Typhoon sequence

Sometimes it may be interesting to visualise a single typhoon sequence. Luckily, this can be easily done with the module pyphoon.visualise. In this example we will show first how to load the data related to a typhoon sequence and next we will show how to animate the list of images!

Make sure to replace path_image with the path of the directory containing all sequence image folders, sequence_no with the typhoon sequence identifier (e.g. 201725) and path_best with the directory path containing all sequence’s TSV best data files.

Load typhoon sequence data

In this example we use the library methods to load the data, which assume that you follow the same data structure presented in section Data. If that is not the case, feel free to implement your own loading functions. Note that the data, once loaded, should be of type list.

On the one hand, to load the typhoon image data we use methods read_source_images() and get_image_ids(), which load the images and get their correspoding sample ids, respectively. Each sample is identified by a unique ids, which is constructed using the sequence identifier of the sequence that frame belongs to and the date the sample data was registered.

>>> from pyphoon.io.h5 import read_source_images
>>> from pyphoon.io.utils import get_image_ids
>>> images = read_source_images(join(path_image, sequence_no))
>>> images_ids = get_image_ids(join(path_image, sequence_no))

Above, images is a list containing the images of the sequence as arrays and image_ids is a list with the corresponding image sample ids.

On the other hand, we load best data is done similarly, using methods read_tsv() and get_best_ids().

>>> from pyphoon.io.tsv import read_tsv
>>> from pyphoon.io.utils import get_best_ids
>>> best = read_tsv(join(path_best, sequence_no))
>>> best_ids = get_best_ids(image)

Above, best is a list containing the best data of each sample in the typhoon sequence. Likewise, best_ids contains the corresponding sample ids.

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Visualise a typhoon sequence

Plotting one specific image frame from the sequence is rather easy.

>>> import matplotlib.pyplot as plt
>>> plt.imshow(images[10], cmap="Greys")
>>> plt.title(images_ids[10])
>>> plt.show()

You can easily display all the image frames in a typhoon sequence using the class DisplaySequence.

>>> from pyphoon.visualise import DisplaySequence
>>> DisplaySequence(
...    images=images,
...    images_ids=images_ids,
...    name=sequence_no,
...    interval=100
...).run

If you want to display the sequence in a Jupyter notebook use the method run_html() instead as

>>> from pyphoon.visualise import DisplaySequence
>>> from IPython.display import HTML
>>> HTML(DisplaySequence(
...    images=images,
...    images_ids=images_ids,
...    name=sequence_no,
...    interval=100
...).run_html())