_axes/canonical.svg
Added: trunk/matplotlib/lib/matplotlib/tests/baseline_images/test_axes/canonical.pdf
===================================================================
(Binary files differ)
Property changes on: trunk/matplotlib/lib/matplotlib/tests/baseline_images/test_axes/canonical.pdf
___________________________________________________________________
Added: svn:mime-type
+ application/octet-stream
Added: trunk/matplotlib/lib/matplotlib/tests/baseline_images/test_axes/canonical.png
===================================================================
(Binary files differ)
Property changes on: trunk/matplotlib/lib/matplotlib/tests/baseline_images/test_axes/canonical.png
___________________________________________________________________
Added: svn:mime-type
+ application/octet-stream
Added: trunk/matplotlib/lib/matplotlib/tests/baseline_images/test_axes/canonical.svg
===================================================================
--- trunk/matplotlib/lib/matplotlib/tests/baseline_images/test_axes/canonical.svg (rev 0)
+++ trunk/matplotlib/lib/matplotlib/tests/baseline_images/test_axes/canonical.svg 2011-02-17 15:50:10 UTC (rev 8984)
@@ -0,0 +1,216 @@
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+ "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
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This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.
|
|
From: <js...@us...> - 2011-02-17 04:33:40
|
Revision: 8983
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8983&view=rev
Author: jswhit
Date: 2011-02-17 04:33:34 +0000 (Thu, 17 Feb 2011)
Log Message:
-----------
include zorder keyword for drawmapscale.
Modified Paths:
--------------
trunk/toolkits/basemap/lib/mpl_toolkits/basemap/__init__.py
Modified: trunk/toolkits/basemap/lib/mpl_toolkits/basemap/__init__.py
===================================================================
--- trunk/toolkits/basemap/lib/mpl_toolkits/basemap/__init__.py 2011-02-12 16:10:15 UTC (rev 8982)
+++ trunk/toolkits/basemap/lib/mpl_toolkits/basemap/__init__.py 2011-02-17 04:33:34 UTC (rev 8983)
@@ -3454,7 +3454,7 @@
def drawmapscale(self,lon,lat,lon0,lat0,length,barstyle='simple',\
units='km',fontsize=9,yoffset=None,labelstyle='simple',\
fontcolor='k',fillcolor1='w',fillcolor2='k',ax=None,\
- format='%d'):
+ format='%d',zorder=None):
"""
Draw a map scale at ``lon,lat`` of length ``length``
representing distance in the map
@@ -3487,6 +3487,7 @@
fillcolor1(2) colors of the alternating filled regions
(default white and black). Only relevant for
'fancy' barstyle.
+ zorder sets the zorder for the map scale.
============== ====================================================
Extra keyword ``ax`` can be used to override the default axis instance.
@@ -3625,6 +3626,8 @@
fontsize=fontsize,color=fontcolor))
else:
raise KeyError("barstyle must be 'simple' or 'fancy'")
+ if zorder is not None:
+ rets = [ret.set_zorder(zorder) for ret in rets]
return rets
def nightshade(self,date,color="k",delta=0.25,alpha=0.5,ax=None,zorder=2):
This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.
|
|
From: <js...@us...> - 2011-02-12 16:10:21
|
Revision: 8982
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8982&view=rev
Author: jswhit
Date: 2011-02-12 16:10:15 +0000 (Sat, 12 Feb 2011)
Log Message:
-----------
add comments.
Modified Paths:
--------------
trunk/toolkits/basemap/examples/lic_demo.py
Modified: trunk/toolkits/basemap/examples/lic_demo.py
===================================================================
--- trunk/toolkits/basemap/examples/lic_demo.py 2011-02-12 16:08:44 UTC (rev 8981)
+++ trunk/toolkits/basemap/examples/lic_demo.py 2011-02-12 16:10:15 UTC (rev 8982)
@@ -8,7 +8,7 @@
try:
from scikits.vectorplot import lic_internal
except ImportError:
- raise ImportError('need vectorplot scikit for this example')
+ raise ImportError('need vectorplot scikit for this example')
# H*wind data from http://www.aoml.noaa.gov/hrd/data_sub/wind.html
ncfile = NetCDFFile('rita.nc')
@@ -20,7 +20,7 @@
lons, lats = np.meshgrid(lons1,lats1)
ncfile.close()
-# downsample to finer grid.
+# downsample to finer grid for nicer looking plot.
nlats = 2*udat.shape[0]; nlons = 2*udat.shape[1]
lons = np.linspace(lons1[0],lons1[-1],nlons)
lats = np.linspace(lats1[0],lats1[-1],nlats)
@@ -31,11 +31,13 @@
fig = plt.figure(figsize=(8,8))
m = Basemap(projection='cyl',llcrnrlat=lats1[0],llcrnrlon=lons1[0],urcrnrlat=lats1[-1],urcrnrlon=lons1[-1],resolution='i')
+# pass texture, kernel and data to LIC function from vectorplot.
kernellen=31
texture = np.random.rand(udat.shape[0],udat.shape[1]).astype(np.float32)
kernel = np.sin(np.arange(kernellen)*np.pi/kernellen).astype(np.float32)
image = lic_internal.line_integral_convolution(udat.astype(np.float32),\
vdat.astype(np.float32), texture, kernel)
+# plot the resulting image.
im = m.imshow(image,plt.cm.gist_stern)
m.drawcoastlines()
m.drawmeridians(np.arange(-120,-60,2),labels=[0,0,0,1])
This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.
|
|
From: <js...@us...> - 2011-02-12 16:08:50
|
Revision: 8981
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8981&view=rev
Author: jswhit
Date: 2011-02-12 16:08:44 +0000 (Sat, 12 Feb 2011)
Log Message:
-----------
interpolate to finer grid for nicer looking plot
Modified Paths:
--------------
trunk/toolkits/basemap/examples/lic_demo.py
Modified: trunk/toolkits/basemap/examples/lic_demo.py
===================================================================
--- trunk/toolkits/basemap/examples/lic_demo.py 2011-02-12 16:01:55 UTC (rev 8980)
+++ trunk/toolkits/basemap/examples/lic_demo.py 2011-02-12 16:08:44 UTC (rev 8981)
@@ -2,7 +2,7 @@
# flow field (from Hurricane Earl). Produces something akin to streamlines.
# Requires vectorplot scikit (http://scikits.appspot.com/vectorplot).
from netCDF4 import Dataset as NetCDFFile
-from mpl_toolkits.basemap import Basemap
+from mpl_toolkits.basemap import Basemap, interp
import numpy as np
import matplotlib.pyplot as plt
try:
@@ -20,7 +20,15 @@
lons, lats = np.meshgrid(lons1,lats1)
ncfile.close()
+# downsample to finer grid.
+nlats = 2*udat.shape[0]; nlons = 2*udat.shape[1]
+lons = np.linspace(lons1[0],lons1[-1],nlons)
+lats = np.linspace(lats1[0],lats1[-1],nlats)
+lons, lats = np.meshgrid(lons, lats)
+udat = interp(udat,lons1,lats1,lons,lats,order=3)
+vdat = interp(vdat,lons1,lats1,lons,lats,order=3)
+
fig = plt.figure(figsize=(8,8))
m = Basemap(projection='cyl',llcrnrlat=lats1[0],llcrnrlon=lons1[0],urcrnrlat=lats1[-1],urcrnrlon=lons1[-1],resolution='i')
kernellen=31
This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.
|
|
From: <js...@us...> - 2011-02-12 16:02:02
|
Revision: 8980
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8980&view=rev
Author: jswhit
Date: 2011-02-12 16:01:55 +0000 (Sat, 12 Feb 2011)
Log Message:
-----------
obsolete file.
Removed Paths:
-------------
trunk/toolkits/basemap/lib/mpl_toolkits/basemap/pupynere.py
Deleted: trunk/toolkits/basemap/lib/mpl_toolkits/basemap/pupynere.py
===================================================================
--- trunk/toolkits/basemap/lib/mpl_toolkits/basemap/pupynere.py 2011-02-12 14:01:34 UTC (rev 8979)
+++ trunk/toolkits/basemap/lib/mpl_toolkits/basemap/pupynere.py 2011-02-12 16:01:55 UTC (rev 8980)
@@ -1,688 +0,0 @@
-"""
-NetCDF reader/writer module.
-
-This module implements the Scientific.IO.NetCDF API to read and create
-NetCDF files. The same API is also used in the PyNIO and pynetcdf
-modules, allowing these modules to be used interchangebly when working
-with NetCDF files. The major advantage of ``scipy.io.netcdf`` over other
-modules is that it doesn't require the code to be linked to the NetCDF
-libraries as the other modules do.
-
-The code is based on the `NetCDF file format specification
-<http://www.unidata.ucar.edu/software/netcdf/guide_15.html>`_. A NetCDF
-file is a self-describing binary format, with a header followed by
-data. The header contains metadata describing dimensions, variables
-and the position of the data in the file, so access can be done in an
-efficient manner without loading unnecessary data into memory. We use
-the ``mmap`` module to create Numpy arrays mapped to the data on disk,
-for the same purpose.
-
-The structure of a NetCDF file is as follows:
-
- C D F <VERSION BYTE> <NUMBER OF RECORDS>
- <DIMENSIONS> <GLOBAL ATTRIBUTES> <VARIABLES METADATA>
- <NON-RECORD DATA> <RECORD DATA>
-
-Record data refers to data where the first axis can be expanded at
-will. All record variables share a same dimension at the first axis,
-and they are stored at the end of the file per record, ie
-
- A[0], B[0], ..., A[1], B[1], ..., etc,
-
-so that new data can be appended to the file without changing its original
-structure. Non-record data are padded to a 4n bytes boundary. Record data
-are also padded, unless there is exactly one record variable in the file,
-in which case the padding is dropped. All data is stored in big endian
-byte order.
-
-The Scientific.IO.NetCDF API allows attributes to be added directly to
-instances of ``netcdf_file`` and ``netcdf_variable``. To differentiate
-between user-set attributes and instance attributes, user-set attributes
-are automatically stored in the ``_attributes`` attribute by overloading
-``__setattr__``. This is the reason why the code sometimes uses
-``obj.__dict__['key'] = value``, instead of simply ``obj.key = value``;
-otherwise the key would be inserted into userspace attributes.
-
-To create a NetCDF file::
-
- >>> import time
- >>> f = netcdf_file('simple.nc', 'w')
- >>> f.history = 'Created for a test'
- >>> f.createDimension('time', 10)
- >>> time = f.createVariable('time', 'i', ('time',))
- >>> time[:] = range(10)
- >>> time.units = 'days since 2008-01-01'
- >>> f.close()
-
-To read the NetCDF file we just created::
-
- >>> f = netcdf_file('simple.nc', 'r')
- >>> print f.history
- Created for a test
- >>> time = f.variables['time']
- >>> print time.units
- days since 2008-01-01
- >>> print time.shape
- (10,)
- >>> print time[-1]
- 9
- >>> f.close()
-
-TODO: properly implement ``_FillValue``.
-"""
-
-__all__ = ['netcdf_file', 'netcdf_variable']
-
-
-from operator import mul
-from mmap import mmap, ACCESS_READ
-
-from numpy import fromstring, ndarray, dtype, empty, array, asarray, squeeze,\
- zeros, ma
-from numpy import little_endian as LITTLE_ENDIAN
-
-
-ABSENT = '\x00\x00\x00\x00\x00\x00\x00\x00'
-ZERO = '\x00\x00\x00\x00'
-NC_BYTE = '\x00\x00\x00\x01'
-NC_CHAR = '\x00\x00\x00\x02'
-NC_SHORT = '\x00\x00\x00\x03'
-NC_INT = '\x00\x00\x00\x04'
-NC_FLOAT = '\x00\x00\x00\x05'
-NC_DOUBLE = '\x00\x00\x00\x06'
-NC_DIMENSION = '\x00\x00\x00\n'
-NC_VARIABLE = '\x00\x00\x00\x0b'
-NC_ATTRIBUTE = '\x00\x00\x00\x0c'
-
-
-TYPEMAP = { NC_BYTE: ('b', 1),
- NC_CHAR: ('c', 1),
- NC_SHORT: ('h', 2),
- NC_INT: ('i', 4),
- NC_FLOAT: ('f', 4),
- NC_DOUBLE: ('d', 8) }
-
-REVERSE = { 'b': NC_BYTE,
- 'c': NC_CHAR,
- 'h': NC_SHORT,
- 'i': NC_INT,
- 'f': NC_FLOAT,
- 'd': NC_DOUBLE,
-
- # these come from asarray(1).dtype.char and asarray('foo').dtype.char,
- # used when getting the types from generic attributes.
- 'l': NC_INT,
- 'S': NC_CHAR }
-
-
-class netcdf_file(object):
- """
- A ``netcdf_file`` object has two standard attributes: ``dimensions`` and
- ``variables``. The values of both are dictionaries, mapping dimension
- names to their associated lengths and variable names to variables,
- respectively. Application programs should never modify these
- dictionaries.
-
- All other attributes correspond to global attributes defined in the
- NetCDF file. Global file attributes are created by assigning to an
- attribute of the ``netcdf_file`` object.
-
- """
- def __init__(self, filename, mode='r', mmap=True, version=1,\
- maskandscale=False):
- self.filename = filename
- self.use_mmap = mmap
- self.version_byte = version
- self._maskandscale = maskandscale
-
- assert mode in 'rw', "Mode must be either 'r' or 'w'."
- self.mode = mode
-
- self.dimensions = {}
- self.variables = {}
-
- self._dims = []
- self._recs = 0
- self._recsize = 0
-
- self.fp = open(self.filename, '%sb' % mode)
-
- self._attributes = {}
-
- if mode is 'r':
- self._read()
-
- def __setattr__(self, attr, value):
- # Store user defined attributes in a separate dict,
- # so we can save them to file later.
- try:
- self._attributes[attr] = value
- except AttributeError:
- pass
- self.__dict__[attr] = value
-
- def close(self):
- if not self.fp.closed:
- try:
- self.flush()
- finally:
- self.fp.close()
- __del__ = close
-
- def createDimension(self, name, length):
- self.dimensions[name] = length
- self._dims.append(name)
-
- def createVariable(self, name, type, dimensions):
- shape = tuple([self.dimensions[dim] for dim in dimensions])
- shape_ = tuple([dim or 0 for dim in shape]) # replace None with 0 for numpy
-
- if isinstance(type, basestring): type = dtype(type)
- typecode, size = type.char, type.itemsize
- dtype_ = '>%s' % typecode
- if size > 1: dtype_ += str(size)
-
- data = empty(shape_, dtype=dtype_)
- self.variables[name] = netcdf_variable(data, typecode, shape,\
- dimensions, maskandscale=self._maskandscale)
- return self.variables[name]
-
- def flush(self):
- if self.mode is 'w':
- self._write()
- sync = flush
-
- def _write(self):
- self.fp.write('CDF')
- self.fp.write(array(self.version_byte, '>b').tostring())
-
- # Write headers and data.
- self._write_numrecs()
- self._write_dim_array()
- self._write_gatt_array()
- self._write_var_array()
-
- def _write_numrecs(self):
- # Get highest record count from all record variables.
- for var in self.variables.values():
- if var.isrec and len(var.data) > self._recs:
- self.__dict__['_recs'] = len(var.data)
- self._pack_int(self._recs)
-
- def _write_dim_array(self):
- if self.dimensions:
- self.fp.write(NC_DIMENSION)
- self._pack_int(len(self.dimensions))
- for name in self._dims:
- self._pack_string(name)
- length = self.dimensions[name]
- self._pack_int(length or 0) # replace None with 0 for record dimension
- else:
- self.fp.write(ABSENT)
-
- def _write_gatt_array(self):
- self._write_att_array(self._attributes)
-
- def _write_att_array(self, attributes):
- if attributes:
- self.fp.write(NC_ATTRIBUTE)
- self._pack_int(len(attributes))
- for name, values in attributes.items():
- self._pack_string(name)
- self._write_values(values)
- else:
- self.fp.write(ABSENT)
-
- def _write_var_array(self):
- if self.variables:
- self.fp.write(NC_VARIABLE)
- self._pack_int(len(self.variables))
-
- # Sort variables non-recs first, then recs.
- variables = self.variables.items()
- variables.sort(key=lambda (k, v): v._shape and not v.isrec)
- variables.reverse()
- variables = [k for (k, v) in variables]
-
- # Set the metadata for all variables.
- for name in variables:
- self._write_var_metadata(name)
- # Now that we have the metadata, we know the vsize of
- # each record variable, so we can calculate recsize.
- self.__dict__['_recsize'] = sum([
- var._vsize for var in self.variables.values()
- if var.isrec])
- # Set the data for all variables.
- for name in variables:
- self._write_var_data(name)
- else:
- self.fp.write(ABSENT)
-
- def _write_var_metadata(self, name):
- var = self.variables[name]
-
- self._pack_string(name)
- self._pack_int(len(var.dimensions))
- for dimname in var.dimensions:
- dimid = self._dims.index(dimname)
- self._pack_int(dimid)
-
- self._write_att_array(var._attributes)
-
- nc_type = REVERSE[var.typecode()]
- self.fp.write(nc_type)
-
- if not var.isrec:
- vsize = var.data.size * var.data.itemsize
- vsize += -vsize % 4
- else: # record variable
- try:
- vsize = var.data[0].size * var.data.itemsize
- except IndexError:
- vsize = 0
- rec_vars = len([var for var in self.variables.values()
- if var.isrec])
- if rec_vars > 1:
- vsize += -vsize % 4
- self.variables[name].__dict__['_vsize'] = vsize
- self._pack_int(vsize)
-
- # Pack a bogus begin, and set the real value later.
- self.variables[name].__dict__['_begin'] = self.fp.tell()
- self._pack_begin(0)
-
- def _write_var_data(self, name):
- var = self.variables[name]
-
- # Set begin in file header.
- the_beguine = self.fp.tell()
- self.fp.seek(var._begin)
- self._pack_begin(the_beguine)
- self.fp.seek(the_beguine)
-
- # Write data.
- if not var.isrec:
- self.fp.write(var.data.tostring())
- count = var.data.size * var.data.itemsize
- self.fp.write('0' * (var._vsize - count))
- else: # record variable
- # Handle rec vars with shape[0] < nrecs.
- if self._recs > len(var.data):
- shape = (self._recs,) + var.data.shape[1:]
- var.data.resize(shape)
-
- pos0 = pos = self.fp.tell()
- for rec in var.data:
- # Apparently scalars cannot be converted to big endian. If we
- # try to convert a ``=i4`` scalar to, say, '>i4' the dtype
- # will remain as ``=i4``.
- if not rec.shape and (rec.dtype.byteorder == '<' or
- (rec.dtype.byteorder == '=' and LITTLE_ENDIAN)):
- rec = rec.byteswap()
- self.fp.write(rec.tostring())
- # Padding
- count = rec.size * rec.itemsize
- self.fp.write('0' * (var._vsize - count))
- pos += self._recsize
- self.fp.seek(pos)
- self.fp.seek(pos0 + var._vsize)
-
- def _write_values(self, values):
- values = asarray(values)
- values = values.astype(values.dtype.newbyteorder('>'))
-
- nc_type = REVERSE[values.dtype.char]
- self.fp.write(nc_type)
-
- if values.dtype.char == 'S':
- nelems = values.itemsize
- else:
- nelems = values.size
- self._pack_int(nelems)
-
- if not values.shape and (values.dtype.byteorder == '<' or
- (values.dtype.byteorder == '=' and LITTLE_ENDIAN)):
- values = values.byteswap()
- self.fp.write(values.tostring())
- count = values.size * values.itemsize
- self.fp.write('0' * (-count % 4)) # pad
-
- def _read(self):
- # Check magic bytes and version
- magic = self.fp.read(3)
- assert magic == 'CDF', "Error: %s is not a valid NetCDF 3 file" % self.filename
- self.__dict__['version_byte'] = fromstring(self.fp.read(1), '>b')[0]
-
- # Read file headers and set data.
- self._read_numrecs()
- self._read_dim_array()
- self._read_gatt_array()
- self._read_var_array()
-
- def _read_numrecs(self):
- self.__dict__['_recs'] = self._unpack_int()
-
- def _read_dim_array(self):
- header = self.fp.read(4)
- assert header in [ZERO, NC_DIMENSION]
- count = self._unpack_int()
-
- for dim in range(count):
- name = self._unpack_string()
- length = self._unpack_int() or None # None for record dimension
- self.dimensions[name] = length
- self._dims.append(name) # preserve order
-
- def _read_gatt_array(self):
- for k, v in self._read_att_array().items():
- self.__setattr__(k, v)
-
- def _read_att_array(self):
- header = self.fp.read(4)
- assert header in [ZERO, NC_ATTRIBUTE]
- count = self._unpack_int()
-
- attributes = {}
- for attr in range(count):
- name = self._unpack_string()
- attributes[name] = self._read_values()
- return attributes
-
- def _read_var_array(self):
- header = self.fp.read(4)
- assert header in [ZERO, NC_VARIABLE]
-
- begin = 0
- dtypes = {'names': [], 'formats': []}
- rec_vars = []
- count = self._unpack_int()
- for var in range(count):
- name, dimensions, shape, attributes, typecode, size, dtype_, begin_, vsize = self._read_var()
- if shape and shape[0] is None:
- rec_vars.append(name)
- self.__dict__['_recsize'] += vsize
- if begin == 0: begin = begin_
- dtypes['names'].append(name)
- dtypes['formats'].append(str(shape[1:]) + dtype_)
-
- # Handle padding with a virtual variable.
- if typecode in 'bch':
- actual_size = reduce(mul, (1,) + shape[1:]) * size
- padding = -actual_size % 4
- if padding:
- dtypes['names'].append('_padding_%d' % var)
- dtypes['formats'].append('(%d,)>b' % padding)
-
- # Data will be set later.
- data = None
- else:
- if self.use_mmap:
- mm = mmap(self.fp.fileno(), begin_+vsize, access=ACCESS_READ)
- data = ndarray.__new__(ndarray, shape, dtype=dtype_,
- buffer=mm, offset=begin_, order=0)
- else:
- pos = self.fp.tell()
- self.fp.seek(begin_)
- data = fromstring(self.fp.read(vsize), dtype=dtype_)
- data.shape = shape
- self.fp.seek(pos)
-
- # Add variable.
- self.variables[name] = netcdf_variable(
- data, typecode, shape, dimensions, attributes,
- maskandscale=self._maskandscale)
-
- if rec_vars:
- # Remove padding when only one record variable.
- if len(rec_vars) == 1:
- dtypes['names'] = dtypes['names'][:1]
- dtypes['formats'] = dtypes['formats'][:1]
-
- # Build rec array.
- if self.use_mmap:
- mm = mmap(self.fp.fileno(), begin+self._recs*self._recsize, access=ACCESS_READ)
- rec_array = ndarray.__new__(ndarray, (self._recs,), dtype=dtypes,
- buffer=mm, offset=begin, order=0)
- else:
- pos = self.fp.tell()
- self.fp.seek(begin)
- rec_array = fromstring(self.fp.read(self._recs*self._recsize), dtype=dtypes)
- rec_array.shape = (self._recs,)
- self.fp.seek(pos)
-
- for var in rec_vars:
- self.variables[var].__dict__['data'] = rec_array[var]
-
- def _read_var(self):
- name = self._unpack_string()
- dimensions = []
- shape = []
- dims = self._unpack_int()
-
- for i in range(dims):
- dimid = self._unpack_int()
- dimname = self._dims[dimid]
- dimensions.append(dimname)
- dim = self.dimensions[dimname]
- shape.append(dim)
- dimensions = tuple(dimensions)
- shape = tuple(shape)
-
- attributes = self._read_att_array()
- nc_type = self.fp.read(4)
- vsize = self._unpack_int()
- begin = [self._unpack_int, self._unpack_int64][self.version_byte-1]()
-
- typecode, size = TYPEMAP[nc_type]
- if typecode is 'c':
- dtype_ = '>c'
- else:
- dtype_ = '>%s' % typecode
- if size > 1: dtype_ += str(size)
-
- return name, dimensions, shape, attributes, typecode, size, dtype_, begin, vsize
-
- def _read_values(self):
- nc_type = self.fp.read(4)
- n = self._unpack_int()
-
- typecode, size = TYPEMAP[nc_type]
-
- count = n*size
- values = self.fp.read(count)
- self.fp.read(-count % 4) # read padding
-
- if typecode is not 'c':
- values = fromstring(values, dtype='>%s%d' % (typecode, size))
- if values.shape == (1,): values = values[0]
- else:
- values = values.rstrip('\x00')
- return values
-
- def _pack_begin(self, begin):
- if self.version_byte == 1:
- self._pack_int(begin)
- elif self.version_byte == 2:
- self._pack_int64(begin)
-
- def _pack_int(self, value):
- self.fp.write(array(value, '>i').tostring())
- _pack_int32 = _pack_int
-
- def _unpack_int(self):
- return fromstring(self.fp.read(4), '>i')[0]
- _unpack_int32 = _unpack_int
-
- def _pack_int64(self, value):
- self.fp.write(array(value, '>q').tostring())
-
- def _unpack_int64(self):
- return fromstring(self.fp.read(8), '>q')[0]
-
- def _pack_string(self, s):
- count = len(s)
- self._pack_int(count)
- self.fp.write(s)
- self.fp.write('0' * (-count % 4)) # pad
-
- def _unpack_string(self):
- count = self._unpack_int()
- s = self.fp.read(count).rstrip('\x00')
- self.fp.read(-count % 4) # read padding
- return s
-
-
-class netcdf_variable(object):
- """
- ``netcdf_variable`` objects are constructed by calling the method
- ``createVariable`` on the netcdf_file object.
-
- ``netcdf_variable`` objects behave much like array objects defined in
- Numpy, except that their data resides in a file. Data is read by
- indexing and written by assigning to an indexed subset; the entire
- array can be accessed by the index ``[:]`` or using the methods
- ``getValue`` and ``assignValue``. ``netcdf_variable`` objects also
- have attribute ``shape`` with the same meaning as for arrays, but
- the shape cannot be modified. There is another read-only attribute
- ``dimensions``, whose value is the tuple of dimension names.
-
- All other attributes correspond to variable attributes defined in
- the NetCDF file. Variable attributes are created by assigning to an
- attribute of the ``netcdf_variable`` object.
-
- """
- def __init__(self, data, typecode, shape, dimensions, attributes=None,\
- maskandscale=False):
- self.data = data
- self._typecode = typecode
- self._shape = shape
- self.dimensions = dimensions
- self._maskandscale = maskandscale
-
- self._attributes = attributes or {}
- for k, v in self._attributes.items():
- self.__dict__[k] = v
-
- def __setattr__(self, attr, value):
- # Store user defined attributes in a separate dict,
- # so we can save them to file later.
- try:
- self._attributes[attr] = value
- except AttributeError:
- pass
- self.__dict__[attr] = value
-
- @property
- def isrec(self):
- return self.data.shape and not self._shape[0]
-
- @property
- def shape(self):
- return self.data.shape
-
- def __len__(self):
- return self.data.shape[0]
-
- def getValue(self):
- return self.data.item()
-
- def assignValue(self, value):
- self.data.itemset(value)
-
- def typecode(self):
- return self._typecode
-
- def __getitem__(self, index):
- data = squeeze(self.data[index])
- if self._maskandscale:
- return _unmaskandscale(self,data)
- else:
- return data
-
- def __setitem__(self, index, data):
- if self._maskandscale:
- data = _maskandscale(self,data)
- # Expand data for record vars?
- if self.isrec:
- if isinstance(index, tuple):
- rec_index = index[0]
- else:
- rec_index = index
- if isinstance(rec_index, slice):
- recs = (rec_index.start or 0) + len(data)
- else:
- recs = rec_index + 1
- if recs > len(self.data):
- shape = (recs,) + self._shape[1:]
- self.data.resize(shape)
- self.data[index] = data
-
-
-NetCDFFile = netcdf_file
-NetCDFVariable = netcdf_variable
-
-# default _FillValue for netcdf types (apply also to corresponding
-# DAP types).
-_default_fillvals = {'c':'\0',
- 'S':"",
- 'b':-127,
- 'B':-127,
- 'h':-32767,
- 'H':65535,
- 'i':-2147483647L,
- 'L':4294967295L,
- 'q':-2147483647L,
- 'f':9.9692099683868690e+36,
- 'd':9.9692099683868690e+36}
-def _unmaskandscale(var,data):
- # if _maskandscale mode set to True, perform
- # automatic unpacking using scale_factor/add_offset
- # and automatic conversion to masked array using
- # missing_value/_Fill_Value.
- totalmask = zeros(data.shape, bool)
- fill_value = None
- if hasattr(var, 'missing_value') and (data == var.missing_value).any():
- mask=data==var.missing_value
- fill_value = var.missing_value
- totalmask += mask
- if hasattr(var, '_FillValue') and (data == var._FillValue).any():
- mask=data==var._FillValue
- if fill_value is None:
- fill_value = var._FillValue
- totalmask += mask
- else:
- fillval = _default_fillvals[var.typecode()]
- if (data == fillval).any():
- mask=data==fillval
- if fill_value is None:
- fill_value = fillval
- totalmask += mask
- # all values where data == missing_value or _FillValue are
- # masked. fill_value set to missing_value if it exists,
- # otherwise _FillValue.
- if fill_value is not None:
- data = ma.masked_array(data,mask=totalmask,fill_value=fill_value)
- # if variable has scale_factor and add_offset attributes, rescale.
- if hasattr(var, 'scale_factor') and hasattr(var, 'add_offset'):
- data = var.scale_factor*data + var.add_offset
- return data
-
-def _maskandscale(var,data):
- # if _maskandscale mode set to True, perform
- # automatic packing using scale_factor/add_offset
- # and automatic filling of masked arrays using
- # missing_value/_Fill_Value.
- # use missing_value as fill value.
- # if no missing value set, use _FillValue.
- if hasattr(data,'mask'):
- if hasattr(var, 'missing_value'):
- fillval = var.missing_value
- elif hasattr(var, '_FillValue'):
- fillval = var._FillValue
- else:
- fillval = _default_fillvals[var.typecode()]
- data = data.filled(fill_value=fillval)
- # pack using scale_factor and add_offset.
- if hasattr(var, 'scale_factor') and hasattr(var, 'add_offset'):
- data = (data - var.add_offset)/var.scale_factor
- return data
This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.
|
|
From: <js...@us...> - 2011-02-12 14:01:41
|
Revision: 8979
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8979&view=rev
Author: jswhit
Date: 2011-02-12 14:01:34 +0000 (Sat, 12 Feb 2011)
Log Message:
-----------
use netcdf4-python instead of built-in NetCDFFile.
Modified Paths:
--------------
trunk/toolkits/basemap/MANIFEST.in
trunk/toolkits/basemap/examples/ccsm_popgrid.py
trunk/toolkits/basemap/examples/fcstmaps.py
trunk/toolkits/basemap/examples/fcstmaps_axesgrid.py
trunk/toolkits/basemap/examples/lic_demo.py
trunk/toolkits/basemap/examples/plothighsandlows.py
trunk/toolkits/basemap/examples/ploticos.py
trunk/toolkits/basemap/examples/plotprecip.py
trunk/toolkits/basemap/examples/plotsst.py
trunk/toolkits/basemap/examples/pnganim.py
Removed Paths:
-------------
trunk/toolkits/basemap/examples/NetCDFFile_tst.py
Modified: trunk/toolkits/basemap/MANIFEST.in
===================================================================
--- trunk/toolkits/basemap/MANIFEST.in 2011-02-12 13:58:04 UTC (rev 8978)
+++ trunk/toolkits/basemap/MANIFEST.in 2011-02-12 14:01:34 UTC (rev 8979)
@@ -80,7 +80,6 @@
include examples/C02562.orog.nc
include examples/ccsm_popgrid.nc
include examples/rita.nc
-include examples/NetCDFFile_tst.py
include examples/maskoceans.py
include examples/README
include lib/mpl_toolkits/__init__.py
Deleted: trunk/toolkits/basemap/examples/NetCDFFile_tst.py
===================================================================
--- trunk/toolkits/basemap/examples/NetCDFFile_tst.py 2011-02-12 13:58:04 UTC (rev 8978)
+++ trunk/toolkits/basemap/examples/NetCDFFile_tst.py 2011-02-12 14:01:34 UTC (rev 8979)
@@ -1,70 +0,0 @@
-import sys
-import unittest
-import os
-import tempfile
-from numpy import ma
-from numpy.testing import assert_array_equal, assert_array_almost_equal
-from numpy.random.mtrand import uniform
-try:
- from netCDF4 import Dataset as NetCDFFile
-except ImportError:
- from mpl_toolkits.basemap import NetCDFFile
-
-# test automatic conversion of masked arrays, and
-# packing/unpacking of short ints.
-
-FILE_NAME = tempfile.mktemp(".nc")
-ndim = 10
-ranarr = 100.*uniform(size=(ndim))
-packeddata = 10.*uniform(size=(ndim))
-missing_value = -9999.
-ranarr[::2] = missing_value
-maskedarr = ma.masked_values(ranarr,-9999.)
-scale_factor = (packeddata.max()-packeddata.min())/(2.*32766.)
-add_offset = 0.5*(packeddata.max()+packeddata.min())
-packeddata2 = ((packeddata-add_offset)/scale_factor).astype('i2')
-
-class TestCase(unittest.TestCase):
-
- def setUp(self):
- self.file = FILE_NAME
- file = NetCDFFile(self.file,'w')
- file.createDimension('n', None) # use unlimited dim.
- foo = file.createVariable('maskeddata', 'f8', ('n',))
- foo.missing_value = missing_value
- bar = file.createVariable('packeddata', 'i2', ('n',))
- bar.scale_factor = scale_factor
- bar.add_offset = add_offset
- foo[0:ndim] = maskedarr
- bar[0:ndim] = packeddata
- file.close()
-
- def tearDown(self):
- # Remove the temporary files
- os.remove(self.file)
-
- def runTest(self):
- """testing auto-conversion of masked arrays and packed integers"""
- # no auto-conversion.
- file = NetCDFFile(self.file,maskandscale=False)
- datamasked = file.variables['maskeddata']
- datapacked = file.variables['packeddata']
- if hasattr(datapacked,'set_auto_maskandscale'):
- datapacked.set_auto_maskandscale(False)
- # check missing_value, scale_factor and add_offset attributes.
- assert datamasked.missing_value == missing_value
- assert datapacked.scale_factor == scale_factor
- assert datapacked.add_offset == add_offset
- assert_array_equal(datapacked[:],packeddata2)
- assert_array_almost_equal(datamasked[:],ranarr)
- file.close()
- # auto-conversion
- file = NetCDFFile(self.file)
- datamasked = file.variables['maskeddata']
- datapacked = file.variables['packeddata']
- assert_array_almost_equal(datamasked[:].filled(datamasked.missing_value),ranarr)
- assert_array_almost_equal(datapacked[:],packeddata,decimal=4)
- file.close()
-
-if __name__ == '__main__':
- unittest.main()
Modified: trunk/toolkits/basemap/examples/ccsm_popgrid.py
===================================================================
--- trunk/toolkits/basemap/examples/ccsm_popgrid.py 2011-02-12 13:58:04 UTC (rev 8978)
+++ trunk/toolkits/basemap/examples/ccsm_popgrid.py 2011-02-12 14:01:34 UTC (rev 8979)
@@ -25,10 +25,7 @@
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
-try:
- from netCDF4 import Dataset as NetCDFFile
-except ImportError:
- from mpl_toolkits.basemap import NetCDFFile
+from netCDF4 import Dataset as NetCDFFile
# read in data from netCDF file.
infile = 'ccsm_popgrid.nc'
Modified: trunk/toolkits/basemap/examples/fcstmaps.py
===================================================================
--- trunk/toolkits/basemap/examples/fcstmaps.py 2011-02-12 13:58:04 UTC (rev 8978)
+++ trunk/toolkits/basemap/examples/fcstmaps.py 2011-02-12 14:01:34 UTC (rev 8979)
@@ -6,10 +6,7 @@
import numpy.ma as ma
import datetime
from mpl_toolkits.basemap import Basemap, addcyclic, num2date
-try:
- from netCDF4 import Dataset as NetCDFFile
-except ImportError:
- from mpl_toolkits.basemap import NetCDFFile
+from netCDF4 import Dataset as NetCDFFile
# today's date is default.
Modified: trunk/toolkits/basemap/examples/fcstmaps_axesgrid.py
===================================================================
--- trunk/toolkits/basemap/examples/fcstmaps_axesgrid.py 2011-02-12 13:58:04 UTC (rev 8978)
+++ trunk/toolkits/basemap/examples/fcstmaps_axesgrid.py 2011-02-12 14:01:34 UTC (rev 8979)
@@ -8,10 +8,7 @@
import datetime
from mpl_toolkits.basemap import Basemap, addcyclic, num2date
from mpl_toolkits.axes_grid1 import AxesGrid
-try:
- from netCDF4 import Dataset as NetCDFFile
-except ImportError:
- from mpl_toolkits.basemap import NetCDFFile
+from netCDF4 import Dataset as NetCDFFile
# today's date is default.
Modified: trunk/toolkits/basemap/examples/lic_demo.py
===================================================================
--- trunk/toolkits/basemap/examples/lic_demo.py 2011-02-12 13:58:04 UTC (rev 8978)
+++ trunk/toolkits/basemap/examples/lic_demo.py 2011-02-12 14:01:34 UTC (rev 8979)
@@ -1,10 +1,7 @@
# example showing how to use Line Integral Convolution to visualize a vector
# flow field (from Hurricane Earl). Produces something akin to streamlines.
# Requires vectorplot scikit (http://scikits.appspot.com/vectorplot).
-try:
- from netCDF4 import Dataset as NetCDFFile
-except ImportError:
- from mpl_toolkits.basemap import NetCDFFile
+from netCDF4 import Dataset as NetCDFFile
from mpl_toolkits.basemap import Basemap
import numpy as np
import matplotlib.pyplot as plt
Modified: trunk/toolkits/basemap/examples/plothighsandlows.py
===================================================================
--- trunk/toolkits/basemap/examples/plothighsandlows.py 2011-02-12 13:58:04 UTC (rev 8978)
+++ trunk/toolkits/basemap/examples/plothighsandlows.py 2011-02-12 14:01:34 UTC (rev 8979)
@@ -7,10 +7,7 @@
import sys
from mpl_toolkits.basemap import Basemap, addcyclic
from scipy.ndimage.filters import minimum_filter, maximum_filter
-try:
- from netCDF4 import Dataset as NetCDFFile
-except ImportError:
- from mpl_toolkits.basemap import NetCDFFile
+from netCDF4 import Dataset as NetCDFFile
def extrema(mat,mode='wrap',window=10):
"""find the indices of local extrema (min and max)
Modified: trunk/toolkits/basemap/examples/ploticos.py
===================================================================
--- trunk/toolkits/basemap/examples/ploticos.py 2011-02-12 13:58:04 UTC (rev 8978)
+++ trunk/toolkits/basemap/examples/ploticos.py 2011-02-12 14:01:34 UTC (rev 8979)
@@ -2,10 +2,7 @@
import matplotlib.pyplot as plt
import numpy as np
from numpy import ma
-try:
- from netCDF4 import Dataset as NetCDFFile
-except ImportError:
- from mpl_toolkits.basemap import NetCDFFile
+from netCDF4 import Dataset as NetCDFFile
# read in orography of icosahedral global grid.
f = NetCDFFile('C02562.orog.nc')
lons = (180./np.pi)*f.variables['grid_center_lon'][:]
Modified: trunk/toolkits/basemap/examples/plotprecip.py
===================================================================
--- trunk/toolkits/basemap/examples/plotprecip.py 2011-02-12 13:58:04 UTC (rev 8978)
+++ trunk/toolkits/basemap/examples/plotprecip.py 2011-02-12 14:01:34 UTC (rev 8979)
@@ -1,8 +1,5 @@
from mpl_toolkits.basemap import Basemap, cm
-try:
- from netCDF4 import Dataset as NetCDFFile
-except ImportError:
- from mpl_toolkits.basemap import NetCDFFile
+from netCDF4 import Dataset as NetCDFFile
import numpy as np
import matplotlib.pyplot as plt
import copy
Modified: trunk/toolkits/basemap/examples/plotsst.py
===================================================================
--- trunk/toolkits/basemap/examples/plotsst.py 2011-02-12 13:58:04 UTC (rev 8978)
+++ trunk/toolkits/basemap/examples/plotsst.py 2011-02-12 14:01:34 UTC (rev 8979)
@@ -1,8 +1,5 @@
from mpl_toolkits.basemap import Basemap, date2index, num2date
-try:
- from netCDF4 import Dataset as NetCDFFile
-except:
- from mpl_toolkits.basemap import NetCDFFile
+from netCDF4 import Dataset as NetCDFFile
import numpy as np
import matplotlib.pyplot as plt
import sys, datetime
Modified: trunk/toolkits/basemap/examples/pnganim.py
===================================================================
--- trunk/toolkits/basemap/examples/pnganim.py 2011-02-12 13:58:04 UTC (rev 8978)
+++ trunk/toolkits/basemap/examples/pnganim.py 2011-02-12 14:01:34 UTC (rev 8979)
@@ -10,10 +10,7 @@
import numpy.ma as ma
import datetime, sys, time, subprocess
from mpl_toolkits.basemap import Basemap, shiftgrid, date2index, num2date
-try:
- from netCDF4 import Dataset as NetCDFFile
-except:
- from mpl_toolkits.basemap import NetCDFFile
+from netCDF4 import Dataset as NetCDFFile
# times for March 1993 'storm of the century'
date1 = datetime.datetime(1993,3,10,0)
This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.
|
|
From: <js...@us...> - 2011-02-12 13:58:10
|
Revision: 8978
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8978&view=rev
Author: jswhit
Date: 2011-02-12 13:58:04 +0000 (Sat, 12 Feb 2011)
Log Message:
-----------
httplib2 and dap removed
Modified Paths:
--------------
trunk/toolkits/basemap/setup.cfg
Modified: trunk/toolkits/basemap/setup.cfg
===================================================================
--- trunk/toolkits/basemap/setup.cfg 2011-02-12 13:56:44 UTC (rev 8977)
+++ trunk/toolkits/basemap/setup.cfg 2011-02-12 13:58:04 UTC (rev 8978)
@@ -6,6 +6,4 @@
# False: do not install
# auto: install only if the package is unavailable. This
# is the default behavior
-pydap = auto
-httplib2 = auto
pyshapelib = auto
This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.
|
|
From: <js...@us...> - 2011-02-12 13:56:51
|
Revision: 8977
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8977&view=rev
Author: jswhit
Date: 2011-02-12 13:56:44 +0000 (Sat, 12 Feb 2011)
Log Message:
-----------
remove more vestiges of netcdf support
Modified Paths:
--------------
trunk/toolkits/basemap/lib/mpl_toolkits/basemap/__init__.py
Removed Paths:
-------------
trunk/toolkits/basemap/lib/mpl_toolkits/basemap/netcdf.py
trunk/toolkits/basemap/lib/mpl_toolkits/basemap/netcdftime.py
Modified: trunk/toolkits/basemap/lib/mpl_toolkits/basemap/__init__.py
===================================================================
--- trunk/toolkits/basemap/lib/mpl_toolkits/basemap/__init__.py 2011-02-12 13:54:34 UTC (rev 8976)
+++ trunk/toolkits/basemap/lib/mpl_toolkits/basemap/__init__.py 2011-02-12 13:56:44 UTC (rev 8977)
@@ -11,12 +11,6 @@
:func:`shiftgrid`: shifts global lat/lon grids east or west.
:func:`addcyclic`: Add cyclic (wraparound) point in longitude.
-
-:func:`num2date`: convert from a numeric time value to a datetime object.
-
-:func:`date2num`: convert from a datetime object to a numeric time value.
-
-:func:`date2index`: compute a time variable index corresponding to a date.
"""
from matplotlib import __version__ as _matplotlib_version
from matplotlib.cbook import is_scalar, dedent
@@ -38,7 +32,7 @@
import numpy as np
import numpy.ma as ma
from shapelib import ShapeFile
-import _geoslib, netcdftime
+import _geoslib
# basemap data files now installed in lib/matplotlib/toolkits/basemap/data
# check to see if environment variable BASEMAPDATA set to a directory,
@@ -3974,160 +3968,6 @@
else:
return corners
-def num2date(times,units='days since 0001-01-01 00:00:00',calendar='proleptic_gregorian'):
- """
- Return datetime objects given numeric time values. The units
- of the numeric time values are described by the ``units`` argument
- and the ``calendar`` keyword. The returned datetime objects represent
- UTC with no time-zone offset, even if the specified
- units contain a time-zone offset.
-
- Default behavior is the same as the matplotlib.dates.num2date function
- but the reference time and calendar can be changed via the
- ``units`` and ``calendar`` keywords.
-
- .. tabularcolumns:: |l|L|
-
- ============== ====================================================
- Arguments Description
- ============== ====================================================
- times numeric time values. Maximum resolution is 1 second.
- ============== ====================================================
-
- .. tabularcolumns:: |l|L|
-
- ============== ====================================================
- Keywords Description
- ============== ====================================================
- units a string of the form '<time units> since
- <reference time>' describing the units and
- origin of the time coordinate.
- <time units> can be days, hours, minutes
- or seconds. <reference time> is the time origin.
- Default is 'days since 0001-01-01 00:00:00'.
- calendar describes the calendar used in the time
- calculations. All the values currently defined in
- the CF metadata convention
- (http://cf-pcmdi.llnl.gov/documents/cf-conventions/)
- are supported.
- Valid calendars ``standard``, ``gregorian``,
- ``proleptic_gregorian``, ``noleap``, ``365_day``,
- ``julian``, ``all_leap``, ``366_day``.
- Default is ``proleptic_gregorian``.
- ============== ====================================================
-
- Returns a datetime instance, or an array of datetime instances.
-
- The datetime instances returned are 'real' python datetime
- objects if the date falls in the Gregorian calendar (i.e.
- calendar=``proleptic_gregorian``, or calendar = ``standard``
- or ``gregorian`` and the date is after 1582-10-15).
- Otherwise, they are 'phony' datetime
- objects which support some but not all the methods of 'real' python
- datetime objects. The datetime instances do not contain
- a time-zone offset, even if the specified units contains one.
- """
- cdftime = netcdftime.utime(units,calendar=calendar)
- return cdftime.num2date(times)
-
-def date2num(dates,units='days since 0001-01-01 00:00:00',calendar='proleptic_gregorian'):
- """
- Return numeric time values given datetime objects. The units
- of the numeric time values are described by the ``units`` argument
- and the ``calendar`` keyword. The datetime objects must
- be in UTC with no time-zone offset. If there is a
- time-zone offset in units, it will be applied to the
- returned numeric values.
-
- Default behavior is the same as the matplotlib.dates.date2num function
- but the reference time and calendar can be changed via the
- ``units`` and ``calendar`` keywords.
-
- .. tabularcolumns:: |l|L|
-
- ============== ====================================================
- Arguments Description
- ============== ====================================================
- dates A datetime object or a sequence of datetime objects.
- The datetime objects should not include a
- time-zone offset.
- ============== ====================================================
-
- .. tabularcolumns:: |l|L|
-
- ============== ====================================================
- Keywords Description
- ============== ====================================================
- units a string of the form '<time units> since
- <reference time>' describing the units and
- origin of the time coordinate.
- <time units> can be days, hours, minutes
- or seconds. <reference time> is the time origin.
- Default is 'days since 0001-01-01 00:00:00'.
- calendar describes the calendar used in the time
- calculations. All the values currently defined in
- the CF metadata convention
- (http://cf-pcmdi.llnl.gov/documents/cf-conventions/)
- are supported.
- Valid calendars ``standard``, ``gregorian``,
- ``proleptic_gregorian``, ``noleap``, ``365_day``,
- ``julian``, ``all_leap``, ``366_day``.
- Default is ``proleptic_gregorian``.
- ============== ====================================================
-
- Returns a numeric time value, or an array of numeric time values.
-
- The maximum resolution of the numeric time values is 1 second.
- """
- cdftime = netcdftime.utime(units,calendar=calendar)
- return cdftime.date2num(dates)
-
-def date2index(dates, nctime, calendar=None,select='exact'):
- """
- Return indices of a netCDF time variable corresponding to the given dates.
-
- .. tabularcolumns:: |l|L|
-
- ============== ====================================================
- Arguments Description
- ============== ====================================================
- dates A datetime object or a sequence of datetime objects.
- The datetime objects should not include a
- time-zone offset.
- nctime A netCDF time variable object. The nctime object
- must have a ``units`` attribute.
- ============== ====================================================
-
- .. tabularcolumns:: |l|L|
-
- ============== ====================================================
- Keywords Description
- ============== ====================================================
- calendar describes the calendar used in the time
- calculations. All the values currently defined in
- the CF metadata convention
- (http://cf-pcmdi.llnl.gov/documents/cf-conventions/)
- are supported.
- Valid calendars ``standard``, ``gregorian``,
- ``proleptic_gregorian``, ``noleap``, ``365_day``,
- ``julian``, ``all_leap``, ``366_day``.
- If ``calendar=None``, will use ``calendar`` attribute
- of ``nctime`` object, and if that attribute does
- not exist calendar is set to ``standard``.
- Default is ``None``.
- select The index selection method. ``exact`` will return the
- indices perfectly matching the dates given.
- ``before`` and ``after`` will return the indices
- corresponding to the dates just before or after
- the given dates if an exact match cannot be found.
- ``nearest`` will return the indices that
- correspond to the closest dates. Default ``exact``.
- ============== ====================================================
-
- Returns an index or a sequence of indices.
- """
- return netcdftime.date2index(dates, nctime, calendar=calendar, select=select)
-
def maskoceans(lonsin,latsin,datain,inlands=False):
"""
mask data (``datain``), defined on a grid with latitudes ``latsin``
Deleted: trunk/toolkits/basemap/lib/mpl_toolkits/basemap/netcdf.py
===================================================================
--- trunk/toolkits/basemap/lib/mpl_toolkits/basemap/netcdf.py 2011-02-12 13:54:34 UTC (rev 8976)
+++ trunk/toolkits/basemap/lib/mpl_toolkits/basemap/netcdf.py 2011-02-12 13:56:44 UTC (rev 8977)
@@ -1,81 +0,0 @@
-from numpy import ma, squeeze
-from pupynere import netcdf_file, _unmaskandscale
-from dap.client import open as open_remote
-from dap.dtypes import ArrayType, GridType, typemap
-
-_typecodes = dict([[_v,_k] for _k,_v in typemap.items()])
-
-class _RemoteFile(object):
- """A NetCDF file reader. API is the same as Scientific.IO.NetCDF."""
-
- def __init__(self, file, maskandscale=False, cache=None,\
- username=None, password=None, verbose=False):
- self._buffer = open_remote(file,cache=cache,\
- username=username,password=password,verbose=verbose)
- self._maskandscale = maskandscale
- self._parse()
-
- def read(self, size=-1):
- """Alias for reading the file buffer."""
- return self._buffer.read(size)
-
- def _parse(self):
- """Initial parsing of the header."""
- # Read header info.
- self._dim_array()
- self._gatt_array()
- self._var_array()
-
- def _dim_array(self):
- """Read a dict with dimensions names and sizes."""
- self.dimensions = {}
- self._dims = []
- for k,d in self._buffer.iteritems():
- if (isinstance(d, ArrayType) or isinstance(d, GridType)) and len(d.shape) == 1 and k == d.dimensions[0]:
- name = k
- length = len(d)
- self.dimensions[name] = length
- self._dims.append(name) # preserve dim order
-
- def _gatt_array(self):
- """Read global attributes."""
- self.__dict__.update(self._buffer.attributes)
-
- def _var_array(self):
- """Read all variables."""
- # Read variables.
- self.variables = {}
- for k,d in self._buffer.iteritems():
- if isinstance(d, GridType) or isinstance(d, ArrayType):
- name = k
- self.variables[name] = _RemoteVariable(d,self._maskandscale)
-
- def close(self):
- # this is a no-op provided for compatibility
- pass
-
-class _RemoteVariable(object):
- def __init__(self, var, maskandscale):
- self._var = var
- self._maskandscale = maskandscale
- self.dtype = var.type
- self.shape = var.shape
- self.dimensions = var.dimensions
- self.__dict__.update(var.attributes)
-
- def __getitem__(self, index):
- datout = squeeze(self._var.__getitem__(index))
- # automatically
- # - remove singleton dimensions
- # - create a masked array using missing_value or _FillValue attribute
- # - apply scale_factor and add_offset to packed integer data
- if self._maskandscale:
- return _unmaskandscale(self,datout)
- else:
- return datout
-
- def __len__(self):
- return self.shape[0]
-
- def typecode(self):
- return _typecodes[self.dtype]
Deleted: trunk/toolkits/basemap/lib/mpl_toolkits/basemap/netcdftime.py
===================================================================
--- trunk/toolkits/basemap/lib/mpl_toolkits/basemap/netcdftime.py 2011-02-12 13:54:34 UTC (rev 8976)
+++ trunk/toolkits/basemap/lib/mpl_toolkits/basemap/netcdftime.py 2011-02-12 13:56:44 UTC (rev 8977)
@@ -1,1050 +0,0 @@
-"""
-Performs conversions of netCDF time coordinate data to/from datetime objects.
-"""
-import math, numpy, re, time
-from datetime import datetime as real_datetime
-
-_units = ['days','hours','minutes','seconds','day','hour','minute','second']
-_calendars = ['standard','gregorian','proleptic_gregorian','noleap','julian','all_leap','365_day','366_day','360_day']
-
-__version__ = '0.7.1'
-
-class datetime:
- """
-Phony datetime object which mimics the python datetime object,
-but allows for dates that don't exist in the proleptic gregorian calendar.
-Doesn't do timedelta operations, doesn't overload + and -.
-
-Has strftime, timetuple and __repr__ methods. The format
-of the string produced by __repr__ is controlled by self.format
-(default %Y-%m-%d %H:%M:%S).
-
-Instance variables are year,month,day,hour,minute,second,dayofwk,dayofyr
-and format.
- """
- def __init__(self,year,month,day,hour=0,minute=0,second=0,dayofwk=-1,dayofyr=1):
- """dayofyr set to 1 by default - otherwise time.strftime will complain"""
- self.year=year
- self.month=month
- self.day=day
- self.hour=hour
- self.minute=minute
- self.dayofwk=dayofwk
- self.dayofyr=dayofyr
- self.second=second
- self.format='%Y-%m-%d %H:%M:%S'
- def strftime(self,format=None):
- if format is None:
- format = self.format
- return _strftime(self,format)
- def timetuple(self):
- return (self.year,self.month,self.day,self.hour,self.minute,self.second,self.dayofwk,self.dayofyr,-1)
- def __repr__(self):
- return self.strftime(self.format)
-
-def JulianDayFromDate(date,calendar='standard'):
-
- """
-
-creates a Julian Day from a 'datetime-like' object. Returns the fractional
-Julian Day (resolution 1 second).
-
-if calendar='standard' or 'gregorian' (default), Julian day follows Julian
-Calendar on and before 1582-10-5, Gregorian calendar after 1582-10-15.
-
-if calendar='proleptic_gregorian', Julian Day follows gregorian calendar.
-
-if calendar='julian', Julian Day follows julian calendar.
-
-Algorithm:
-
-Meeus, Jean (1998) Astronomical Algorithms (2nd Edition). Willmann-Bell,
-Virginia. p. 63
-
- """
-
- # based on redate.py by David Finlayson.
-
- year=date.year; month=date.month; day=date.day
- hour=date.hour; minute=date.minute; second=date.second
- # Convert time to fractions of a day
- day = day + hour/24.0 + minute/1440.0 + second/86400.0
-
- # Start Meeus algorithm (variables are in his notation)
- if (month < 3):
- month = month + 12
- year = year - 1
-
- A = int(year/100)
-
- jd = int(365.25 * (year + 4716)) + int(30.6001 * (month + 1)) + \
- day - 1524.5
-
- # optionally adjust the jd for the switch from
- # the Julian to Gregorian Calendar
- # here assumed to have occurred the day after 1582 October 4
- if calendar in ['standard','gregorian']:
- if jd >= 2299170.5:
- # 1582 October 15 (Gregorian Calendar)
- B = 2 - A + int(A/4)
- elif jd < 2299160.5:
- # 1582 October 5 (Julian Calendar)
- B = 0
- else:
- raise ValueError, 'impossible date (falls in gap between end of Julian calendar and beginning of Gregorian calendar'
- elif calendar == 'proleptic_gregorian':
- B = 2 - A + int(A/4)
- elif calendar == 'julian':
- B = 0
- else:
- raise ValueError, 'unknown calendar, must be one of julian,standard,gregorian,proleptic_gregorian, got %s' % calendar
-
- # adjust for Julian calendar if necessary
- jd = jd + B
-
- return jd
-
-def _NoLeapDayFromDate(date):
-
- """
-
-creates a Julian Day for a calendar with no leap years from a datetime
-instance. Returns the fractional Julian Day (resolution 1 second).
-
- """
-
- year=date.year; month=date.month; day=date.day
- hour=date.hour; minute=date.minute; second=date.second
- # Convert time to fractions of a day
- day = day + hour/24.0 + minute/1440.0 + second/86400.0
-
- # Start Meeus algorithm (variables are in his notation)
- if (month < 3):
- month = month + 12
- year = year - 1
-
- jd = int(365. * (year + 4716)) + int(30.6001 * (month + 1)) + \
- day - 1524.5
-
- return jd
-
-def _AllLeapFromDate(date):
-
- """
-
-creates a Julian Day for a calendar where all years have 366 days from
-a 'datetime-like' object.
-Returns the fractional Julian Day (resolution 1 second).
-
- """
-
- year=date.year; month=date.month; day=date.day
- hour=date.hour; minute=date.minute; second=date.second
- # Convert time to fractions of a day
- day = day + hour/24.0 + minute/1440.0 + second/86400.0
-
- # Start Meeus algorithm (variables are in his notation)
- if (month < 3):
- month = month + 12
- year = year - 1
-
- jd = int(366. * (year + 4716)) + int(30.6001 * (month + 1)) + \
- day - 1524.5
-
- return jd
-
-def _360DayFromDate(date):
-
- """
-
-creates a Julian Day for a calendar where all months have 30 daysfrom
-a 'datetime-like' object.
-Returns the fractional Julian Day (resolution 1 second).
-
- """
-
- year=date.year; month=date.month; day=date.day
- hour=date.hour; minute=date.minute; second=date.second
- # Convert time to fractions of a day
- day = day + hour/24.0 + minute/1440.0 + second/86400.0
-
- jd = int(360. * (year + 4716)) + int(30. * (month - 1)) + day
-
- return jd
-
-def DateFromJulianDay(JD,calendar='standard'):
- """
-
-returns a 'datetime-like' object given Julian Day. Julian Day is a
-fractional day with a resolution of 1 second.
-
-if calendar='standard' or 'gregorian' (default), Julian day follows Julian
-Calendar on and before 1582-10-5, Gregorian calendar after 1582-10-15.
-
-if calendar='proleptic_gregorian', Julian Day follows gregorian calendar.
-
-if calendar='julian', Julian Day follows julian calendar.
-
-The datetime object is a 'real' datetime object if the date falls in
-the Gregorian calendar (i.e. calendar='proleptic_gregorian', or
-calendar = 'standard'/'gregorian' and the date is after 1582-10-15).
-Otherwise, it's a 'phony' datetime object which is actually an instance
-of netcdftime.datetime.
-
-
-Algorithm:
-
-Meeus, Jean (1998) Astronomical Algorithms (2nd Edition). Willmann-Bell,
-Virginia. p. 63
-
- """
-
- # based on redate.py by David Finlayson.
-
- if JD < 0:
- raise ValueError, 'Julian Day must be positive'
-
- dayofwk = int(math.fmod(int(JD + 1.5),7))
- (F, Z) = math.modf(JD + 0.5)
- Z = int(Z)
- if calendar in ['standard','gregorian']:
- if JD < 2299160.5:
- A = Z
- else:
- alpha = int((Z - 1867216.25)/36524.25)
- A = Z + 1 + alpha - int(alpha/4)
-
- elif calendar == 'proleptic_gregorian':
- alpha = int((Z - 1867216.25)/36524.25)
- A = Z + 1 + alpha - int(alpha/4)
- elif calendar == 'julian':
- A = Z
- else:
- raise ValueError, 'unknown calendar, must be one of julian,standard,gregorian,proleptic_gregorian, got %s' % calendar
-
- B = A + 1524
- C = int((B - 122.1)/365.25)
- D = int(365.25 * C)
- E = int((B - D)/30.6001)
-
- # Convert to date
- day = B - D - int(30.6001 * E) + F
- nday = B-D-123
- if nday <= 305:
- dayofyr = nday+60
- else:
- dayofyr = nday-305
- if E < 14:
- month = E - 1
- else:
- month = E - 13
-
- if month > 2:
- year = C - 4716
- else:
- year = C - 4715
-
- # a leap year?
- leap = 0
- if year % 4 == 0:
- leap = 1
- if calendar == 'proleptic_gregorian' or \
- (calendar in ['standard','gregorian'] and JD >= 2299160.5):
- if year % 100 == 0 and year % 400 != 0:
- print year % 100, year % 400
- leap = 0
- if leap and month > 2:
- dayofyr = dayofyr + leap
-
- # Convert fractions of a day to time
- (dfrac, days) = math.modf(day/1.0)
- (hfrac, hours) = math.modf(dfrac * 24.0)
- (mfrac, minutes) = math.modf(hfrac * 60.0)
- seconds = round(mfrac * 60.0) # seconds are rounded
-
- if seconds > 59:
- seconds = 0
- minutes = minutes + 1
- if minutes > 59:
- minutes = 0
- hours = hours + 1
- if hours > 23:
- hours = 0
- days = days + 1
-
- # return a 'real' datetime instance if calendar is gregorian.
- if calendar == 'proleptic_gregorian' or \
- (calendar in ['standard','gregorian'] and JD >= 2299160.5):
- return real_datetime(year,month,int(days),int(hours),int(minutes),int(seconds))
- else:
- # or else, return a 'datetime-like' instance.
- return datetime(year,month,int(days),int(hours),int(minutes),int(seconds),dayofwk,dayofyr)
-
-def _DateFromNoLeapDay(JD):
- """
-
-returns a 'datetime-like' object given Julian Day for a calendar with no leap
-days. Julian Day is a fractional day with a resolution of 1 second.
-
- """
-
- # based on redate.py by David Finlayson.
-
- if JD < 0:
- raise ValueError, 'Julian Day must be positive'
-
- dayofwk = int(math.fmod(int(JD + 1.5),7))
- (F, Z) = math.modf(JD + 0.5)
- Z = int(Z)
- A = Z
- B = A + 1524
- C = int((B - 122.1)/365.)
- D = int(365. * C)
- E = int((B - D)/30.6001)
-
- # Convert to date
- day = B - D - int(30.6001 * E) + F
- nday = B-D-123
- if nday <= 305:
- dayofyr = nday+60
- else:
- dayofyr = nday-305
- if E < 14:
- month = E - 1
- else:
- month = E - 13
-
- if month > 2:
- year = C - 4716
- else:
- year = C - 4715
-
- # Convert fractions of a day to time
- (dfrac, days) = math.modf(day/1.0)
- (hfrac, hours) = math.modf(dfrac * 24.0)
- (mfrac, minutes) = math.modf(hfrac * 60.0)
- seconds = round(mfrac * 60.0) # seconds are rounded
-
- if seconds > 59:
- seconds = 0
- minutes = minutes + 1
- if minutes > 59:
- minutes = 0
- hours = hours + 1
- if hours > 23:
- hours = 0
- days = days + 1
-
- return datetime(year,month,int(days),int(hours),int(minutes),int(seconds), dayofwk, dayofyr)
-
-def _DateFromAllLeap(JD):
- """
-
-returns a 'datetime-like' object given Julian Day for a calendar where all
-years have 366 days.
-Julian Day is a fractional day with a resolution of 1 second.
-
- """
-
- # based on redate.py by David Finlayson.
-
- if JD < 0:
- raise ValueError, 'Julian Day must be positive'
-
- dayofwk = int(math.fmod(int(JD + 1.5),7))
- (F, Z) = math.modf(JD + 0.5)
- Z = int(Z)
- A = Z
- B = A + 1524
- C = int((B - 122.1)/366.)
- D = int(366. * C)
- E = int((B - D)/30.6001)
-
- # Convert to date
- day = B - D - int(30.6001 * E) + F
- nday = B-D-123
- if nday <= 305:
- dayofyr = nday+60
- else:
- dayofyr = nday-305
- if E < 14:
- month = E - 1
- else:
- month = E - 13
- if month > 2:
- dayofyr = dayofyr+1
-
- if month > 2:
- year = C - 4716
- else:
- year = C - 4715
-
- # Convert fractions of a day to time
- (dfrac, days) = math.modf(day/1.0)
- (hfrac, hours) = math.modf(dfrac * 24.0)
- (mfrac, minutes) = math.modf(hfrac * 60.0)
- seconds = round(mfrac * 60.0) # seconds are rounded
-
- if seconds > 59:
- seconds = 0
- minutes = minutes + 1
- if minutes > 59:
- minutes = 0
- hours = hours + 1
- if hours > 23:
- hours = 0
- days = days + 1
-
- return datetime(year,month,int(days),int(hours),int(minutes),int(seconds), dayofwk, dayofyr)
-
-def _DateFrom360Day(JD):
- """
-
-returns a 'datetime-like' object given Julian Day for a calendar where all
-months have 30 days.
-Julian Day is a fractional day with a resolution of 1 second.
-
- """
-
- if JD < 0:
- raise ValueError, 'Julian Day must be positive'
-
- #jd = int(360. * (year + 4716)) + int(30. * (month - 1)) + day
- (F, Z) = math.modf(JD)
- year = int((Z-0.5)/360.) - 4716
- dayofyr = JD - (year+4716)*360
- month = int((dayofyr-0.5)/30)+1
- day = dayofyr - (month-1)*30 + F
-
- # Convert fractions of a day to time
- (dfrac, days) = math.modf(day/1.0)
- (hfrac, hours) = math.modf(dfrac * 24.0)
- (mfrac, minutes) = math.modf(hfrac * 60.0)
- seconds = round(mfrac * 60.0) # seconds are rounded
-
- if seconds > 59:
- seconds = 0
- minutes = minutes + 1
- if minutes > 59:
- minutes = 0
- hours = hours + 1
- if hours > 23:
- hours = 0
- days = days + 1
-
- return datetime(year,month,int(days),int(hours),int(minutes),int(seconds),-1, int(dayofyr))
-
-def _dateparse(timestr):
- """parse a string of the form time-units since yyyy-mm-dd hh:mm:ss
- return a tuple (units, datetimeinstance)"""
- timestr_split = timestr.split()
- units = timestr_split[0].lower()
- if units not in _units:
- raise ValueError,"units must be one of 'seconds', 'minutes', 'hours' or 'days' (or singular version of these), got '%s'" % units
- if timestr_split[1].lower() != 'since':
- raise ValueError,"no 'since' in unit_string"
- # parse the date string.
- n = timestr.find('since')+6
- year,month,day,hour,minute,second,utc_offset = _parse_date(timestr[n:])
- return units, utc_offset, datetime(year, month, day, hour, minute, second)
-
-class utime:
- """
-Performs conversions of netCDF time coordinate
-data to/from datetime objects.
-
-To initialize: C{t = utime(unit_string,calendar='standard')}
-
-where
-
-B{C{unit_string}} is a string of the form
-C{'time-units since <time-origin>'} defining the time units.
-
-Valid time-units are days, hours, minutes and seconds (the singular forms
-are also accepted). An example unit_string would be C{'hours
-since 0001-01-01 00:00:00'}.
-
-The B{C{calendar}} keyword describes the calendar used in the time calculations.
-All the values currently defined in the U{CF metadata convention
-<http://cf-pcmdi.llnl.gov/documents/cf-conventions/1.1/cf-conventions.html#time-coordinate>}
-are accepted. The default is C{'standard'}, which corresponds to the mixed
-Gregorian/Julian calendar used by the C{udunits library}. Valid calendars
-are:
-
-C{'gregorian'} or C{'standard'} (default):
-
-Mixed Gregorian/Julian calendar as defined by udunits.
-
-C{'proleptic_gregorian'}:
-
-A Gregorian calendar extended to dates before 1582-10-15. That is, a year
-is a leap year if either (i) it is divisible by 4 but not by 100 or (ii)
-it is divisible by 400.
-
-C{'noleap'} or C{'365_day'}:
-
-Gregorian calendar without leap years, i.e., all years are 365 days long.
-all_leap or 366_day Gregorian calendar with every year being a leap year,
-i.e., all years are 366 days long.
-
-C{'360_day'}:
-
-All years are 360 days divided into 30 day months.
-
-C{'julian'}:
-
-Proleptic Julian calendar, extended to dates after 1582-10-5. A year is a
-leap year if it is divisible by 4.
-
-The C{L{num2date}} and C{L{date2num}} class methods can used to convert datetime
-instances to/from the specified time units using the specified calendar.
-
-The datetime instances returned by C{num2date} are 'real' python datetime
-objects if the date falls in the Gregorian calendar (i.e.
-C{calendar='proleptic_gregorian', 'standard'} or C{'gregorian'} and
-the date is after 1582-10-15). Otherwise, they are 'phony' datetime
-objects which are actually instances of C{L{netcdftime.datetime}}. This is
-because the python datetime module cannot handle the weird dates in some
-calendars (such as C{'360_day'} and C{'all_leap'}) which don't exist in any real
-world calendar.
-
-
-Example usage:
-
->>> from netcdftime import utime
->>> from datetime import datetime
->>> cdftime = utime('hours since 0001-01-01 00:00:00')
->>> date = datetime.now()
->>> print date
-2006-03-17 16:04:02.561678
->>>
->>> t = cdftime.date2num(date)
->>> print t
-17577328.0672
->>>
->>> date = cdftime.num2date(t)
->>> print date
-2006-03-17 16:04:02
->>>
-
-The resolution of the transformation operation is 1 second.
-
-Warning: Dates between 1582-10-5 and 1582-10-15 do not exist in the
-C{'standard'} or C{'gregorian'} calendars. An exception will be raised if you pass
-a 'datetime-like' object in that range to the C{L{date2num}} class method.
-
-Words of Wisdom from the British MetOffice concerning reference dates:
-
-"udunits implements the mixed Gregorian/Julian calendar system, as
-followed in England, in which dates prior to 1582-10-15 are assumed to use
-the Julian calendar. Other software cannot be relied upon to handle the
-change of calendar in the same way, so for robustness it is recommended
-that the reference date be later than 1582. If earlier dates must be used,
-it should be noted that udunits treats 0 AD as identical to 1 AD."
-
-@ivar origin: datetime instance defining the origin of the netCDF time variable.
-@ivar calendar: the calendar used (as specified by the C{calendar} keyword).
-@ivar unit_string: a string defining the the netCDF time variable.
-@ivar units: the units part of C{unit_string} (i.e. 'days', 'hours', 'seconds').
- """
- def __init__(self,unit_string,calendar='standard'):
- """
-@param unit_string: a string of the form
-C{'time-units since <time-origin>'} defining the time units.
-
-Valid time-units are days, hours, minutes and seconds (the singular forms
-are also accepted). An example unit_string would be C{'hours
-since 0001-01-01 00:00:00'}.
-
-@keyword calendar: describes the calendar used in the time calculations.
-All the values currently defined in the U{CF metadata convention
-<http://cf-pcmdi.llnl.gov/documents/cf-conventions/1.1/cf-conventions.html#time-coordinate>}
-are accepted. The default is C{'standard'}, which corresponds to the mixed
-Gregorian/Julian calendar used by the C{udunits library}. Valid calendars
-are:
- - C{'gregorian'} or C{'standard'} (default):
- Mixed Gregorian/Julian calendar as defined by udunits.
- - C{'proleptic_gregorian'}:
- A Gregorian calendar extended to dates before 1582-10-15. That is, a year
- is a leap year if either (i) it is divisible by 4 but not by 100 or (ii)
- it is divisible by 400.
- - C{'noleap'} or C{'365_day'}:
- Gregorian calendar without leap years, i.e., all years are 365 days long.
- - C{'all_leap'} or C{'366_day'}:
- Gregorian calendar with every year being a leap year, i.e.,
- all years are 366 days long.
- -C{'360_day'}:
- All years are 360 days divided into 30 day months.
- -C{'julian'}:
- Proleptic Julian calendar, extended to dates after 1582-10-5. A year is a
- leap year if it is divisible by 4.
-
-@returns: A class instance which may be used for converting times from netCDF
-units to datetime objects.
- """
- if calendar in _calendars:
- self.calendar = calendar
- else:
- raise ValueError, "calendar must be one of %s, got '%s'" % (str(_calendars),calendar)
- units, tzoffset, self.origin = _dateparse(unit_string)
- self.tzoffset = tzoffset # time zone offset in minutes
- self.units = units
- self.unit_string = unit_string
- if self.calendar in ['noleap','365_day'] and self.origin.month == 2 and self.origin.day == 29:
- raise ValueError, 'cannot specify a leap day as the reference time with the noleap calendar'
- if self.calendar == '360_day' and self.origin.day > 30:
- raise ValueError, 'there are only 30 days in every month with the 360_day calendar'
- if self.calendar in ['noleap','365_day']:
- self._jd0 = _NoLeapDayFromDate(self.origin)
- elif self.calendar in ['all_leap','366_day']:
- self._jd0 = _AllLeapFromDate(self.origin)
- elif self.calendar == '360_day':
- self._jd0 = _360DayFromDate(self.origin)
- else:
- self._jd0 = JulianDayFromDate(self.origin,calendar=self.calendar)
-
- def date2num(self,date):
- """
-Returns C{time_value} in units described by L{unit_string}, using
-the specified L{calendar}, given a 'datetime-like' object.
-
-The datetime object must represent UTC with no time-zone offset.
-If there is a time-zone offset implied by L{unit_string}, it will
-be applied to the returned numeric values.
-
-Resolution is 1 second.
-
-If C{calendar = 'standard'} or C{'gregorian'} (indicating
-that the mixed Julian/Gregorian calendar is to be used), an
-exception will be raised if the 'datetime-like' object describes
-a date between 1582-10-5 and 1582-10-15.
-
-Works for scalars, sequences and numpy arrays.
-Returns a scalar if input is a scalar, else returns a numpy array.
- """
- isscalar = False
- try:
- date[0]
- except:
- isscalar = True
- if not isscalar:
- date = numpy.array(date)
- shape = date.shape
- if self.calendar in ['julian','standard','gregorian','proleptic_gregorian']:
- if isscalar:
- jdelta = JulianDayFromDate(date,self.calendar)-self._jd0
- else:
- jdelta = [JulianDayFromDate(d,self.calendar)-self._jd0 for d in date.flat]
- elif self.calendar in ['noleap','365_day']:
- if date.month == 2 and date.day == 29:
- raise ValueError, 'there is no leap day in the noleap calendar'
- if isscalar:
- jdelta = _NoLeapDayFromDate(date) - self._jd0
- else:
- jdelta = [_NoLeapDayFromDate(d)-self._jd0 for d in date.flat]
- elif self.calendar in ['all_leap','366_day']:
- if isscalar:
- jdelta = _AllLeapFromDate(date) - self._jd0
- else:
- jdelta = [_AllLeapFromDate(d)-self._jd0 for d in date.flat]
- elif self.calendar == '360_day':
- if self.calendar == '360_day' and date.day > 30:
- raise ValueError, 'there are only 30 days in every month with the 360_day calendar'
- if isscalar:
- jdelta = _360DayFromDate(date) - self._jd0
- else:
- jdelta = [_360DayFromDate(d)-self._jd0 for d in date.flat]
- if not isscalar:
- jdelta = numpy.array(jdelta)
- # convert to desired units, add time zone offset.
- if self.units in ['second','seconds']:
- jdelta = jdelta*86400. + self.tzoffset*60.
- elif self.units in ['minute','minutes']:
- jdelta = jdelta*1440. + self.tzoffset
- elif self.units in ['hour','hours']:
- jdelta = jdelta*24. + self.tzoffset/60.
- elif self.units in ['day','days']:
- jdelta = jdelta + self.tzoffset/1440.
- if isscalar:
- return jdelta
- else:
- return numpy.reshape(jdelta,shape)
-
- def num2date(self,time_value):
- """
-Return a 'datetime-like' object given a C{time_value} in units
-described by L{unit_string}, using L{calendar}.
-
-dates are in UTC with no offset, even if L{unit_string} contains
-a time zone offset from UTC.
-
-Resolution is 1 second.
-
-Works for scalars, sequences and numpy arrays.
-Returns a scalar if input is a scalar, else returns a numpy array.
-
-The datetime instances returned by C{num2date} are 'real' python datetime
-objects if the date falls in the Gregorian calendar (i.e.
-C{calendar='proleptic_gregorian'}, or C{calendar = 'standard'/'gregorian'} and
-the date is after 1582-10-15). Otherwise, they are 'phony' datetime
-objects which are actually instances of netcdftime.datetime. This is
-because the python datetime module cannot handle the weird dates in some
-calendars (such as C{'360_day'} and C{'all_leap'}) which
-do not exist in any real world calendar.
- """
- isscalar = False
- try:
- time_value[0]
- except:
- isscalar = True
- if not isscalar:
- time_value = numpy.array(time_value, dtype='d')
- shape = time_value.shape
- # convert to desired units, remove time zone offset.
- if self.units in ['second','seconds']:
- jdelta = time_value/86400. - self.tzoffset/1440.
- elif self.units in ['minute','minutes']:
- jdelta = time_value/1440. - self.tzoffset/1440.
- elif self.units in ['hour','hours']:
- jdelta = time_value/24. - self.tzoffset/1440.
- elif self.units in ['day','days']:
- jdelta = time_value - self.tzoffset/1440.
- jd = self._jd0 + jdelta
- if self.calendar in ['julian','standard','gregorian','proleptic_gregorian']:
- if not isscalar:
- date = [DateFromJulianDay(j,self.calendar) for j in jd.flat]
- else:
- date = DateFromJulianDay(jd,self.calendar)
- elif self.calendar in ['noleap','365_day']:
- if not isscalar:
- date = [_DateFromNoLeapDay(j) for j in jd.flat]
- else:
- date = _DateFromNoLeapDay(jd)
- elif self.calendar in ['all_leap','366_day']:
- if not isscalar:
- date = [_DateFromAllLeap(j) for j in jd.flat]
- else:
- date = _DateFromAllLeap(jd)
- elif self.calendar == '360_day':
- if not isscalar:
- date = [_DateFrom360Day(j) for j in jd.flat]
- else:
- date = _DateFrom360Day(jd)
- if isscalar:
- return date
- else:
- return numpy.reshape(numpy.array(date),shape)
-
-def _parse_date(origin):
- """Parses a date string and returns a tuple
- (year,month,day,hour,minute,second,utc_offset).
- utc_offset is in minutes.
-
- This function parses the 'origin' part of the time unit. It should be
- something like::
-
- 2004-11-03 14:42:27.0 +2:00
-
- Lots of things are optional; just the date is mandatory.
-
- by Roberto De Almeida
-
- excerpted from coards.py - http://cheeseshop.python.org/pypi/coards/
- """
- # yyyy-mm-dd [hh:mm:ss[.s][ [+-]hh[:][mm]]]
- p = re.compile( r'''(?P<year>\d{1,4}) # yyyy
- - #
- (?P<month>\d{1,2}) # mm or m
- - #
- (?P<day>\d{1,2}) # dd or d
- #
- (?: # [optional time and timezone]
- \s #
- (?P<hour>\d{1,2}) # hh or h
- : #
- (?P<min>\d{1,2}) # mm or m
- (?:
- \:
- (?P<sec>\d{1,2}) # ss or s (optional)
- )?
- #
- (?: # [optional decisecond]
- \. # .
- (?P<dsec>\d) # s
- )? #
- (?: # [optional timezone]
- \s #
- (?P<ho>[+-]? # [+ or -]
- \d{1,2}) # hh or h
- :? # [:]
- (?P<mo>\d{2})? # [mm]
- )? #
- )? #
- $ # EOL
- ''', re.VERBOSE)
-
- m = p.match(origin.strip())
- if m:
- c = m.groupdict(0)
- # UTC offset.
- offset = int(c['ho'])*60 + int(c['mo'])
- return int(c['year']),int(c['month']),int(c['day']),int(c['hour']),int(c['min']),int(c['sec']),offset
-
- raise Exception('Invalid date origin: %s' % origin)
-
-# remove the unsupposed "%s" command. But don't
-# do it if there's an even number of %s before the s
-# because those are all escaped. Can't simply
-# remove the s because the result of
-# %sY
-# should be %Y if %s isn't supported, not the
-# 4 digit year.
-_illegal_s = re.compile(r"((^|[^%])(%%)*%s)")
-
-def _findall(text, substr):
- # Also finds overlaps
- sites = []
- i = 0
- while 1:
- j = text.find(substr, i)
- if j == -1:
- break
- sites.append(j)
- i=j+1
- return sites
-
-# Every 28 years the calendar repeats, except through century leap
-# years where it's 6 years. But only if you're using the Gregorian
-# calendar. ;)
-
-def _strftime(dt, fmt):
- if _illegal_s.search(fmt):
- raise TypeError("This strftime implementation does not handle %s")
- # don't use strftime method at all.
- #if dt.year > 1900:
- # return dt.strftime(fmt)
-
- year = dt.year
- # For every non-leap year century, advance by
- # 6 years to get into the 28-year repeat cycle
- delta = 2000 - year
- off = 6*(delta // 100 + delta // 400)
- year = year + off
-
- # Move to around the year 2000
- year = year + ((2000 - year)//28)*28
- timetuple = dt.timetuple()
- s1 = time.strftime(fmt, (year,) + timetuple[1:])
- sites1 = _findall(s1, str(year))
-
- s2 = time.strftime(fmt, (year+28,) + timetuple[1:])
- sites2 = _findall(s2, str(year+28))
-
- sites = []
- for site in sites1:
- if site in sites2:
- sites.append(site)
-
- s = s1
- syear = "%4d" % (dt.year,)
- for site in sites:
- s = s[:site] + syear + s[site+4:]
- return s
-
-def date2num(dates,units,calendar='standard'):
- """
-date2num(dates,units,calendar='standard')
-
-Return numeric time values given datetime objects. The units
-of the numeric time values are described by the L{units} argument
-and the L{calendar} keyword. The datetime objects must
-be in UTC with no time-zone offset. If there is a
-time-zone offset in C{units}, it will be applied to the
-returned numeric values.
-
-Like the matplotlib C{date2num} function, except that it allows
-for different units and calendars. Behaves the same if
-C{units = 'days since 0001-01-01 00:00:00'} and
-C{calendar = 'proleptic_gregorian'}.
-
-@param dates: A datetime object or a sequence of datetime objects.
- The datetime objects should not include a time-zone offset.
-
-@param units: a string of the form C{'B{time units} since B{reference time}}'
- describing the time units. B{C{time units}} can be days, hours, minutes
- or seconds. B{C{reference time}} is the time origin. A valid choice
- would be units=C{'hours since 1800-01-01 00:00:00 -6:00'}.
-
-@param calendar: describes the calendar used in the time calculations.
- All the values currently defined in the U{CF metadata convention
- <http://cf-pcmdi.llnl.gov/documents/cf-conventions/>} are supported.
- Valid calendars C{'standard', 'gregorian', 'proleptic_gregorian'
- 'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'}.
- Default is C{'standard'}, which is a mixed Julian/Gregorian calendar.
-
-@return: a numeric time value, or an array of numeric time values.
-
-The maximum resolution of the numeric time values is 1 second.
- """
- cdftime = utime(units,calendar=calendar)
- return cdftime.date2num(dates)
-
-def num2date(times,units,calendar='standard'):
- """
-num2date(times,units,calendar='standard')
-
-Return datetime objects given numeric time values. The units
-of the numeric time values are described by the C{units} argument
-and the C{calendar} keyword. The returned datetime objects represent
-UTC with no time-zone offset, even if the specified
-C{units} contain a time-zone offset.
-
-Like the matplotlib C{num2date} function, except that it allows
-for different units and calendars. Behaves the same if
-C{units = 'days since 001-01-01 00:00:00'} and
-C{calendar = 'proleptic_gregorian'}.
-
-@param times: numeric time values. Maximum resolution is 1 second.
-
-@param units: a string of the form C{'B{time units} since B{reference time}}'
-describing the time units. B{C{time units}} can be days, hours, minutes
-or seconds. B{C{reference time}} is the time origin. A valid choice
-would be units=C{'hours since 1800-01-01 00:00:00 -6:00'}.
-
-@param calendar: describes the calendar used in the time calculations.
-All the values currently defined in the U{CF metadata convention
-<http://cf-pcmdi.llnl.gov/documents/cf-conventions/>} are supported.
-Valid calendars C{'standard', 'gregorian', 'proleptic_gregorian'
-'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'}.
-Default is C{'standard'}, which is a mixed Julian/Gregorian calendar.
-
-@return: a datetime instance, or an array of datetime instances.
-
-The datetime instances returned are 'real' python datetime
-objects if the date falls in the Gregorian calendar (i.e.
-C{calendar='proleptic_gregorian'}, or C{calendar = 'standard'} or C{'gregorian'}
-and the date is after 1582-10-15). Otherwise, they are 'phony' datetime
-objects which support some but not all the methods of 'real' python
-datetime objects. This is because the python datetime module cannot
-the uses the C{'proleptic_gregorian'} calendar, even before the switch
-occured from the Julian calendar in 1582. The datetime instances
-do not contain a time-zone offset, even if the specified C{units}
-contains one.
- """
- cdftime = utime(units,calendar=calendar)
- return cdftime.num2date(times)
-
-def _check_index(indices, dates, nctime, calendar):
- """Return True if the time indices given correspond to the given dates,
- False otherwise.
-
- Parameters:
-
- indices : sequence of integers
- Positive integers indexing the time variable.
-
- dates : sequence of datetime objects
- Reference dates.
-
- nctime : netCDF Variable object
- NetCDF time object.
-
- calendar : string
- Calendar of nctime.
- """
- if (indices <0).any():
- return False
-
- if (indices >= nctime.shape[0]).any():
- return False
-
-# t = nctime[indices]
-# fancy indexing not available, fall back on this.
- t=[]
- for ind in indices:
- t.append(nctime[ind])
- return numpy.all( num2date(t, nctime.units, calendar) == dates)
-
-
-def date2index(dates, nctime, calendar=None, select='exact'):
- """
- date2index(dates, nctime, calendar=None, select='exact')
-
- Return indices of a netCDF time variable corresponding to the given dates.
-
- @param dates: A datetime object or a sequence of datetime objects.
- The datetime objects should not include a time-zone offset.
-
- @param nctime: A netCDF time variable object. The nctime object must have a
- C{units} attribute. The entries are assumed to be stored in increasing
- order.
-
- @param calendar: Describes the calendar used in the time calculation.
- Valid calendars C{'standard', 'gregorian', 'proleptic_gregorian'
- 'noleap', '365_day', '360_day', 'julian', 'all_leap', '366_day'}.
- Default is C{'standard'}, which is a mixed Julian/Gregorian calendar
- If C{calendar} is None, its value is given by C{nctime.calendar} or
- C{standard} if no such attribute exists.
-
- @param select: C{'exact', 'before', 'after', 'nearest'}
- The index selection method. C{exact} will return the indices perfectly
- matching the dates given. C{before} and C{after} will return the indices
- corresponding to the dates just before or just after the given dates if
- an exact match cannot be found. C{nearest} will return the indices that
- correpond to the closest dates.
- """
- # Setting the calendar.
-
- if calendar == None:
- calendar = getattr(nctime, 'calendar', 'standard')
-
- num = numpy.atleast_1d(date2num(dates, nctime.units, calendar))
-
- # Trying to infer the correct index from the starting time and the stride.
- # This assumes that the times are increasing uniformly.
- t0, t1 = nctime[:2]
- dt = t1 - t0
- index = numpy.array((num-t0)/dt, int)
-
- # Checking that the index really corresponds to the given date.
- # If the times do not correspond, then it means that the times
- # are not increasing uniformly and we try the bisection method.
- if not _check_index(index, dates, nctime, calendar):
-
- # Use the bisection method. Assumes the dates are ordered.
- import bisect
-
- index = numpy.array([bisect.bisect_left(nctime, n) for n in num], int)
-
- # Find the dates for which the match is not perfect.
- # Use list comprehension instead of the simpler `nctime[index]` since
- # not all time objects support numpy integer indexing (eg dap).
- ncnum = numpy.squeeze([nctime[i] for i in index])
- mismatch = numpy.nonzero(ncnum != num)[0]
-
- if select == 'exact':
- if len(mismatch) > 0:
- raise ValueError, 'Some dates not found.'
-
- elif select == 'before':
- index[mismatch] -= 1
-
- elif select == 'after':
- pass
-
- elif select == 'nearest':
- nearest_to_left = num[mismatch] < numpy.array( [nctime[i-1] + nctime[i] for i in index[mismatch]]) / 2.
- index[mismatch] = index[mismatch] - 1 * nearest_to_left
-
- else:
- raise ValueError("%s is not an option for the `select` argument."%select)
-
- # convert numpy scalars or single element arrays to python ints.
- return _toscalar(index)
-
-
-def _toscalar(a):
- if a.shape in [(),(1,)]:
- return a.item()
- else:
- return a
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|
|
From: <js...@us...> - 2011-02-12 13:54:40
|
Revision: 8976
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8976&view=rev
Author: jswhit
Date: 2011-02-12 13:54:34 +0000 (Sat, 12 Feb 2011)
Log Message:
-----------
no longer needed since NetCDFFile has been removed
Removed Paths:
-------------
trunk/toolkits/basemap/lib/dap/
trunk/toolkits/basemap/lib/httplib2/
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|
|
From: <js...@us...> - 2011-02-12 13:53:36
|
Revision: 8975
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8975&view=rev
Author: jswhit
Date: 2011-02-12 13:53:30 +0000 (Sat, 12 Feb 2011)
Log Message:
-----------
remove deprecated NetCDFFile
Modified Paths:
--------------
trunk/toolkits/basemap/Changelog
trunk/toolkits/basemap/lib/mpl_toolkits/basemap/__init__.py
trunk/toolkits/basemap/setup.py
Modified: trunk/toolkits/basemap/Changelog
===================================================================
--- trunk/toolkits/basemap/Changelog 2011-02-12 04:35:09 UTC (rev 8974)
+++ trunk/toolkits/basemap/Changelog 2011-02-12 13:53:30 UTC (rev 8975)
@@ -1,3 +1,7 @@
+version 1.0.2 (not yet released)
+ * added lic_demo.py to examples (line integral convolution,
+ requires scikit.vectorplot).
+ * removed deprecated NetCDFFile.
version 1.0.1 (svn revision 8967)
* regenerated C source with cython 0.14.1.
* added new "allsky" example from Tom Loredo.
Modified: trunk/toolkits/basemap/lib/mpl_toolkits/basemap/__init__.py
===================================================================
--- trunk/toolkits/basemap/lib/mpl_toolkits/basemap/__init__.py 2011-02-12 04:35:09 UTC (rev 8974)
+++ trunk/toolkits/basemap/lib/mpl_toolkits/basemap/__init__.py 2011-02-12 13:53:30 UTC (rev 8975)
@@ -4,10 +4,6 @@
Contains the :class:`Basemap` class (which does most of the
heavy lifting), and the following functions:
-:func:`NetCDFFile`: Read local and remote NetCDF datasets. Deprecated
-as of version 1.0.1 (will be removed in 1.0.2). Use netcdf4-python
-(http://netcdf4-python.googlecode.com) module instead.
-
:func:`interp`: bilinear interpolation between rectilinear grids.
:func:`maskoceans`: mask 'wet' points of an input array.
@@ -54,7 +50,7 @@
else:
basemap_datadir = os.sep.join([os.path.dirname(__file__), 'data'])
-__version__ = '1.0.1'
+__version__ = '1.0.2'
# supported map projections.
_projnames = {'cyl' : 'Cylindrical Equidistant',
@@ -3978,52 +3974,6 @@
else:
return corners
-def NetCDFFile(file, mode='r', maskandscale=True, cache=None, mmap=True,\
- username=None, password=None, verbose=False):
- """NetCDF File reader/writer. API is the same as Scientific.IO.NetCDF.
-
- If ``file`` is a URL that starts with `http`, it is assumed
- to be a remote OPenDAP dataset, and pydap is used
- to retrieve the data. Only the OPenDAP Array and Grid data
- types are recognized. If file does not start with `http`, it
- is assumed to be a local netCDF file and is read
- with scipy.io.netcdf. Both pydap and scipy.io.netcdf are written
- by Roberto De Almeida.
-
- Data will
- automatically be converted to and from masked arrays if the variable
- has either a ``missing_value`` or ``_FillValue`` attribute, and
- some data points are equal to the value specified by that attribute.
- In addition, variables that have the ``scale_factor`` and ``add_offset``
- attribute will automatically be converted to and from short integers.
- To suppress these automatic conversions, set the ``maskandscale``
- keyword to False.
-
- The keywords ``cache``, ``username``, ``password`` and ``verbose`` are only
- valid for remote OPenDAP datasets. ``username`` and ``password`` are used
- to access OPenDAP datasets that require authentication. ``verbose=True``
- will make the pydap client print out the URLs being accessed.
- ``cache`` is a location (a directory) for caching data, so that repeated
- accesses to the same URL avoid the network.
-
- The keyword ``mmap`` is only valid for local netCDF files. When
- ``mmap=True`` (default), the mmap module is used to access the data.
- This may be slow for very large netCDF variables.
- """
- import netcdf
- import warnings
- msg=dedent("""
-
- NetCDFFile will be removed in 1.0.2, please use netcdf4-python
- (http://netcdf4-python.googlecode.com) instead
- """)
- warnings.warn(msg,DeprecationWarning)
- if file.startswith('http'):
- return netcdf._RemoteFile(file,maskandscale=maskandscale,\
- cache=cache,username=username,password=password,verbose=verbose)
- else:
- return netcdf.netcdf_file(file,mode=mode,mmap=mmap,maskandscale=maskandscale)
-
def num2date(times,units='days since 0001-01-01 00:00:00',calendar='proleptic_gregorian'):
"""
Return datetime objects given numeric time values. The units
Modified: trunk/toolkits/basemap/setup.py
===================================================================
--- trunk/toolkits/basemap/setup.py 2011-02-12 04:35:09 UTC (rev 8974)
+++ trunk/toolkits/basemap/setup.py 2011-02-12 13:53:30 UTC (rev 8975)
@@ -241,7 +241,7 @@
setup(
name = "basemap",
- version = "1.0.1",
+ version = "1.0.2",
description = "Plot data on map projections with matplotlib",
long_description = """
An add-on toolkit for matplotlib that lets you plot data
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|
|
From: <js...@us...> - 2011-02-12 04:35:17
|
Revision: 8974
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8974&view=rev
Author: jswhit
Date: 2011-02-12 04:35:09 +0000 (Sat, 12 Feb 2011)
Log Message:
-----------
fix import
Modified Paths:
--------------
trunk/toolkits/basemap/examples/lic_demo.py
Modified: trunk/toolkits/basemap/examples/lic_demo.py
===================================================================
--- trunk/toolkits/basemap/examples/lic_demo.py 2011-02-11 21:04:16 UTC (rev 8973)
+++ trunk/toolkits/basemap/examples/lic_demo.py 2011-02-12 04:35:09 UTC (rev 8974)
@@ -9,7 +9,7 @@
import numpy as np
import matplotlib.pyplot as plt
try:
- from vectorplot import lic_internal
+ from scikits.vectorplot import lic_internal
except ImportError:
raise ImportError('need vectorplot scikit for this example')
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|
|
From: <js...@us...> - 2011-02-11 21:04:22
|
Revision: 8973
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8973&view=rev
Author: jswhit
Date: 2011-02-11 21:04:16 +0000 (Fri, 11 Feb 2011)
Log Message:
-----------
no regridding
Modified Paths:
--------------
trunk/toolkits/basemap/examples/lic_demo.py
Modified: trunk/toolkits/basemap/examples/lic_demo.py
===================================================================
--- trunk/toolkits/basemap/examples/lic_demo.py 2011-02-11 20:52:28 UTC (rev 8972)
+++ trunk/toolkits/basemap/examples/lic_demo.py 2011-02-11 21:04:16 UTC (rev 8973)
@@ -15,27 +15,26 @@
# H*wind data from http://www.aoml.noaa.gov/hrd/data_sub/wind.html
ncfile = NetCDFFile('rita.nc')
-u = ncfile.variables['sfc_u'][0,:,:]
-v = ncfile.variables['sfc_v'][0,:,:]
+udat = ncfile.variables['sfc_u'][0,:,:]
+vdat = ncfile.variables['sfc_v'][0,:,:]
lons1 = ncfile.variables['longitude'][:]
lats1 = ncfile.variables['latitude'][:]
lat0 = lats1[len(lats1)/2]; lon0 = lons1[len(lons1)/2]
-print lat0,lon0
lons, lats = np.meshgrid(lons1,lats1)
ncfile.close()
+
fig = plt.figure(figsize=(8,8))
-m = Basemap(projection='stere',lat_0=lat0,lon_0=lon0,width=1.e6,height=1.e6,resolution='i')
-nxv = 301; nyv = 301; kernellen=41
-udat, vdat, xv, yv = m.transform_vector(u,v,lons1,lats1,nxv,nyv,returnxy=True)
+m = Basemap(projection='cyl',llcrnrlat=lats1[0],llcrnrlon=lons1[0],urcrnrlat=lats1[-1],urcrnrlon=lons1[-1],resolution='i')
+kernellen=31
texture = np.random.rand(udat.shape[0],udat.shape[1]).astype(np.float32)
kernel = np.sin(np.arange(kernellen)*np.pi/kernellen).astype(np.float32)
image = lic_internal.line_integral_convolution(udat.astype(np.float32),\
vdat.astype(np.float32), texture, kernel)
im = m.imshow(image,plt.cm.gist_stern)
m.drawcoastlines()
-m.drawmeridians(np.arange(0,360,2),labels=[0,0,0,1])
-m.drawparallels(np.arange(-30,30,2),labels=[1,0,0,0])
+m.drawmeridians(np.arange(-120,-60,2),labels=[0,0,0,1])
+m.drawparallels(np.arange(0,30,2),labels=[1,0,0,0])
plt.title('Hurricane Rita flow field visualized with Line Integral Convolution',\
fontsize=13)
plt.show()
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|
|
From: <js...@us...> - 2011-02-11 20:52:34
|
Revision: 8972
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8972&view=rev
Author: jswhit
Date: 2011-02-11 20:52:28 +0000 (Fri, 11 Feb 2011)
Log Message:
-----------
use rita data from AOML for lic example.
Modified Paths:
--------------
trunk/toolkits/basemap/MANIFEST.in
trunk/toolkits/basemap/examples/lic_demo.py
Added Paths:
-----------
trunk/toolkits/basemap/examples/rita.nc
Removed Paths:
-------------
trunk/toolkits/basemap/examples/hurrearl.nc
Modified: trunk/toolkits/basemap/MANIFEST.in
===================================================================
--- trunk/toolkits/basemap/MANIFEST.in 2011-02-11 20:29:37 UTC (rev 8971)
+++ trunk/toolkits/basemap/MANIFEST.in 2011-02-11 20:52:28 UTC (rev 8972)
@@ -79,7 +79,7 @@
include examples/nws_precip_conus_20061222.nc
include examples/C02562.orog.nc
include examples/ccsm_popgrid.nc
-include examples/hurrearl.nc
+include examples/rita.nc
include examples/NetCDFFile_tst.py
include examples/maskoceans.py
include examples/README
Deleted: trunk/toolkits/basemap/examples/hurrearl.nc
===================================================================
(Binary files differ)
Modified: trunk/toolkits/basemap/examples/lic_demo.py
===================================================================
--- trunk/toolkits/basemap/examples/lic_demo.py 2011-02-11 20:29:37 UTC (rev 8971)
+++ trunk/toolkits/basemap/examples/lic_demo.py 2011-02-11 20:52:28 UTC (rev 8972)
@@ -13,14 +13,14 @@
except ImportError:
raise ImportError('need vectorplot scikit for this example')
-date = '2010090100'
-lat0=22.6; lon0=-69.2
-
-ncfile = NetCDFFile('hurrearl.nc')
-u = ncfile.variables['u10m'][:,:]
-v = ncfile.variables['v10m'][:,:]
-lons1 = ncfile.variables['lon'][:]
-lats1 = ncfile.variables['lat'][:]
+# H*wind data from http://www.aoml.noaa.gov/hrd/data_sub/wind.html
+ncfile = NetCDFFile('rita.nc')
+u = ncfile.variables['sfc_u'][0,:,:]
+v = ncfile.variables['sfc_v'][0,:,:]
+lons1 = ncfile.variables['longitude'][:]
+lats1 = ncfile.variables['latitude'][:]
+lat0 = lats1[len(lats1)/2]; lon0 = lons1[len(lons1)/2]
+print lat0,lon0
lons, lats = np.meshgrid(lons1,lats1)
ncfile.close()
@@ -36,6 +36,6 @@
m.drawcoastlines()
m.drawmeridians(np.arange(0,360,2),labels=[0,0,0,1])
m.drawparallels(np.arange(-30,30,2),labels=[1,0,0,0])
-plt.title('Hurricane Earl flow field visualized with Line Integral Convolution',\
+plt.title('Hurricane Rita flow field visualized with Line Integral Convolution',\
fontsize=13)
plt.show()
Added: trunk/toolkits/basemap/examples/rita.nc
===================================================================
(Binary files differ)
Property changes on: trunk/toolkits/basemap/examples/rita.nc
___________________________________________________________________
Added: svn:mime-type
+ application/octet-stream
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|
|
From: <js...@us...> - 2011-02-11 20:29:43
|
Revision: 8971
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8971&view=rev
Author: jswhit
Date: 2011-02-11 20:29:37 +0000 (Fri, 11 Feb 2011)
Log Message:
-----------
remove un-needed imports
Modified Paths:
--------------
trunk/toolkits/basemap/examples/lic_demo.py
Modified: trunk/toolkits/basemap/examples/lic_demo.py
===================================================================
--- trunk/toolkits/basemap/examples/lic_demo.py 2011-02-11 19:30:12 UTC (rev 8970)
+++ trunk/toolkits/basemap/examples/lic_demo.py 2011-02-11 20:29:37 UTC (rev 8971)
@@ -5,7 +5,7 @@
from netCDF4 import Dataset as NetCDFFile
except ImportError:
from mpl_toolkits.basemap import NetCDFFile
-from mpl_toolkits.basemap import Basemap, cm, shiftgrid
+from mpl_toolkits.basemap import Basemap
import numpy as np
import matplotlib.pyplot as plt
try:
@@ -26,10 +26,9 @@
fig = plt.figure(figsize=(8,8))
m = Basemap(projection='stere',lat_0=lat0,lon_0=lon0,width=1.e6,height=1.e6,resolution='i')
-nxv = 501; nyv = 501
+nxv = 301; nyv = 301; kernellen=41
udat, vdat, xv, yv = m.transform_vector(u,v,lons1,lats1,nxv,nyv,returnxy=True)
texture = np.random.rand(udat.shape[0],udat.shape[1]).astype(np.float32)
-kernellen=51
kernel = np.sin(np.arange(kernellen)*np.pi/kernellen).astype(np.float32)
image = lic_internal.line_integral_convolution(udat.astype(np.float32),\
vdat.astype(np.float32), texture, kernel)
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|
|
From: <js...@us...> - 2011-02-11 19:30:20
|
Revision: 8970
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8970&view=rev
Author: jswhit
Date: 2011-02-11 19:30:12 +0000 (Fri, 11 Feb 2011)
Log Message:
-----------
add new Line Integral Convolution (LIC) example (requires vectorplot scikit)
Modified Paths:
--------------
trunk/toolkits/basemap/MANIFEST.in
trunk/toolkits/basemap/examples/README
trunk/toolkits/basemap/examples/run_all.py
Added Paths:
-----------
trunk/toolkits/basemap/examples/hurrearl.nc
trunk/toolkits/basemap/examples/lic_demo.py
Modified: trunk/toolkits/basemap/MANIFEST.in
===================================================================
--- trunk/toolkits/basemap/MANIFEST.in 2011-02-10 07:37:05 UTC (rev 8969)
+++ trunk/toolkits/basemap/MANIFEST.in 2011-02-11 19:30:12 UTC (rev 8970)
@@ -75,9 +75,11 @@
include examples/cities.shx
include examples/show_colormaps.py
include examples/plotprecip.py
+include examples/lic_demo.py
include examples/nws_precip_conus_20061222.nc
include examples/C02562.orog.nc
include examples/ccsm_popgrid.nc
+include examples/hurrearl.nc
include examples/NetCDFFile_tst.py
include examples/maskoceans.py
include examples/README
Modified: trunk/toolkits/basemap/examples/README
===================================================================
--- trunk/toolkits/basemap/examples/README 2011-02-10 07:37:05 UTC (rev 8969)
+++ trunk/toolkits/basemap/examples/README 2011-02-11 19:30:12 UTC (rev 8970)
@@ -141,3 +141,6 @@
daynight.py shows how to shade the regions of a map where the sun has set.
ploticos.py demonstrates plotting on unstructured grids.
+
+lic_demo.py shows how to use vectorplot scikit to visualize vector fields with
+Line Integral Convolutions (LIC).
Added: trunk/toolkits/basemap/examples/hurrearl.nc
===================================================================
(Binary files differ)
Property changes on: trunk/toolkits/basemap/examples/hurrearl.nc
___________________________________________________________________
Added: svn:mime-type
+ application/octet-stream
Added: trunk/toolkits/basemap/examples/lic_demo.py
===================================================================
--- trunk/toolkits/basemap/examples/lic_demo.py (rev 0)
+++ trunk/toolkits/basemap/examples/lic_demo.py 2011-02-11 19:30:12 UTC (rev 8970)
@@ -0,0 +1,42 @@
+# example showing how to use Line Integral Convolution to visualize a vector
+# flow field (from Hurricane Earl). Produces something akin to streamlines.
+# Requires vectorplot scikit (http://scikits.appspot.com/vectorplot).
+try:
+ from netCDF4 import Dataset as NetCDFFile
+except ImportError:
+ from mpl_toolkits.basemap import NetCDFFile
+from mpl_toolkits.basemap import Basemap, cm, shiftgrid
+import numpy as np
+import matplotlib.pyplot as plt
+try:
+ from vectorplot import lic_internal
+except ImportError:
+ raise ImportError('need vectorplot scikit for this example')
+
+date = '2010090100'
+lat0=22.6; lon0=-69.2
+
+ncfile = NetCDFFile('hurrearl.nc')
+u = ncfile.variables['u10m'][:,:]
+v = ncfile.variables['v10m'][:,:]
+lons1 = ncfile.variables['lon'][:]
+lats1 = ncfile.variables['lat'][:]
+lons, lats = np.meshgrid(lons1,lats1)
+ncfile.close()
+
+fig = plt.figure(figsize=(8,8))
+m = Basemap(projection='stere',lat_0=lat0,lon_0=lon0,width=1.e6,height=1.e6,resolution='i')
+nxv = 501; nyv = 501
+udat, vdat, xv, yv = m.transform_vector(u,v,lons1,lats1,nxv,nyv,returnxy=True)
+texture = np.random.rand(udat.shape[0],udat.shape[1]).astype(np.float32)
+kernellen=51
+kernel = np.sin(np.arange(kernellen)*np.pi/kernellen).astype(np.float32)
+image = lic_internal.line_integral_convolution(udat.astype(np.float32),\
+ vdat.astype(np.float32), texture, kernel)
+im = m.imshow(image,plt.cm.gist_stern)
+m.drawcoastlines()
+m.drawmeridians(np.arange(0,360,2),labels=[0,0,0,1])
+m.drawparallels(np.arange(-30,30,2),labels=[1,0,0,0])
+plt.title('Hurricane Earl flow field visualized with Line Integral Convolution',\
+ fontsize=13)
+plt.show()
Property changes on: trunk/toolkits/basemap/examples/lic_demo.py
___________________________________________________________________
Added: svn:executable
+ *
Modified: trunk/toolkits/basemap/examples/run_all.py
===================================================================
--- trunk/toolkits/basemap/examples/run_all.py 2011-02-10 07:37:05 UTC (rev 8969)
+++ trunk/toolkits/basemap/examples/run_all.py 2011-02-11 19:30:12 UTC (rev 8970)
@@ -10,6 +10,7 @@
test_files.remove('plotsst.py')
test_files.remove('embedding_map_in_wx.py') # requires wx
test_files.remove('plothighsandlows.py') # requires scipy
+test_files.remove('lic_demo.py')
print test_files
py_path = os.environ.get('PYTHONPATH')
if py_path is None:
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From: <ef...@us...> - 2011-02-10 07:37:11
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Revision: 8969
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8969&view=rev
Author: efiring
Date: 2011-02-10 07:37:05 +0000 (Thu, 10 Feb 2011)
Log Message:
-----------
LogNorm: speed-up by dealing with mask explicitly
Modified Paths:
--------------
trunk/matplotlib/lib/matplotlib/colors.py
Modified: trunk/matplotlib/lib/matplotlib/colors.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/colors.py 2011-02-10 01:21:27 UTC (rev 8968)
+++ trunk/matplotlib/lib/matplotlib/colors.py 2011-02-10 07:37:05 UTC (rev 8969)
@@ -921,9 +921,17 @@
mask=mask)
#result = (ma.log(result)-np.log(vmin))/(np.log(vmax)-np.log(vmin))
# in-place equivalent of above can be much faster
- np.ma.log(result, result)
- result -= np.log(vmin)
- result /= (np.log(vmax) - np.log(vmin))
+ resdat = result.data
+ mask = result.mask
+ if mask is np.ma.nomask:
+ mask = (resdat <= 0)
+ else:
+ mask |= resdat <= 0
+ np.putmask(resdat, mask, 1)
+ np.log(resdat, resdat)
+ resdat -= np.log(vmin)
+ resdat /= (np.log(vmax) - np.log(vmin))
+ result = np.ma.array(resdat, mask=mask, copy=False)
if is_scalar:
result = result[0]
return result
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From: <ef...@us...> - 2011-02-10 01:21:34
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Revision: 8968
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8968&view=rev
Author: efiring
Date: 2011-02-10 01:21:27 +0000 (Thu, 10 Feb 2011)
Log Message:
-----------
bugfix: handle alpha correctly in colormapping with uint8
Modified Paths:
--------------
trunk/matplotlib/lib/matplotlib/colors.py
Modified: trunk/matplotlib/lib/matplotlib/colors.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/colors.py 2011-02-09 17:57:14 UTC (rev 8967)
+++ trunk/matplotlib/lib/matplotlib/colors.py 2011-02-10 01:21:27 UTC (rev 8968)
@@ -547,6 +547,8 @@
if alpha is not None:
alpha = min(alpha, 1.0) # alpha must be between 0 and 1
alpha = max(alpha, 0.0)
+ if bytes:
+ alpha = int(alpha * 255)
if (lut[-1] == 0).all():
lut[:-1, -1] = alpha
# All zeros is taken as a flag for the default bad
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From: <js...@us...> - 2011-02-09 17:57:20
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Revision: 8967
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8967&view=rev
Author: jswhit
Date: 2011-02-09 17:57:14 +0000 (Wed, 09 Feb 2011)
Log Message:
-----------
add missing nc file to MANIFEST
Modified Paths:
--------------
trunk/toolkits/basemap/Changelog
trunk/toolkits/basemap/MANIFEST.in
Modified: trunk/toolkits/basemap/Changelog
===================================================================
--- trunk/toolkits/basemap/Changelog 2011-02-09 07:45:18 UTC (rev 8966)
+++ trunk/toolkits/basemap/Changelog 2011-02-09 17:57:14 UTC (rev 8967)
@@ -1,4 +1,4 @@
-version 1.0.1 (svn revision 8963)
+version 1.0.1 (svn revision 8967)
* regenerated C source with cython 0.14.1.
* added new "allsky" example from Tom Loredo.
* added 'celestial' keyword - if True astronomical convention for
Modified: trunk/toolkits/basemap/MANIFEST.in
===================================================================
--- trunk/toolkits/basemap/MANIFEST.in 2011-02-09 07:45:18 UTC (rev 8966)
+++ trunk/toolkits/basemap/MANIFEST.in 2011-02-09 17:57:14 UTC (rev 8967)
@@ -69,7 +69,6 @@
include examples/garp.py
include examples/setwh.py
include examples/ccsm_popgrid.py
-include examples/ccsm_popgrid.nc
include examples/plot_tissot.py
include examples/cities.dbf
include examples/cities.shp
@@ -77,6 +76,8 @@
include examples/show_colormaps.py
include examples/plotprecip.py
include examples/nws_precip_conus_20061222.nc
+include examples/C02562.orog.nc
+include examples/ccsm_popgrid.nc
include examples/NetCDFFile_tst.py
include examples/maskoceans.py
include examples/README
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From: <ef...@us...> - 2011-02-09 07:45:24
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Revision: 8966
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8966&view=rev
Author: efiring
Date: 2011-02-09 07:45:18 +0000 (Wed, 09 Feb 2011)
Log Message:
-----------
_image.cpp: speed up image_frombyte; patch by C. Gohlke
Non-contiguous arrays, such as those resulting from pan and zoom,
are handled efficiently without additional copying. This
noticeably speeds up zoom and pan on large images.
Modified Paths:
--------------
trunk/matplotlib/src/_image.cpp
Modified: trunk/matplotlib/src/_image.cpp
===================================================================
--- trunk/matplotlib/src/_image.cpp 2011-02-09 04:16:08 UTC (rev 8965)
+++ trunk/matplotlib/src/_image.cpp 2011-02-09 07:45:18 UTC (rev 8966)
@@ -1085,7 +1085,7 @@
Py::Object x = args[0];
int isoutput = Py::Int(args[1]);
- PyArrayObject *A = (PyArrayObject *) PyArray_ContiguousFromObject(x.ptr(), PyArray_UBYTE, 3, 3);
+ PyArrayObject *A = (PyArrayObject *) PyArray_FromObject(x.ptr(), PyArray_UBYTE, 3, 3);
if (A == NULL)
{
throw Py::ValueError("Array must have 3 dimensions");
@@ -1104,35 +1104,86 @@
agg::int8u *arrbuf;
agg::int8u *buffer;
+ agg::int8u *dstbuf;
arrbuf = reinterpret_cast<agg::int8u *>(A->data);
size_t NUMBYTES(imo->colsIn * imo->rowsIn * imo->BPP);
- buffer = new agg::int8u[NUMBYTES];
+ buffer = dstbuf = new agg::int8u[NUMBYTES];
if (buffer == NULL) //todo: also handle allocation throw
{
throw Py::MemoryError("_image_module::frombyte could not allocate memory");
}
- const size_t N = imo->rowsIn * imo->colsIn * imo->BPP;
- size_t i = 0;
- if (A->dimensions[2] == 4)
+ if PyArray_ISCONTIGUOUS(A)
{
- memmove(buffer, arrbuf, N);
+ if (A->dimensions[2] == 4)
+ {
+ memmove(dstbuf, arrbuf, imo->rowsIn * imo->colsIn * 4);
+ }
+ else
+ {
+ size_t i = imo->rowsIn * imo->colsIn;
+ while (i--)
+ {
+ *dstbuf++ = *arrbuf++;
+ *dstbuf++ = *arrbuf++;
+ *dstbuf++ = *arrbuf++;
+ *dstbuf++ = 255;
+ }
+ }
}
+ else if ((A->strides[1] == 4) && (A->strides[2] == 1))
+ {
+ const size_t N = imo->colsIn * 4;
+ const size_t stride = A->strides[0];
+ for (size_t rownum = 0; rownum < imo->rowsIn; rownum++)
+ {
+ memmove(dstbuf, arrbuf, N);
+ arrbuf += stride;
+ dstbuf += N;
+ }
+ }
+ else if ((A->strides[1] == 3) && (A->strides[2] == 1))
+ {
+ const size_t stride = A->strides[0] - imo->colsIn * 3;
+ for (size_t rownum = 0; rownum < imo->rowsIn; rownum++)
+ {
+ for (size_t colnum = 0; colnum < imo->colsIn; colnum++)
+ {
+ *dstbuf++ = *arrbuf++;
+ *dstbuf++ = *arrbuf++;
+ *dstbuf++ = *arrbuf++;
+ *dstbuf++ = 255;
+ }
+ arrbuf += stride;
+ }
+ }
else
{
- while (i < N)
+ PyArrayIterObject *iter;
+ iter = (PyArrayIterObject *)PyArray_IterNew((PyObject *)A);
+ if (A->dimensions[2] == 4)
{
- memmove(buffer, arrbuf, 3);
- buffer += 3;
- arrbuf += 3;
- *buffer++ = 255;
- i += 4;
+ while (iter->index < iter->size) {
+ *dstbuf++ = *((unsigned char *)iter->dataptr);
+ PyArray_ITER_NEXT(iter);
+ }
}
- buffer -= N;
- arrbuf -= imo->rowsIn * imo->colsIn;
+ else
+ {
+ while (iter->index < iter->size) {
+ *dstbuf++ = *((unsigned char *)iter->dataptr);
+ PyArray_ITER_NEXT(iter);
+ *dstbuf++ = *((unsigned char *)iter->dataptr);
+ PyArray_ITER_NEXT(iter);
+ *dstbuf++ = *((unsigned char *)iter->dataptr);
+ PyArray_ITER_NEXT(iter);
+ *dstbuf++ = 255;
+ }
+ }
+ Py_DECREF(iter);
}
if (isoutput)
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