def test_interp (self):
input = self.var.get()
# Interpolation along X axis
for slope in (float('nan'),0,1,2):
output = interpolate(self.var, inaxis=self.x, outaxis=self.x2, interp_type='linear', d_above=slope, d_below=slope).transpose(YAxis,XAxis).get()
if np.isnan(slope):
self.assertTrue(np.all(np.isnan(output[:,0])), output)
self.assertTrue(np.all(np.isnan(output[:,-1])), output)
self.assertTrue(np.all(np.isfinite(output[:,1:-1])), output)
else:
self.assertTrue(np.all(np.isfinite(output)), output)
# Check extrapolation (out of range by half a coordinate unit)
self.assertTrue(np.all(output[:,0] == input[:,0] - 0.5*slope), output)
self.assertTrue(np.all(output[:,-1] == input[:,-1] + 0.5*slope), output)
# Interpolation along Y axis
for slope in (float('nan'),0,1,2):
output = interpolate(self.var, inaxis=self.y, outaxis=self.y2, interp_type='linear', d_above=slope, d_below=slope).transpose(YAxis,XAxis).get()
if np.isnan(slope):
self.assertTrue(np.all(np.isnan(output[0,:])), output)
self.assertTrue(np.all(np.isnan(output[-1,:])), output)
self.assertTrue(np.all(np.isfinite(output[1:-1,:])), output)
else:
self.assertTrue(np.all(np.isfinite(output)), output)
# Check extrapolation (out of range by half a coordinate unit)
self.assertTrue(np.all(output[0,:] == input[0,:] - 0.5*slope), output)
self.assertTrue(np.all(output[-1,:] == input[-1,:] + 0.5*slope), output)
def interp2theta(var, theta, values, interp='linear', **kwargs):
from pygeode.interp import interpolate, sorted
# inaxis axis
iaxis = var.whichaxis(ZAxis)
# # sort theta (must be monotonically increasing)
# var = sorted(var, iaxis, reverse=False)
# theta = sorted(theta, iaxis, reverse=False)
# prepare input
inaxis = var.axes[iaxis]
assert theta.hasaxis(
inaxis), 'vertical axis of var and theta are incompatible'
# create new axis
outaxis = Isentrope(values=values, **kwargs)
# interpolate to isentropic levels
ivar = interpolate(var, inaxis, outaxis, inx=theta, interp_type=interp)
# return variable interpolated to isentropic level(s)
return ivar
## Dynamical Tropopause
# axis for PV iso-surfaces (dynamical tropopause)
class DynamicalTP(ZAxis):
name = 'PViso' # default name
units = '(K m^2)/(s kg)'
plotatts = ZAxis.plotatts.copy()
plotatts['formatstr'] = '%3.1f' # one digit behind decimal
# Formatting attributes for axis labels and ticks (see formatter method for application)
plotatts[
'plottitle'] = 'Dynamical TP' # name displayed in plots (axis label)
plotatts[
'plotunits'] = 'PVU' # displayed units (after offset and scalefactor have been applied)
plotatts[
'scalefactor'] = 1e6 # conversion factor; assumed units are meters
def verticalVelocity(w, z, interpType='linear', **kwargs):
from pygeode.axis import Height, ZAxis
from pygeode.interp import interpolate
from warnings import warn
# figure out axes
oldZ = findZAxis(w)
assert isinstance(z, ZAxis), 'interpolation only works along vertical axis'
if (not isinstance(z, Height)) or (not isinstance(oldZ, Height)):
warn(
'The current implementation of verticalVelocity is designed for interpolation between Height coordinates only.'
)
assert oldZ.__class__ == z.__class__, 'old and new axes are not of the same type (class)'
# interpolate values
vv = interpolate(w, oldZ, z, interp_type=interpType)
# attributes (defaults)
vv.atts['name'] = 'w'
vv.atts['units'] = 'm/s'
vv.atts['long_name'] = 'vertical velocity on full model levels'
vv.atts['standard_name'] = 'vertical velocity'
vv.atts['interpolation'] = interpType
# plot attributes (defaults)
vv.plotatts = variablePlotatts['w']
# apply user-defined attributes (from kwargs; override defaults)
vv.atts.update(kwargs)
# assign short name
vv.name = vv.atts['name']
vv.units = vv.atts['units']
return vv
def interp2theta(var, theta, values, interp='linear', **kwargs):
from pygeode.interp import interpolate, sorted
# inaxis axis
iaxis = var.whichaxis(ZAxis)
# # sort theta (must be monotonically increasing)
# var = sorted(var, iaxis, reverse=False)
# theta = sorted(theta, iaxis, reverse=False)
# prepare input
inaxis = var.axes[iaxis]
assert theta.hasaxis(inaxis), 'vertical axis of var and theta are incompatible'
# create new axis
outaxis = Isentrope(values=values, **kwargs)
# interpolate to isentropic levels
ivar = interpolate(var, inaxis, outaxis, inx=theta, interp_type=interp)
# return variable interpolated to isentropic level(s)
return ivar
## Dynamical Tropopause
# axis for PV iso-surfaces (dynamical tropopause)
class DynamicalTP(ZAxis):
name = 'PViso' # default name
units = '(K m^2)/(s kg)'
plotatts = ZAxis.plotatts.copy()
plotatts['formatstr'] = '%3.1f' # one digit behind decimal
# Formatting attributes for axis labels and ticks (see formatter method for application)
plotatts['plottitle'] = 'Dynamical TP' # name displayed in plots (axis label)
plotatts['plotunits'] = 'PVU' # displayed units (after offset and scalefactor have been applied)
plotatts['scalefactor'] = 1e6 # conversion factor; assumed units are meters
def verticalVelocity(w, z, interpType="linear", **kwargs):
from pygeode.axis import Height, ZAxis
from pygeode.interp import interpolate
from warnings import warn
# figure out axes
oldZ = findZAxis(w)
assert isinstance(z, ZAxis), "interpolation only works along vertical axis"
if (not isinstance(z, Height)) or (not isinstance(oldZ, Height)):
warn(
"The current implementation of verticalVelocity is designed for interpolation between Height coordinates only."
)
assert oldZ.__class__ == z.__class__, "old and new axes are not of the same type (class)"
# interpolate values
vv = interpolate(w, oldZ, z, interp_type=interpType)
# attributes (defaults)
vv.atts["name"] = "w"
vv.atts["units"] = "m/s"
vv.atts["long_name"] = "vertical velocity on full model levels"
vv.atts["standard_name"] = "vertical velocity"
vv.atts["interpolation"] = interpType
# plot attributes (defaults)
vv.plotatts = variablePlotatts["w"]
# apply user-defined attributes (from kwargs; override defaults)
vv.atts.update(kwargs)
# assign short name
vv.name = vv.atts["name"]
vv.units = vv.atts["units"]
return vv
def verticalVelocity(w, z, interpType='linear', **kwargs):
from pygeode.axis import Height, ZAxis
from pygeode.interp import interpolate
from warnings import warn
# figure out axes
oldZ = findZAxis(w)
assert isinstance(z,ZAxis), 'interpolation only works along vertical axis'
if (not isinstance(z,Height)) or (not isinstance(oldZ,Height)):
warn('The current implementation of verticalVelocity is designed for interpolation between Height coordinates only.')
assert oldZ.__class__ == z.__class__, 'old and new axes are not of the same type (class)'
# interpolate values
vv = interpolate(w, oldZ, z, interp_type=interpType)
# attributes (defaults)
vv.atts['name'] = 'w'
vv.atts['units'] = 'm/s'
vv.atts['long_name'] = 'vertical velocity on full model levels'
vv.atts['standard_name'] = 'vertical velocity'
vv.atts['interpolation'] = interpType
# plot attributes (defaults)
vv.plotatts = variablePlotatts['w']
# apply user-defined attributes (from kwargs; override defaults)
vv.atts.update(kwargs)
# assign short name
vv.name = vv.atts['name']
vv.units = vv.atts['units']
return vv
def test_nointerp (self):
input = self.var.get()
output = interpolate(self.var, inaxis=self.x, outaxis=self.x, interp_type='linear').transpose(YAxis,XAxis).get()
# GSL interoplates over nans, so we need to undo this for a direct comparison
masked_output = np.array(output)
masked_output[1,1] = float('nan')
self.assertTrue(alleq(masked_output,input), output)
self.assertEqual(output[1,1], 5.) # check how GSL interoplates over the nan
# Repeat, but for the y axis
output = interpolate(self.var, inaxis=self.y, outaxis=self.y, interp_type='linear').transpose(YAxis,XAxis).get()
# GSL interoplates over nans, so we need to undo this for a direct comparison
masked_output = np.array(output)
masked_output[1,1] = float('nan')
self.assertTrue(alleq(masked_output,input), output)
self.assertEqual(output[1,1], 5.) # check how GSL interoplates over the nan
def test_2d_interp(self):
input = self.var.get()
output = interpolate(self.var, inaxis=self.x, outaxis=self.x6, inx=self.xfield, interp_type='linear').transpose(YAxis,XAxis).get()
nan = float('nan')
expected = np.array([[1,2,3,nan,nan],[nan,4,5,6,nan],[nan,nan,7,8,9],[nan,10,11,12,nan]])
self.assertTrue(alleq(output,expected), output)
def test_1(): from pygeode.axis import XAxis from pygeode.interp import interpolate # Input data inaxis = XAxis([3,2,1]) indata = inaxis ** 2 # Output axis outaxis = XAxis([1.5, 2.5]) outdata = interpolate(indata, inaxis=inaxis, outaxis=outaxis, interp_type='linear') outdata = list(outdata.get())
def test_2(): from pygeode.axis import XAxis, YAxis from pygeode.interp import interpolate # Input data inaxis = XAxis([3,2,1]) extra_axis = YAxis([2,4,6]) indata = inaxis ** 2 + extra_axis*0 # Output axis outaxis = XAxis([1.5, 2.5]) outx = outaxis + extra_axis*0 outdata = interpolate(indata, inaxis=inaxis, outaxis=outaxis, outx=outx, interp_type='linear') outdata = list(outdata.get())
def test_1():
from pygeode.axis import XAxis
from pygeode.interp import interpolate
# Input data
inaxis = XAxis([3, 2, 1])
indata = inaxis**2
# Output axis
outaxis = XAxis([1.5, 2.5])
outdata = interpolate(indata,
inaxis=inaxis,
outaxis=outaxis,
interp_type='linear')
outdata = list(outdata.get())
def test_2():
from pygeode.axis import XAxis, YAxis
from pygeode.interp import interpolate
# Input data
inaxis = XAxis([3, 2, 1])
extra_axis = YAxis([2, 4, 6])
indata = inaxis**2 + extra_axis * 0
# Output axis
outaxis = XAxis([1.5, 2.5])
outx = outaxis + extra_axis * 0
outdata = interpolate(indata,
inaxis=inaxis,
outaxis=outaxis,
outx=outx,
interp_type='linear')
outdata = list(outdata.get())
def test_nm_interp (self): # Interpolation with non-monotonic source data - should fail with ValueError output = interpolate(self.var, inaxis=self.y, outaxis=self.y2, inx=self.y_nm, interp_type='linear').transpose(YAxis,XAxis).get()
