def test_unjson_dataframe(self):
'''Test unjson dataframe with `nan` values'''
csv_utils.unjson_dataframe(json_data)
assert_frame_equal(json_data, unjson_data, check_like=True)
figsize = width / float(dpi), height / float(dpi)
# Create a figure of the right size with one axes that takes up the full figure
fig = plt.figure(figsize=figsize)
ax = fig.add_axes([0, 0, 1, 1])
# Hide spines, ticks, etc.
ax.axis('off')
# Display the image.
ax.imshow(im_data)
return fig, ax
subjects = pandas.read_csv(subjects_with_marks_path)
reductions_all = pandas.read_csv(reducer_export_path)
reductions = reductions_all[reductions_all.reducer_key == 'points']
reductions = reductions.dropna(axis=1, how='all')
unjson_dataframe(reductions)
reductions_counts = reductions_all[reductions_all.reducer_key == 'counts']
reductions_counts = reductions_counts.dropna(axis=1, how='all')
bbox_props = {
'boxstyle': 'round',
'fc': 'w',
'ec': '0.5',
'alpha': 1
}
text_props = {
'bbox': bbox_props,
'ha': 'left',
'va': 'top',
'size': 18
}
from panoptes_aggregation.csv_utils import unjson_dataframe
from astropy.wcs import WCS
import numpy as np
from gz3d_fits import cov_to_ellipse
from plot_fits_files import set_up_axes
from make_subject_fits import define_wcs
import matplotlib.pyplot as plt
import mpl_style
import progressbar as pb
plt.style.use(mpl_style.style1)
path = '/Volumes/Work/GZ3D'
data = pandas.read_csv(path + '/point_reducer_galaxy_and_star_mpl6.csv')
unjson_dataframe(data)
widgets = [
'Plot: ',
pb.Percentage(), ' ',
pb.Bar(marker='0', left='[', right=']'), ' ',
pb.ETA()
]
pbar = pb.ProgressBar(widgets=widgets, max_value=len(data))
subjects = pandas.read_csv(path + '/galaxy-zoo-3d-subjects-mpl5-mpl6.csv')
subjects.columns = [
'subject_id', 'project_id', 'workflow_id', 'subject_set_id',
'data.metadata', 'data.locations', 'classifications_count', 'retired_at',
'retirement_reason'
]