def test_ProHotspot_subtask(model, project_task, analysis_model, grid_task):
open_cp.prohotspot.ProspectiveHotSpotContinuous.return_value.predict.return_value = OurContinuousPrediction(20, 30, 10, 20)
provider = prohotspotcts.ProHotspotCts(model)
provider.space_length = 75
subtask = standard_calls(provider, project_task, analysis_model, grid_task)
prediction = subtask(datetime.datetime(2017,6,7))
l = open_cp.prohotspot.ProspectiveHotSpotContinuous.call_args_list
assert len(l) == 1
assert l[0][1]["grid_size"] == 75
timeunit = l[0][1]["time_unit"]
assert timeunit == np.timedelta64(7, "D")
pred = open_cp.prohotspot.ProspectiveHotSpotContinuous.return_value
assert isinstance(pred.weight, open_cp.prohotspot.ClassicWeight)
assert isinstance(pred.distance, open_cp.prohotspot.DistanceDiagonalsSame)
np.testing.assert_array_equal(pred.data.timestamps, [np.datetime64("2017-05-21T12:30"),
np.datetime64("2017-05-21T13:00"), np.datetime64("2017-05-21T13:30")])
np.testing.assert_array_equal(pred.data.xcoords, [0,10,20])
np.testing.assert_array_equal(pred.data.ycoords, [10,20,0])
predict_date = np.datetime64(datetime.datetime(2017,6,7))
pred.predict.assert_called_with(predict_date, predict_date)
assert prediction.xsize == 50
assert prediction.ysize == 50
assert prediction.xoffset == 25
assert prediction.yoffset == 35
assert prediction.xextent == 15
assert prediction.yextent == 10
assert prediction.intensity_matrix[0,0] == 1
def test_ProHotspot_distance(model, project_task, analysis_model, grid_task):
provider = prohotspotcts.ProHotspotCts(model)
provider.distance_type = 1
assert provider.settings_string == "DiagsDiff / Classic(8x8) @ 50m, 168h"
subtask = standard_calls(provider, project_task, analysis_model, grid_task)
subtask(datetime.datetime(2017,6,7))
pred = open_cp.prohotspot.ProspectiveHotSpotContinuous.return_value
assert isinstance(pred.distance, open_cp.prohotspot.DistanceDiagonalsDifferent)
def test_ProHotspot_space_length(model, project_task, analysis_model, grid_task):
provider = prohotspotcts.ProHotspotCts(model)
provider.space_length = 23
assert provider.settings_string == "DiagsSame / Classic(8x8) @ 23m, 168h"
subtask = standard_calls(provider, project_task, analysis_model, grid_task)
subtask(datetime.datetime(2017,6,7))
l = open_cp.prohotspot.ProspectiveHotSpotContinuous.call_args_list
assert l[0][1]["grid_size"] == 23
def test_ProHotspot_window_length(model, project_task, analysis_model, grid_task):
provider = prohotspotcts.ProHotspotCts(model)
provider.time_window_length = datetime.timedelta(days=4)
assert provider.settings_string == "DiagsSame / Classic(8x8) @ 50m, 96h"
subtask = standard_calls(provider, project_task, analysis_model, grid_task)
subtask(datetime.datetime(2017,6,7))
l = open_cp.prohotspot.ProspectiveHotSpotContinuous.call_args_list
timeunit = l[0][1]["time_unit"]
assert timeunit == np.timedelta64(4 * 24, "h")
def test_ProHotspot_kernel(model, project_task, analysis_model, grid_task):
provider = prohotspotcts.ProHotspotCts(model)
provider.weight_model.space_bandwidth = 5
provider.weight_model.time_bandwidth = 9
assert provider.settings_string == "DiagsSame / Classic(5x9) @ 50m, 168h"
subtask = standard_calls(provider, project_task, analysis_model, grid_task)
subtask(datetime.datetime(2017,6,7))
pred = open_cp.prohotspot.ProspectiveHotSpotContinuous.return_value
assert pred.weight.space_bandwidth == 5
assert pred.weight.time_bandwidth == 9
def test_ProHotspot(model, project_task, analysis_model, grid_task):
provider = prohotspotcts.ProHotspotCts(model)
assert provider.settings_string == "DiagsSame / Classic(8x8) @ 50m, 168h"
standard_calls(provider, project_task, analysis_model, grid_task)
def test_ProHotspot_serialise(model, project_task, analysis_model, grid_task):
serialise( prohotspotcts.ProHotspotCts(model) )
