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%matplotlib inline
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from planet4 import io, markings
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db = io.DBManager()
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img_name = 'ESP_021605_0985'
data = db.get_image_name_markings(img_name)
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image_ids = data.image_id.unique()
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def show_image_id(i):
p4id = markings.ImageID(image_ids[i])
p4id.plot_all()
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from ipywidgets import interact
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interact(show_image_id, i=(0, len(image_ids)-1))
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img_id = image_ids[177]
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img_id
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blotchfname = '/Users/klay6683/Dropbox/data/planet4/inca_p4id_APF0000km4/'+img_id+'_blotches.hdf'
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pd.read_hdf(blotchfname)
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def get_blotch_list():
return [markings.Blotch(row) for _,row in
pd.read_hdf(blotchfname).iterrows()]
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fanfname = '/Users/klay6683/Dropbox/data/planet4/inca_p4id_APF0000km4/'+img_id+'_fans.hdf'
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pd.read_hdf(fanfname)
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fnotchfname = '/Users/klay6683/Dropbox/data/planet4/inca_p4id_APF0000km4/'+img_id+"_fnotches.hdf"
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pd.read_hdf(fnotchfname)
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def get_fan_list():
return [markings.Fan(row) for _, row in pd.read_hdf(fanfname).iterrows()]
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%matplotlib nbagg
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p4id.plot_blotches(blotches=get_blotch_list())
plt.savefig("/Users/klay6683/Desktop/blotches_clustered.pdf")
plt.xlim(0,190)
plt.ylim(650, 370)
plt.savefig("/Users/klay6683/Desktop/blotches_clustered_zoomed.pdf")
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p4id.plot_fans(fans=get_fan_list())
plt.savefig("/Users/klay6683/Desktop/fans_clustered.pdf")
plt.xlim(0,190)
plt.ylim(650, 370)
plt.savefig("/Users/klay6683/Desktop/fans_clustered_zoomed.pdf")
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fig, ax = plt.subplots()
p4id.plot_blotches(ax=ax, blotches=get_blotch_list())
p4id.plot_fans(ax=ax, fans=get_fan_list())
plt.savefig("/Users/klay6683/Desktop/combined_fnotched.pdf")
plt.xlim(0,190)
plt.ylim(650, 370)
plt.savefig("/Users/klay6683/Desktop/combined_fnotched_zoomed.pdf")
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a = (26.8, 412)
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b = np.array((24.2, 414.2))
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from numpy.linalg import norm
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norm(a-b)
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s = pd.read_clipboard(index_col=0, header=None, squeeze=True)
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b = markings.Blotch(s)
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b.p1
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