def test_control_predition_for_feature():
start_time = datetime.now()
x, y = get_feedback1()
hr = SpaceRepetitionReference(epoch=start_time)
hf = SpaceRepetitionFeedback(x[0:4], y, epoch=start_time)
hctrl = SpaceRepetitionController(epoch=start_time,
reference=hr,
feedback=hf)
graph_handle, data_dict = hctrl.plot_graphs(stop=30)
training_moments_1 = hctrl.range_for(stop=30, curve=1, day_step_size=0.1)
results_1 = [
hctrl.recollect_scalar(training_moment, curve=1)
for training_moment in training_moments_1
]
training_moments_2 = hctrl.range_for(stop=30, curve=2, day_step_size=0.1)
results_2 = [
hctrl.recollect_scalar(training_moment, curve=2)
for training_moment in training_moments_2
]
training_moments_3 = hr.range_for(stop=30, curve=3, day_step_size=0.1)
results_3 = [
hctrl.recollect_scalar(training_moment, curve=3)
for training_moment in training_moments_3
]
ctrl_plot = graph_handle.axarr[-1]
ctrl_plot.plot(training_moments_1, results_1, color='xkcd:azure')
ctrl_plot.plot(training_moments_2, results_2, color='xkcd:darkgreen')
ctrl_plot.plot(training_moments_3, results_3, color='xkcd:maroon')
hr.save_figure("results/space_ctrl_predictions.pdf")
graph_handle.close()
def test_feedback_graph_too_short():
x, y = get_feedback1()
start_time = datetime.now()
hr = SpaceRepetitionReference(epoch=start_time)
hf = SpaceRepetitionFeedback(x, y, epoch=start_time)
hdl, _ = hf.plot_graph(stop=4)
hr.save_figure("results/space_feedback_too_short.pdf")
hdl.close()
def test_feedback_graph_too_long():
x, y = get_feedback1()
start_time = datetime.now()
hr = SpaceRepetitionReference(epoch=start_time)
hf = SpaceRepetitionFeedback(x, y, epoch=start_time)
hdl, _ = hf.plot_graph(stop=50) # it should automatically fit the data
hr.save_figure("results/space_feedback_too_long.pdf")
hdl.close()
def test_learning_tracker_scheduled_offsets_from_generator():
hr = SpaceRepetitionReference(epoch=datetime.now())
targets = [
0.0, 0.4589442709995035, 0.8952268306891566, 1.3571621263040674,
1.881320415336438, 2.517823066268917, 3.3604547989757783,
4.635636774985627, 7.118908457377074, 16.123000823500735
]
for r, t in zip(hr.schedule_as_offset(stop=40), targets):
assert abs(r - t) <= 0.001
def test_reference_scheduled_datetimes_from_generator():
start_time = datetime.now()
hr = SpaceRepetitionReference(epoch=datetime.now())
targets = [
0.0, 0.4589442709995035, 0.8952268306891566, 1.3571621263040674,
1.881320415336438, 2.517823066268917, 3.3604547989757783,
4.635636774985627, 7.118908457377074, 16.123000823500735
]
datetime_targets = [start_time + timedelta(days=t) for t in targets]
stop_date = start_time + timedelta(days=40)
for r, t in zip(hr.schedule(stop=stop_date), datetime_targets):
assert abs((r - t).total_seconds()) <= 0.001
def test_control_graph_too_short():
start_time = datetime.now()
x, y = get_feedback1()
stop_date = 5
hr = SpaceRepetitionReference(epoch=start_time)
hf = SpaceRepetitionFeedback(x[0:2], y, epoch=start_time)
hctrl = SpaceRepetitionController(reference=hr,
feedback=hf,
epoch=start_time)
graph_handle, data_dict = hctrl.plot_graphs(stop=stop_date)
hctrl.save_figure("results/spaced_control_too_short.pdf")
graph_handle.close()
def test_generator_controller():
start_time = datetime.now()
x, y = get_feedback1()
hr = SpaceRepetitionReference(epoch=start_time)
hf = SpaceRepetitionFeedback(x[0:4], y, epoch=start_time)
hctrl = SpaceRepetitionController(reference=hr,
feedback=hf,
epoch=start_time)
hdl, _ = hctrl.plot_graphs(stop=43)
hctrl.save_figure("results/space_control.pdf")
hdl.close()
def test_control_predition_range_for_feature():
start_time = datetime.now()
x, y = get_feedback1()
hr = SpaceRepetitionReference(epoch=start_time)
hf = SpaceRepetitionFeedback(x[0:4], y, epoch=start_time)
hctrl = SpaceRepetitionController(epoch=start_time,
reference=hr,
feedback=hf)
training_moments = hctrl.range_for(stop=30, curve=1, day_step_size=0.1)
assert training_moments[0] == hctrl.days_offset_from_epoch_to_datetime(
hctrl.dates_as_day_offsets[0])
training_moments = hctrl.range_for(stop=30, curve=2, day_step_size=0.1)
assert training_moments[0] == hctrl.days_offset_from_epoch_to_datetime(
hctrl.dates_as_day_offsets[1])
def test_reference_prediction_range_for_feature():
start_time = datetime.now()
hr = SpaceRepetitionReference(
epoch=start_time,
plasticity_root=0.03699,
plasticity_denominator_offset=0.0054,
)
training_moments = hr.range_for(stop=30, curve=1, day_step_size=0.1)
assert training_moments[0] == hr.days_offset_from_epoch_to_datetime(
hr.dates_as_day_offsets[0])
assert training_moments[-1] == \
hr.days_offset_from_epoch_to_datetime(30) - timedelta(days=0.1)
training_moments = hr.range_for(stop=30, curve=2, day_step_size=0.1)
assert training_moments[0] == hr.days_offset_from_epoch_to_datetime(
hr.dates_as_day_offsets[1])
def test_a_control_series():
start_time = datetime.now()
x, y = get_feedback1()
stop_date = 2 * x[-1] * 0.5
hr = SpaceRepetitionReference(epoch=start_time)
hf = SpaceRepetitionFeedback(x[0:2], y, epoch=start_time)
hctrl = SpaceRepetitionController(reference=hr,
feedback=hf,
epoch=start_time)
graph_handle, data_dict = hctrl.plot_graphs(stop=stop_date)
hctrl.save_figure("results/spaced_0.pdf")
graph_handle.close()
#hr = SpaceRepetitionReference(plot=False, range=range_, epoch=start_time)
hf = SpaceRepetitionFeedback(x[0:3], y, epoch=start_time)
hctrl.initialize_feedback(feedback=hf)
graph_handle, _ = hctrl.plot_graphs(stop=stop_date)
hctrl.save_figure("results/spaced_1.pdf")
graph_handle.close()
#hr = SpaceRepetitionReference(plot=False,range=range_,epoch=start_time)
hf = SpaceRepetitionFeedback(x[0:4], y, epoch=start_time)
hctrl.initialize_feedback(feedback=hf)
graph_handle, _ = hctrl.plot_graphs(stop=stop_date)
hctrl.save_figure("results/spaced_2.pdf")
graph_handle.close()
#hr = SpaceRepetitionReference(plot=False,range=range_,epoch=start_time)
hf = SpaceRepetitionFeedback(x[0:5], y, epoch=start_time)
hctrl.initialize_feedback(feedback=hf)
graph_handle, _ = hctrl.plot_graphs(stop=stop_date)
data_dict.clear()
hctrl.save_figure("results/spaced_3.pdf")
graph_handle.close()
#hr = SpaceRepetitionReference(plot=False,range=range_,epoch=start_time)
hf = SpaceRepetitionFeedback(x[0:6], y, epoch=start_time)
hctrl.initialize_feedback(feedback=hf)
graph_handle, _ = hctrl.plot_graphs(stop=stop_date)
data_dict.clear()
hctrl.save_figure("results/spaced_4.pdf")
graph_handle.close()
#hr = SpaceRepetitionReference(plot=False,range=range_,epoch=start_time)
hf = SpaceRepetitionFeedback(x[0:7], y, epoch=start_time)
hctrl.initialize_feedback(feedback=hf)
graph_handle, _ = hctrl.plot_graphs(stop=stop_date)
data_dict.clear()
hctrl.save_figure("results/spaced_5.pdf")
graph_handle.close()
#hr = SpaceRepetitionReference(plot=False,range=range_,epoch=start_time)
hf = SpaceRepetitionFeedback(x[0:8], y, epoch=start_time)
hctrl.initialize_feedback(feedback=hf)
graph_handle, _ = hctrl.plot_graphs(stop=stop_date)
graph_handle.epoch # the epoch
graph_handle.axarr # array of matplotlib axes mapping the subplots
graph_handle.figure # the matplotlib figure
graph_handle.axarr[-1] # the control plot
data_dict.clear()
hctrl.save_figure("results/spaced_6.pdf")
graph_handle.close()
def test_reference_prediction_feature():
start_time = datetime.now()
hr = SpaceRepetitionReference(epoch=start_time, )
graph_handle, data_dict = hr.plot_graph(stop=30)
training_moments_1 = hr.range_for(stop=30, curve=1, day_step_size=0.1)
results_1 = [
hr.recollect_scalar(training_moment, curve=1)
for training_moment in training_moments_1
]
training_moments_2 = hr.range_for(stop=30, curve=2, day_step_size=0.1)
results_2 = [
hr.recollect_scalar(training_moment, curve=2)
for training_moment in training_moments_2
]
training_moments_3 = hr.range_for(stop=30, curve=3, day_step_size=0.1)
results_3 = [
hr.recollect_scalar(training_moment, curve=3)
for training_moment in training_moments_3
]
reference_plot = graph_handle.axarr
reference_plot.plot(training_moments_1, results_1, color='xkcd:azure')
reference_plot.plot(training_moments_2, results_2, color='xkcd:darkgreen')
reference_plot.plot(training_moments_3, results_3, color='xkcd:maroon')
hr.save_figure("results/space_reference_predictions.pdf")
graph_handle.close()
def test_reference_plot_closing_features():
start_time = datetime.now()
hr = SpaceRepetitionReference(epoch=start_time)
hdl, _ = hr.plot_graph(stop=42)
hdl.close()
def test_reference_graph_too_long():
hr = SpaceRepetitionReference(epoch=datetime.now())
hdl, _ = hr.plot_graph(stop=60)
hr.save_figure("results/space_reference_too_long_plot.pdf")
hdl.close()
def test_reference_sizeof_growing_deques():
hr = SpaceRepetitionReference(epoch=datetime.now())
# the deques should grow at the same rate, otherwise
# we will have ring buffer slippage
assert len(hr.forgetting_enclosures) == len(hr.dates_as_day_offsets)
assert len(hr.forgetting_enclosures) == len(hr.results_at_training_moments)
def test_reference_deque_maxlen():
hr = SpaceRepetitionReference(epoch=datetime.now())
assert hr.maxlen == SpaceRepetitionReference.Max_Length