def test_file_html_handles_js_only_resources(self, mock_warn, test_plot):
js_resources = JSResources(mode="relative", components=["bokeh"])
template = Template("<head>{{ bokeh_js }}</head><body></body>")
output = bes.file_html(test_plot, (js_resources, None),
"title",
template=template)
html = "<head>%s</head><body></body>" % js_resources.render_js()
assert output == html
def test_file_html_handles_js_only_resources():
js_resources = JSResources(mode="relative", components=["bokeh"])
template = Template("<head>{{ bokeh_js }}</head><body></body>")
output = embed.file_html(_embed_test_plot, (js_resources, None),
"title",
template=template)
html = encode_utf8("<head>%s</head><body></body>" %
js_resources.render_js())
assert output == html
def test_file_html_handles_js_only_resources():
js_resources = JSResources(mode="relative")
template = Template("<head>{{ bokeh_js }}</head><body></body>")
output = embed.file_html(_embed_test_plot,
None,
"title",
template=template,
js_resources=js_resources)
html = "<head>%s</head><body></body>" % js_resources.use_widgets(
False).render_js()
assert output == html
def test_file_html_provides_warning_if_no_css(self, mock_warn: MagicMock,
test_plot: figure) -> None:
js_resources = JSResources()
bes.file_html(test_plot, (js_resources, None), "title")
mock_warn.assert_called_once_with(
'No Bokeh CSS Resources provided to template. If required you will need to provide them manually.'
)
def test_file_html_provides_warning_if_both_resources_and_js_provided(
mock_warn):
js_resources = JSResources()
embed.file_html(_embed_test_plot, CDN, "title", js_resources=js_resources)
mock_warn.assert_called_once_with(
'Both resources and js_resources provided. resources will override js_resources.'
)
def __init__(self, contents, **kwargs):
"""
Writes out the content as raw text or HTML.
:param contents: Bokeh plotting figure.
:param kwargs: Optional styling arguments. The `style` keyword argument has special
meaning in that it allows styling to be grouped as one argument.
It is also useful in case a styling parameter name clashes with a standard
block parameter.
"""
self.resource_deps = [
JScript(script_string=s, name='bokeh_js')
for s in JSResources().js_raw
]
self.resource_deps += [
Css(css_string=s, name='bokeh_css') for s in CSSResources().css_raw
]
super(BokehPlotBlock, self).__init__(**kwargs)
if not isinstance(contents, BokehFigure):
raise ValueError(
"Expected bokeh.plotting.figure.Figure type but got %s",
type(contents))
script, div = components(contents)
self._contents = script + div
def test_file_html_handles_js_only_resources():
js_resources = JSResources()
template = Template("<head>{{ bokeh_js }}</head><body></body>")
output = embed.file_html(_embed_test_plot,
None,
"title",
template=template,
js_resources=js_resources)
rendered_js = JS_RESOURCES.render(js_raw=js_resources.js_raw)
assert output == "<head>%s</head><body></body>" % rendered_js
def save_script_tags(open_file):
# This loads more JS files than is strictly necessary. We really only
# need the main bokeh file and the widgets file. But it's not yet clear
# that the gain in loading time is worth the extra complexity of weeding
# out the other files.
for f in JSResources(mode='cdn').js_files:
open_file.write(f'<script type="text/javascript" src="{f}" '
'crossorigin="anonymous"></script>\n')
open_file.write('<script type="text/javascript"> \n'
' Bokeh.set_log_level("info"); \n'
'</script>\n')
def test_file_html_provides_warning_if_no_css(mock_warn):
js_resources = JSResources()
embed.file_html(_embed_test_plot, (js_resources, None), "title")
mock_warn.assert_called_once_with(
'No Bokeh CSS Resources provided to template. If required you will need to provide them manually.'
)
var year = slider.value,
sources = %s,
new_source_data = sources[year].data;
renderer_source.data = new_source_data;
text_source.data = {'year': [String(year)]};
""" % js_source_array
callback = CustomJS(args=sources, code=code)
slider = Slider(start=years[0], end=years[-1], value=1, step=1, title="Year", callback=callback, name='testy')
callback.args["renderer_source"] = renderer_source
callback.args["slider"] = slider
callback.args["text_source"] = text_source
# Stick the plot and the slider together
layout = column(plot, slider)
# Open our custom template
with open('gapminder_template.jinja', 'r') as f:
template = Template(f.read())
# Use inline resources, render the html and open
js_resources = JSResources(mode='inline')
title = "Bokeh - Gapminder Bubble Plot"
html = file_html(layout, resources=(js_resources, None), title=title, template=template)
output_file = 'gapminder.html'
with io.open(output_file, mode='w', encoding='utf-8') as f:
f.write(html)
view(output_file)
def test_file_html_handles_js_only_resources(self, mock_warn, test_plot):
js_resources = JSResources(mode="relative", components=["bokeh"])
template = Template("<head>{{ bokeh_js }}</head><body></body>")
output = bes.file_html(test_plot, (js_resources, None), "title", template=template)
html = encode_utf8("<head>%s</head><body></body>" % js_resources.render_js())
assert output == html
def test_file_html_handles_js_only_resources():
js_resources = JSResources(mode="relative", components=["bokeh"])
template = Template("<head>{{ bokeh_js }}</head><body></body>")
output = embed.file_html(_embed_test_plot, (js_resources, None), "title", template=template)
html = "<head>%s</head><body></body>" % js_resources.render_js()
assert output == html
def main(arguments):
parser = argparse.ArgumentParser(
description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument('details', help="details of filtering results")
parser.add_argument('hits', help="output of annotate_hits.py")
parser.add_argument(
'annotations',
help="extra annotations for type strains and filter_outliers details")
parser.add_argument('taxonomy', help="taxonomy in csv format")
parser.add_argument('type_strains',
help='text file of type strain versions')
parser.add_argument('--param',
action='append',
default=[],
help='colon separated index.html information')
parser.add_argument('--index-template',
default='data/index.jinja',
help='location for index.html template [%(default)s]')
parser.add_argument('--plot-template',
default='data/plot.jinja',
help='location for the plot template [%(default)s]')
parser.add_argument('--log-in',
help="output of 'deenurp filter_is_outs --log'",
type=argparse.FileType('r'))
parser.add_argument('-i',
'--plot-index',
default='index.html',
help=('name of plot index file, assumed to '
'have the same parent dir as plot_dir'))
parser.add_argument('-d',
'--plot-dir',
default='plot_details',
help=('output directory for plots; index file '
'will be named $plot_dir.html'))
parser.add_argument('--plot-map',
metavar='CSV',
type=argparse.FileType('w'),
help='tax_id,outfile')
parser.add_argument('-N', type=int, help='max number of taxa to read')
args = parser.parse_args(arguments)
plot_dir = args.plot_dir
plot_dir_name = os.path.basename(plot_dir)
plot_index = args.plot_index
json_data_file = 'index.json'
try:
os.makedirs(plot_dir)
except OSError:
pass
if args.log_in:
deenurp_args = {}
for line in args.log_in:
spl = line.split('args: ')
if spl[-1].startswith('{'):
deenurp_args = json.loads(spl[-1])
break
taxonomy = pd.read_csv(args.taxonomy,
usecols=['tax_id', 'species', 'tax_name'],
dtype={
'species': str,
'tax_id': str
})
taxonomy = taxonomy.set_index('tax_id')
species = taxonomy[['species']].join(taxonomy['tax_name'],
on='species',
how='inner')
species = species.drop_duplicates().set_index('species')
hits = pd.read_table(args.hits,
header=None,
dtype={
'seqname': str,
'hit': str,
'pct_id': float
},
na_filter=False,
names=['seqname', 'hit', 'pct_id'],
usecols=['seqname', 'hit', 'pct_id'])
hits = hits.set_index('seqname')
annos = pd.read_csv(
args.annotations,
usecols=['seqname', 'tax_id', 'description', 'version'],
dtype=str).set_index('seqname')
types = set(t.strip() for t in open(args.type_strains) if t)
annos['is_type'] = annos['version'].apply(lambda x: x in types)
details = pd.read_csv(args.details,
usecols=[
'seqname', 'tax_id', 'centroid', 'cluster',
'dist', 'is_out', 'x', 'y'
],
dtype={
'seqname': str,
'tax_id': str,
'centroid': str,
'is_out': bool,
'cluster': str,
'dist': float,
'x': float,
'y': float
})
details = details.set_index('seqname')
details = details.join(taxonomy['species'], on='tax_id') # get species_id
details = details.join(annos[['description', 'version', 'is_type']])
hits = hits.join(annos[['tax_id', 'version']], on='hit') # get tax_id
hits = hits.join(taxonomy['species'], on='tax_id') # get species_id
hits = hits.join(species, on='species') # get species tax name
hits = hits.rename(
columns={
'species': 'hit_id',
'tax_name': 'type strain hit',
'version': 'hit_version'
})
hits = hits.drop('tax_id', axis=1) # we only care about the species_id
details = details.join(species, on='species') # get species tax name
details = details.join(hits)
details = details.reset_index() # move seqname back as a column
# output file purposes
details.loc[:, 'species_name'] = details['tax_name']
# make the hit_name link back to an ncbi url to the actual record
url = ('<a href="https://www.ncbi.nlm.nih.gov/nuccore/{version}">'
'<div title="{hit}">{hit}</div></a>')
def hit_ncbi_link(row):
if pd.isnull(row['type strain hit']):
tag = ''
else:
tag = url.format(**{
'version': row['hit_version'],
'hit': row['type strain hit']
})
return tag
details.loc[:, 'type strain hit'] = details.apply(hit_ncbi_link, axis=1)
details['outlier'] = details['is_out'].apply(lambda x: 'yes' if x else '')
details['type strain'] = details['is_type'].apply(lambda x: 'yes'
if x else '')
# to retain sorting and use with NumberFormatter
details['identity'] = details['pct_id'] / 100
details['dist_from_cent'] = details['dist'] * 100
# define table layout for index page
table = gviz_api.DataTable([('tax_id', 'string'), ('species', 'string'),
('records', 'number'),
('clustered', 'boolean'),
('is_outs', 'number'), ('pct out', 'number')])
if args.plot_map:
map_out = csv.writer(args.plot_map)
map_out.writerow(['tax_id', 'html'])
table_data = []
by_species = details.groupby(by=['species', 'species_name'], sort=False)
by_species = itertools.islice(by_species, args.N)
for (species_id, species_name), species in by_species:
if species.x.isnull().all():
continue
species = species.copy().sort_values(by='dist')
label = '_'.join(species_name.lower().split())
step_plt, pca_plt, tab = paired_plots(
species,
title='{} - {}'.format(species_id, species_name),
text_cols=[
'seqname', 'description', 'type strain', 'dist', 'outlier',
'type strain hit', 'identity'
])
html = file_html(gridplot([[step_plt, pca_plt], [tab]]),
(JSResources(mode='cdn'), CSSResources(mode='cdn')),
title='{} - {}'.format(species_id, species_name),
template=jinja2.Template(
open(args.plot_template, 'r').read()))
filename = '{}.html'.format(label)
with open(os.path.join(args.plot_dir, filename), 'w') as out:
out.write(html)
if args.plot_map:
map_out.writerow([species_id, filename])
n_out = int(sum(species['is_out']))
pct_out = (100.0 * n_out) / len(species)
clustered = not (species.cluster == -1).all()
table_data.append([
species_id,
'<a href="{}/{}">{}</a>'.format(plot_dir_name, filename,
species_name),
len(species), clustered, n_out if clustered else None,
(pct_out, '%.01f%%' % pct_out) if clustered else None
])
with open(os.path.join(plot_dir, json_data_file), 'w') as fout:
table.AppendData(table_data)
fout.write(table.ToJSon())
# plot index should refer to json data according to its relative
# path, assuming that this file is in same directory as plot_dir
with open(plot_index, 'w') as fout:
index = jinja2.Template(open(args.index_template).read())
fout.write(
index.render(json_data=os.path.join(plot_dir_name, json_data_file),
deenurp_args=deenurp_args,
params=dict(p.split(':') for p in args.param)))
import requests
from sqlalchemy import create_engine, String, Integer
from sqlalchemy.sql import text, bindparam
from google.cloud import bigquery
import geopandas as gpd
from shapely.geometry import shape
from datetime import datetime
from cartoframes.viz import Layer, Map, color_category_style, popup_element
from bokeh.plotting import figure
from bokeh.embed import components
from bokeh.resources import CSSResources, JSResources
from shapely import wkt
bokeh_css = CSSResources(mode="cdn", version="2.2.3", minified=True)
bokeh_js = JSResources(mode="cdn", version="2.2.3", minified=True)
application = Flask(__name__, template_folder="templates")
bqclient = bigquery.Client.from_service_account_json(
"Musa509-Lab5-42148b13cb70.json")
#load credentials from a file
with open("pg-credentials.json", "r") as f_in:
pg_creds = json.load(f_in)
# mapbox
with open("mapbox_token.json", "r") as mb_token:
MAPBOX_TOKEN = json.load(mb_token)["token"]
# load credentials from JSON file
# Import the markers from the file
import_marker = process_PAsearch.get_markerpos(stub_loc['stub_dir'][0])
df_MRK = pd.DataFrame.from_dict(import_marker, orient='index')
df_MRK.columns = ['StgX', 'StgY'] # add the column names
# ------------ Create the plots --------------
# Open our custom template
with open('PB_template.jinja', 'r') as f:
template = Template(f.read())
# Use inline resources, render the html and open
bokehlayout = create_bokehplot.makelayout(df_EDAX, df_MRK, img_list)
title = 'Particle Search Results'
js_resources = JSResources(mode='cdn')
css_resources = CSSResources(mode='cdn')
html = file_html(bokehlayout,
resources=(js_resources, css_resources),
title=title,
template=template,
template_variables=sample_info)
script, div = components(bokehlayout)
"""html = template.render(js_resources=js_resources,
css_resources=css_resources,
div=div)"""
output_file = directory + '.html'
with open(directory + '/' + output_file, mode='w', encoding='utf-8') as f:
def test_file_html_handles_js_only_resources():
js_resources = JSResources(mode="relative")
template = Template("<head>{{ bokeh_js }}</head><body></body>")
output = embed.file_html(_embed_test_plot, None, "title", template=template, js_resources=js_resources)
html = "<head>%s</head><body></body>" % js_resources.use_widgets(False).render_js()
assert output == html
