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changed outline of code, new functions now handle ds not fpaths and a…
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…dded additional example function to run on fpath
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@Lauraschwarz
Lauraschwarz committed Sep 24, 2024
1 parent 0b43ebc commit 637ce0c
Showing 1 changed file with 88 additions and 91 deletions.
179 changes: 88 additions & 91 deletions examples/convert_file_formats.py
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from movement.io import load_poses, save_poses

# %%
# Define the file path
# Load the dataset
# --------------------
# This should the location to your outputfile by one of our
# supported pose estimation
# frameworks (e.g., DeepLabCut, SLEAP), containing predicted pose tracks.
# For example, the path could be something like:

# uncomment and edit the following line to point to your own local file
# file_path = "/path/to/my/data.h5"

# %%
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"SLEAP_three-mice_Aeon_proofread.analysis.h5"
)["poses"]
print(fpath)

# %%
# Now we are loading this dataset into our xarray dataset that we can then
# modify to our liking.
ds = load_poses.from_sleap_file(fpath, fps=30)
print(ds)
# %%
# Rename Keypoints of your choice
# --------------------------------
Expand All @@ -53,120 +58,112 @@

# %%
# Now we can run the function and see that
# the keypoints have been renamed
def rename_keypoints(fpath, rename_dict):
fpath = pathlib.Path(fpath)

# this determines the filename of your modified file
# change it if you like to change the filename
dest_path = fpath.parent / f"{fpath.stem}_renamed.csv"

if dest_path.exists():
print(f"Skipping {fpath} as {dest_path} already exists.")
return

if fpath.exists():
# load the data
ds = load_poses.from_sleap_file(fpath, fps=60)
# get the current names of the keypoints
keypoint_names = ds.coords["keypoints"].values
print("Original keypoints:", keypoint_names)
# rename the keypoints
if rename_dict is None or len(rename_dict) == 0:
print("No KPs to rename. Skipping renaming step.")
else:
new_keypoints = [rename_dict.get(kp, kp) for kp in keypoint_names]
print("New keypoints:", new_keypoints)
# Assign the modified values back to the Dataset
ds = ds.assign_coords(keypoints=new_keypoints)
# save poses to dlc file format
save_poses.to_dlc_file(ds, dest_path)
# raise ValueError if path does not exist.

# the keypoints have been renamed.
# this function takes the dataset and the rename_dict as input.
def rename_keypoints(ds, rename_dict):
# get the current names of the keypoints
keypoint_names = ds.coords["keypoints"].values
print("Original keypoints:", keypoint_names)
# rename the keypoints
if rename_dict is None or len(rename_dict) == 0:
print("No KPs to rename. Skipping renaming step.")
else:
raise ValueError(
f"File '{fpath}' does not exist. "
f"Please check the file path and try again."
)
new_keypoints = [rename_dict.get(kp, kp) for kp in keypoint_names]
print("New keypoints:", new_keypoints)
# Assign the modified values back to the Dataset
ds = ds.assign_coords(keypoints=new_keypoints)
return ds


# %%
# Delete Keypoints of your choice
# --------------------------------
# First, create a list of keypoints.
# to delete modify this list accordingly
kps_to_delete = ["abdomen_pre", "abdomen", "tailbase", "front_L", "front_R"]
# %%
# Now we can go ahead and delete those Keypoints


def delete_keypoints(fpath, delete_keypoints):
fpath = pathlib.Path(fpath)
kps_to_delete = ["abdomen_pre", "abdomen", "tailbase", "front_L", "front_R"]

# this determines the filename of your modified file
# change it if you like to change the filename
dest_path = fpath.parent / f"{fpath.stem}_deletedKPs.csv"
# check if the file already exists
if dest_path.exists():
print(f"Skipping {fpath} as {dest_path} already exists.")
return

if fpath.exists():
# load the data
ds = load_poses.from_sleap_file(fpath, fps=60)
if delete_keypoints is None or len(delete_keypoints) == 0:
print("No KPs to delete. Skipping deleting step.")
else:
# Delete the specified keypoints
# and their corresponding data
ds = ds.drop_sel(keypoints=delete_keypoints)
# save poses to dlc file format
save_poses.to_dlc_file(ds, dest_path)
# raise ValueError if path does not exist.
# %%
# Now we can go ahead and delete those Keypoints
def delete_keypoints(ds, delete_keypoints):
if delete_keypoints is None or len(delete_keypoints) == 0:
print("No KPs to delete. Skipping deleting step.")
else:
raise ValueError(
f"File '{fpath}' does not exist. "
f"Please check the file path and try again."
)
# Delete the specified keypoints
# and their corresponding data
ds = ds.drop_sel(keypoints=delete_keypoints)
return ds


# %%
# Delete Keypoints of your choice
# --------------------------------
# Again create a list with the
# desired order of the keypoints

ordered_keypoints = ["nose", "earL", "earR", "neck", "hipL", "hipR", "tail"]


# %%
# Now we can go ahead and reorder
# those keypoints
def reorder_keypoints(ds, ordered_keypoints):
# reorder the keypoints
if ordered_keypoints is None or len(ordered_keypoints) == 0:
print("No KPs to reorder. Skipping reordering step.")
else:
# Reorder the keypoints in the Dataset
ds = ds.reindex(keypoints=ordered_keypoints)
return ds


def reorder_keypoints(fpath, ordered_keypoints):
fpath = pathlib.Path(fpath)

dest_path = fpath.parent / f"{fpath.stem}_modified.csv"

if dest_path.exists():
print(f"Skipping {fpath} as {dest_path} already exists.")
return
# %%
# and how can I use this when I only have my filepath????
# -----------
# Great! Now we know how we can modify our movement datasets!
# let's put it all together and see how we could use this in a real world
# scenario.
# This function will convert all files in the folder to the desired format.
# The function will rename the keypoints, delete specified keypoints,
# and reorder them in the dataset.
# The function will then save the modified dataset to a new file.


FPATH = "/path/to/your/data/"


def convert_all(FPATH, ext="_inference.slp"):
source_folder = pathlib.Path(FPATH)
fpaths = list(source_folder.rglob(f"*{ext}"))

for fpath in fpaths:
fpath = pathlib.Path(fpath)

# this determines the filename of your modified file
# change it if you like to change the filename
dest_path = fpath.parent / "tracking_2D_8KP.csv"

if dest_path.exists():
print(f"Skipping {fpath} as {dest_path} already exists.")
return

if fpath.exists():
print(f"processing: {fpath}")
# load the data
ds = load_poses.from_sleap_file(fpath, fps=60)
ds_renamed = rename_keypoints(ds, rename_dict)
ds_deleted = delete_keypoints(ds_renamed, kps_to_delete)
ds_reordered = reorder_keypoints(ds_deleted, ordered_keypoints)
# save poses to dlc file format
# here we are also splitting the multi animal file into 2
# separate files for each animal
save_poses.to_dlc_file(
ds_reordered, dest_path, split_individuals=True
)

if fpath.exists():
# load the data
ds = load_poses.from_sleap_file(fpath, fps=60)
# reorder the keypoints
if ordered_keypoints is None or len(ordered_keypoints) == 0:
print("No KPs to reorder. Skipping reordering step.")
else:
# Reorder the keypoints in the Dataset
ds = ds.reindex(keypoints=ordered_keypoints)

# save poses to dlc file format
save_poses.to_dlc_file(ds, dest_path)

# raise ValueError if path does not exist.
else:
raise ValueError(
f"File '{fpath}' does not exist. "
f"Please check the file path and try again."
)
raise ValueError(
f"File '{fpath}' does not exist. "
f"Please check the file path and try again."
)

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