Source code for fury.animation.helpers
import numpy as np
from fury.decorators import warn_on_args_to_kwargs
[docs]
@warn_on_args_to_kwargs()
def get_previous_timestamp(timestamps, current_time, *, include_last=False):
"""Return the maximum previous timestamp of a given time.
Parameters
----------
timestamps : ndarray
Sorted list of timestamps.
current_time : float or int
The time to get previous timestamp for.
include_last: bool, optional, default: False
If `True`, even the last timestamp will be considered a valid previous
timestamp.
Returns
-------
float or int
The previous timestamp
"""
for timestamp in timestamps[::-1] if include_last else timestamps[-2::-1]:
if timestamp <= current_time:
return timestamp
return timestamps[0]
[docs]
@warn_on_args_to_kwargs()
def get_next_timestamp(timestamps, current_time, *, include_first=False):
"""Return the minimum next timestamp of a given time.
Parameters
----------
timestamps : ndarray
Sorted list of timestamps.
current_time : float or int
The time to get previous timestamp for.
include_first: bool, optional, default: False
If `True`, even the first timestamp will be considered a valid next
timestamp.
Returns
-------
float or int
The next timestamp
"""
for timestamp in timestamps[:] if include_first else timestamps[1:]:
if timestamp > current_time:
return timestamp
return timestamps[-1]
[docs]
def get_timestamps_from_keyframes(keyframes):
"""Return a sorted array of timestamps given dict of keyframes.
Parameters
----------
keyframes : dict
keyframes dict that contains timestamps as keys.
Returns
-------
ndarray
Array of sorted timestamps extracted from the keyframes.
"""
return np.sort(np.array(list(keyframes)), axis=None)
[docs]
def get_values_from_keyframes(keyframes):
"""Return an array of keyframes values sorted using timestamps.
Parameters
----------
keyframes : dict
keyframes dict that contains timestamps as keys and data as values.
Returns
-------
ndarray
Array of sorted values extracted from the keyframes.
"""
return np.asarray(
[keyframes.get(t, {}).get("value", None) for t in sorted(keyframes.keys())]
)
[docs]
def get_time_tau(t, t0, t1):
"""Return a capped time tau between 0 and 1.
Parameters
----------
t : float or int
Current time to calculate tau for.
t0 : float or int
Lower timestamp of the time period.
t1 : float or int
Higher timestamp of the time period.
Returns
-------
float
The time tau
"""
return 0 if t <= t0 else 1 if t >= t1 else (t - t0) / (t1 - t0)
[docs]
def lerp(v0, v1, t0, t1, t):
"""Return a linearly interpolated value.
Parameters
----------
v0: ndarray or float or int.
The first value
v1: ndarray or float or int.
The second value
t : float or int
Current time to interpolate at.
t0 : float or int
Timestamp associated with v0.
t1 : float or int
Timestamp associated with v1.
Returns
-------
ndarray or float
The interpolated value
"""
if t0 == t1:
return v0
v = v1 - v0
dt = get_time_tau(t, t0, t1)
return dt * v + v0
[docs]
def euclidean_distances(points):
"""Return a list of euclidean distances of a list of points or values.
Parameters
----------
points: ndarray
Array of points or valued to calculate euclidean distances between.
Returns
-------
list
A List of euclidean distance between each consecutive points or values.
"""
return [np.linalg.norm(x - y) for x, y in zip(points, points[1:])]
