def test_bar_chart():
"""Make sure some dummy data generates a ``bokeh`` plot"""
# Make a toy dataframe
data = DataFrame({
'meow': {
'foo': 12,
'bar': 23,
'baz': 2
},
'mix': {
'foo': 45,
'bar': 31,
'baz': 23
},
'deliver': {
'foo': 62,
'bar': 20,
'baz': 9
}
})
data = data.reset_index()
# And generate a figure
plt = bar_chart(data, 'index')
assert str(type(plt)) == "<class 'bokeh.plotting.figure.Figure'>"
def jwst_inventory(instruments=JWST_INSTRUMENT_NAMES,
dataproducts=['image', 'spectrum', 'cube'],
caom=False,
plot=False):
"""Gather a full inventory of all JWST data in each instrument
service by instrument/dtype
Parameters
----------
instruments: sequence
The list of instruments to count
dataproducts: sequence
The types of dataproducts to count
caom: bool
Query CAOM service
plot: bool
Return a pie chart of the data
Returns
-------
astropy.table.table.Table
The table of record counts for each instrument and mode
"""
logging.info('Searching database...')
# Iterate through instruments
inventory, keywords = [], {}
for instrument in instruments:
ins = [instrument]
for dp in dataproducts:
count = instrument_inventory(instrument, dataproduct=dp, caom=caom)
ins.append(count)
# Get the total
ins.append(sum(ins[-3:]))
# Add it to the list
inventory.append(ins)
# Add the keywords to the dict
keywords[instrument] = instrument_keywords(instrument, caom=caom)
logging.info(
'Completed database search for {} instruments and {} data products.'.
format(instruments, dataproducts))
# Make the table
all_cols = ['instrument'] + dataproducts + ['total']
table = pd.DataFrame(inventory, columns=all_cols)
# Plot it
if plot:
# Determine plot location and names
output_dir = get_config()['outputs']
if caom:
output_filename = 'database_monitor_caom'
else:
output_filename = 'database_monitor_jwst'
# Make the plot
plt = bar_chart(table,
'instrument',
dataproducts,
title="JWST Inventory")
# Save the plot as full html
html_filename = output_filename + '.html'
outfile = os.path.join(output_dir, 'monitor_mast', html_filename)
output_file(outfile)
save(plt)
set_permissions(outfile)
logging.info(
'Saved Bokeh plots as HTML file: {}'.format(html_filename))
# Save the plot as components
plt.sizing_mode = 'stretch_both'
script, div = components(plt)
div_outfile = os.path.join(output_dir, 'monitor_mast',
output_filename + "_component.html")
with open(div_outfile, 'w') as f:
f.write(div)
f.close()
set_permissions(div_outfile)
script_outfile = os.path.join(output_dir, 'monitor_mast',
output_filename + "_component.js")
with open(script_outfile, 'w') as f:
f.write(script)
f.close()
set_permissions(script_outfile)
logging.info(
'Saved Bokeh components files: {}_component.html and {}_component.js'
.format(output_filename, output_filename))
# Melt the table
table = pd.melt(table,
id_vars=['instrument'],
value_vars=dataproducts,
value_name='files',
var_name='dataproduct')
return table, keywords