def test_dimensions(set_schema):
tmin = Variable(tree=[
'select', [
['source', [
{'type': 'Table', 'id': 30, 'name': 'cnty_24k97_data', 'field': 'fid'},
]],
'tmin'
]
])
assert tmin.dimensions == 'time'
counties = Variable(tree=[
'select', [
['source', [
{'type': 'Layer', 'id': 26, 'name': 'cnty_24k97', 'field': 'fid'},
]],
'name'
]
])
assert counties.dimensions == 'space'
tmin = Variable(tree=[
'select', [
['join', [
{'type': 'Layer', 'id': 26, 'name': 'cnty_24k97', 'field': 'fid'},
{'type': 'Table', 'id': 30, 'name': 'cnty_24k97_data', 'field': 'fid'},
]],
'tmin'
]
])
assert tmin.dimensions == 'spacetime'
def test_named_nodes():
v = Variable(tree=[
'named',
[
'TestName',
[
'mean',
[
_matrix_val({
'values': np.array([[1, 2], [3, 4]]),
'spatial_key': spatial_key,
'temporal_key': temporal_key
}),
_matrix_val({
'values': np.array([[5, 6], [7, 8]]),
'spatial_key': spatial_key,
'temporal_key': temporal_key
})
]
]
]
])
np.testing.assert_array_equal(v.data().values, np.array([[3, 4], [5, 6]]))
assert v.root.name() == 'TestName'
def test_abscent_source(set_schema):
v = Variable(tree=[
'join', [
{'type': 'Layer', 'id': -1, 'name': 'cnty_24k97', 'field': 'fid'},
{'type': 'Table', 'id': -1, 'name': 'cnty_24k97_data', 'field': 'fid'},
]
])
with pytest.raises(ObjectDoesNotExist):
v.data()
def test_join_two_tables(set_schema):
tmin = Variable(tree=[
'select', [
['join', [
{'type': 'Table', 'id': 30, 'name': 'cnty_24k97_data', 'field': 'fid'},
{'type': 'Table', 'id': 30, 'name': 'cnty_24k97_data', 'field': 'fid'},
]],
'tmin'
]
])
assert len(tmin.data()) == 3650
def test_get_layers(set_schema):
tmin = Variable(tree=[
'select', [
['join', [
{'type': 'Layer', 'id': 26, 'name': 'cnty_24k97', 'field': 'fid'},
{'type': 'Table', 'id': 30, 'name': 'cnty_24k97_data', 'field': 'fid'},
]],
'tmin'
]
])
assert tmin.get_layers() == set([26])
def test_temporal_mean_operator():
v = Variable(tree=[
'tmean',
[
_matrix_val({
'values': np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),
'spatial_key': spatial_key3,
'temporal_key': temporal_key3
})
]
])
np.testing.assert_array_equal(v.data().values, np.array([2, 5, 8]))
def test_raster(set_schema):
tree = ["select", [
["raster", [
{ "id": "modis_indices_ndvi", "name": "Land indices"},
[ "source", [
{ "field": "fid", "type": "Layer", "id": "26", "name": "cnty_24k97"}
]],
"2015-001,2015-030"
]],
{"field": "mean", "name": "raster"}
]]
mean = Variable(tree=tree)
len(mean.get_layers()) == 1
len(mean.get_rasters()) == 1
def submit(request):
if not request.is_ajax() or not request.method == 'POST':
return HttpResponse('invalid request to /submit')
elif not 'jtv_verified' in request.session or request.session['jtv_verified'] != True:
return HttpResponse(json.dumps({
'success': False,
'message': 'You have not verified your JTV account! Please do that before signing up for monobattles!'
}))
elif not Variable.get_bool('monobattles_enabled'):
return HttpResponse(json.dumps({
'success': False,
'message': 'Monobattles are currently disabled'
}))
elif not request.POST['sc2_name'] or not request.POST['sc2_charcode'] or not request.POST['sc2_charcode'].isdigit():
return HttpResponse(json.dumps({
'success': False,
'message': 'Please fill out your sc2 character name and code'
}))
submission = ViewerSubmission(
sc2_name=request.POST['sc2_name'],
sc2_charcode=request.POST['sc2_charcode'],
submit_time=time()
)
submission.save()
return HttpResponse(json.dumps({
'success': True,
'message': 'You signed up for monobattles!'
}))
def manage_action(request):
if not request.is_ajax() or not request.method == 'POST':
return HttpResponse('invalid request to /manage-action')
elif not request.user.is_authenticated() or not request.user.has_perm('variables.add_variable'):
return HttpResponse(json.dumps({
'success': False,
'message': 'You are not allowed to enable/disable monobattles'
}))
if request.POST['action'] == 'enable':
Variable.set('monobattles_enabled', True)
Variable.set('monobattles_last_enabled_time', time())
return HttpResponse(json.dumps({
'success': True,
'message': 'Monobattles are ON!'
}))
Variable.set('monobattles_enabled', False)
last_enabled = Variable.get_decimal('monobattles_last_enabled_time', time())
submissions_query = ViewerSubmission.objects.filter(
submit_time__gte=last_enabled
).order_by('submit_time')
submissions = []
for s in submissions_query:
submissions.append({
'name': s.sc2_name,
'code': s.sc2_charcode,
'time': s.__unicode__()
})
return HttpResponse(json.dumps({
'success': True,
'message': 'Monobattles have been disabled',
'submissions': submissions
}))
def test_mean_operator():
v = Variable(tree=[
'mean',
[
_matrix_val({
'values': np.array([[1, 2], [3, 4]]),
'spatial_key': spatial_key,
'temporal_key': temporal_key
}),
_matrix_val({
'values': np.array([[5, 6], [7, 8]]),
'spatial_key': spatial_key,
'temporal_key': temporal_key
})
]
])
np.testing.assert_array_equal(v.data().values, np.array([[3, 4], [5, 6]]))
with pytest.raises(ValueError):
v = Variable(tree=[
'mean',
[
_matrix_val({
'values': np.array([[1, 2], [3, 4]]),
'spatial_key': spatial_key,
'temporal_key': temporal_key
}),
_matrix_val({
'values': np.array([[1], [2]]),
'spatial_key': [1],
'temporal_key': [date(2010, 1, 1)]
}),
]
])
v.data()
def test_example_0_5_select(set_schema):
tmin = [
'select', [
['join', [
{'type': 'Layer', 'id': 26, 'name': 'cnty_24k97', 'field': 'fid'},
{'type': 'Table', 'id': 30, 'name': 'cnty_24k97_data', 'field': 'fid'},
]],
'tmin'
]
]
tmax = [
'select', [
['join', [
{'type': 'Layer', 'id': 26, 'name': 'cnty_24k97', 'field': 'fid'},
{'type': 'Table', 'id': 30, 'name': 'cnty_24k97_data', 'field': 'fid'},
]],
'tmax'
]
]
t_summer = ['tfilter', [
['mean', [
tmin,
tmax
]],
{
'filter_type': 'inclusive',
'date_ranges': [
{'start': '2010-06-01', 'end': '2010-08-31'},
{'start': '2011-06-01', 'end': '2011-08-31'},
{'start': '2012-06-01', 'end': '2012-08-31'},
{'start': '2013-06-01', 'end': '2013-08-31'},
{'start': '2014-06-01', 'end': '2014-08-31'}
]
}
]]
t_norm_summer = Variable(tree=['tmean', [t_summer]])
print t_norm_summer.data()
assert np.allclose(
t_norm_summer.data().values, [
14.188587, 22.986413
]
)
def test_temporal_filter_operator():
twobyeight = _matrix_val({
'values':
np.array([[1, 2, 3, 4, 5, 6, 7, 8], [1, 2, 3, 4, 5, 6, 7, 8]]),
'spatial_key': [1, 2],
'temporal_key': [
DateRange(date(2010, 1, 1), date(2010, 1, 2)),
DateRange(date(2010, 1, 2), date(2010, 1, 3)),
DateRange(date(2010, 1, 3), date(2010, 1, 4)),
DateRange(date(2010, 1, 4), date(2010, 1, 5)),
DateRange(date(2010, 1, 5), date(2010, 1, 6)),
DateRange(date(2010, 1, 6), date(2010, 1, 7)),
DateRange(date(2010, 1, 7), date(2010, 1, 8)),
DateRange(date(2010, 1, 8), date(2010, 1, 9)),
]
})
v = Variable(tree=[
'tfilter',
[
twobyeight, {
'filter_type':
'inclusive',
'date_ranges': [
{
'start': '2010-01-02',
'end': '2010-01-04'
},
{
'start': '2010-01-06',
'end': '2010-01-08'
},
]
}
]
])
np.testing.assert_array_equal(v.data().values,
[[2, 3, 4, 6, 7, 8], [2, 3, 4, 6, 7, 8]])
v = Variable(tree=[
'tfilter',
[
twobyeight, {
'filter_type':
'exclusive',
'date_ranges': [
{
'start': '2010-01-02',
'end': '2010-01-04'
},
{
'start': '2010-01-06',
'end': '2010-01-08'
},
]
}
]
])
np.testing.assert_array_equal(v.data().values, [[1, 5], [1, 5]])
def index(request):
params = {}
if 'jtv_verified' in request.session and request.session['jtv_verified'] == True:
params['jtv_verified'] = True
else:
params['jtv_verified'] = False
params['verify_form'] = VerifyForm()
params['submit_form'] = SubmitForm()
params['monobattles_enabled'] = Variable.get_bool('monobattles_enabled');
return render_to_response('viewers/index.html',
params,
context_instance=RequestContext(request)
)
def manage(request):
params = {}
if request.method == 'POST':
username = request.POST['username']
password = request.POST['password']
user = authenticate(username=username, password=password)
if user is not None:
login(request, user)
return redirect('/manage')
else:
params['error'] = "Invalid username or password"
if request.user.is_authenticated() and request.user.has_perm('variables.add_variable'):
template = 'viewers/manage.html'
params['is_enabled'] = Variable.get_bool('monobattles_enabled')
else:
params['login_form'] = AuthenticationForm()
template = 'viewers/manage_login.html'
return render_to_response(template,
params,
context_instance=RequestContext(request)
)
def test_spatial_filter():
f1 = Feature()
f2 = Feature()
f1.geometry = GEOSGeometry(
'GEOMETRYCOLLECTION(POLYGON(( 12 12, 12 18, 18 18, 18 17, 12 12)))')
f2.geometry = GEOSGeometry(
'GEOMETRYCOLLECTION(POLYGON(( 1 1, 1 2, 2 2, 2 1, 1 1)))')
v = Variable(tree=[
'sfilter',
[{
'values': np.array([[1, 2, 3, 4], [5, 6, 7, 8]]),
'spatial_key': [f1, f2],
'temporal_key': []
}, {
'filter_type':
'inclusive',
'containing_geometries': [
GEOSGeometry(
'GEOMETRYCOLLECTION(POLYGON(( 10 10, 10 20, 20 20, 20 15, 10 10 )))'
)
]
}]
])
np.testing.assert_array_equal(v.data().values, [[1, 2, 3, 4]])
v = Variable(tree=[
'sfilter',
[{
'values': np.array([[1, 2, 3, 4], [5, 6, 7, 8]]),
'spatial_key': [f1, f2],
'temporal_key': []
}, {
'filter_type':
'exclusive',
'containing_geometries': [
GEOSGeometry(
'GEOMETRYCOLLECTION(POLYGON(( 10 10, 10 20, 20 20, 20 15, 10 10 )))'
)
]
}]
])
np.testing.assert_array_equal(v.data().values, [[5, 6, 7, 8]])
def test_arithmetic_operators_matrices():
v = Variable(tree=[
'+',
[
_matrix_val({
'values': np.array([[1, 2], [3, 4]]),
'spatial_key': spatial_key,
'temporal_key': temporal_key
}),
_matrix_val({
'values': np.array([[2, 3], [4, 5]]),
'spatial_key': spatial_key,
'temporal_key': temporal_key
})
]
])
np.testing.assert_array_equal(v.data().values, np.array([[3, 5], [7, 9]]))
v = Variable(tree=[
'+',
[
_matrix_val({
'values': np.array([[1, 2], [3, 4]]),
'spatial_key': spatial_key,
'temporal_key': temporal_key
}),
_scalar_val(2)
]
])
np.testing.assert_array_equal(v.data().values, np.array([[3, 4], [5, 6]]))
v = Variable(tree=[
'+',
[
_matrix_val({
'values': np.array([[1, 2], [3, 4]]),
'spatial_key': spatial_key,
'temporal_key': temporal_key
}),
_matrix_val({
'values': np.array([[1, 2, 3], [4, 5, 6]]),
'spatial_key': spatial_key,
'temporal_key': temporal_key3
})
]
])
np.testing.assert_array_equal(
v.data().values,
np.array([
[2., 4., float('nan')],
[7., 9., float('nan')],
]))
with pytest.raises(ValueError):
v = Variable(tree=[
'+',
[
_matrix_val({
'values': np.array([[1, 2], [3, 4]]),
'spatial_key': spatial_key,
'temporal_key': temporal_key
}),
_matrix_val({
'values': np.array([[1, 2, 3], [4, 5, 6]]),
'spatial_key': spatial_key3,
'temporal_key': temporal_key3
})
]
])
print v.data().values
def test_arithmetic_operators_scalar():
v = Variable(tree=['+', [_scalar_val(1), _scalar_val(2)]])
assert v.data() == _scalar_val(3)
v = Variable(
tree=['+', [['+', [_scalar_val(1), _scalar_val(2)]],
_scalar_val(3)]])
assert v.data() == _scalar_val(6)
v = Variable(
tree=['+', [_scalar_val(3), ['+', [_scalar_val(1),
_scalar_val(2)]]]])
assert v.data() == _scalar_val(6)
v = Variable(
tree=['-', [['-', [_scalar_val(6), _scalar_val(2)]],
_scalar_val(1)]])
assert v.data() == _scalar_val(3)
v = Variable(
tree=['*', [_scalar_val(3), ['*', [_scalar_val(1),
_scalar_val(3)]]]])
assert v.data() == _scalar_val(9)
v = Variable(tree=['/', [_scalar_val(3), _scalar_val(1)]])
assert v.data() == _scalar_val(3)
def test_value_filter_operator():
test_matrix = _matrix_val({
'values': np.array([[1, 2], [3, 4]]),
'spatial_key': spatial_key,
'temporal_key': temporal_key
})
v = Variable(
tree=['filter', [test_matrix, {
'comparison': '>',
'comparator': 3
}]])
np.testing.assert_array_equal(
v.data().values, [[float('nan'), float('nan')], [float('nan'), 4]])
v = Variable(
tree=['filter', [test_matrix, {
'comparison': '>=',
'comparator': 3
}]])
np.testing.assert_array_equal(v.data().values,
[[float('nan'), float('nan')], [3, 4]])
v = Variable(
tree=['filter', [test_matrix, {
'comparison': '<',
'comparator': 3
}]])
np.testing.assert_array_equal(
v.data().values, [[1, 2], [float('nan'), float('nan')]])
v = Variable(
tree=['filter', [test_matrix, {
'comparison': '<=',
'comparator': 3
}]])
np.testing.assert_array_equal(v.data().values, [[1, 2], [3, float('nan')]])
v = Variable(
tree=['filter', [test_matrix, {
'comparison': '==',
'comparator': 3
}]])
np.testing.assert_array_equal(
v.data().values, [[float('nan'), float('nan')], [3, float('nan')]])
masked_matrix = _matrix_val({
'values':
ma.array([[float('nan'), float('nan')], [3, float('nan')]]),
'spatial_key':
spatial_key,
'temporal_key':
temporal_key
})
v = Variable(tree=[
'filter', [masked_matrix, {
'comparison': '==',
'comparator': 2
}]
])
np.testing.assert_array_equal(v.data().values,
[[float('nan'), float('nan')],
[float('nan'), float('nan')]])
def test_join_operator(set_schema, monkeypatch):
with mock.patch('django.db.connection') as connection:
connection.schema_name = 'test'
connection.cursor.return_value.fetchall.return_value = [
(1, None, None, {
'tmin': 2
}, DateRange(date(2010, 1, 1), date(2010, 1, 1))),
(2, None, None, {
'tmin': 5
}, DateRange(date(2010, 1, 2), date(2010, 1, 2))),
(1, None, None, {
'tmin': 4
}, DateRange(date(2010, 1, 1), date(2010, 1, 1))),
(2, None, None, {
'tmin': 8
}, DateRange(date(2010, 1, 2), date(2010, 1, 2))),
]
v = Variable(tree=[
'join',
[{
'type': 'Layer',
'id': 1,
'name': 'cnty24k97',
'field': 'fid'
}, {
'type': 'Table',
'id': 1,
'name': 'cnty24k97_data',
'field': 'fid'
}, 'tmin']
])
np.testing.assert_array_equal(v.data().values,
np.array([[2, 5], [4, 8]]))
v = Variable(tree=[
'join',
[{
'type': 'Table',
'id': 1,
'name': 'cnty24k97_data',
'field': 'fid'
}, {
'type': 'Layer',
'id': 1,
'name': 'cnty24k97',
'field': 'fid'
}, 'tmin']
])
np.testing.assert_array_equal(v.data().values,
np.array([[2, 5], [4, 8]]))
# THIS JOIN only works between tables and layers
v = Variable(tree=[
'join',
[{
'type': 'Table',
'id': 1,
'field': 'fid'
}, {
'type': 'Table',
'id': 1,
'field': 'fid'
}, 'test']
])
with pytest.raises(ValueError):
v.data()
v = Variable(tree=[
'join',
[{
'type': 'Layer',
'id': 1,
'field': 'fid'
}, {
'type': 'Layer',
'id': 1,
'field': 'fid'
}, 'test']
])
with pytest.raises(ValueError):
v.data()
def test_select_join_operator(set_schema, monkeypatch):
with mock.patch('django.db.connection') as connection:
connection.schema_name = 'test'
connection.cursor.return_value.description.__iter__.return_value = (
('shaid', 23, None, 4, None, None,
None), ('record_id', 23, None, 4, None, None,
None), ('date_range', 1082, None, 4, None, None,
None), ('tmin', 25, None, -1, None, None, None))
connection.cursor.return_value.fetchall.return_value = [
(1, 1, DateRange(date(2010, 1, 1), date(2010, 1, 1)), 2),
(1, 2, DateRange(date(2010, 1, 2), date(2010, 1, 2)), 5),
(2, 1, DateRange(date(2010, 1, 1), date(2010, 1, 1)), 4),
(2, 2, DateRange(date(2010, 1, 2), date(2010, 1, 2)), 8),
]
v = Variable(tree=[
'select',
[
[
'join',
[
{
'type': 'Layer',
'id': 26,
'field': 'fid'
},
{
'type': 'Table',
'id': 30,
'field': 'fid'
},
]
],
'tmin',
]
])
data = v.data()
np.testing.assert_array_equal(data.values, np.array([[2, 5], [4, 8]]))
v = Variable(tree=[
'select',
[[
'join',
[
{
'type': 'Layer',
'id': 26,
'field': 'fid'
},
{
'type': 'Table',
'id': 30,
'field': 'fid'
},
]
], 'tmin']
])
np.testing.assert_array_equal(v.data().values,
np.array([[2, 5], [4, 8]]))
v = Variable(tree=[
'select',
[[
'join',
[
{
'type': 'Table',
'id': 26,
'field': 'fid'
},
{
'type': 'Table',
'id': -1,
'field': 'fid'
},
]
], 'test']
])
with pytest.raises(ObjectDoesNotExist):
v.data()
v = Variable(tree=[
'select',
[[
'join',
[
{
'type': 'Layer',
'id': 1,
'field': 'fid'
},
{
'type': 'Layer',
'name': "",
'field': 'fid'
},
]
], 'test']
])
with pytest.raises(ObjectDoesNotExist):
v.data()
