def interpolate_digits(model, mnist):
imgs, labels = mnist.train.next_batch(100)
idxs = np.random.randint(0, imgs.shape[0] - 1, 2)
mus, _ = model.encode(np.vstack(imgs[i] for i in idxs))
plot.interpolate(model,
*mus,
name="interpolate_{}->{}".format(*(labels[i]
for i in idxs)),
outdir=PLOTS_DIR)
def plot_exercise_from_db(exId, exerciseCode, sensorType=ACCELEROMETER_CODE):
conn = sqlite3.connect(path + "merged_ankle")
c = conn.cursor()
c.execute(
'SELECT * FROM {tn} WHERE exercise_id={exid} AND sensor_type={st}'.
format(tn=READINGS_TABLE_NAME, st=sensorType, exid=exId))
table = np.array(c.fetchall())
if table.size == 0:
return None
values = table[:, READING_VALUES]
# extract reps
reps = table[:, 6]
rep_starts = np.zeros([reps.shape[0], 1])
for i in range(0, reps.shape[0] - 1):
if reps[i] != reps[i + 1] or i == 0:
rep_starts[i] = True
# print(rep_starts)
sensorReadingData = np.zeros(
[np.shape(values)[0], SENSOR_TO_VAR_COUNT[sensorType]])
i = 0
for reading in values:
vals = np.array(reading.split(" "))
vals = vals.astype(np.float)
sensorReadingData[i] = vals
i = i + 1
# print(sensorReadingData[:, 0])
timestamps = table[:, 4].astype("int64")
timestamps = timestamps - timestamps[0]
plt.figure()
plt.suptitle(EXERCISE_CODES_TO_NAME[exerciseCode] + " " +
SENSOR_TO_NAME[sensorType] + " " + str(exId),
fontsize=13)
plt.subplot(3, 1, 1)
plt.xticks(np.arange(min(timestamps), max(timestamps) + 1, 1000))
plt.ylabel('x')
addRepSeparators(plt, rep_starts, timestamps)
plt.plot(timestamps, sensorReadingData[:, 0], 'r-')
plt.subplot(3, 1, 2)
plt.ylabel('y')
plt.xticks(np.arange(min(timestamps), max(timestamps) + 1, 1000))
addRepSeparators(plt, rep_starts, timestamps)
# resampling
interpol = interpolate(timestamps, sensorReadingData[:, 1])
plt.plot(interpol['x'], interpol['y'], 'b-')
# plt.plot(timestamps, sensorReadingData[:, 1], 'b-')
# plt.plot(timestamps, smooth(sensorReadingData[:, 1], 40), 'b--')
plt.subplot(3, 1, 3)
plt.ylabel('z')
plt.xticks(np.arange(min(timestamps), max(timestamps) + 1, 1000))
addRepSeparators(plt, rep_starts, timestamps)
plt.plot(timestamps, sensorReadingData[:, 2], 'g-')
return plt