RF: Add keyword arguments to module: animation

fury/animation/helpers.py

@@ -1,154 +1,158 @@
-import numpy as np
-
-
-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]
-
-
-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]
-
-
-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)
-
-
-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())]
-    )
-
-
-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)
-
-
-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
-
-
-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:])]
+import numpy as np
+
+from fury.decorators import warn_on_args_to_kwargs
+
+
+@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]
+
+
+@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]
+
+
+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)
+
+
+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())]
+    )
+
+
+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)
+
+
+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
+
+
+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:])]