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Merged
bjlittle merged 8 commits into from
Sep 15, 2016
Merged

Moveplottests #2139

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cc44b54
remove check_graphic from regridding tests
marqh Sep 12, 2016
fc88776
remove check_graphic from grib_load tests
marqh Sep 12, 2016
5e543e7
no graphic tests for experimental regrid
marqh Sep 12, 2016
eae2a17
remove graphics tests from trajectory
marqh Sep 12, 2016
b3b9b0a
numpy18 f32 bug, tidy unused images
marqh Sep 13, 2016
2300ff7
developer comments
marqh Sep 13, 2016
3b658cf
use unittest assertAlmostEqual
marqh Sep 14, 2016
c494b69
assertArrayShapeStats
marqh Sep 15, 2016
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66 changes: 14 additions & 52 deletions lib/iris/tests/experimental/regrid/test_regrid_area_weighted_rectilinear_src_and_grid.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
# (C) British Crown Copyright 2013 - 2015, Met Office
# (C) British Crown Copyright 2013 - 2016, Met Office
#
# This file is part of Iris.
#
Expand Down Expand Up @@ -37,12 +37,6 @@
import iris.analysis._interpolation
import iris.tests.stock

# Run tests in no graphics mode if matplotlib is not available.
if tests.MPL_AVAILABLE:
import matplotlib.pyplot as plt
import iris.quickplot as qplt


RESULT_DIR = ('experimental', 'regrid',
'regrid_area_weighted_rectilinear_src_and_grid')

Expand Down Expand Up @@ -161,7 +155,7 @@ def _resampled_grid(cube, x_samplefactor, y_samplefactor):
return new_cube


class TestAreaWeightedRegrid(tests.GraphicsTest):
class TestAreaWeightedRegrid(tests.IrisTest):
def setUp(self):
# A cube with a hybrid height derived coordinate.
self.realistic_cube = iris.tests.stock.realistic_4d()[:2, :5, :20, :30]
Expand Down Expand Up @@ -367,25 +361,11 @@ def test_regrid_to_higher_res(self):
res = regrid_area_weighted(src, dest)
self.assertCMLApproxData(res, RESULT_DIR + ('higher.cml',))

@tests.skip_plot
def test_hybrid_height(self):
src = self.realistic_cube
dest = _resampled_grid(src, 0.7, 0.8)
res = regrid_area_weighted(src, dest)
self.assertCMLApproxData(res, RESULT_DIR + ('hybridheight.cml',))
# Consider a single slice to allow visual tests of altitudes.
src = src[1, 2]
res = res[1, 2]
qplt.pcolormesh(res)
self.check_graphic()
plt.contourf(res.coord('grid_longitude').points,
res.coord('grid_latitude').points,
res.coord('altitude').points)
self.check_graphic()
plt.contourf(res.coord('grid_longitude').points,
res.coord('grid_latitude').points,
res.coord('surface_altitude').points)
self.check_graphic()

def test_missing_data(self):
src = self.simple_cube.copy()
Expand Down Expand Up @@ -443,7 +423,6 @@ def test_ten_by_ten_subset(self):
res = regrid_area_weighted(src, dest)
self.assertTrue(res, src[indices])

@tests.skip_plot
def test_cross_section(self):
# Slice to get a cross section.
# Constant latitude
Expand All @@ -458,10 +437,6 @@ def test_cross_section(self):
res = regrid_area_weighted(src, dest)
self.assertCMLApproxData(res, RESULT_DIR +
('const_lat_cross_section.cml',))
# Plot a single slice.
qplt.plot(res[0])
qplt.plot(src[0], 'r')
self.check_graphic()

# Constant longitude
src = self.realistic_cube[0, :, :, 10]
Expand All @@ -475,10 +450,6 @@ def test_cross_section(self):
res = regrid_area_weighted(src, dest)
self.assertCMLApproxData(res, RESULT_DIR +
('const_lon_cross_section.cml',))
# Plot a single slice.
qplt.plot(res[0])
qplt.plot(src[0], 'r')
self.check_graphic()

def test_scalar_source_cube(self):
src = self.simple_cube[1, 2]
Expand All @@ -495,39 +466,35 @@ def test_scalar_source_cube(self):
self.assertEqual(res.data, src.data)

@tests.skip_data
@tests.skip_plot
def test_global_data_reduce_res(self):
src = iris.tests.stock.global_pp()
src.coord('latitude').guess_bounds()
src.coord('longitude').guess_bounds()
dest = _resampled_grid(src, 0.4, 0.3)
res = regrid_area_weighted(src, dest)
qplt.pcolormesh(res)
self.check_graphic()
self.assertArrayAlmostEqual(res.data.mean(), 280.137698)
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@djkirkham djkirkham Sep 12, 2016

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Here and elsewhere you're using assertArrayAlmostEqual for scalars.

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@djkirkham djkirkham Sep 12, 2016

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Out of interest, why have you used 'AlmostEqual', rather than 'Equal'?

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@marqh marqh Sep 12, 2016

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Out of interest, why have you used 'AlmostEqual', rather than 'Equal'?

because every time someone compares two floats for equality in a test, a fairy dies ;)

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@djkirkham djkirkham Sep 13, 2016

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So it's a precision issue? In that case, maybe a hash of data would be better to test. NumPy arrays can't be hashed, but the underyling buffer (ndarray.data) can be, if the writeable flag of the ndarray is set to False.

I'm wondering if testing the mean/standard deviation means we wouldn't catch bugs which only changed the data slightly. It's probably nothing to worry about, but just a thought.

self.assertArrayAlmostEqual(res.data.std(), 15.998966)

@tests.skip_data
@tests.skip_plot
def test_global_data_increase_res(self):
src = iris.tests.stock.global_pp()
src.coord('latitude').guess_bounds()
src.coord('longitude').guess_bounds()
dest = _resampled_grid(src, 1.5, 1.5)
res = regrid_area_weighted(src, dest)
qplt.pcolormesh(res)
self.check_graphic()
self.assertArrayAlmostEqual(res.data.mean(), 279.955722)
self.assertArrayAlmostEqual(res.data.std(), 16.313940)

@tests.skip_data
@tests.skip_plot
def test_global_data_same_res(self):
src = iris.tests.stock.global_pp()
src.coord('latitude').guess_bounds()
src.coord('longitude').guess_bounds()
res = regrid_area_weighted(src, src)
qplt.pcolormesh(res)
self.check_graphic()
self.assertArrayAlmostEqual(res.data.mean(), 279.945167)
self.assertArrayAlmostEqual(res.data.std(), 16.345842)

@tests.skip_data
@tests.skip_plot
def test_global_data_subset(self):
src = iris.tests.stock.global_pp()
src.coord('latitude').guess_bounds()
Expand All @@ -545,12 +512,10 @@ def test_global_data_subset(self):
dest.add_dim_coord(dest_lon, 1)

res = regrid_area_weighted(src, dest)
qplt.pcolormesh(res)
plt.gca().coastlines()
self.check_graphic()
self.assertArrayAlmostEqual(res.data.mean(), 280.979336)
self.assertArrayAlmostEqual(res.data.std(), 16.640421)

@tests.skip_data
@tests.skip_plot
def test_circular_subset(self):
src = iris.tests.stock.global_pp()
src.coord('latitude').guess_bounds()
Expand All @@ -568,12 +533,10 @@ def test_circular_subset(self):
dest.add_dim_coord(dest_lon, 1)

res = regrid_area_weighted(src, dest)
qplt.pcolormesh(res)
plt.gca().coastlines()
self.check_graphic()
self.assertArrayAlmostEqual(res.data.mean(), 285.653967)
self.assertArrayAlmostEqual(res.data.std(), 15.212710)

@tests.skip_data
@tests.skip_plot
def test_non_circular_subset(self):
src = iris.tests.stock.global_pp()
src.coord('latitude').guess_bounds()
Expand All @@ -592,9 +555,8 @@ def test_non_circular_subset(self):
dest.add_dim_coord(dest_lon, 1)

res = regrid_area_weighted(src, dest)
qplt.pcolormesh(res)
plt.gca().coastlines()
self.check_graphic()
self.assertArrayAlmostEqual(res.data.mean(), 285.550800)
self.assertArrayAlmostEqual(res.data.std(), 15.190245)


if __name__ == "__main__":
Expand Down
56 changes: 0 additions & 56 deletions lib/iris/tests/integration/test_grib_load.py
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Expand Up @@ -42,13 +42,6 @@
from unittest import skipIf


# Run tests in no graphics mode if matplotlib is not available.
if tests.MPL_AVAILABLE:
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
import iris.plot as iplt
import iris.quickplot as qplt

if tests.GRIB_AVAILABLE:
try:
import iris_grib
Expand Down Expand Up @@ -97,64 +90,32 @@ def test_load_masked(self):
self.assertCML(cubes, ('grib_load', 'missing_values_grib2.cml'))

@skip_irisgrib_fails
@tests.skip_plot
def test_y_fastest(self):
cubes = iris.load(tests.get_data_path(("GRIB", "y_fastest",
"y_fast.grib2")))
self.assertCML(cubes, ("grib_load", "y_fastest.cml"))
iplt.contourf(cubes[0])
plt.gca().coastlines()
plt.title("y changes fastest")
self.check_graphic()

@tests.skip_plot
def test_polar_stereo_grib1(self):
cube = iris.load_cube(tests.get_data_path(
("GRIB", "polar_stereo", "ST4.2013052210.01h")))
self.assertCML(cube, ("grib_load", "polar_stereo_grib1.cml"))
qplt.contourf(cube, norm=LogNorm())
plt.gca().coastlines()
plt.gca().gridlines()
plt.title("polar stereo grib1")
self.check_graphic()

@tests.skip_plot
def test_polar_stereo_grib2(self):
cube = iris.load_cube(tests.get_data_path(
("GRIB", "polar_stereo",
"CMC_glb_TMP_ISBL_1015_ps30km_2013052000_P006.grib2")))
self.assertCML(cube, ("grib_load", "polar_stereo_grib2.cml"))

qplt.contourf(cube)
plt.gca().coastlines()
plt.gca().gridlines()
plt.title("polar stereo grib2")
self.check_graphic()

@tests.skip_plot
def test_lambert_grib1(self):
cube = iris.load_cube(tests.get_data_path(
("GRIB", "lambert", "lambert.grib1")))
self.assertCML(cube, ("grib_load", "lambert_grib1.cml"))

qplt.contourf(cube)
plt.gca().coastlines()
plt.gca().gridlines()
plt.title("lambert grib1")
self.check_graphic()

@tests.skip_plot
def test_lambert_grib2(self):
cube = iris.load_cube(tests.get_data_path(
("GRIB", "lambert", "lambert.grib2")))
self.assertCML(cube, ("grib_load", "lambert_grib2.cml"))

qplt.contourf(cube)
plt.gca().coastlines()
plt.gca().gridlines()
plt.title("lambert grib2")
self.check_graphic()

def test_regular_gg_grib1(self):
cube = iris.load_cube(tests.get_data_path(
('GRIB', 'gaussian', 'regular_gg.grib1')))
Expand Down Expand Up @@ -191,38 +152,21 @@ def _old_compat_load(name):
name)))[0]
return [cube]

@tests.skip_plot
def test_ij_directions_ipos_jpos(self):
cubes = self._old_compat_load("ipos_jpos.grib2")
self.assertCML(cubes, ("grib_load", "ipos_jpos.cml"))
iplt.contourf(cubes[0])
plt.gca().coastlines()
plt.title("ipos_jpos cube")
self.check_graphic()

def test_ij_directions_ipos_jneg(self):
cubes = self._old_compat_load("ipos_jneg.grib2")
self.assertCML(cubes, ("grib_load", "ipos_jneg.cml"))
iplt.contourf(cubes[0])
plt.gca().coastlines()
plt.title("ipos_jneg cube")
self.check_graphic()

def test_ij_directions_ineg_jneg(self):
cubes = self._old_compat_load("ineg_jneg.grib2")
self.assertCML(cubes, ("grib_load", "ineg_jneg.cml"))
iplt.contourf(cubes[0])
plt.gca().coastlines()
plt.title("ineg_jneg cube")
self.check_graphic()

def test_ij_directions_ineg_jpos(self):
cubes = self._old_compat_load("ineg_jpos.grib2")
self.assertCML(cubes, ("grib_load", "ineg_jpos.cml"))
iplt.contourf(cubes[0])
plt.gca().coastlines()
plt.title("ineg_jpos cube")
self.check_graphic()


@tests.skip_data
Expand Down
46 changes: 24 additions & 22 deletions lib/iris/tests/integration/test_regridding.py
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@@ -1,4 +1,4 @@
# (C) British Crown Copyright 2013 - 2015, Met Office
# (C) British Crown Copyright 2013 - 2016, Met Office
#
# This file is part of Iris.
#
Expand Down Expand Up @@ -32,20 +32,15 @@
from iris.cube import Cube
from iris.tests.stock import global_pp

# Run tests in no graphics mode if matplotlib is not available.
if tests.MPL_AVAILABLE:
import iris.quickplot as qplt


@tests.skip_data
@tests.skip_plot
class TestOSGBToLatLon(tests.GraphicsTest):
class TestOSGBToLatLon(tests.IrisTest):
def setUp(self):
path = tests.get_data_path(
('NIMROD', 'uk2km', 'WO0000000003452',
'201007020900_u1096_ng_ey00_visibility0180_screen_2km'))
self.src = iris.load_cube(path)[0]
self.src.data = self.src.data.astype(np.float32)
self.src.data = self.src.data.astype(np.float64)
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@bjlittle bjlittle Sep 13, 2016 •
edited
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@marqh Is this up-casting to avoid numpy 1.8 issues?

If so, would you agree a comment might be handy? As for line +76 ...

self.grid = Cube(np.empty((73, 96)))
cs = GeogCS(6370000)
lat = DimCoord(np.linspace(46, 65, 73), 'latitude', units='degrees',
Expand All @@ -58,23 +53,27 @@ def setUp(self):
def _regrid(self, method):
regridder = Regridder(self.src, self.grid, method, 'mask')
result = regridder(self.src)
qplt.pcolor(result, antialiased=False)
qplt.plt.gca().coastlines()
return result

def test_linear(self):
self._regrid('linear')
self.check_graphic()
result = self._regrid('linear')
self.assertEqual(result.shape, (73, 96))
self.assertArrayAlmostEqual(result.data.mean(), -16100.351951)
self.assertArrayAlmostEqual(result.data.std(), 5603.850769)

def test_nearest(self):
self._regrid('nearest')
self.check_graphic()
result = self._regrid('nearest')
self.assertEqual(result.shape, (73, 96))
self.assertArrayAlmostEqual(result.data.mean(), -16095.965585)
self.assertArrayAlmostEqual(result.data.std(), 5612.657155)


@tests.skip_data
@tests.skip_plot
class TestGlobalSubsample(tests.GraphicsTest):
class TestGlobalSubsample(tests.IrisTest):
def setUp(self):
self.src = global_pp()
_ = self.src.data
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self.src.data on it's own will do the job, no need to assign

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@marqh marqh Sep 13, 2016

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it will, but it can make for messy output during debugging
I tend to prefer to assign to _ as a way to throw this away (so to speak)

self.src.data = self.src.data.astype(np.float64)
# Subsample and shift the target grid so that we can see a visual
# difference between regridding scheme methods.
grid = self.src[1::2, 1::3]
Expand All @@ -85,16 +84,19 @@ def setUp(self):
def _regrid(self, method):
regridder = Regridder(self.src, self.grid, method, 'mask')
result = regridder(self.src)
qplt.pcolormesh(result)
qplt.plt.gca().coastlines()
return result

def test_linear(self):
self._regrid('linear')
self.check_graphic()
result = self._regrid('linear')
self.assertEqual(result.shape, (36, 32))
self.assertArrayAlmostEqual(result.data.mean(), 280.35907)
self.assertArrayAlmostEqual(result.data.std(), 15.997223)

def test_nearest(self):
self._regrid('nearest')
self.check_graphic()
result = self._regrid('nearest')
self.assertEqual(result.shape, (36, 32))
self.assertArrayAlmostEqual(result.data.mean(), 280.33726)
self.assertArrayAlmostEqual(result.data.std(), 16.064001)


if __name__ == "__main__":
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