Revision: 5199
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5199&view=rev
Author: jswhit
Date: 2008-05-20 08:01:46 -0700 (Tue, 20 May 2008)
Log Message:
-----------
convert to np/plt (from numpy, pylab)
Modified Paths:
--------------
trunk/toolkits/basemap/lib/mpl_toolkits/basemap/basemap.py
Modified: trunk/toolkits/basemap/lib/mpl_toolkits/basemap/basemap.py
===================================================================
--- trunk/toolkits/basemap/lib/mpl_toolkits/basemap/basemap.py 2008-05-20
12:24:54 UTC (rev 5198)
+++ trunk/toolkits/basemap/lib/mpl_toolkits/basemap/basemap.py 2008-05-20
15:01:46 UTC (rev 5199)
@@ -33,8 +33,8 @@
from matplotlib.transforms import Bbox
import pyproj, sys, os, math, dbflib
from proj import Proj
-import numpy as npy
-from numpy import linspace, squeeze, ma
+import numpy as np
+from numpy import ma
from shapelib import ShapeFile
import _geoslib, pupynere, netcdftime
@@ -504,7 +504,7 @@
self.llcrnrlon = llcrnrlon; self.llcrnrlat = llcrnrlat
self.urcrnrlon = urcrnrlon; self.urcrnrlat = urcrnrlat
# FIXME: won't work for points exactly on equator??
- if npy.abs(lat_0) < 1.e-2: lat_0 = 1.e-2
+ if np.abs(lat_0) < 1.e-2: lat_0 = 1.e-2
projparams['lat_0'] = lat_0
elif projection == 'geos':
if lon_0 is None:
@@ -652,7 +652,7 @@
self.latmin = lats.min()
self.latmax = lats.max()
- # if ax == None, pylab.gca may be used.
+ # if ax == None, pyplot.gca may be used.
self.ax = ax
self.lsmask = None
@@ -685,13 +685,13 @@
for seg in self.coastsegs:
x, y = zip(*seg)
self.coastpolygons.append((x,y))
- x = npy.array(x,npy.float64); y = npy.array(y,npy.float64)
+ x = np.array(x,np.float64); y = np.array(y,np.float64)
xd = (x[1:]-x[0:-1])**2
yd = (y[1:]-y[0:-1])**2
- dist = npy.sqrt(xd+yd)
+ dist = np.sqrt(xd+yd)
split = dist > 5000000.
- if npy.sum(split) and self.projection not in
['merc','cyl','mill']:
- ind =
(npy.compress(split,squeeze(split*npy.indices(xd.shape)))+1).tolist()
+ if np.sum(split) and self.projection not in
['merc','cyl','mill']:
+ ind =
(np.compress(split,np.squeeze(split*np.indices(xd.shape)))+1).tolist()
iprev = 0
ind.append(len(xd))
for i in ind:
@@ -779,9 +779,9 @@
re = self.projparams['R']
# center of stereographic projection restricted to be
# nearest one of 6 points on the sphere (every 90 deg lat/lon).
- lon0 = 90.*(npy.around(lon_0/90.))
- lat0 = 90.*(npy.around(lat_0/90.))
- if npy.abs(int(lat0)) == 90: lon0=0.
+ lon0 = 90.*(np.around(lon_0/90.))
+ lat0 = 90.*(np.around(lat_0/90.))
+ if np.abs(int(lat0)) == 90: lon0=0.
maptran = pyproj.Proj(proj='stere',lon_0=lon0,lat_0=lat0,R=re)
# boundary polygon for orthographic projection
# in stereographic coorindates.
@@ -806,7 +806,7 @@
# numpy array (first column is lons, second is lats).
polystring = bdatfile.read(bytecount)
# binary data is little endian.
- b = npy.array(npy.fromstring(polystring,dtype='<f4'),'f8')
+ b = np.array(np.fromstring(polystring,dtype='<f4'),'f8')
b.shape = (npts,2)
b2 = b.copy()
# if map boundary polygon is a valid one in lat/lon
@@ -833,7 +833,7 @@
lats.insert(0,-90.)
lons.append(lonend)
lats.append(-90.)
- b = npy.empty((len(lons),2),npy.float64)
+ b = np.empty((len(lons),2),np.float64)
b[:,0] = lons; b[:,1] = lats
poly = _geoslib.Polygon(b)
antart = True
@@ -887,16 +887,16 @@
b[:,0], b[:,1] = maptran(b[:,0], b[:,1])
else:
b[:,0], b[:,1] = self(b[:,0], b[:,1])
- goodmask = npy.logical_and(b[:,0]<1.e20,b[:,1]<1.e20)
+ goodmask = np.logical_and(b[:,0]<1.e20,b[:,1]<1.e20)
# if less than two points are valid in
# map proj coords, skip this geometry.
- if npy.sum(goodmask) <= 1: continue
+ if np.sum(goodmask) <= 1: continue
if name != 'gshhs':
# if not a polygon,
# just remove parts of geometry that are undefined
# in this map projection.
- bx = npy.compress(goodmask, b[:,0])
- by = npy.compress(goodmask, b[:,1])
+ bx = np.compress(goodmask, b[:,0])
+ by = np.compress(goodmask, b[:,1])
# for orthographic projection, all points
# outside map projection region are eliminated
# with the above step, so we're done.
@@ -947,16 +947,16 @@
maptran = self
if self.projection in ['ortho','geos']:
# circular region.
- thetas = linspace(0.,2.*npy.pi,2*nx*ny)[:-1]
+ thetas = np.linspace(0.,2.*np.pi,2*nx*ny)[:-1]
if self.projection == 'ortho':
rminor = self.rmajor
rmajor = self.rmajor
else:
rminor = self._height
rmajor = self._width
- x = rmajor*npy.cos(thetas) + rmajor
- y = rminor*npy.sin(thetas) + rminor
- b = npy.empty((len(x),2),npy.float64)
+ x = rmajor*np.cos(thetas) + rmajor
+ y = rminor*np.sin(thetas) + rminor
+ b = np.empty((len(x),2),np.float64)
b[:,0]=x; b[:,1]=y
boundaryxy = _geoslib.Polygon(b)
# compute proj instance for full disk, if necessary.
@@ -981,41 +981,41 @@
# quasi-elliptical region.
lon_0 = self.projparams['lon_0']
# left side
- lats1 = linspace(-89.9,89.9,ny).tolist()
+ lats1 = np.linspace(-89.9,89.9,ny).tolist()
lons1 = len(lats1)*[lon_0-179.9]
# top.
- lons2 = linspace(lon_0-179.9,lon_0+179.9,nx).tolist()
+ lons2 = np.linspace(lon_0-179.9,lon_0+179.9,nx).tolist()
lats2 = len(lons2)*[89.9]
# right side
- lats3 = linspace(89.9,-89.9,ny).tolist()
+ lats3 = np.linspace(89.9,-89.9,ny).tolist()
lons3 = len(lats3)*[lon_0+179.9]
# bottom.
- lons4 = linspace(lon_0+179.9,lon_0-179.9,nx).tolist()
+ lons4 = np.linspace(lon_0+179.9,lon_0-179.9,nx).tolist()
lats4 = len(lons4)*[-89.9]
- lons = npy.array(lons1+lons2+lons3+lons4,npy.float64)
- lats = npy.array(lats1+lats2+lats3+lats4,npy.float64)
+ lons = np.array(lons1+lons2+lons3+lons4,np.float64)
+ lats = np.array(lats1+lats2+lats3+lats4,np.float64)
x, y = maptran(lons,lats)
- b = npy.empty((len(x),2),npy.float64)
+ b = np.empty((len(x),2),np.float64)
b[:,0]=x; b[:,1]=y
boundaryxy = _geoslib.Polygon(b)
else: # all other projections are rectangular.
# left side (x = xmin, ymin <= y <= ymax)
- yy = linspace(self.ymin, self.ymax, ny)[:-1]
+ yy = np.linspace(self.ymin, self.ymax, ny)[:-1]
x = len(yy)*[self.xmin]; y = yy.tolist()
# top (y = ymax, xmin <= x <= xmax)
- xx = npy.linspace(self.xmin, self.xmax, nx)[:-1]
+ xx = np.np.linspace(self.xmin, self.xmax, nx)[:-1]
x = x + xx.tolist()
y = y + len(xx)*[self.ymax]
# right side (x = xmax, ymin <= y <= ymax)
- yy = linspace(self.ymax, self.ymin, ny)[:-1]
+ yy = np.linspace(self.ymax, self.ymin, ny)[:-1]
x = x + len(yy)*[self.xmax]; y = y + yy.tolist()
# bottom (y = ymin, xmin <= x <= xmax)
- xx = linspace(self.xmax, self.xmin, nx)[:-1]
+ xx = np.linspace(self.xmax, self.xmin, nx)[:-1]
x = x + xx.tolist()
y = y + len(xx)*[self.ymin]
- x = npy.array(x,npy.float64)
- y = npy.array(y,npy.float64)
- b = npy.empty((4,2),npy.float64)
+ x = np.array(x,np.float64)
+ y = np.array(y,np.float64)
+ b = np.empty((4,2),np.float64)
b[:,0]=[self.xmin,self.xmin,self.xmax,self.xmax]
b[:,1]=[self.ymin,self.ymax,self.ymax,self.ymin]
boundaryxy = _geoslib.Polygon(b)
@@ -1032,7 +1032,7 @@
lons = [self.llcrnrlon, self.llcrnrlon, self.urcrnrlon,
self.urcrnrlon]
lats = [llcrnrlat, urcrnrlat, urcrnrlat, llcrnrlat]
x, y = self(lons, lats)
- b = npy.empty((len(x),2),npy.float64)
+ b = np.empty((len(x),2),np.float64)
b[:,0]=x; b[:,1]=y
boundaryxy = _geoslib.Polygon(b)
else:
@@ -1042,7 +1042,7 @@
n = 1
lonprev = lons[0]
for lon,lat in zip(lons[1:],lats[1:]):
- if npy.abs(lon-lonprev) > 90.:
+ if np.abs(lon-lonprev) > 90.:
if lonprev < 0:
lon = lon - 360.
else:
@@ -1050,7 +1050,7 @@
lons[n] = lon
lonprev = lon
n = n + 1
- b = npy.empty((len(lons),2),npy.float64)
+ b = np.empty((len(lons),2),np.float64)
b[:,0]=lons; b[:,1]=lats
boundaryll = _geoslib.Polygon(b)
return boundaryll, boundaryxy
@@ -1075,10 +1075,10 @@
# get current axes instance (if none specified).
if ax is None and self.ax is None:
try:
- ax = pylab.gca()
+ ax = plt.gca()
except:
- import pylab
- ax = pylab.gca()
+ import matplotlib.pyplot as plt
+ ax = plt.gca()
elif ax is None and self.ax is not None:
ax = self.ax
limb = None
@@ -1104,19 +1104,19 @@
# quasi-elliptical region.
lon_0 = self.projparams['lon_0']
# left side
- lats1 = linspace(-89.9,89.9,ny).tolist()
+ lats1 = np.linspace(-89.9,89.9,ny).tolist()
lons1 = len(lats1)*[lon_0-179.9]
# top.
- lons2 = linspace(lon_0-179.9,lon_0+179.9,nx).tolist()
+ lons2 = np.linspace(lon_0-179.9,lon_0+179.9,nx).tolist()
lats2 = len(lons2)*[89.9]
# right side
- lats3 = linspace(89.9,-89.9,ny).tolist()
+ lats3 = np.linspace(89.9,-89.9,ny).tolist()
lons3 = len(lats3)*[lon_0+179.9]
# bottom.
- lons4 = linspace(lon_0+179.9,lon_0-179.9,nx).tolist()
+ lons4 = np.linspace(lon_0+179.9,lon_0-179.9,nx).tolist()
lats4 = len(lons4)*[-89.9]
- lons = npy.array(lons1+lons2+lons3+lons4,npy.float64)
- lats = npy.array(lats1+lats2+lats3+lats4,npy.float64)
+ lons = np.array(lons1+lons2+lons3+lons4,np.float64)
+ lats = np.array(lats1+lats2+lats3+lats4,np.float64)
x, y = self(lons,lats)
xy = zip(x,y)
limb = Polygon(xy,edgecolor=color,linewidth=linewidth)
@@ -1185,32 +1185,32 @@
# get current axes instance (if none specified).
if ax is None and self.ax is None:
try:
- ax = pylab.gca()
+ ax = plt.gca()
except:
- import pylab
- ax = pylab.gca()
+ import matplotlib.pyplot as plt
+ ax = plt.gca()
elif ax is None and self.ax is not None:
ax = self.ax
# get axis background color.
axisbgc = ax.get_axis_bgcolor()
np = 0
for x,y in self.coastpolygons:
- xa = npy.array(x,npy.float32)
- ya = npy.array(y,npy.float32)
+ xa = np.array(x,np.float32)
+ ya = np.array(y,np.float32)
# check to see if all four corners of domain in polygon (if so,
# don't draw since it will just fill in the whole map).
delx = 10; dely = 10
if self.projection in ['cyl']:
delx = 0.1
dely = 0.1
- test1 = npy.fabs(xa-self.urcrnrx) < delx
- test2 = npy.fabs(xa-self.llcrnrx) < delx
- test3 = npy.fabs(ya-self.urcrnry) < dely
- test4 = npy.fabs(ya-self.llcrnry) < dely
- hasp1 = npy.sum(test1*test3)
- hasp2 = npy.sum(test2*test3)
- hasp4 = npy.sum(test2*test4)
- hasp3 = npy.sum(test1*test4)
+ test1 = np.fabs(xa-self.urcrnrx) < delx
+ test2 = np.fabs(xa-self.llcrnrx) < delx
+ test3 = np.fabs(ya-self.urcrnry) < dely
+ test4 = np.fabs(ya-self.llcrnry) < dely
+ hasp1 = np.sum(test1*test3)
+ hasp2 = np.sum(test2*test3)
+ hasp4 = np.sum(test2*test4)
+ hasp3 = np.sum(test1*test4)
if not hasp1 or not hasp2 or not hasp3 or not hasp4:
xy = zip(xa.tolist(),ya.tolist())
if self.coastpolygontypes[np] not in [2,4]:
@@ -1245,10 +1245,10 @@
# get current axes instance (if none specified).
if ax is None and self.ax is None:
try:
- ax = pylab.gca()
+ ax = plt.gca()
except:
- import pylab
- ax = pylab.gca()
+ import matplotlib.pyplot as plt
+ ax = plt.gca()
elif ax is None and self.ax is not None:
ax = self.ax
coastlines = LineCollection(self.coastsegs,antialiaseds=(antialiased,))
@@ -1283,10 +1283,10 @@
# get current axes instance (if none specified).
if ax is None and self.ax is None:
try:
- ax = pylab.gca()
+ ax = plt.gca()
except:
- import pylab
- ax = pylab.gca()
+ import matplotlib.pyplot as plt
+ ax = plt.gca()
elif ax is None and self.ax is not None:
ax = self.ax
countries = LineCollection(self.cntrysegs,antialiaseds=(antialiased,))
@@ -1321,10 +1321,10 @@
# get current axes instance (if none specified).
if ax is None and self.ax is None:
try:
- ax = pylab.gca()
+ ax = plt.gca()
except:
- import pylab
- ax = pylab.gca()
+ import matplotlib.pyplot as plt
+ ax = plt.gca()
elif ax is None and self.ax is not None:
ax = self.ax
states = LineCollection(self.statesegs,antialiaseds=(antialiased,))
@@ -1359,10 +1359,10 @@
# get current axes instance (if none specified).
if ax is None and self.ax is None:
try:
- ax = pylab.gca()
+ ax = plt.gca()
except:
- import pylab
- ax = pylab.gca()
+ import matplotlib.pyplot as plt
+ ax = plt.gca()
elif ax is None and self.ax is not None:
ax = self.ax
rivers = LineCollection(self.riversegs,antialiaseds=(antialiased,))
@@ -1484,10 +1484,10 @@
# get current axes instance (if none specified).
if ax is None and self.ax is None:
try:
- ax = pylab.gca()
+ ax = plt.gca()
except:
- import pylab
- ax = pylab.gca()
+ import matplotlib.pyplot as plt
+ ax = plt.gca()
elif ax is None and self.ax is not None:
ax = self.ax
# make LineCollections for each polygon.
@@ -1537,7 +1537,7 @@
ax - axes instance (overrides default axes instance)
additional keyword arguments control text properties for labels (see
- pylab.text documentation)
+ plt.text documentation)
returns a dictionary whose keys are the parallels, and
whose values are tuples containing lists of the Line2D and Text
instances
@@ -1546,10 +1546,10 @@
# get current axes instance (if none specified).
if ax is None and self.ax is None:
try:
- ax = pylab.gca()
+ ax = plt.gca()
except:
- import pylab
- ax = pylab.gca()
+ import matplotlib.pyplot as plt
+ ax = plt.gca()
elif ax is None and self.ax is not None:
ax = self.ax
# don't draw meridians past latmax, always draw parallel at latmax.
@@ -1565,13 +1565,13 @@
xoffset = (self.urcrnrx-self.llcrnrx)/100.
if self.projection in ['merc','cyl','mill','moll','robin','sinu']:
- lons = npy.arange(self.llcrnrlon,self.urcrnrlon+0.01,0.01)
+ lons = np.arange(self.llcrnrlon,self.urcrnrlon+0.01,0.01)
elif self.projection in ['tmerc']:
lon_0 = self.projparams['lon_0']
# tmerc only defined within +/- 90 degrees of lon_0
- lons = npy.arange(lon_0-90,lon_0+90.01,0.01)
+ lons = np.arange(lon_0-90,lon_0+90.01,0.01)
else:
- lons = npy.arange(0,360.01,0.01)
+ lons = np.arange(0,360.01,0.01)
# make sure latmax degree parallel is drawn if projection not merc or
cyl or miller
try:
circlesl = circles.tolist()
@@ -1586,28 +1586,28 @@
ydelta = 0.01*(self.ymax-self.ymin)
linecolls = {}
for circ in circlesl:
- lats = circ*npy.ones(len(lons),npy.float32)
+ lats = circ*np.ones(len(lons),np.float32)
x,y = self(lons,lats)
# remove points outside domain.
# leave a little slop around edges (3*xdelta)
# don't really know why, but this appears to be needed to
# or lines sometimes don't reach edge of plot.
- testx =
npy.logical_and(x>=self.xmin-3*xdelta,x<=self.xmax+3*xdelta)
- x = npy.compress(testx, x)
- y = npy.compress(testx, y)
- testy =
npy.logical_and(y>=self.ymin-3*ydelta,y<=self.ymax+3*ydelta)
- x = npy.compress(testy, x)
- y = npy.compress(testy, y)
+ testx = np.logical_and(x>=self.xmin-3*xdelta,x<=self.xmax+3*xdelta)
+ x = np.compress(testx, x)
+ y = np.compress(testx, y)
+ testy = np.logical_and(y>=self.ymin-3*ydelta,y<=self.ymax+3*ydelta)
+ x = np.compress(testy, x)
+ y = np.compress(testy, y)
lines = []
if len(x) > 1 and len(y) > 1:
# split into separate line segments if necessary.
# (not necessary for mercator or cylindrical or miller).
xd = (x[1:]-x[0:-1])**2
yd = (y[1:]-y[0:-1])**2
- dist = npy.sqrt(xd+yd)
+ dist = np.sqrt(xd+yd)
split = dist > 500000.
- if npy.sum(split) and self.projection not in
['merc','cyl','mill','moll','robin','sinu']:
- ind =
(npy.compress(split,squeeze(split*npy.indices(xd.shape)))+1).tolist()
+ if np.sum(split) and self.projection not in
['merc','cyl','mill','moll','robin','sinu']:
+ ind =
(np.compress(split,np.squeeze(split*np.indices(xd.shape)))+1).tolist()
xl = []
yl = []
iprev = 0
@@ -1650,15 +1650,15 @@
if self.projection in ['cyl','merc','mill','moll','robin','sinu']
and side in ['t','b']: continue
if side in ['l','r']:
nmax = int((self.ymax-self.ymin)/dy+1)
- yy = linspace(self.llcrnry,self.urcrnry,nmax)
+ yy = np.linspace(self.llcrnry,self.urcrnry,nmax)
# mollweide inverse transform undefined at South Pole
if self.projection == 'moll' and yy[0] < 1.e-4:
yy[0] = 1.e-4
if side == 'l':
- lons,lats =
self(self.llcrnrx*npy.ones(yy.shape,npy.float32),yy,inverse=True)
+ lons,lats =
self(self.llcrnrx*np.ones(yy.shape,np.float32),yy,inverse=True)
lons = lons.tolist(); lats = lats.tolist()
else:
- lons,lats =
self(self.urcrnrx*npy.ones(yy.shape,npy.float32),yy,inverse=True)
+ lons,lats =
self(self.urcrnrx*np.ones(yy.shape,np.float32),yy,inverse=True)
lons = lons.tolist(); lats = lats.tolist()
if max(lons) > 1.e20 or max(lats) > 1.e20:
raise ValueError,'inverse transformation undefined -
please adjust the map projection region'
@@ -1666,12 +1666,12 @@
lons = [(lon+360) % 360 for lon in lons]
else:
nmax = int((self.xmax-self.xmin)/dx+1)
- xx = linspace(self.llcrnrx,self.urcrnrx,nmax)
+ xx = np.linspace(self.llcrnrx,self.urcrnrx,nmax)
if side == 'b':
- lons,lats =
self(xx,self.llcrnry*npy.ones(xx.shape,npy.float32),inverse=True)
+ lons,lats =
self(xx,self.llcrnry*np.ones(xx.shape,np.float32),inverse=True)
lons = lons.tolist(); lats = lats.tolist()
else:
- lons,lats =
self(xx,self.urcrnry*npy.ones(xx.shape,npy.float32),inverse=True)
+ lons,lats =
self(xx,self.urcrnry*np.ones(xx.shape,np.float32),inverse=True)
lons = lons.tolist(); lats = lats.tolist()
if max(lons) > 1.e20 or max(lats) > 1.e20:
raise ValueError,'inverse transformation undefined -
please adjust the map projection region'
@@ -1697,7 +1697,7 @@
latlabstr = u'-%s\N{DEGREE SIGN}'%fmt
else:
latlabstr = u'%s\N{DEGREE SIGN}S'%fmt
- latlab = latlabstr%npy.fabs(lat)
+ latlab = latlabstr%np.fabs(lat)
elif lat>0:
if rcParams['text.usetex']:
if labelstyle=='+/-':
@@ -1779,7 +1779,7 @@
ax - axes instance (overrides default axes instance)
additional keyword arguments control text properties for labels (see
- pylab.text documentation)
+ plt.text documentation)
returns a dictionary whose keys are the meridians, and
whose values are tuples containing lists of the Line2D and Text
instances
@@ -1788,10 +1788,10 @@
# get current axes instance (if none specified).
if ax is None and self.ax is None:
try:
- ax = pylab.gca()
+ ax = plt.gca()
except:
- import pylab
- ax = pylab.gca()
+ import matplotlib.pyplot as plt
+ ax = plt.gca()
elif ax is None and self.ax is not None:
ax = self.ax
# don't draw meridians past latmax, always draw parallel at latmax.
@@ -1807,35 +1807,35 @@
xoffset = (self.urcrnrx-self.llcrnrx)/100.
if self.projection not in ['merc','cyl','mill','moll','robin','sinu']:
- lats = npy.arange(-latmax,latmax+0.01,0.01)
+ lats = np.arange(-latmax,latmax+0.01,0.01)
else:
- lats = npy.arange(-90,90.01,0.01)
+ lats = np.arange(-90,90.01,0.01)
xdelta = 0.01*(self.xmax-self.xmin)
ydelta = 0.01*(self.ymax-self.ymin)
linecolls = {}
for merid in meridians:
- lons = merid*npy.ones(len(lats),npy.float32)
+ lons = merid*np.ones(len(lats),np.float32)
x,y = self(lons,lats)
# remove points outside domain.
# leave a little slop around edges (3*xdelta)
# don't really know why, but this appears to be needed to
# or lines sometimes don't reach edge of plot.
- testx =
npy.logical_and(x>=self.xmin-3*xdelta,x<=self.xmax+3*xdelta)
- x = npy.compress(testx, x)
- y = npy.compress(testx, y)
- testy =
npy.logical_and(y>=self.ymin-3*ydelta,y<=self.ymax+3*ydelta)
- x = npy.compress(testy, x)
- y = npy.compress(testy, y)
+ testx = np.logical_and(x>=self.xmin-3*xdelta,x<=self.xmax+3*xdelta)
+ x = np.compress(testx, x)
+ y = np.compress(testx, y)
+ testy = np.logical_and(y>=self.ymin-3*ydelta,y<=self.ymax+3*ydelta)
+ x = np.compress(testy, x)
+ y = np.compress(testy, y)
lines = []
if len(x) > 1 and len(y) > 1:
# split into separate line segments if necessary.
# (not necessary for mercator or cylindrical or miller).
xd = (x[1:]-x[0:-1])**2
yd = (y[1:]-y[0:-1])**2
- dist = npy.sqrt(xd+yd)
+ dist = np.sqrt(xd+yd)
split = dist > 500000.
- if npy.sum(split) and self.projection not in
['merc','cyl','mill','moll','robin','sinu']:
- ind =
(npy.compress(split,squeeze(split*npy.indices(xd.shape)))+1).tolist()
+ if np.sum(split) and self.projection not in
['merc','cyl','mill','moll','robin','sinu']:
+ ind =
(np.compress(split,np.squeeze(split*np.indices(xd.shape)))+1).tolist()
xl = []
yl = []
iprev = 0
@@ -1884,12 +1884,12 @@
if self.projection in ['cyl','merc','mill','sinu','robin','moll']
and side in ['l','r']: continue
if side in ['l','r']:
nmax = int((self.ymax-self.ymin)/dy+1)
- yy = linspace(self.llcrnry,self.urcrnry,nmax)
+ yy = np.linspace(self.llcrnry,self.urcrnry,nmax)
if side == 'l':
- lons,lats =
self(self.llcrnrx*npy.ones(yy.shape,npy.float32),yy,inverse=True)
+ lons,lats =
self(self.llcrnrx*np.ones(yy.shape,np.float32),yy,inverse=True)
lons = lons.tolist(); lats = lats.tolist()
else:
- lons,lats =
self(self.urcrnrx*npy.ones(yy.shape,npy.float32),yy,inverse=True)
+ lons,lats =
self(self.urcrnrx*np.ones(yy.shape,np.float32),yy,inverse=True)
lons = lons.tolist(); lats = lats.tolist()
if max(lons) > 1.e20 or max(lats) > 1.e20:
raise ValueError,'inverse transformation undefined -
please adjust the map projection region'
@@ -1897,12 +1897,12 @@
lons = [(lon+360) % 360 for lon in lons]
else:
nmax = int((self.xmax-self.xmin)/dx+1)
- xx = linspace(self.llcrnrx,self.urcrnrx,nmax)
+ xx = np.linspace(self.llcrnrx,self.urcrnrx,nmax)
if side == 'b':
- lons,lats =
self(xx,self.llcrnry*npy.ones(xx.shape,npy.float32),inverse=True)
+ lons,lats =
self(xx,self.llcrnry*np.ones(xx.shape,np.float32),inverse=True)
lons = lons.tolist(); lats = lats.tolist()
else:
- lons,lats =
self(xx,self.urcrnry*npy.ones(xx.shape,npy.float32),inverse=True)
+ lons,lats =
self(xx,self.urcrnry*np.ones(xx.shape,np.float32),inverse=True)
lons = lons.tolist(); lats = lats.tolist()
if max(lons) > 1.e20 or max(lats) > 1.e20:
raise ValueError,'inverse transformation undefined -
please adjust the map projection region'
@@ -1930,7 +1930,7 @@
lonlabstr = u'-%s\N{DEGREE SIGN}'%fmt
else:
lonlabstr = u'%s\N{DEGREE SIGN}W'%fmt
- lonlab = lonlabstr%npy.fabs(lon2-360)
+ lonlab = lonlabstr%np.fabs(lon2-360)
elif lon2<180 and lon2 != 0:
if rcParams['text.usetex']:
if labelstyle=='+/-':
@@ -2002,7 +2002,7 @@
del_s - points on great circle computed every delta kilometers
(default 100).
Other keyword arguments (**kwargs) control plotting of great circle
line,
- see pylab.plot documentation for details.
+ see plt.plot documentation for details.
Note: cannot handle situations in which the great circle intersects
the edge of the map projection domain, and then re-enters the domain.
@@ -2055,8 +2055,8 @@
raise ValueError, 'lons and lats must be increasing!'
# check that lons in -180,180 for non-cylindrical projections.
if self.projection not in ['cyl','merc','mill']:
- lonsa = npy.array(lons)
- count = npy.sum(lonsa < -180.00001) + npy.sum(lonsa > 180.00001)
+ lonsa = np.array(lons)
+ count = np.sum(lonsa < -180.00001) + np.sum(lonsa > 180.00001)
if count > 1:
raise ValueError,'grid must be shifted so that lons are
monotonically increasing and fit in range -180,+180 (see shiftgrid function)'
# allow for wraparound point to be outside.
@@ -2109,8 +2109,8 @@
raise ValueError, 'lons and lats must be increasing!'
# check that lons in -180,180 for non-cylindrical projections.
if self.projection not in ['cyl','merc','mill']:
- lonsa = npy.array(lons)
- count = npy.sum(lonsa < -180.00001) + npy.sum(lonsa > 180.00001)
+ lonsa = np.array(lons)
+ count = np.sum(lonsa < -180.00001) + np.sum(lonsa > 180.00001)
if count > 1:
raise ValueError,'grid must be shifted so that lons are
monotonically increasing and fit in range -180,+180 (see shiftgrid function)'
# allow for wraparound point to be outside.
@@ -2127,10 +2127,10 @@
vin = vin.filled(1)
masked = True # override kwarg with reality
uvc = uin + 1j*vin
- uvmag = npy.abs(uvc)
+ uvmag = np.abs(uvc)
delta = 0.1 # increment in longitude
dlon = delta*uin/uvmag
- dlat = delta*(vin/uvmag)*npy.cos(latsout*npy.pi/180.0)
+ dlat = delta*(vin/uvmag)*np.cos(latsout*np.pi/180.0)
farnorth = latsout+dlat >= 90.0
somenorth = farnorth.any()
if somenorth:
@@ -2139,10 +2139,10 @@
lon1 = lonsout + dlon
lat1 = latsout + dlat
xn, yn = self(lon1, lat1)
- vecangle = npy.arctan2(yn-y, xn-x)
+ vecangle = np.arctan2(yn-y, xn-x)
if somenorth:
- vecangle[farnorth] += npy.pi
- uvcout = uvmag * npy.exp(1j*vecangle)
+ vecangle[farnorth] += np.pi
+ uvcout = uvmag * np.exp(1j*vecangle)
uout = uvcout.real
vout = uvcout.imag
if masked:
@@ -2184,10 +2184,10 @@
else:
masked = False
uvc = uin + 1j*vin
- uvmag = npy.abs(uvc)
+ uvmag = np.abs(uvc)
delta = 0.1 # increment in longitude
dlon = delta*uin/uvmag
- dlat = delta*(vin/uvmag)*npy.cos(lats*npy.pi/180.0)
+ dlat = delta*(vin/uvmag)*np.cos(lats*np.pi/180.0)
farnorth = lats+dlat >= 90.0
somenorth = farnorth.any()
if somenorth:
@@ -2196,10 +2196,10 @@
lon1 = lons + dlon
lat1 = lats + dlat
xn, yn = self(lon1, lat1)
- vecangle = npy.arctan2(yn-y, xn-x)
+ vecangle = np.arctan2(yn-y, xn-x)
if somenorth:
- vecangle[farnorth] += npy.pi
- uvcout = uvmag * npy.exp(1j*vecangle)
+ vecangle[farnorth] += np.pi
+ uvcout = uvmag * np.exp(1j*vecangle)
uout = uvcout.real
vout = uvcout.imag
if masked:
@@ -2218,10 +2218,10 @@
# get current axes instance (if none specified).
if ax is None and self.ax is None:
try:
- ax = pylab.gca()
+ ax = plt.gca()
except:
- import pylab
- ax = pylab.gca()
+ import matplotlib.pyplot as plt
+ ax = plt.gca()
elif ax is None and self.ax is not None:
ax = self.ax
# update data limits for map domain.
@@ -2250,15 +2250,15 @@
def scatter(self, *args, **kwargs):
"""
- Plot points with markers on the map (see pylab.scatter documentation).
+ Plot points with markers on the map (see plt.scatter documentation).
extra keyword 'ax' can be used to override the default axes instance.
"""
if not kwargs.has_key('ax') and self.ax is None:
try:
- ax = pylab.gca()
+ ax = plt.gca()
except:
- import pylab
- ax = pylab.gca()
+ import matplotlib.pyplot as plt
+ ax = plt.gca()
elif not kwargs.has_key('ax') and self.ax is not None:
ax = self.ax
else:
@@ -2271,7 +2271,7 @@
try:
ret = ax.scatter(*args, **kwargs)
try:
- pylab.draw_if_interactive()
+ plt.draw_if_interactive()
except:
pass
except:
@@ -2284,15 +2284,15 @@
def plot(self, *args, **kwargs):
"""
- Draw lines and/or markers on the map (see pylab.plot documentation).
+ Draw lines and/or markers on the map (see plt.plot documentation).
extra keyword 'ax' can be used to override the default axis instance.
"""
if not kwargs.has_key('ax') and self.ax is None:
try:
- ax = pylab.gca()
+ ax = plt.gca()
except:
- import pylab
- ax = pylab.gca()
+ import matplotlib.pyplot as plt
+ ax = plt.gca()
elif not kwargs.has_key('ax') and self.ax is not None:
ax = self.ax
else:
@@ -2305,7 +2305,7 @@
try:
ret = ax.plot(*args, **kwargs)
try:
- pylab.draw_if_interactive()
+ plt.draw_if_interactive()
except:
pass
except:
@@ -2318,17 +2318,17 @@
def imshow(self, *args, **kwargs):
"""
- Display an image over the map (see pylab.imshow documentation).
+ Display an image over the map (see plt.imshow documentation).
extent and origin keywords set automatically so image will be drawn
over map region.
extra keyword 'ax' can be used to override the default axis instance.
"""
if not kwargs.has_key('ax') and self.ax is None:
try:
- ax = pylab.gca()
+ ax = plt.gca()
except:
- import pylab
- ax = pylab.gca()
+ import matplotlib.pyplot as plt
+ ax = plt.gca()
elif not kwargs.has_key('ax') and self.ax is not None:
ax = self.ax
else:
@@ -2345,16 +2345,16 @@
try:
ret = ax.imshow(*args, **kwargs)
try:
- pylab.draw_if_interactive()
+ plt.draw_if_interactive()
except:
pass
except:
ax.hold(b)
raise
ax.hold(b)
- # reset current active image (only if pylab is imported).
+ # reset current active image (only if pyplot is imported).
try:
- pylab.gci._current = ret
+ plt.gci._current = ret
except:
pass
# set axes limits to fit map region.
@@ -2364,7 +2364,7 @@
def pcolor(self,x,y,data,**kwargs):
"""
Make a pseudo-color plot over the map.
- see pylab.pcolor documentation for definition of **kwargs
+ see plt.pcolor documentation for definition of **kwargs
If x or y are outside projection limb (i.e. they have values > 1.e20)
they will be convert to masked arrays with those values masked.
As a result, those values will not be plotted.
@@ -2372,18 +2372,18 @@
"""
if not kwargs.has_key('ax') and self.ax is None:
try:
- ax = pylab.gca()
+ ax = plt.gca()
except:
- import pylab
- ax = pylab.gca()
+ import matplotlib.pyplot as plt
+ ax = plt.gca()
elif not kwargs.has_key('ax') and self.ax is not None:
ax = self.ax
else:
ax = kwargs.pop('ax')
# make x,y masked arrays
# (masked where data is outside of projection limb)
- x = ma.masked_values(npy.where(x > 1.e20,1.e20,x), 1.e20)
- y = ma.masked_values(npy.where(y > 1.e20,1.e20,y), 1.e20)
+ x = ma.masked_values(np.where(x > 1.e20,1.e20,x), 1.e20)
+ y = ma.masked_values(np.where(y > 1.e20,1.e20,y), 1.e20)
# allow callers to override the hold state by passing hold=True|False
b = ax.ishold()
h = kwargs.pop('hold',None)
@@ -2392,16 +2392,16 @@
try:
ret = ax.pcolor(x,y,data,**kwargs)
try:
- pylab.draw_if_interactive()
+ plt.draw_if_interactive()
except:
pass
except:
ax.hold(b)
raise
ax.hold(b)
- # reset current active image (only if pylab is imported).
+ # reset current active image (only if pyplot is imported).
try:
- pylab.gci._current = ret
+ plt.gci._current = ret
except:
pass
# set axes limits to fit map region.
@@ -2411,15 +2411,15 @@
def pcolormesh(self,x,y,data,**kwargs):
"""
Make a pseudo-color plot over the map.
- see pylab.pcolormesh documentation for definition of **kwargs
+ see plt.pcolormesh documentation for definition of **kwargs
extra keyword 'ax' can be used to override the default axis instance.
"""
if not kwargs.has_key('ax') and self.ax is None:
try:
- ax = pylab.gca()
+ ax = plt.gca()
except:
- import pylab
- ax = pylab.gca()
+ import matplotlib.pyplot as plt
+ ax = plt.gca()
elif not kwargs.has_key('ax') and self.ax is not None:
ax = self.ax
else:
@@ -2432,16 +2432,16 @@
try:
ret = ax.pcolormesh(x,y,data,**kwargs)
try:
- pylab.draw_if_interactive()
+ plt.draw_if_interactive()
except:
pass
except:
ax.hold(b)
raise
ax.hold(b)
- # reset current active image (only if pylab is imported).
+ # reset current active image (only if pyplot is imported).
try:
- pylab.gci._current = ret
+ plt.gci._current = ret
except:
pass
# set axes limits to fit map region.
@@ -2450,15 +2450,15 @@
def contour(self,x,y,data,*args,**kwargs):
"""
- Make a contour plot over the map (see pylab.contour documentation).
+ Make a contour plot over the map (see plt.contour documentation).
extra keyword 'ax' can be used to override the default axis instance.
"""
if not kwargs.has_key('ax') and self.ax is None:
try:
- ax = pylab.gca()
+ ax = plt.gca()
except:
- import pylab
- ax = pylab.gca()
+ import matplotlib.pyplot as plt
+ ax = plt.gca()
elif not kwargs.has_key('ax') and self.ax is not None:
ax = self.ax
else:
@@ -2482,10 +2482,10 @@
function to adjust the data to be consistent with the map
projection
region (see examples/contour_demo.py).""")
# mask for points outside projection limb.
- xymask = npy.logical_or(npy.greater(x,1.e20),npy.greater(y,1.e20))
+ xymask = np.logical_or(np.greater(x,1.e20),np.greater(y,1.e20))
data = ma.asarray(data)
# combine with data mask.
- mask = npy.logical_or(ma.getmaskarray(data),xymask)
+ mask = np.logical_or(ma.getmaskarray(data),xymask)
data = ma.masked_array(data,mask=mask)
# allow callers to override the hold state by passing hold=True|False
b = ax.ishold()
@@ -2495,7 +2495,7 @@
try:
CS = ax.contour(x,y,data,*args,**kwargs)
try:
- pylab.draw_if_interactive()
+ plt.draw_if_interactive()
except:
pass
except:
@@ -2504,29 +2504,29 @@
ax.hold(b)
# set axes limits to fit map region.
self.set_axes_limits(ax=ax)
- # reset current active image (only if pylab is imported).
+ # reset current active image (only if pyplot is imported).
try:
try: # new contour.
- if CS._A is not None: pylab.gci._current = CS
+ if CS._A is not None: plt.gci._current = CS
except: # old contour.
- if CS[1].mappable is not None: pylab.gci._current =
CS[1].mappable
+ if CS[1].mappable is not None: plt.gci._current =
CS[1].mappable
except:
pass
return CS
def contourf(self,x,y,data,*args,**kwargs):
"""
- Make a filled contour plot over the map (see pylab.contourf
documentation).
+ Make a filled contour plot over the map (see plt.contourf
documentation).
If x or y are outside projection limb (i.e. they have values > 1.e20),
the corresponing data elements will be masked.
Extra keyword 'ax' can be used to override the default axis instance.
"""
if not kwargs.has_key('ax') and self.ax is None:
try:
- ax = pylab.gca()
+ ax = plt.gca()
except:
- import pylab
- ax = pylab.gca()
+ import matplotlib.pyplot as plt
+ ax = plt.gca()
elif not kwargs.has_key('ax') and self.ax is not None:
ax = self.ax
else:
@@ -2550,10 +2550,10 @@
function to adjust the data to be consistent with the map
projection
region (see examples/contour_demo.py).""")
# mask for points outside projection limb.
- xymask = npy.logical_or(npy.greater(x,1.e20),npy.greater(y,1.e20))
+ xymask = np.logical_or(np.greater(x,1.e20),np.greater(y,1.e20))
data = ma.asarray(data)
# combine with data mask.
- mask = npy.logical_or(ma.getmaskarray(data),xymask)
+ mask = np.logical_or(ma.getmaskarray(data),xymask)
data = ma.masked_array(data,mask=mask)
# allow callers to override the hold state by passing hold=True|False
b = ax.ishold()
@@ -2563,7 +2563,7 @@
try:
CS = ax.contourf(x,y,data,*args,**kwargs)
try:
- pylab.draw_if_interactive()
+ plt.draw_if_interactive()
except:
pass
except:
@@ -2572,12 +2572,12 @@
ax.hold(b)
# set axes limits to fit map region.
self.set_axes_limits(ax=ax)
- # reset current active image (only if pylab is imported).
+ # reset current active image (only if pyplot is imported).
try:
try: # new contour.
- if CS._A is not None: pylab.gci._current = CS
+ if CS._A is not None: plt.gci._current = CS
except: # old contour.
- if CS[1].mappable is not None: pylab.gci._current =
CS[1].mappable
+ if CS[1].mappable is not None: plt.gci._current =
CS[1].mappable
except:
pass
return CS
@@ -2587,15 +2587,15 @@
Make a vector plot (u, v) with arrows on the map.
Extra arguments (*args and **kwargs) passed to quiver Axes method (see
- pylab.quiver documentation for details).
+ plt.quiver documentation for details).
extra keyword 'ax' can be used to override the default axis instance.
"""
if not kwargs.has_key('ax') and self.ax is None:
try:
- ax = pylab.gca()
+ ax = plt.gca()
except:
- import pylab
- ax = pylab.gca()
+ import matplotlib.pyplot as plt
+ ax = plt.gca()
elif not kwargs.has_key('ax') and self.ax is not None:
ax = self.ax
else:
@@ -2608,7 +2608,7 @@
try:
ret = ax.quiver(x,y,u,v,*args,**kwargs)
try:
- pylab.draw_if_interactive()
+ plt.draw_if_interactive()
except:
pass
except:
@@ -2656,13 +2656,13 @@
extra keyword 'ax' can be used to override the default axis instance.
"""
# look for axes instance (as keyword, an instance variable
- # or from pylab.gca().
+ # or from plt.gca().
if not kwargs.has_key('ax') and self.ax is None:
try:
- ax = pylab.gca()
+ ax = plt.gca()
except:
- import pylab
- ax = pylab.gca()
+ import matplotlib.pyplot as plt
+ ax = plt.gca()
elif not kwargs.has_key('ax') and self.ax is not None:
ax = self.ax
else:
@@ -2677,9 +2677,9 @@
lsmaskf =
open(os.path.join(basemap_datadir,'5minmask.bin'),'rb')
nlons = 4320; nlats = nlons/2
delta = 360./float(nlons)
- lsmask_lons = npy.arange(-180+0.5*delta,180.,delta)
- lsmask_lats = npy.arange(-90.+0.5*delta,90.,delta)
- lsmask =
npy.reshape(npy.fromstring(lsmaskf.read(),npy.uint8),(nlats,nlons))
+ lsmask_lons = np.arange(-180+0.5*delta,180.,delta)
+ lsmask_lats = np.arange(-90.+0.5*delta,90.,delta)
+ lsmask =
np.reshape(np.fromstring(lsmaskf.read(),np.uint8),(nlats,nlons))
lsmaskf.close()
# instance variable lsmask is set on first invocation,
# it contains the land-sea mask interpolated to the native
@@ -2708,28 +2708,28 @@
lons, lats = self(x, y, inverse=True)
lon_0 = self.projparams['lon_0']
lats = lats[:,nx/2]
- lons1 = (lon_0+180.)*npy.ones(lons.shape[0],npy.float64)
- lons2 = (lon_0-180.)*npy.ones(lons.shape[0],npy.float64)
+ lons1 = (lon_0+180.)*np.ones(lons.shape[0],np.float64)
+ lons2 = (lon_0-180.)*np.ones(lons.shape[0],np.float64)
xmax,ytmp = self(lons1,lats)
xmin,ytmp = self(lons2,lats)
for j in range(lats.shape[0]):
xx = x[j,:]
- mask[j,:]=npy.where(npy.logical_or(xx<xmin[j],xx>xmax[j]),\
+ mask[j,:]=np.where(np.logical_or(xx<xmin[j],xx>xmax[j]),\
255,mask[j,:])
self.lsmask = mask
# optionally, set lakes to ocean color.
if lakes:
- mask = npy.where(self.lsmask==2,0,self.lsmask)
+ mask = np.where(self.lsmask==2,0,self.lsmask)
else:
mask = self.lsmask
ny, nx = mask.shape
- rgba = npy.ones((ny,nx,4),npy.uint8)
- rgba_land = npy.array(rgba_land,npy.uint8)
- rgba_ocean = npy.array(rgba_ocean,npy.uint8)
+ rgba = np.ones((ny,nx,4),np.uint8)
+ rgba_land = np.array(rgba_land,np.uint8)
+ rgba_ocean = np.array(rgba_ocean,np.uint8)
for k in range(4):
- rgba[:,:,k] = npy.where(mask,rgba_land[k],rgba_ocean[k])
+ rgba[:,:,k] = np.where(mask,rgba_land[k],rgba_ocean[k])
# make points outside projection limb transparent.
- rgba[:,:,3] = npy.where(mask==255,0,rgba[:,:,3])
+ rgba[:,:,3] = np.where(mask==255,0,rgba[:,:,3])
# plot mask as rgba image.
im = self.imshow(rgba,interpolation='nearest',ax=ax,**kwargs)
return im
@@ -2760,10 +2760,10 @@
from matplotlib.image import pil_to_array
if not kwargs.has_key('ax') and self.ax is None:
try:
- ax = pylab.gca()
+ ax = plt.gca()
except:
- import pylab
- ax = pylab.gca()
+ import matplotlib.pyplot as plt
+ ax = plt.gca()
elif not kwargs.has_key('ax') and self.ax is not None:
ax = self.ax
else:
@@ -2786,12 +2786,12 @@
pilImage = Image.open(self._bm_file)
self._bm_rgba = pil_to_array(pilImage)
# convert to normalized floats.
- self._bm_rgba = self._bm_rgba.astype(npy.float32)/255.
+ self._bm_rgba = self._bm_rgba.astype(np.float32)/255.
# define lat/lon grid that image spans.
nlons = self._bm_rgba.shape[1]; nlats = self._bm_rgba.shape[0]
delta = 360./float(nlons)
- self._bm_lons = npy.arange(-180.+0.5*delta,180.,delta)
- self._bm_lats = npy.arange(-90.+0.5*delta,90.,delta)
+ self._bm_lons = np.arange(-180.+0.5*delta,180.,delta)
+ self._bm_lats = np.arange(-90.+0.5*delta,90.,delta)
if self.projection != 'cyl':
if newfile or not hasattr(self,'_bm_rgba_warped'):
@@ -2799,10 +2799,10 @@
# projection grid.
# nx and ny chosen to have roughly the
# same horizontal res as original image.
- dx = 2.*npy.pi*self.rmajor/float(nlons)
+ dx = 2.*np.pi*self.rmajor/float(nlons)
nx = int((self.xmax-self.xmin)/dx)+1
ny = int((self.ymax-self.ymin)/dx)+1
- self._bm_rgba_warped = npy.zeros((ny,nx,4),npy.float64)
+ self._bm_rgba_warped = np.zeros((ny,nx,4),np.float64)
# interpolate rgba values from geographic coords (proj='cyl')
# to map projection coords.
# if masked=True, values outside of
@@ -2814,8 +2814,8 @@
# for ortho,geos mask pixels outside projection limb.
if self.projection in ['geos','ortho']:
lonsr,latsr = self(x,y,inverse=True)
- mask = ma.zeros((nx,ny,4),npy.int8)
- mask[:,:,0] = npy.logical_or(lonsr>1.e20,latsr>1.e30)
+ mask = ma.zeros((nx,ny,4),np.int8)
+ mask[:,:,0] = np.logical_or(lonsr>1.e20,latsr>1.e30)
for k in range(1,4):
mask[:,:,k] = mask[:,:,0]
self._bm_rgba_warped = \
@@ -2862,10 +2862,10 @@
# get current axes instance (if none specified).
if ax is None and self.ax is None:
try:
- ax = pylab.gca()
+ ax = plt.gca()
except:
- import pylab
- ax = pylab.gca()
+ import matplotlib.pyplot as plt
+ ax = plt.gca()
elif ax is None and self.ax is not None:
ax = self.ax
# not valid for cylindrical projection
@@ -3091,8 +3091,8 @@
else:
# irregular (but still rectilinear) input grid.
xoutflat = xout.flatten(); youtflat = yout.flatten()
- ix = (npy.searchsorted(xin,xoutflat)-1).tolist()
- iy = (npy.searchsorted(yin,youtflat)-1).tolist()
+ ix = (np.searchsorted(xin,xoutflat)-1).tolist()
+ iy = (np.searchsorted(yin,youtflat)-1).tolist()
xoutflat = xoutflat.tolist(); xin = xin.tolist()
youtflat = youtflat.tolist(); yin = yin.tolist()
xcoords = []; ycoords = []
@@ -3110,33 +3110,33 @@
ycoords.append(len(yin)) # outside range on upper end
else:
ycoords.append(float(j)+(youtflat[m]-yin[j])/(yin[j+1]-yin[j]))
- xcoords = npy.reshape(xcoords,xout.shape)
- ycoords = npy.reshape(ycoords,yout.shape)
+ xcoords = np.reshape(xcoords,xout.shape)
+ ycoords = np.reshape(ycoords,yout.shape)
# data outside range xin,yin will be clipped to
# values on boundary.
if masked:
- xmask =
npy.logical_or(npy.less(xcoords,0),npy.greater(xcoords,len(xin)-1))
- ymask =
npy.logical_or(npy.less(ycoords,0),npy.greater(ycoords,len(yin)-1))
- xymask = npy.logical_or(xmask,ymask)
- xcoords = npy.clip(xcoords,0,len(xin)-1)
- ycoords = npy.clip(ycoords,0,len(yin)-1)
+ xmask =
np.logical_or(np.less(xcoords,0),np.greater(xcoords,len(xin)-1))
+ ymask =
np.logical_or(np.less(ycoords,0),np.greater(ycoords,len(yin)-1))
+ xymask = np.logical_or(xmask,ymask)
+ xcoords = np.clip(xcoords,0,len(xin)-1)
+ ycoords = np.clip(ycoords,0,len(yin)-1)
# interpolate to output grid using bilinear interpolation.
if order == 1:
- xi = xcoords.astype(npy.int32)
- yi = ycoords.astype(npy.int32)
+ xi = xcoords.astype(np.int32)
+ yi = ycoords.astype(np.int32)
xip1 = xi+1
yip1 = yi+1
- xip1 = npy.clip(xip1,0,len(xin)-1)
- yip1 = npy.clip(yip1,0,len(yin)-1)
- delx = xcoords-xi.astype(npy.float32)
- dely = ycoords-yi.astype(npy.float32)
+ xip1 = np.clip(xip1,0,len(xin)-1)
+ yip1 = np.clip(yip1,0,len(yin)-1)
+ delx = xcoords-xi.astype(np.float32)
+ dely = ycoords-yi.astype(np.float32)
dataout = (1.-delx)*(1.-dely)*datain[yi,xi] + \
delx*dely*datain[yip1,xip1] + \
(1.-delx)*dely*datain[yip1,xi] + \
delx*(1.-dely)*datain[yi,xip1]
elif order == 0:
- xcoordsi = npy.around(xcoords).astype(npy.int32)
- ycoordsi = npy.around(ycoords).astype(npy.int32)
+ xcoordsi = np.around(xcoords).astype(np.int32)
+ ycoordsi = np.around(ycoords).astype(np.int32)
dataout = datain[ycoordsi,xcoordsi]
else:
raise ValueError,'order keyword must be 0 or 1'
@@ -3145,7 +3145,7 @@
newmask = ma.mask_or(ma.getmask(dataout), xymask)
dataout = ma.masked_array(dataout,mask=newmask)
elif masked and is_scalar(masked):
- dataout = npy.where(xymask,masked,dataout)
+ dataout = np.where(xymask,masked,dataout)
return dataout
def shiftgrid(lon0,datain,lonsin,start=True):
@@ -3163,13 +3163,13 @@
returns dataout,lonsout (data and longitudes on shifted grid).
"""
- if npy.fabs(lonsin[-1]-lonsin[0]-360.) > 1.e-4:
+ if np.fabs(lonsin[-1]-lonsin[0]-360.) > 1.e-4:
raise ValueError, 'cyclic point not included'
if lon0 < lonsin[0] or lon0 > lonsin[-1]:
raise ValueError, 'lon0 outside of range of lonsin'
- i0 = npy.argmin(npy.fabs(lonsin-lon0))
- dataout = npy.zeros(datain.shape,datain.dtype)
- lonsout = npy.zeros(lonsin.shape,lonsin.dtype)
+ i0 = np.argmin(np.fabs(lonsin-lon0))
+ dataout = np.zeros(datain.shape,datain.dtype)
+ lonsout = np.zeros(lonsin.shape,lonsin.dtype)
if start:
lonsout[0:len(lonsin)-i0] = lonsin[i0:]
else:
@@ -3193,13 +3193,13 @@
if hasattr(arrin,'mask'):
arrout = ma.zeros((nlats,nlons+1),arrin.dtype)
else:
- arrout = npy.zeros((nlats,nlons+1),arrin.dtype)
+ arrout = np.zeros((nlats,nlons+1),arrin.dtype)
arrout[:,0:nlons] = arrin[:,:]
arrout[:,nlons] = arrin[:,0]
if hasattr(lonsin,'mask'):
lonsout = ma.zeros(nlons+1,lonsin.dtype)
else:
- lonsout = npy.zeros(nlons+1,lonsin.dtype)
+ lonsout = np.zeros(nlons+1,lonsin.dtype)
lonsout[0:nlons] = lonsin[:]
lonsout[nlons] = lonsin[-1] + lonsin[1]-lonsin[0]
return arrout,lonsout
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