def test_calcCentralDisplacement_withinCorrectRange(self):
df = preprocess.execute("../../Data/TestData/bee-data_NT_test.csv")
arena = classArena.classArena(df)
dt_segment, cum_dist_end_segment, end_trajectory = cs.getSegment(
df, 10, 0, 0)
for i in range(0, 20):
dt_segment, cum_dist_end_segment, end_trajectory = cs.getSegment(
df, 10, 0.3, cum_dist_end_segment)
length_segment = cs.getSegmentLength(dt_segment)
features_segment = sg.Segment(dt_segment, length_segment, arena, 0)
cent_displ = features_segment.getFeature(
enums.eFeature.CentralDisplacement).value
# print("cent_displ:", cent_displ)
self.assertLessEqual(cent_displ,
1) # test never bigger than arena size
self.assertGreater(cent_displ, 0) # test positive
self.assertGreaterEqual(
cent_displ,
(features_segment.ellipse.centre[0] - arena.centre_x) * 2 /
arena.diameter) # test greater than ellipse centre x
self.assertGreaterEqual(
cent_displ,
(features_segment.ellipse.centre[1] - arena.centre_y) * 2 /
arena.diameter) # test greater than ellipse centre y
def test_locationDensity(self):
df = preprocess.execute(
"../../Data/TestData/bee-data_NT_test_locationDensity.csv")
#(traj, lseg, ovlp, cum_dist_end_prev)
arena = classArena.classArena(df)
dt_first_segment, cum_dist_end_segment, end_trajectory = cs.getSegment(
df, 7, 0, 0)
length_first_segment = cs.getSegmentLength(dt_first_segment)
features_first_segment = sg.Segment(dt_first_segment,
length_first_segment, arena, 0)
feat = features_first_segment.getFeature(
enums.eFeature.LocationDensity)
SumDistanceBetweenEachPairPoints = 1 + math.sqrt(1**2 + 2**2) + 2 \
+ 2 + math.sqrt(1**2 + 2**2) \
+ 1
nCr = 6
LocationDensity_TrueValue = SumDistanceBetweenEachPairPoints / nCr
self.assertEqual(feat.value, LocationDensity_TrueValue)
def test_iQRangeDistanceCentre(self):
df = preprocess.execute("../../Data/TestData/bee-data_NT_test.csv")
arena = classArena.classArena(df)
dt_first_segment, cum_dist_end_segment, end_trajectory = cs.getSegment(
df, 10, 0, 0)
dt_second_segment, cum_dist_end_segment, end_trajectory = cs.getSegment(
df, 10, 0.3, cum_dist_end_segment)
len_second_segment = cs.getSegmentLength(dt_second_segment)
second_segment_features = sg.Segment(dt_second_segment,
len_second_segment, arena, 0)
feat = second_segment_features.getFeature(enums.eFeature.IQRange)
self.assertAlmostEqual(feat.value, 0.0164803959758471)
def test_MaximumLoopLength(self):
df = pd.read_csv("../../Data/TestData/bee-data_NT_test_maxloop.csv")
arena = classArena.classArena(df)
dt_first_segment, cum_dist_end_segment, end_trajectory = cs.getSegment(
df, 20, 0, 0)
length_first_segment = cs.getSegmentLength(dt_first_segment)
features_first_segment = sg.Segment(dt_first_segment,
length_first_segment,
arena,
index=0)
feat = features_first_segment.getFeature(enums.eFeature.MaximumLoop)
self.assertEqual(feat.value, 15)
def test_checkCorrectingRotation(self):
df = preprocess.execute(
"../../Data/TestData/bee-data_NT_test_maxloop.csv")
#(traj, lseg, ovlp, cum_dist_end_prev)
arena = classArena.classArena(df)
dt_first_segment, cum_dist_end_segment, end_trajectory = cs.getSegment(
df, 20, 0, 0)
length_first_segment = cs.getSegmentLength(dt_first_segment)
features_first_segment = sg.Segment(dt_first_segment,
length_first_segment, arena, 0)
feat = features_first_segment.getFeature(enums.eFeature.MeanSpeed)
self.assertEqual(feat.value, 118.75)
def test_sumAbsAngles(self):
df = preprocess.execute(
"../../Data/TestData/bee-data_NT_test_sum_abs_angles.csv")
#(traj, lseg, ovlp, cum_dist_end_prev)
arena = classArena.classArena(df)
dt_first_segment, cum_dist_end_segment, end_trajectory = cs.getSegment(
df, 7, 0, 0)
length_first_segment = cs.getSegmentLength(dt_first_segment)
features_first_segment = sg.Segment(dt_first_segment,
length_first_segment, arena, 0)
feat = features_first_segment.getFeature(
enums.eFeature.SumAbsoluteAngles)
self.assertEqual(feat.value, 2 * math.pi)
def test_MedianDistanceCentre(self):
df = preprocess.execute("../../Data/TestData/bee-data_NT_test.csv")
arena = classArena.classArena(df)
dt_first_segment, cum_dist_end_segment, end_trajectory = cs.getSegment(
df, 10, 0, 0)
dt_second_segment, cum_dist_end_segment, end_trajectory = cs.getSegment(
df, 10, 0.3, cum_dist_end_segment)
length_second_segment = cs.getSegmentLength(dt_second_segment)
features_second_segment = sg.Segment(dt_second_segment,
length_second_segment, arena, 0)
feat = features_second_segment.getFeature(
enums.eFeature.MedianDistanceFromCentre)
self.assertAlmostEqual(feat.value, 0.8628325515)
def test_pathEfficiency(self):
df = preprocess.execute(
"../../Data/TestData/bee-data_NT_test_sum_abs_angles.csv")
#(traj, lseg, ovlp, cum_dist_end_prev)
arena = classArena.classArena(df)
dt_first_segment, cum_dist_end_segment, end_trajectory = cs.getSegment(
df, 20, 0, 0)
length_first_segment = cs.getSegmentLength(dt_first_segment)
features_first_segment = sg.Segment(dt_first_segment,
length_first_segment, arena, 0)
feat = features_first_segment.getFeature(enums.eFeature.PathEfficiency)
PathEfficiency_TrueValue = 1.0 / 7.0
self.assertEqual(feat.value, PathEfficiency_TrueValue)
def drawArena(df):
#lets say diameter is rounded up
height = df[['y_mm']].max() - df[['y_mm']].min()
width = df[['x_mm']].max() - df[['x_mm']].min()
arena = classArena.classArena(df)
circumference_x = []
circumference_y = []
for iDegree in range(1, 360 + 1):
a = arena.centre_x
b = arena.centre_y
radians = iDegree / 360.0 * 2 * math.pi
x = a + width.iloc[0] / 2.0 * math.cos(radians)
y = b + height.iloc[0] / 2.0 * math.sin(radians)
circumference_x.append(x)
circumference_y.append(y)
plt.plot(circumference_x, circumference_y)
def test_areaFormula(self):
df = preprocess.execute("../../Data/TestData/bee-data_NT_test.csv")
arena = classArena.classArena(df)
dt_first_segment, cum_dist_end_segment, end_trajectory = cs.getSegment(
df, 10, 0, 0)
dt_second_segment, cum_dist_end_segment, end_trajectory = cs.getSegment(
df, 10, 0.3, cum_dist_end_segment)
length_second_segment = cs.getSegmentLength(dt_second_segment)
features_second_segment = sg.Segment(dt_second_segment,
length_second_segment, arena, 0)
#features_second_segment.calcMinEnclosingEllipseArea
points = np.array([[-1, 0, 0, 1], [0, 1, -1, 0]]).T
ellipse = features_second_segment.findMinEnclosingEllipse(points)
min_enclosing_ellipse_area = features_second_segment.calcMinEnclosingEllipseArea(
ellipse.radii)
self.assertAlmostEqual(min_enclosing_ellipse_area, math.pi)
# add filemode="w" to overwrite
#initialisation
datapath = "../../Data/"
logging.basicConfig(filename=os.path.join(datapath, "sample.log"),
level=logging.DEBUG,
filemode="w")
df_nt = pd.read_csv(datapath + "bee-data_NT.csv")
df_procaine = pd.read_csv(datapath + "bee-data_procaine.csv")
df_saline = pd.read_csv(datapath + "bee-data_saline.csv")
dfs_combined = pd.concat([df_nt, df_procaine, df_saline], axis=0)
temp_arena = classArena.classArena(dfs_combined)
#main.process_all_dfs(seg_length = 50, overlap = 0.7, folder_name = "length50",
# data_folder_path = datapath,
# data_nt = df_nt, data_procaine = df_procaine, data_saline = df_saline,
# arena = temp_arena)
main.process_all_dfs(seg_length=100,
overlap=0.7,
folder_name="length100",
data_folder_path=datapath,
data_nt=df_nt,
data_procaine=df_procaine,
data_saline=df_saline,
arena=temp_arena)