def live_render_plot_update_example():
fig = get_total_infected_people_figure(["#75968f", "#933b41", "#550b1d"])
js, tag = autoload_static(fig, INLINE,
f"{PROTOCOL}://{DOMAIN}:{PORT}/plot.js")
return tag, js
def plotbar(events, userid):
xvalues = [x1.title for x1 in events]
y1values=[y1.prefearfactor for y1 in events]
y2values=[y2.postfearfactor for y2 in events]
yr=OrderedDict(PredictedFear=y1values, ActualFear=y2values)
plotheight=400
plotwidth=600
p2 = figure(x_range=xvalues, plot_width=plotwidth, plot_height=plotheight, title="Imagined vs real")
#p2.xaxis.major_label_orientation = "vertical"
p2.xaxis.major_label_orientation = pi/4
p2.vbar(x=xvalues, top=y1values, width=0.5, fill_color="red")
p2.vbar(x=xvalues, top=y2values, width=0.5, fill_color="blue")
userfilepath=filepath+str(userid)+'.js'
js, tag = autoload_static(p2, CDN, '/'+userfilepath+'?id='+str(randint(1, 1000000)))
with open(userfilepath, 'w') as f:
f.write(js)
return js,tag
def get_plottag(script_path):
""" Saves js in script_path and returns tag for embedding in html
"""
import numpy as np
import pandas as pd
import os
y_data = np.random.randn(100)
x_data = pd.date_range('31-Aug-2014', periods=len(y_data))
figure(x_axis_type='datetime',
tools='pan,wheel_zoom,box_zoom,reset,previewsave,crosshair',
name='test plot')
hold()
line(x_data, y_data,
line_color="#D95B43", line_width=4, alpha=0.7,
legend='random',
background_fill= '#cccccc')
circle(x_data, y_data,
color='red', fill_color=None, size=6,
legend='random')
curplot().title = 'Test Plot'
xaxis().axis_label='date'
yaxis().axis_label='some random numbers'
grid().grid_line_color='white'
grid().grid_line_alpha = 0.5
plotid = curplot()._id
script_path = os.path.join(script_path, plotid+'.js')
js, tag = autoload_static(curplot(), CDN, script_path=script_path)
with open(script_path, 'w') as f:
f.write(js)
return tag
def _process_script(source, filename, env, js_name, use_relative_paths=False):
# Explicitly make sure old extensions are not included until a better
# automatic mechanism is available
Model._clear_extensions()
# quick and dirty way to inject Google API key
if "GOOGLE_API_KEY" in source:
GOOGLE_API_KEY = getenv('GOOGLE_API_KEY')
if GOOGLE_API_KEY is None:
if env.config.bokeh_missing_google_api_key_ok:
GOOGLE_API_KEY = "MISSING_API_KEY"
else:
raise SphinxError(
"The GOOGLE_API_KEY environment variable is not set. Set GOOGLE_API_KEY to a valid API key, "
"or set bokeh_missing_google_api_key_ok=True in conf.py to build anyway (with broken GMaps)"
)
run_source = source.replace("GOOGLE_API_KEY", GOOGLE_API_KEY)
else:
run_source = source
c = ExampleHandler(source=run_source, filename=filename)
d = Document()
c.modify_document(d)
if c.error:
raise RuntimeError(c.error_detail)
resources = get_sphinx_resources()
js_path = join(env.bokeh_plot_auxdir, js_name)
js, script = autoload_static(d.roots[0], resources, js_name)
with open(js_path, "w") as f:
f.write(js)
return (script, js, js_path, source)
def javascript(self) -> str:
"""javascript to save"""
if self._javascript is None:
self._javascript, self._source = autoload_static(self.figure,
self.bokeh_source,
self.file_name)
return self._javascript
def cliffTable_bokeh(cliff):
""" Returns a JavaScript tag for embedding a Bokeh DataTable on the website.
stats: a Pandas DataFrame conatining AID statistical information
"""
cliff.insert(0, 'Target CID', cliff.index)
source = ColumnDataSource(cliff)
columns = [
TableColumn(field="Target CID", title="Target CID"),
TableColumn(field="NN_CID", title="NN_CID"),
TableColumn(field="Similarity", title="Similarity"),
TableColumn(field="Target_Activity", title="Target_Activity"),
TableColumn(field="NN_Activity", title="NN_Activity"),
TableColumn(field="Cliff", title="Cliff"),
]
data_table = DataTable(source=source,
columns=columns,
editable=False,
height=1600,
fit_columns=True,
row_headers=False)
js, tag = autoload_static(data_table, CDN, 'static/js/clifftable.js')
js_file = open('static/js/clifftable.js', 'w')
js_file.write(js)
js_file.close()
return tag
def live_render_plot():
fig = get_total_infected_people_figure([
"#75968f", "#a5bab7", "#c9d9d3", "#e2e2e2", "#dfccce", "#ddb7b1",
"#cc7878", "#933b41", "#550b1d"
])
js, tag = autoload_static(fig, INLINE,
f"{PROTOCOL}://{DOMAIN}:{PORT}/plot.js")
return tag, js
def get_slider():
slider = Slider(start=0.1, end=4, value=1, step=.1, title="power")
slider.js_on_change(
'value', CustomJS(args=dict(), code=get_slider_callback_function()))
js, tag = autoload_static(slider, INLINE,
f"{PROTOCOL}://{DOMAIN}:{PORT}/plot.js")
return tag, js
def run(self, *args, show=False, **kwargs):
# html = file_html(self.fig, CDN, self.div_id)
if show:
plotting.output_notebook()
fig = self.create_fig(*args, **kwargs)
if show:
bokeh.plotting.show(fig)
else:
js, tag = autoload_static(fig, CDN, self.js_path)
return fig, js, tag
def plotbar(events, userid):
"""
Arch: I tried to install bokeh 0.10.0 ver and that was
giving a lot of errors in the Bar(method args)- StopIteration
and also while trying to load the latest bokeh.min.js from CDN
So I am going back to the bokeh 0.8.1 ver- at least it works
"""
xr = [x.title for x in events]
y1values = [y1.prefearfactor for y1 in events]
y2values = [y2.postfearfactor for y2 in events]
yr = OrderedDict(PredictedFear=y1values, ActualFear=y2values)
"""
height=400
width=600
bar = figure(plot_width=width, plot_height=height, title="Imagined vs real")
# use the `rect` renderer to display stacked bars of the medal results. Note
# that we set y_range explicitly on the first renderer
bar.rect(xr, y1values, height=0.5, width=0.4, color="red", alpha=0.6)
bar.rect(xr, y2values, height=0.5, width=0.4, color="blue", alpha=0.6)
"""
bar = Bar(yr,
xr,
xlabel="Events",
ylabel="Fear factor",
title="Imagined vs real fear",
width=800,
height=600,
legend=True,
palette=['#c1ff55', '#b7feea'],
stacked=True,
tools=None,
xgrid=None,
ygrid=None)
bar.toolbar_location = None
#output_file("stacked_bar.html", autosave=True)
#show(bar) - commented out so it doesnt try to open display in linux
#generating unique filenames by- concatenating userid to a rolledindex-
#we dont expect a user to generate more than
"""
global rollingindex
userfilepath = filepath+str(userid)+str(rollingindex.next())+'.js'
"""
userfilepath = filepath + str(userid) + '.js'
js, tag = autoload_static(
bar, CDN, '/' + userfilepath + '?id=' + str(randint(1, 1000000)))
with open(userfilepath, 'w') as f:
f.write(js)
return js, tag
def changelist_view(self, request, extra_context=None):
response = super().changelist_view(request,
extra_context=extra_context)
if hasattr(response, "context_data"):
queryset = response.context_data["cl"].queryset
if queryset.exists():
figure = queryset.plot_summary_info()
js, tag = autoload_static(figure, CDN, "tmp_bokeh_figure")
curdoc().theme = "dark_minimal"
extra_context = {"bokeh_tag": tag, "bokeh_js": js}
response.context_data.update(extra_context)
return response
def embed_fig(p, js_file):
js, tag = autoload_static(p, CDN, "/js/" + js_file)
with open("js/" + js_file, 'w') as f:
f.write(js)
reg = '\n<script src="/js/' + js_file + '".*?>.*?</script>'
for file in glob("_drafts/*.markdown") + glob("_posts/**/*.markdown"):
with open(file, 'r') as f:
text = f.read()
if re.findall(reg, text):
new_text = re.sub(reg, tag, text)
with open(file, 'w') as f:
f.write(new_text)
def plot(newest_changes):
filelist = os.listdir('/home/maximilianklein/snapshot_data/{}/'.format(newest_changes))
site_linkss_file = [f for f in filelist if f.startswith('site_linkss')][0]
if newest_changes == 'newest-changes':
date_range = site_linkss_file.split('site_linkss-index-from-')[1].split('.csv')[0].replace('-',' ')
csv_to_read = '/home/maximilianklein/snapshot_data/{}/{}'.format(newest_changes,site_linkss_file)
df = pandas.DataFrame.from_csv(csv_to_read)
no_gender_perc = df['nan'].sum() / df.sum().sum()
print('no gender %', no_gender_perc)
del df['nan']
df['total'] = df.sum(axis=1)
df['nonbin'] = df['total'] - df['male'] - df['female']
df['fem_per'] = df['female'] / (df['total'])
df['nonbin_per'] = df['nonbin'] / df['total']
dfs = df.sort('total', ascending=False)
htmltable = dfs[['total','fem_per','nonbin_per']]
htmltable.columns=['Total','Women %', 'Non-binary %']
table_html = htmltable.to_html(na_rep='n/a', max_rows=20)
TOOLS = "pan,wheel_zoom,box_zoom,reset,hover,save"
title_suffix = 'Changes since {}'.format(date_range) if newest_changes == 'newest-changes' else 'All Time'
p = figure(x_axis_type="log", x_range=[0.1, 10**6], y_range=[0, 1],
title="Language by Gender {}".format(title_suffix), tools=TOOLS)
p.circle(dfs['total'], dfs['fem_per'], size=12, line_color="black", fill_alpha=0.8)
p.text(dfs["total"]+0.001, dfs["fem_per"]+0.001,
text=dfs.index,text_color="#333333",
text_align="center", text_font_size="10pt")
hover = p.select(dict(type=HoverTool))
hover.point_policy = "follow_mouse"
hover.tooltips = OrderedDict([
("Language", "@lang_name"),
("Total gendered biographies", "@gendered_total"),
("Percentage Female biographies", "@fem_percent")
])
js_filename = "gender_by_language_{}.js".format(newest_changes)
output_path = "./files/assets/js/"
script_path = "./assets/js/"
# generate javascript plot and corresponding script tag
js, tag = autoload_static(p, CDN, script_path + js_filename)
with open(output_path + js_filename, 'w') as js_file:
js_file.write(js)
return {'plot_tag':tag, 'table_html':table_html}
def test_script_attrs(self, mock_make_id):
js, tag = embed.autoload_static(_embed_test_plot, CDN, "some/path")
html = bs4.BeautifulSoup(tag)
scripts = html.findAll(name='script')
self.assertEqual(len(scripts), 1)
attrs = scripts[0].attrs
self.assertTrue(set(attrs), set(['src',
'data-bokeh-model-id',
'id',
'data-bokeh-doc-id']))
self.assertEqual(attrs['data-bokeh-doc-id'], 'ID')
self.assertEqual(attrs['data-bokeh-model-id'], str(_embed_test_plot._id))
self.assertEqual(attrs['src'], 'some/path')
def test_script_attrs(self, mock_uuid):
mock_uuid.uuid4 = mock.Mock()
mock_uuid.uuid4.return_value = "uuid"
js, tag = embed.autoload_static(_embed_test_plot, CDN, "some/path")
html = bs4.BeautifulSoup(tag)
scripts = html.findAll(name="script")
self.assertEqual(len(scripts), 1)
attrs = scripts[0].attrs
self.assertTrue(set(attrs), set(["src", "data-bokeh-model-id", "async", "id", "data-bokeh-doc-id"]))
self.assertEqual(attrs["async"], "false")
self.assertEqual(attrs["data-bokeh-doc-id"], "uuid")
self.assertEqual(attrs["data-bokeh-model-id"], str(_embed_test_plot._id))
self.assertEqual(attrs["src"], "some/path")
def changelist_view(self, request, extra_context=None):
response = super().changelist_view(request,
extra_context=extra_context)
if hasattr(response, "context_data"):
queryset = response.context_data["cl"].queryset
if queryset.count() > 10:
month_distribution_plot = queryset.plot_measurement_by_month()
figure_layout = [month_distribution_plot]
figure = layout(figure_layout)
js, tag = autoload_static(figure, CDN, "tmp_bokeh_figure")
extra_context = {"bokeh_tag": tag, "bokeh_js": js}
response.context_data.update(extra_context)
return response
def test_script_attrs(self, mock_make_id):
js, tag = embed.autoload_static(_embed_test_plot, CDN, "some/path")
html = bs4.BeautifulSoup(tag)
scripts = html.findAll(name='script')
self.assertEqual(len(scripts), 1)
attrs = scripts[0].attrs
self.assertTrue(
set(attrs),
set(['src', 'data-bokeh-model-id', 'id', 'data-bokeh-doc-id']))
self.assertEqual(attrs['data-bokeh-doc-id'], 'ID')
self.assertEqual(attrs['data-bokeh-model-id'],
str(_embed_test_plot._id))
self.assertEqual(attrs['src'], 'some/path')
def process_source(self, source, path, js_filename):
Model._clear_extensions()
root, docstring = _evaluate_source(source, path, self.env)
height_hint = root._sphinx_height_hint()
js_path = join(self.env.bokeh_plot_auxdir, js_filename)
js, script_tag = autoload_static(root, RESOURCES, js_filename)
with open(js_path, "w") as f:
f.write(js)
return (script_tag, js_path, source, docstring, height_hint)
def plot(newest_changes):
filelist = os.listdir(
'/home/maximilianklein/snapshot_data/{}/'.format(newest_changes))
culture_file = [f for f in filelist if f.startswith('culture')][0]
if newest_changes == 'newest-changes':
date_range = culture_file.split('culture-index-from-')[1].split(
'.csv')[0].replace('-', ' ')
print(date_range)
csv_to_read = '/home/maximilianklein/snapshot_data/{}/{}'.format(
newest_changes, culture_file)
df = pandas.DataFrame.from_csv(csv_to_read)
no_gender_perc = df['nan'].sum() / df.sum().sum()
del df['nan']
df['total'] = df.sum(axis=1)
df['nonbin'] = df['total'] - df['male'] - df['female']
df['fem_per'] = df['female'] / (df['total'])
df['nonbin_per'] = df['nonbin'] / df['total']
df['fem_per_million'] = df['fem_per'] * 1000000
df['nonbin_per_million'] = df['nonbin_per'] * 1000000
dfs = df.sort('female')
interesante = ['female', 'male', 'nonbin']
htmltable = dfs[interesante]
htmltable.columns = ['Women', 'Men', 'Non-binary']
table_html = htmltable.to_html(na_rep='n/a')
title_suffix = 'Changes since {}'.format(
date_range) if newest_changes == 'newest-changes' else 'All Time'
p = Bar(
dfs[interesante],
title="Gender By Inglehart-Welzel Culture {}".format(title_suffix),
xlabel="Culture",
ylabel=
"Total gendered biographies (Red), Female Percentage *1,000,00(Green)")
#bar.yaxis.formatter = NumeralTickFormatter(format="0.0%")
js_filename = "gender_by_culture_{}.js".format(newest_changes)
output_path = "./files/assets/js/"
script_path = "./assets/js/"
# generate javascript plot and corresponding script tag
js, tag = autoload_static(p, CDN, script_path + js_filename)
with open(output_path + js_filename, 'w') as js_file:
js_file.write(js)
return {'plot_tag': tag, 'table_html': table_html}
def embedPlot_old(plot):
"""Embed plot method for older versions of bokeh"""
from bokeh.resources import Resources
from bokeh.embed import autoload_static
fp = os.path.join(request.folder,'static/temp/')
fp = os.path.join(fp, plot._id+".js")
res = Resources("relative")
res.js_files = ["../static/js/bokeh.min.js"]
res.css_files = ["../static/css/bokeh.min.css"]
jspath = os.path.join('../static/temp/', plot._id+".js")
js,tag = autoload_static(plot, res, jspath)
with open(fp, "w") as f:
f.write(js)
print
return js,tag
def test_script_attrs(self, mock_uuid):
mock_uuid.uuid4 = mock.Mock()
mock_uuid.uuid4.return_value = 'uuid'
js, tag = embed.autoload_static(_embed_test_plot, CDN, "some/path")
html = bs4.BeautifulSoup(tag)
scripts = html.findAll(name='script')
self.assertEqual(len(scripts), 1)
attrs = scripts[0].attrs
self.assertTrue(set(attrs), set(['src',
'data-bokeh-model-id',
'async',
'id',
'data-bokeh-doc-id']))
self.assertEqual(attrs['async'], 'false')
self.assertEqual(attrs['data-bokeh-doc-id'], 'uuid')
self.assertEqual(attrs['data-bokeh-model-id'], str(_embed_test_plot._id))
self.assertEqual(attrs['src'], 'some/path')
def page_desc(module_desc):
module_path, name = module_desc['file'], module_desc['name']
var_name = module_desc.get('var_name', None)
plotting._default_document = Document()
namespace = {}
with open(module_path, "r") as module_file:
code = compile(module_file.read(), module_path, "exec")
eval(code, namespace)
if var_name:
if 'chart' in module_desc['file']:
obj = namespace[var_name]
objs = [obj.chart.plot]
else:
objs = [namespace[var_name]]
else:
objs = plotting.curdoc().context.children
embed_snippet = ""
for i, obj in enumerate(objs):
filename = name + "." + str(i) + ".js"
js, tag = autoload_static(
obj,
Resources(mode="server", root_url=HOSTED_STATIC_ROOT),
os.path.join(DETAIL_URL_ROOT, filename)
)
embed_snippet += tag
with open(os.path.join(SNIPPET_BUILD_DIR, filename), "w") as f:
f.write(js)
detail_snippet = highlight(
open(module_path).read(), PythonLexer(), HtmlFormatter()
)
return dict(
name = name,
embed_snippet = embed_snippet,
detail_snippet = detail_snippet,
detail_page_url = DETAIL_URL_ROOT + name + ".html",
prev_detail_url = "",
prev_detail_name = "",
next_detail_url = "",
next_detail_name ='',
)
def page_desc(module_desc):
module_path, name = module_desc['file'], module_desc['name']
var_name = module_desc.get('var_name', None)
plotting._default_document = Document()
namespace = {}
with open(module_path, "r") as module_file:
code = compile(module_file.read(), module_path, "exec")
eval(code, namespace)
if var_name:
if 'chart' in module_desc['file']:
obj = namespace[var_name]
objs = [obj.chart.plot]
else:
objs = [namespace[var_name]]
else:
objs = plotting.curdoc().context.children
embed_snippet = ""
for i, obj in enumerate(objs):
filename = name + "." + str(i) + ".js"
js, tag = autoload_static(
obj,
Resources(mode="server", root_url=HOSTED_STATIC_ROOT),
os.path.join(DETAIL_URL_ROOT, filename)
)
embed_snippet += tag
with open(os.path.join(SNIPPET_BUILD_DIR, filename), "w") as f:
f.write(js)
detail_snippet = highlight(
open(module_path).read(), PythonLexer(), HtmlFormatter()
)
return dict(
name = name,
embed_snippet = embed_snippet,
detail_snippet = detail_snippet,
detail_page_url = DETAIL_URL_ROOT + name + ".html",
prev_detail_url = "",
prev_detail_name = "",
next_detail_url = "",
next_detail_name ='',
)
def wrapped_func(newest_changes):
p, date_range, table_html, has_changes = plot_func(newest_changes)
if has_changes:
js_filename = "gender_by_{}_{}.js".format(characteristic,
newest_changes)
script_path = "./assets/js/"
output_path = "./files/assets/js/"
js, tag = autoload_static(p, CDN, script_path + js_filename)
with open(output_path + js_filename, 'w') as js_file:
js_file.write(js)
else:
tag, table_html = None, None
return {'plot_tag': tag,
'table_html': table_html,
'date_range': date_range,
'has_changes': has_changes}
def graph():
db = mysql.connector.connect(user='******', password='******',
host='10.0.51.21',
database='SOC_Portal')
cur = db.cursor(buffered=True)
cur.execute('SELECT startDate, totalTime FROM PastTasks WHERE status="Complete" ORDER BY startDate ASC')
dates = []
times = []
for item in cur:
d = item[0]
h,m,s = item[1].split(":")
t = datetime.time(0,int(h),int(m))
dates.append(d)
times.append(t)
rows = cur.fetchall()
df = pd.DataFrame([[ij for ij in i] for i in rows])
df.rename(columns={0: 'endDate', 1: 'totalTime'}, inplace = True);
# prepare some data
x = dates#df['endDate']
y = times#df['totalTime']
# create a new plot with a title and axis labels
p = figure(title="User Completion Time", x_axis_type='datetime', x_axis_label = 'Date(M/D)', y_axis_type='datetime', y_axis_label='Average Completion Time' )
# add a line renderer with legend and line thickness
p.line(x, y, color ='#FDC14A', line_width=3)
# must be applied to the 1st element, not the axis itself
#p.yaxis.formatter = DatetimeTickFormatter(
# hourmin = ['%H:%M'],
# hours = ['%H:%M'])
# show the results
output_file("Users.html")
#show(p)
js, tag = autoload_static(p, CDN, "/Users/zachauzenne/Desktop/DESKTOP/SOC_Portal_Site/templates/analystOverview.html")
def test_script_attrs(self, mock_uuid):
mock_uuid.uuid4 = mock.Mock()
mock_uuid.uuid4.return_value = 'uuid'
js, tag = embed.autoload_static(_embed_test_plot, CDN, "some/path")
html = bs4.BeautifulSoup(tag)
scripts = html.findAll(name='script')
self.assertEqual(len(scripts), 1)
attrs = scripts[0].attrs
self.assertTrue(
set(attrs),
set([
'src', 'data-bokeh-model-id', 'async', 'id',
'data-bokeh-doc-id'
]))
self.assertEqual(attrs['async'], 'false')
self.assertEqual(attrs['data-bokeh-doc-id'], 'uuid')
self.assertEqual(attrs['data-bokeh-model-id'],
str(_embed_test_plot._id))
self.assertEqual(attrs['src'], 'some/path')
def plot(newest_changes):
filelist = os.listdir('/home/maximilianklein/snapshot_data/{}/'.format(newest_changes))
culture_file = [f for f in filelist if f.startswith('culture')][0]
if newest_changes == 'newest-changes':
date_range = culture_file.split('culture-index-from-')[1].split('.csv')[0].replace('-',' ')
print(date_range)
csv_to_read = '/home/maximilianklein/snapshot_data/{}/{}'.format(newest_changes,culture_file)
df = pandas.DataFrame.from_csv(csv_to_read)
no_gender_perc = df['nan'].sum() / df.sum().sum()
del df['nan']
df['total'] = df.sum(axis=1)
df['nonbin'] = df['total'] - df['male'] - df['female']
df['fem_per'] = df['female'] / (df['total'])
df['nonbin_per'] = df['nonbin'] / df['total']
df['fem_per_million'] = df['fem_per'] * 1000000
df['nonbin_per_million'] = df['nonbin_per'] * 1000000
dfs = df.sort('female')
interesante = ['female','male','nonbin']
htmltable = dfs[interesante]
htmltable.columns=['Women','Men', 'Non-binary']
table_html = htmltable.to_html(na_rep='n/a')
title_suffix = 'Changes since {}'.format(date_range) if newest_changes == 'newest-changes' else 'All Time'
p = Bar(dfs[interesante], title="Gender By Inglehart-Welzel Culture {}".format(title_suffix),
xlabel = "Culture",
ylabel = "Total gendered biographies (Red), Female Percentage *1,000,00(Green)")
#bar.yaxis.formatter = NumeralTickFormatter(format="0.0%")
js_filename = "gender_by_culture_{}.js".format(newest_changes)
output_path = "./files/assets/js/"
script_path = "./assets/js/"
# generate javascript plot and corresponding script tag
js, tag = autoload_static(p, CDN, script_path + js_filename)
with open(output_path + js_filename, 'w') as js_file:
js_file.write(js)
return {'plot_tag':tag, 'table_html':table_html}
def _process_script(source, filename, env, js_name, use_relative_paths=False):
# Explicitly make sure old extensions are not included until a better
# automatic mechanism is available
Model._clear_extensions()
# quick and dirty way to inject Google API key
if "GOOGLE_API_KEY" in source:
GOOGLE_API_KEY = getenv("GOOGLE_API_KEY")
if GOOGLE_API_KEY is None:
if env.config.bokeh_missing_google_api_key_ok:
GOOGLE_API_KEY = "MISSING_API_KEY"
else:
raise SphinxError(
"The GOOGLE_API_KEY environment variable is not set. Set GOOGLE_API_KEY to a valid API key, "
"or set bokeh_missing_google_api_key_ok=True in conf.py to build anyway (with broken GMaps)"
)
run_source = source.replace("GOOGLE_API_KEY", GOOGLE_API_KEY)
else:
run_source = source
c = ExampleHandler(source=run_source, filename=filename)
d = Document()
# We may need to instantiate deprecated objects as part of documenting
# them in the reference guide. Suppress any warnings here to keep the
# docs build clean just for this case
with warnings.catch_warnings():
if "reference" in env.docname:
warnings.filterwarnings("ignore", category=BokehDeprecationWarning)
c.modify_document(d)
if c.error:
raise RuntimeError(c.error_detail)
resources = get_sphinx_resources()
js_path = join(env.bokeh_plot_auxdir, js_name)
js, script = autoload_static(d.roots[0], resources, js_name)
with open(js_path, "w") as f:
f.write(js)
return (script, js, js_path, source)
def simple_plot(plot, tmp_dir):
js_static_js = "static-flask-bokeh/js/"
js_static_css = "static-flask-bokeh/css/"
js_filename = plot._id + ".js"
js_path = tmp_dir + js_filename
res = Resources()
res.mode = "server"
res.js_files = [js_static_js + "bokeh-0.4.min.js"]
res.css_files = [js_static_css + "bokeh-0.4.min.css"]
js, tag = autoload_static(plot,
res,
js_path)
with open(js_path, "w") as f:
f.write(js)
print("Path: %s" % js_path)
print("Wrote %s" % js_filename)
return tag, plot._id
def render_plot():
import numpy as np
from bokeh.embed import autoload_static
from bokeh.plotting import figure
from bokeh.resources import CDN
N = 4000
x = np.random.random(size=N) * 100
y = np.random.random(size=N) * 100
radii = np.random.random(size=N) * 1.5
colors = [
"#%02x%02x%02x" % (int(r), int(g), 150)
for r, g in zip(50 + 2 * x, 30 + 2 * y)
]
TOOLS = "resize,crosshair,pan,wheel_zoom,box_zoom,reset,tap,previewsave,box_select,poly_select,lasso_select"
p = figure(tools=TOOLS)
p.scatter(x,
y,
radius=radii,
fill_color=colors,
fill_alpha=0.6,
line_color=None)
js, tag = autoload_static(p, CDN, "http://localhost:%s/plot.js" % port)
html = """
<html>
<head>
<title>color_scatter example</title>
</head>
<body>
%s
</body>
</html>
""" % tag
return html, js
def plotsprl(events):
import numpy as np
from bokeh.plotting import figure, output_file, show
from bokeh.models import Range1d
# Skip the first point because it can be troublesome
theta = np.linspace(0, 80 * np.pi, 100000)[1:]
theta2 = np.linspace(0, 90 * np.pi, 100000)[1:]
# Compute the radial coordinates for some different spirals
arch = theta # Archimedean
arch2 = theta2
# Now compute the X and Y coordinates (polar mappers planned for Bokeh later)
arch_x = arch * np.cos(theta)
arch_y = arch * np.sin(theta)
arch2_x = arch2 * np.cos(theta)
arch2_y = arch2 * np.sin(theta)
spiral = figure(plot_width=400,
plot_height=400,
title="GoldenRatio",
x_range=Range1d(start=-50, end=50),
y_range=Range1d(start=-50, end=50))
spiral.xgrid.grid_line_color = None
spiral.ygrid.grid_line_color = None
spiral.line(arch_x, arch_y, color="#c1ff55", line_width=4)
spiral.line(arch2_x, arch2_y, color="#b7feea", line_width=10)
output_file("lines.html")
show(spiral) # show the plot
js, tag = autoload_static(
spiral, CDN, '/' + filepath + '?id=' + str(randint(1, 1000000)))
with open(filepath, 'w') as f:
f.write(js)
return js, tag
def make_snippet(plot):
# js_static_js = "static/js/"
js_static_js = "/usr/lib/python3.4/site-packages/bokeh/server/static/js/"
# js_static_css = "static/css/"
js_static_css = "/usr/lib/python3.4/site-packages/bokeh/server/static/css/"
# js_filename = plot._id + ".js"
# js_path = js_static_js + js_filename
js_path = "output.js"
res = Resources("relative")
res.js_files = [js_static_js + "bokeh.min.js"]
res.css_files = [js_static_css + "bokeh.min.css"]
js, tag = autoload_static(plot, res, js_path)
with open(js_path, "w") as f:
f.write(js)
print("Wrote %s" % js_path)
return tag, plot._id
def make_snippet(plot):
# js_static_js = "static/js/"
js_static_js = "/usr/lib/python3.4/site-packages/bokeh/server/static/js/"
# js_static_css = "static/css/"
js_static_css = "/usr/lib/python3.4/site-packages/bokeh/server/static/css/"
# js_filename = plot._id + ".js"
# js_path = js_static_js + js_filename
js_path = "output.js"
res = Resources("relative")
res.js_files = [js_static_js + "bokeh.min.js"]
res.css_files = [js_static_css + "bokeh.min.css"]
js, tag = autoload_static(plot, res, js_path)
with open(js_path, "w") as f:
f.write(js)
print("Wrote %s" % js_path)
return tag, plot._id
def render_plot():
import numpy as np
from bokeh.embed import autoload_static
from bokeh.plotting import figure
from bokeh.resources import CDN
N = 4000
x = np.random.random(size=N) * 100
y = np.random.random(size=N) * 100
radii = np.random.random(size=N) * 1.5
colors = [
"#%02x%02x%02x" % (int(r), int(g), 150) for r, g in zip(50+2*x, 30+2*y)
]
TOOLS="resize,crosshair,pan,wheel_zoom,box_zoom,reset,tap,save,box_select,poly_select,lasso_select"
p = figure(tools=TOOLS)
p.scatter(x, y, radius=radii,
fill_color=colors, fill_alpha=0.6,
line_color=None)
js, tag = autoload_static(p, CDN, "http://localhost:%s/plot.js" % port)
html = """
<html>
<head>
<title>color_scatter example</title>
</head>
<body>
%s
</body>
</html>
""" % tag
return html, js
def get(self, request, *args, **kwargs):
return self.render_to_json_response({'plot': u''})
# measurement_type_pk = kwargs.get('measurement_type_pk')
# measurement_type = MeasurementType.objects.get(pk=measurement_type_pk)
collection = Collection.objects.get(pk=kwargs.get('pk'))
units = Unit.objects.filter(measurements__match={'measurement_type': measurement_type.pk, 'active': True},
pk__in=[unit.pk for unit in collection.units], active=True)
if units:
bk.hold()
bk.figure(x_axis_type="datetime", tools="pan,wheel_zoom,box_zoom,reset,previewsave")
colors = self.get_colors(len(units))
for i, unit in enumerate(units):
measurements = [(measurement.created_at, measurement.value) for measurement in unit.measurements
if measurement.active and measurement.measurement_type == measurement_type]
measurements.sort(key=lambda measurement: measurement[0])
data = {
'date': [measurement[0] for measurement in measurements],
'value': [measurement[1] for measurement in measurements]
}
bk.line(np.array(data['date']), data['value'], color=colors[i], line_width=2, legend=unit.__unicode__())
bk.grid().grid_line_alpha = 0.3
xax, yax = bk.axis()
xax.axis_label = ugettext('Date')
yax.axis_label = ugettext('Values')
plot = bk.curplot()
bk.get_default_color()
plot.title = ugettext('Measurements type')
# plot.title = ugettext('Measurements type {}'.format(measurement_type.__unicode__()))
js, tag = autoload_static(plot, Resources(mode='server', root_url=settings.STATIC_URL), "")
return self.render_to_json_response({'plot': u'{}<script>{}</script>'.format(tag, js)})
return self.render_to_json_response(ugettext('Not found'), status=404)
def _process_script(source, filename, auxdir, js_name):
# This is lame, but seems to be required for python 2
source = CODING.sub("", source)
# quick and dirty way to inject Google API key
if "GOOGLE_API_KEY" in source:
run_source = source.replace("GOOGLE_API_KEY", GOOGLE_API_KEY)
else:
run_source = source
c = ExampleHandler(source=run_source, filename=filename)
d = Document()
c.modify_document(d)
if c.error:
raise PlotScriptError(c.error_detail)
script_path = join("/scripts", js_name).replace('<<string>>', 'string')
js_path = join(auxdir, js_name).replace('<<string>>', 'string')
js, script = autoload_static(d.roots[0], resources, script_path)
with open(js_path, "w") as f:
f.write(js)
return (script, js, js_path, source)
from bokeh.resources import CDN from bokeh.plotting import figure from bokeh.embed import autoload_static plot = figure() plot.circle([1,2], [3,4]) js, tag = autoload_static(plot, CDN, "some/path") print js print tag
def bladder_report(output_filename, name, input_ply, input_csv):
title = name
f = open(output_filename, 'w')
f.write("""<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8">
<title> {} </title>
</head>
<body>
""".format(title))
df = pd.read_csv(input_csv)
df = df.loc[df['label'] > 0]
p = figure(plot_width=250,
plot_height=250,
x_axis_label='area',
y_axis_label='aniso')
line1 = p.circle('area', 'aniso', size=2, source=df)
p1 = figure(plot_width=250, plot_height=250, x_axis_label='area')
hist, edges = np.histogram(df['area'], density=True, bins=50)
p1.quad(top=hist, bottom=0, left=edges[:-1], right=edges[1:])
p2 = figure(plot_width=250, plot_height=250, x_axis_label='aniso')
hist, edges = np.histogram(df['aniso'], density=True, bins=50)
p2.quad(top=hist, bottom=0, left=edges[:-1], right=edges[1:])
c = gridplot([[p, p1, p2]])
js, tag = autoload_static(
c, CDN,
os.path.splitext(os.path.basename(output_filename))[0] + '-data.js')
g = open(os.path.splitext(output_filename)[0] + '-data.js', 'w')
g.write(js)
f.write('<h2>' + title + '</h2>\n')
f.write('<a href="' + name + '-3d-overlay.html"> 3D View </a>\n')
f.write('<table>\n')
f.write('<tr>\n')
for heading in ['maxproj', 'labels', 'relarea', 'abslogarea', 'aniso']:
f.write('<th>' + heading + '</th>\n')
f.write('</tr>\n')
f.write('<tr>\n')
f.write('<td><a href="../maxproj/' + name + '.png"><img src="../maxproj/' +
name + '-thumb.png" height="200px"></a></td>')
f.write('<td><a href="../image_labels/' + name +
'.png"><img src="../image_labels/' + name +
'-thumb.png" height="200px"></a></td>')
f.write('<td><a href="../image_relarea/' + name +
'.png"><img src="../image_relarea/' + name +
'-thumb.png" height="200px"></a></td>')
f.write('<td><a href="../image_abslogarea/' + name +
'.png"><img src="../image_abslogarea/' + name +
'-thumb.png" height="200px"></a></td>')
f.write('<td><a href="../image_aniso/' + name +
'.png"><img src="../image_aniso/' + name +
'-thumb.png" height="200px"></a></td>')
f.write('</tr>\n')
f.write('</table>\n')
f.write(tag)
df.to_html(f)
f.write('</body>\n')
with open(template_3d, 'r') as g2:
s = g2.read()
t = Template(s)
with open(output_filename[:-5] + '-3d.html', 'w') as f2:
f2.write(
t.substitute({
'name': name,
'filename': name + '.ply',
'csvname': '../cell_data/' + name + '.csv'
}))
with open(template_overlay, 'r') as g2:
s = g2.read()
t = Template(s)
with open(output_filename[:-5] + '-3d-overlay.html', 'w') as f3:
f3.write(
t.substitute({
'name': name,
'filename': name + '.ply',
'filename_extra': name + '_overlay.ply',
'csvname': '../cell_data/' + name + '.csv',
'default_aniso_min': 0,
'default_aniso_max': 1,
'default_area_min': 25,
'default_area_max': 2500,
}))
def iplot(self,
plottype='linear',
jspath=None,
title='',
browser='chrome',
tools=TOOLS,
x_axis_type='datetime',
line_width=2,
background_fill= '#eeeff0',
alpha=0.7,
plot_width=900,
plot_height=400,
xlabel='',
ylabel='',
style='o-'):
"""Writes javascript in given location, embeds it in a html saved in same location, and opens it in a browser
Example
-------
>>> import pandas as pd
>>> import pandasaddons
>>> rdf = pd.RandomDataFrame(index_type='datetime')
>>> rdf.iplot()
>>> rdf = pd.RandomDataFrame(index_type='linear')-0.5
>>> rdf.iplot(plottype='heatmap', xlabel='x', ylabel='y')
"""
if plottype.lower() == 'heatmap':
plot = heatmap_df(self,
tools=tools,
title=title,
alpha=alpha,
plot_width=plot_width,
plot_height=plot_height,
xlabel=xlabel,
ylabel=ylabel,
x_axis_location='above')
else:
plot = plot_df(self,
tools=tools,
title=title,
x_axis_type=x_axis_type,
line_width=line_width,
background_fill=background_fill,
alpha=alpha,
style=style,
plot_width=plot_width,
plot_height=plot_height,
xlabel=xlabel,
ylabel=ylabel)
filename = str(uuid.uuid4())
this_jspath = jspath if jspath else os.environ['TMP']
jsfilename = os.path.join(this_jspath, filename+'.js')
htmlfilename = os.path.join(this_jspath, filename+'.html' )
js, tag = autoload_static(plot, CDN, script_path=jsfilename)
with open(jsfilename, 'w') as f:
f.write(js)
html = '<html><div>'+tag+'</div></html>'
with open(htmlfilename, 'w') as f:
f.write(html)
os.system('start {browser}.exe "{htmlfilename}"'.format(**locals()))
def index(request):
# print(div_tag,div_script)
username = '******'
logintime = '0'
if 'user_name' in request.COOKIES:
username = request.COOKIES['user_name']
else:
return redirect('./../?usr=0', request)
if 'user_name' in request.COOKIES:
username = request.COOKIES['user_name']
if 'login_time' in request.COOKIES:
logintime = request.COOKIES['login_time']
if request.method != 'POST':
print('not post')
return render(request, 'findex.html', locals())
if request.method == 'POST':
print('post')
count = int(request.POST.get('count'))
xl = int(request.POST.get('xl'))
xr = int(request.POST.get('xr'))
yl = int(request.POST.get('yl'))
yr = int(request.POST.get('yr'))
print(xl)
print(xr)
print(yl)
print(yr)
fig = plt.figure()
ax = fig.add_subplot(111)
fig.subplots_adjust(top=0.85)
plt.grid(True)
TOOLS = 'box_select,resize,reset,pan,tap,wheel_zoom,save,hover'
bplot = figure(plot_width=640,
plot_height=480,
tools=TOOLS,
toolbar_location='above')
print(count)
x = []
y = []
z = []
name = []
color = []
contourplot = []
arr = [0] * count
print(arr)
for i in arange(1, count + 1):
tempr = 'result' + str(i)
tempo = 'output' + str(i)
tempc = 'color' + str(i)
result = str(request.POST.get(tempr))
fun = request.POST.get(tempo)
color.append(request.POST.get(tempc))
print(fun)
print(request.POST.get(tempc))
print(result)
print(tempc)
name.append(fun)
a = []
b = []
c = []
if ('x' in result and 'y' in result):
func = lambda x, y: eval(result)
contourplot.append(result)
arr[i - 1] = 1
for i in arange(xl, xr + 1, 0.1):
a.append(i)
for j in arange(yl, yr + 1, 0.1):
b.append(j)
for i in arange(xl, xr + 1, 0.1):
for j in arange(yl, yr + 1, 0.1):
c.append(func(i, j))
x.append(a)
y.append(b)
print(a)
print(b)
print(c)
c = np.array(c)
c = c.reshape((len(a), len(b)))
z.append(c)
elif 'x' in result:
func = lambda x: eval(result)
for i in arange(xl, xr + 1, 0.1):
a.append(i)
b.append(func(i))
x.append(a)
y.append(b)
else:
func = lambda y: eval(result)
for j in arange(yl, yr + 1, 0.1):
a.append(j)
b.append(func(j))
x.append(a)
y.append(b)
ddata = []
k = 0
for i in range(0, len(x)):
if arr[i]:
plt.contour(x[i], y[i], z[k], [1])
k += 1
else:
plt.plot(x[i],
y[i],
marker='.',
markersize=2,
alpha=1,
color=color[i],
label=name[i])
bplot.line(x[i], y[i], color=color[i], legend=name[i])
plt.legend(loc=0)
fig1 = plt.gcf()
if (FileSystemStorage('fplot/static/img/').exists(username +
logintime + '.png')):
os.remove('fplot/static/img/' + username + logintime + 'fplot.png')
fig1.savefig('fplot/static/img/' + username + logintime + 'fplot.png',
dpi=200)
fig1.savefig('fplot/static/img/' + username + logintime + 'fplot.jpg',
dpi=200)
fig1.savefig('fplot/static/img/' + username + logintime + 'fplot.eps',
dpi=200)
fig1.savefig('fplot/static/img/' + username + logintime + 'fplot.pdf',
dpi=200)
fig1.savefig('fplot/static/img/' + username + logintime + 'fplot.svg',
dpi=200)
fig1.savefig('fplot/static/img/' + username + logintime + 'fplot.tiff',
dpi=200)
fig1.savefig('fplot/static/img/' + username + logintime + 'fplot.ps',
dpi=200)
fig1.savefig('fplot/static/img/' + username + logintime + 'fplot.svgz',
dpi=200)
# fig1.savefig('graph/static/img/test.pgf', dpi=200)#latex not installed sudo apt-get install texlive-xetex
fig1.savefig('fplot/static/img/' + username + logintime + 'fplot.jpeg',
dpi=200)
# fig1.savefig('graph/static/img/test.raw', dpi=200)#if needed
fig1.savefig('fplot/static/img/' + username + logintime + 'fplot.tif',
dpi=200)
saved = True
dis = 'static/img/' + username + logintime + 'fplot.png'
# shutil.copyfile('graph/static/img/'+username+logintime+'.png', dis)
saved = True
imagelink = 'img/' + username + logintime + 'fplot.png'
filelink = 'xlsx/' + username + logintime + 'fplot.xlsx'
bplot.legend.location = "top_left"
bplot.legend.background_fill_color = "white"
bplot.legend.background_fill_alpha = 0.5
div_script, div_tag = autoload_static(bplot, CDN, "js")
image = 'img/' + username + logintime + 'fplot'
plotgraph = 1
tabled = 1
return render(request, 'findex.html', locals())
return render(request, 'findex.html', locals())
colormap = {'setosa': 'red', 'versicolor': 'green', 'virginica': 'blue'}
colors = [colormap[x] for x in flowers['species']]
p = figure(title="Iris Morphology")
p.xaxis.axis_label = 'Petal Length'
p.yaxis.axis_label = 'Petal Width'
p.circle(flowers["petal_length"],
flowers["petal_width"],
color=colors,
fill_alpha=0.2,
size=10)
return p
if __name__ == '__main__':
print(
'Opening Tornado app with embedded Bokeh plot on http://localhost:8080/'
)
js, script = autoload_static(make_plot(), CDN, "embed.js")
app = Application([(r"/", IndexHandler, dict(script=script)),
(r"/embed.js", JSHandler, dict(js=js))])
app.listen(8080)
io_loop = IOLoop.current()
io_loop.add_callback(view, "http://localhost:8080/")
io_loop.start()
def test_return_type(self):
r = embed.autoload_static(_embed_test_plot, CDN, "some/path")
self.assertEqual(len(r), 2)
# NEW: create a new plot and share only one range
s3 = figure(width=350, height=350, x_range=s1.x_range, title=None)
s3.square(x, y2, size=10, color="olive", alpha=0.5)
s3.toolbar_location = None;
web_s1_path = "./plots/linked-1.js"
web_s2_path = "./plots/linked-2.js"
web_s3_path = "./plots/linked-3.js"
local_s1_path = os.path.join("..", "..", "build", "plots", "linked-1.js")
local_s2_path = os.path.join("..", "..", "build", "plots", "linked-2.js")
local_s3_path = os.path.join("..", "..", "build", "plots", "linked-3.js")
html_path = os.path.join("..", "..", "build", "index.html")
tags = []
js, tag = autoload_static(s1, CDN, web_s1_path)
script = open(local_s1_path, "w")
script.write(js)
script.close()
tags.append(tag)
js, tag = autoload_static(s2, CDN, web_s2_path)
script = open(local_s2_path, "w")
script.write(js)
script.close()
tags.append(tag)
js, tag = autoload_static(s3, CDN, web_s3_path)
script = open(local_s3_path, "w")
script.write(js)
script.close()
tags.append(tag)
def plot(newest_changes):
filelist = os.listdir('/home/maximilianklein/snapshot_data/{}/'.format(newest_changes))
site_linkss_file = [f for f in filelist if f.startswith('worldmap')][0]
if newest_changes == 'newest-changes':
date_range = site_linkss_file.split('worldmap-index-from-')[1].split('.csv')[0].replace('-',' ')
print(date_range)
csv_to_read = '/home/maximilianklein/snapshot_data/{}/{}'.format(newest_changes,site_linkss_file)
df = pandas.DataFrame.from_csv(csv_to_read)
major = df[df['total'] > 100]
table_html = major.sort('Score', ascending=False).to_html(max_rows=10)
# https://github.com/chdoig/pyladiesatx-bokeh-tutorial
world_countries = wc.data.copy()
country_xs = [world_countries[code]['lons'] for code in world_countries]
country_ys = [world_countries[code]['lats'] for code in world_countries]
country_names = [world_countries[code]['name'] for code in world_countries]
def lookup_wigi(code):
try:
return df.ix[code]['Score']
except KeyError:
return -1
index_vals = np.array([lookup_wigi(code) for code in world_countries])
def fmt(c):
return int(np.nan_to_num(c))
colors = [
"#%02x%02x%02x" % (fmt(r), fmt(g), fmt(b)) for r, g, b in
zip(np.floor(250*(1-index_vals)),
np.floor(200*(1-index_vals)),
np.floor(100*index_vals))]
source = ColumnDataSource(
data=dict(
name=country_names,
wigi_index=[str(idx) for idx in index_vals]
)
)
# setup widgets
TOOLS = "pan,wheel_zoom,box_zoom,reset,hover,save"
title_suffix = 'Changes since {}'.format(date_range) if newest_changes == 'newest-changes' else 'All Time'
p = figure(title="Gender by Country {}".format(title_suffix), tools=TOOLS)
p.patches(country_xs, country_ys, fill_color=colors, source=source)
hover = p.select(dict(type=HoverTool))
hover.point_policy = "follow_mouse"
hover.tooltips = OrderedDict([
("wigi", "@wigi_index"),
("Country", "@name"),
])
js_filename = "gender_by_country_{}.js".format(newest_changes)
script_path = "./assets/js/"
output_path = "./files/assets/js/"
# generate javascript plot and corresponding script tag
js, tag = autoload_static(p, CDN, script_path + js_filename)
with open(output_path + js_filename, 'w') as js_file:
js_file.write(js)
return {'plot_tag':tag, 'table_html':table_html}
def javascript(self) -> str:
"""javascript to save"""
if self._javascript is None:
self._javascript, self._source = autoload_static(
self.figure, self.bokeh_source, self.file_name)
return self._javascript
p.grid.grid_line_color = None
hover = p.select(dict(type=HoverTool))
hover.tooltips = OrderedDict(
[
("name", "@name"),
("atomic number", "@atomic_number"),
("type", "@type"),
("atomic mass", "@mass"),
("CPK color", "$color[hex, swatch]:cpk"),
("electronic configuration", "@electronic"),
]
)
web_path = "./plots/periodic.js"
local_path = os.path.join("..", "..", "build", "plots", "periodic.js")
html_path = os.path.join("..", "..", "build", "index.html")
js, tag = autoload_static(p, CDN, web_path)
script = open(local_path, "w")
script.write(js)
script.close()
html_file = open(html_path, "r")
html = html_file.read()
html_file.close()
html_file = open(html_path, "w")
html_file.write(html.replace("PERIODIC-PLOT", tag))
html_file.close()
def source(self) -> str:
"""The HTML fragment to export"""
if self._source is None:
self._javascript, self._source = autoload_static(
self.figure, self.bokeh_source, self.file_name)
return self._source
def index(request):
# print(div_tag,div_script)
username = '******'
logintime = '0'
if 'user_name' in request.COOKIES:
username = request.COOKIES['user_name']
else:
return redirect('./../?usr=0', request)
if 'user_name' in request.COOKIES:
username = request.COOKIES['user_name']
if 'login_time' in request.COOKIES:
logintime = request.COOKIES['login_time']
if request.method != 'POST':
print('not post')
return render(request, 'pindex.html', locals())
if request.method == 'POST':
print('post')
count = int(request.POST.get('count'))
tl = int(request.POST.get('tl'))
tr = int(request.POST.get('tr'))
print(tl)
print(tr)
fig = plt.figure(figsize=(7, 7))
ax = fig.add_subplot(111)
fig.subplots_adjust(top=0.85)
plt.grid(True)
TOOLS = 'box_select,resize,reset,pan,tap,wheel_zoom,save,hover'
bplot = figure(plot_width=640,
plot_height=480,
tools=TOOLS,
toolbar_location='above')
print(count)
x = []
y = []
name = []
color = []
contourplot = []
arr = [0] * count
print(arr)
for i in arange(1, count + 1):
tempxr = 'resultx' + str(i)
tempxo = 'outputx' + str(i)
tempyr = 'resulty' + str(i)
tempyo = 'outputy' + str(i)
tempc = 'color' + str(i)
resultx = str(request.POST.get(tempxr))
resulty = str(request.POST.get(tempyr))
funx = request.POST.get(tempxo)
funy = request.POST.get(tempyo)
color.append(request.POST.get(tempc))
print(funx)
print(funy)
print(request.POST.get(tempc))
print(resultx)
print(resulty)
print(tempc)
name.append('x:' + (funx) + ';\ny:' + funy)
funcx = lambda t: eval(resultx)
funcy = lambda t: eval(resulty)
t = np.arange(tl, tr, 0.1)
a = funcx(t)
b = funcy(t)
x.append(a)
y.append(b)
ddata = []
k = 0
for i in range(0, len(x)):
plt.plot(x[i],
y[i],
marker='.',
markersize=2,
alpha=1,
color=color[i],
label=name[i])
bplot.line(x[i], y[i], color=color[i], legend=name[i])
plt.legend(loc=0)
fig1 = plt.gcf()
if (FileSystemStorage('pplot/static/img/').exists(username +
logintime + '.png')):
os.remove('pplot/static/img/' + username + logintime + 'pplot.png')
fig1.savefig('pplot/static/img/' + username + logintime + 'pplot.png',
dpi=200)
fig1.savefig('pplot/static/img/' + username + logintime + 'pplot.jpg',
dpi=200)
fig1.savefig('pplot/static/img/' + username + logintime + 'pplot.eps',
dpi=200)
fig1.savefig('pplot/static/img/' + username + logintime + 'pplot.pdf',
dpi=200)
fig1.savefig('pplot/static/img/' + username + logintime + 'pplot.svg',
dpi=200)
fig1.savefig('pplot/static/img/' + username + logintime + 'pplot.tiff',
dpi=200)
fig1.savefig('pplot/static/img/' + username + logintime + 'pplot.ps',
dpi=200)
fig1.savefig('pplot/static/img/' + username + logintime + 'pplot.svgz',
dpi=200)
# fig1.savefig('graph/static/img/test.pgf', dpi=200)#latex not installed sudo apt-get install texlive-xetex
fig1.savefig('pplot/static/img/' + username + logintime + 'pplot.jpeg',
dpi=200)
# fig1.savefig('graph/static/img/test.raw', dpi=200)#if needed
fig1.savefig('pplot/static/img/' + username + logintime + 'pplot.tif',
dpi=200)
saved = True
dis = 'static/img/' + username + logintime + 'pplot.png'
# shutil.copyfile('graph/static/img/'+username+logintime+'.png', dis)
saved = True
imagelink = 'img/' + username + logintime + 'pplot.png'
filelink = 'xlsx/' + username + logintime + 'pplot.xlsx'
bplot.legend.location = "top_left"
bplot.legend.background_fill_color = "white"
bplot.legend.background_fill_alpha = 0.5
div_script, div_tag = autoload_static(bplot, CDN, "js")
image = 'img/' + username + logintime + 'pplot'
plotgraph = 1
tabled = 1
return render(request, 'pindex.html', locals())
self.js = js
def get(self): self.write(self.js)
def make_plot():
colormap = {'setosa': 'red', 'versicolor': 'green', 'virginica': 'blue'}
colors = [colormap[x] for x in flowers['species']]
p = figure(title = "Iris Morphology")
p.xaxis.axis_label = 'Petal Length'
p.yaxis.axis_label = 'Petal Width'
p.circle(flowers["petal_length"], flowers["petal_width"],
color=colors, fill_alpha=0.2, size=10)
return p
if __name__ == '__main__':
print('Opening Tornado app with embedded Bokeh plot on http://localhost:8080/')
js, script = autoload_static(make_plot(), CDN, "embed.js")
app = Application([
(r"/", IndexHandler, dict(script=script)),
(r"/embed.js", JSHandler, dict(js=js))
])
app.listen(8080)
io_loop = IOLoop.current()
io_loop.add_callback(view, "http://localhost:8080/")
io_loop.start()
def test_return_type(self):
r = embed.autoload_static(_embed_test_plot, CDN, "some/path")
self.assertEqual(len(r), 2)
def plotradial(events, userid):
rating_color = OrderedDict([("Actualfear", "#c1ff55"),
("Predictedfear", "#b7feea")])
xr = [x.title for x in events]
i = [i for i, j in enumerate(events)]
y1 = [y.prefearfactor for y in events]
y2 = [y.postfearfactor for y in events]
data = {
'prefearfactor': pd.Series(y1, index=i),
'postfearfactor': pd.Series(y2, index=i)
}
df = pd.DataFrame(data)
width = 500 #400
height = 420 #350
inner_radius = 60 #50
outer_radius = 440 - 20 #360 - 10
minr = 0
maxr = 20
min_pixel = (outer_radius - inner_radius) / (maxr - minr)
big_angle = 2.0 * np.pi / (len(df))
x = np.zeros(len(df))
y = np.zeros(len(df))
#------------------------------------------------------------------------------------
output_file("radialchart.html", title="radial.py example")
p = figure(plot_width=width,
plot_height=height,
title="Imagined vs real fear",
x_axis_type=None,
y_axis_type=None,
toolbar_location=None,
x_range=[-420, 420],
y_range=[-420, 420],
min_border=0,
outline_line_color=None,
background_fill="#f8f8f8",
border_fill="#f8f8f8")
# small wedges
angles = np.pi / 2 - big_angle / 2 - df.index * big_angle
p.annular_wedge(x,
y,
inner_radius,
inner_radius + min_pixel * (df.postfearfactor),
-big_angle + angles,
angles,
color=rating_color['Actualfear'])
p.annular_wedge(x,
y,
inner_radius + min_pixel * (df.postfearfactor),
inner_radius + min_pixel * (df.postfearfactor) +
min_pixel * (df.prefearfactor),
-big_angle + angles,
angles,
color=rating_color['Predictedfear'])
# radial axes
p.annular_wedge(x,
y,
inner_radius,
outer_radius,
-big_angle + angles,
-big_angle + angles,
color="#c2c2d6")
# [x1,x2], [y1,y2] is for rect1 and rect2 x and y start positions (y is inverted)
p.rect([180, 180], [380, 340],
width=30,
height=20,
color=list(rating_color.values()))
#similarly for the legend text
p.text([200, 200], [365, 325],
text=list(rating_color.keys()),
text_font_size="10pt",
text_align="left",
text_baseline="bottom")
p.xgrid.grid_line_color = None
p.ygrid.grid_line_color = None
#generating unique filenames by- adding userid to a rolledindex
"""
global rollingindex
userfilepath = filepath+str(userid)+str(rollingindex.next())+'.js'
"""
userfilepath = filepath + str(userid) + '.js'
js, tag = autoload_static(
p, CDN, '/' + userfilepath + '?id=' + str(randint(1, 1000000)))
with open(userfilepath, 'w') as f:
f.write(js)
return js, tag
def plot(newest_changes):
ra_len = 1 #rolling average lenght
dox = pandas.DataFrame()
interesante = ['female','male','nonbin']
for l in ['b', 'd']:
acro = 'do'+l
filelist = os.listdir('/home/maximilianklein/snapshot_data/{}/'.format(newest_changes))
dox_list = [f for f in filelist if f.startswith(acro)]
dox_file = dox_list[0]
if newest_changes == 'newest-changes':
date_range = dox_file.split('{}-index-from-'.format(acro))[1].split('.csv')[0].replace('-',' ')
csv_to_read = '/home/maximilianklein/snapshot_data/{}/{}'.format(newest_changes,dox_file)
df = pandas.DataFrame.from_csv(csv_to_read)
del df['nan']
df['total'] = df.sum(axis=1)
df['nonbin'] = df['total'] - df['male'] - df['female']
df['fem_per'] = df['female'] / (df['total'])
df['nonbin_per'] = df['nonbin'] / df['total']
for inte in interesante:
dox['{}-{}'.format(acro, inte)] = df[inte]
#ra = pandas.rolling_mean(df['fem_per'], ra_len)
#dox[acro] = ra
time_range = (1400, 2015)
dox = dox[time_range[0]: time_range[1]]
'''dox['Date'] = [dateutil.parser.parse(str(int(x)))
for x in dox['dob'].keys()]'''
tups = zip(['Date of Birth']*3 + ['Date of Death']*3, ['Women', 'Men', 'Non-binary']* 2)
labs = ['-'.join(x) for x in tups]
dox.columns = labs
table_html = dox.to_html(max_rows=20, na_rep="n/a")
title_suffix = 'Changes since {}'.format(date_range) if newest_changes == 'newest-changes' else 'All Time'
p = Line(dox, legend=True, title="Female Ratios {}".format(title_suffix))
#p.below[0].formatter.formats = dict(years=['%Y'])
'''
nonbindox = nonbindox[time_range[0]: time_range[1]]
nonbindox['Date'] = [dateutil.parser.parse(str(int(x)))
for x in nonbindox['dob'].keys()]
p2 = TimeSeries(nonbindox[['dob','dod','Date']], index='Date', legend=True,
title="Non Binary Ratios ".format(title_suffix))
p2.below[0].formatter.formats = dict(years=['%Y'])
p = gridplot([[p1], [p2]], toolbar_location=None)
'''
js_filename = "gender_by_dob_{}.js".format(newest_changes)
script_path = "./assets/js/"
output_path = "./files/assets/js/"
# generate javascript plot and corresponding script tag
js, tag = autoload_static(p, CDN, script_path + js_filename)
with open(output_path + js_filename, 'w') as js_file:
js_file.write(js)
return {'plot_tag':tag, 'table_html':table_html}
#
# <p> Below is a simple plot of stock closing prices </p>
#
# {{ script }}
#
# {{ div }}
#
#</body>
#
#</html>
#""")
p = make_figure(0)
#figJS,figDiv = components(p)
figJS, figDiv = autoload_static(p, CDN, '/static/js/plot.js')
with open('static/js/plot.js', 'w') as f:
f.write(figJS)
#f.close()
#import random
#def plotData():
# j = random.randint(0,1000)
# print j%3
# p = make_figure(j%3)
# figJS, figDiv = autoload_static(p, CDN, '/static/js/plot.js')
# with open('static/js/plot.js', 'w') as f:
# f.write(figJS)
# return figJS, figDiv
## f.close()