Python INLINE.render_css方法代码示例

# 需要导入模块: from bokeh.resources import INLINE [as 别名]
# 或者: from bokeh.resources.INLINE import render_css [as 别名]
def showind():
        
    c0 = request.args['country0']
    
    c1 = request.args['country1']
    
    c2 = request.args['country2']
    
    c3 = request.args['country3']
    
    c4 = request.args['country4']

    countries = [c0, c1, c2, c3, c4]
            
    i0 = request.args['indicator']

    indicator = [i0]
    
    performance = get_indicator(countries,indicator)
    
    chartind = plot_ind(performance)
    
    script,div = components(chartind)
    
    return render_template('showind.html',
                           js_resources=INLINE.render_js(),
                           css_resources=INLINE.render_css(),
                           script=script,
                           div=div)

# 需要导入模块: from bokeh.resources import INLINE [as 别名]
# 或者: from bokeh.resources.INLINE import render_css [as 别名]
def polynomial():
    """ Very simple embedding of a polynomial chart

    """

    # Grab the inputs arguments from the URL
    args = flask.request.args

    # Get all the form arguments in the url with defaults
    color = getitem(args, 'color', 'Black')
    _from = int(getitem(args, '_from', 0))
    to = int(getitem(args, 'to', 10))

    # Create a polynomial line graph with those arguments
    x = list(range(_from, to + 1))
    fig = figure(title="Polynomial")
    fig.line(x, [i ** 2 for i in x], color=colors[color], line_width=2)

    js_resources = INLINE.render_js()
    css_resources = INLINE.render_css()

    script, div = components(fig)
    html = flask.render_template(
        'embed.html',
        plot_script=script,
        plot_div=div,
        js_resources=js_resources,
        css_resources=css_resources,
        color=color,
        _from=_from,
        to=to
    )
    return encode_utf8(html)

# 需要导入模块: from bokeh.resources import INLINE [as 别名]
# 或者: from bokeh.resources.INLINE import render_css [as 别名]
def index(request):    
    plot = figure(responsive=True, tools=[],
               plot_width=500, plot_height=250,
               x_range=(-180, 180), y_range=(-90, 90))
    plot.toolbar_location = None
    plot.axis.visible = None
  
    source = AjaxDataSource(method='GET',
                            data_url='http://localhost:8000/view2d/data/',
                            polling_interval=1000)   
    source.data = dict(x=[], y=[]) # Workaround to initialize the plot
 
    img = load_image("static/images/earth.png") 
    plot.image_rgba(image=[img], x=[-180], y=[-90], dw=[360], dh=[180])
    plot.cross(source=source, x='x', y='y', 
               size=22, line_width=4, color='Orange') # CLU1

    script, div = components(plot, INLINE)
    js_resources = INLINE.render_js()
    css_resources = INLINE.render_css()
    context = {
        'bokeh_script' : script,
        'bokeh_div' : div,
        'js_resources' : js_resources,
        'css_resources' : css_resources
        } 
    return render(request, 'view2d/index.html', context)

# 需要导入模块: from bokeh.resources import INLINE [as 别名]
# 或者: from bokeh.resources.INLINE import render_css [as 别名]
def data_retrieval():


    conn = lite.connect('/Users/shanekenny/PycharmProjects/WiFinder/app/website/WiFinderDBv02.db')
    with conn:
        df = pd.read_sql_query("SELECT W.Log_Count, W.Time, W.Hour, W.Datetime, R.RoomID, R.Capacity, C.ClassID, C.Module, C.Reg_Students, O.Occupancy, O.OccID FROM WIFI_LOGS W JOIN CLASS C ON W.ClassID = C.ClassID JOIN ROOM R ON C.Room = R.RoomID JOIN OCCUPANCY O ON C.ClassID = O.ClassID WHERE R.RoomID = 'B002' AND W.Datetime = '2015-11-12' GROUP BY W.LogID;", conn)


        df['Time'] = df['Time'].apply(pd.to_datetime)
        p = figure(width=800, height=250, x_axis_type="datetime", )
        p.extra_y_ranges = {"foo": Range1d(start=0, end=1)}

        p.line(df['Time'], df['Log_Count'],  color='red',legend='Log Count')
        p.line(df['Time'], df['Reg_Students'], color='green',legend='Registered Students')
        p.line(df['Time'], df['Capacity'], color='blue', legend='Capacity')
        p.line(df['Time'], df['Occupancy']*100, color='orange', legend='Occupancy')

        p.add_layout(LinearAxis(y_range_name="foo"), 'left')

        p2 = figure(width=800, height=250, x_axis_type="datetime", x_range=p.x_range,)
        p2.line(df['Time'], df['Log_Count'], color='red', legend='Log Count')

        r= gridplot([[p, p2]], toolbar_location=None)

        js_resources = INLINE.render_js()
        css_resources = INLINE.render_css()
        script, div = components(r)
        return flask.render_template(
            'explore.html',
            script=script,
            div=div,
            js_resources=js_resources,
            css_resources=css_resources,)

# 需要导入模块: from bokeh.resources import INLINE [as 别名]
# 或者: from bokeh.resources.INLINE import render_css [as 别名]
def second_stock():	
	n = app_stock.vars['name']
	ss = "WIKI/" + n + ".4"
	mydata = quandl.get(ss, encoding='latin1', parse_dates=['Date'], dayfirst=True, index_col='Date', trim_start="2016-05-05", trim_end="2016-06-05", returns = "numpy", authtoken="ZemsPswo-xM16GFxuKP2")
	mydata = pd.DataFrame(mydata)
	#mydata['Date'] = mydata['Date'].astype('datetime64[ns]')
	x = mydata['Date']
	y = mydata['Close']
	p = figure(title="Stock close price", x_axis_label='Date', y_axis_label='close price', plot_height = 300, plot_width = 550)
	p.line(x, y, legend="Price in USD", line_width=3, color = "#2222aa")
	
	
	# Configure resources to include BokehJS inline in the document.
    # For more details see:
    #   http://bokeh.pydata.org/en/latest/docs/reference/resources_embedding.html#bokeh-embed
	js_resources = INLINE.render_js()
	css_resources = INLINE.render_css()

    # For more details see:
    #   http://bokeh.pydata.org/en/latest/docs/user_guide/embedding.html#components
	script, div = components(p, INLINE)
    
	html = flask.render_template(
		'stockgraph.html',
		ticker = app_stock.vars['name'],
		plot_script=script,
		plot_div=div,
		js_resources=js_resources,
		css_resources=css_resources,
	)
	return encode_utf8(html)

# 需要导入模块: from bokeh.resources import INLINE [as 别名]
# 或者: from bokeh.resources.INLINE import render_css [as 别名]
def showbusscore():
    
    c0 = request.args['country0']
    
    c1 = request.args['country1']
    
    c2 = request.args['country2']
    
    c3 = request.args['country3']
    
    c4 = request.args['country4']

    countries = [c0, c1, c2, c3, c4]
    
    i0 = "IC.BUS.EASE.XQ"
    
    indicators = [i0]
    
    dataframes = create_dataframes(countries,indicators)
    
    score = get_mean(dataframes)
    
    chartsco = plot_score(score)
    
    script,div = components(chartsco)
    
    return render_template('showscore.html',
                           js_resources=INLINE.render_js(),
                           css_resources=INLINE.render_css(),
                           script=script,
                           div=div)

# 需要导入模块: from bokeh.resources import INLINE [as 别名]
# 或者: from bokeh.resources.INLINE import render_css [as 别名]
def dataframe_to_linegraph(dataframe, show_columns, title='graph'):
    '''Convert a dataframe to a bokeh line graph'''

    thisplot = figure(
        tools="pan,box_zoom,reset,save",
        title=title,
        x_axis_type="datetime",
        x_axis_label='Month',
        y_axis_label='Count',
        plot_width=1200,
    )

    yvals = [x for x in dataframe.index.tolist()]

    idx = 0
    for col, show in show_columns:
        if not show:
            continue

        width = 2

        try:
            color = Paired[12][idx]
        except IndexError:
            color = Paired[12][-1]

        kwargs = {
            'legend': col,
            'line_width': width,
            'line_color': color
        }
        idx += 1

        xvals = dataframe[col].tolist()
        line = thisplot.line(
            yvals,
            xvals,
            **kwargs
        )

        thisplot.add_tools(
            HoverTool(
                renderers=[line],
                tooltips=[
                    ('Name', col),
                    ('Color', '<span class="bk-tooltip-color-block" '
                     'style="background-color:{}"> </span>'.
                     format(kwargs['line_color'])),
                    ('count', "@y{int}"),
                ]
            )
        )

    thisplot.legend.location = "top_left"
    plot_script, plot_div = components(thisplot)
    js_resources = INLINE.render_js()
    css_resources = INLINE.render_css()

    return (plot_script, plot_div, js_resources, css_resources)

# 需要导入模块: from bokeh.resources import INLINE [as 别名]
# 或者: from bokeh.resources.INLINE import render_css [as 别名]
def save(fig):
    '''
    Saves bokeh plots to HTML in ./Bokeh_plots
    '''
    ## Set up directory for the plot files
    plots_dir = os.path.join('.','Bokeh_plots')
    if not os.path.exists(plots_dir):
        os.makedirs(plots_dir)
    filename = datetime.datetime.now().strftime('%Y-%m-%d_%H-%M-%S')+'.html'
    figfile = os.path.join(plots_dir, filename)

    ## Save and show figure
    from jinja2 import Template

    from bokeh.embed import components
    from bokeh.resources import INLINE

    plots = {'fig':fig}
    script, div = components(plots)

    template = Template('''<!DOCTYPE html>
    <html lang="en">
        <head>
            <meta charset="utf-8">
            <title>Bokeh Scatter Plots</title>
            {{ js_resources }}
            {{ css_resources }}
            {{ script }}
            <style>
                .embed-wrapper {
                    width: 50%;
                    height: 400px;
                    margin: auto;
                }
            </style>
        </head>
        <body>
            {% for key in div.keys() %}
                <div class="embed-wrapper">
                {{ div[key] }}
                </div>
            {% endfor %}
        </body>
    </html>
    ''')
    js_resources = INLINE.render_js()
    css_resources = INLINE.render_css()

    bokeh_html = template.render(js_resources=js_resources,
                       css_resources=css_resources,
                       script=script,
                       div=div)

    with open(figfile, 'w') as f:
        f.write(bokeh_html)

# 需要导入模块: from bokeh.resources import INLINE [as 别名]
# 或者: from bokeh.resources.INLINE import render_css [as 别名]
def app_parse():
    ticker_input = app.vars['ticker']
	# ticker_input = raw_input('Please enter a stock ticker code (e.g., AAPL): ')
    quandl_url = 'https://www.quandl.com/api/v3/datasets/WIKI/'
    api_key = '_Dvc2yU_qTfyYtTzsqFd'
    csv_ext = '.csv'
    json_ext = '.json'
    input_url = quandl_url + ticker_input + json_ext
    input_csv = quandl_url + ticker_input + csv_ext

    r = requests.get(input_url)

    data = json.loads(r.text)
    pd_data = pd.read_csv(input_csv,parse_dates=['Date'])
    x = data["dataset"]["data"]
    data_rows = len(x)
    data_rows_good = np.zeros(data_rows)
    start_date = datetime.now().date() + timedelta(-30)

    booleans = []
    for date_row in range(0,len(pd_data.Date)):
       # ticker_date = datetime.strptime(pd_data.Date[date_row],'%Y-%m-%d').date()
       ticker_date = pd_data.Date[date_row].date()
       if start_date < ticker_date:
           booleans.append(True)
       else:
           booleans.append(False)

    closing_price = pd_data.Close[booleans]

    # output_file("datetime.html")
    # create a new plot with a datetime axis type
    p = figure(width=500, height=500, x_axis_type="datetime")
    p.line(pd_data.Date[booleans], pd_data.Close[booleans], color='red', alpha=0.5)

	js_resources = INLINE.render_js()
	css_resources = INLINE.render_css()
	
	script, div = components(p, INLINE)
    
	html = flask.render_template(
		'datetime.html',
		ticker = app_stock.vars['name'],
		plot_script=script,
		plot_div=div,
		js_resources=js_resources,
		css_resources=css_resources,
	)
	return encode_utf8(html)

# 需要导入模块: from bokeh.resources import INLINE [as 别名]
# 或者: from bokeh.resources.INLINE import render_css [as 别名]
def polynomial():
    """ Very simple embedding of a polynomial chart

    """



    # connect to google spreadsheet and get sheet
    scope = ['https://spreadsheets.google.com/feeds']
    credentials = ServiceAccountCredentials.from_json_keyfile_name('oauth-keyfile.json', scopes=scope)
    gc = gspread.authorize(credentials)
    responses = gc.open("Homework Histogram (Responses)")
    responses = responses.worksheet("Form Responses 1")

    # create plot html elements
    data = pd.DataFrame(responses.get_all_records())
    # hist = Histogram(data, values='Question 1')

    # create a list of plots
    scripts = []
    divs = []
    for question in ['Question 1', 'Question 2']:
        hist = Histogram(data, values=question)
        script, div = components(hist, INLINE)
        scripts.append(script)
        divs.append(div)



    # Configure resources to include BokehJS inline in the document.
    # For more details see:
    #   http://bokeh.pydata.org/en/latest/docs/reference/resources_embedding.html#bokeh-embed
    js_resources = INLINE.render_js()
    css_resources = INLINE.render_css()
    # script, div = components(hist, INLINE)

    # For more details see:
    #   http://bokeh.pydata.org/en/latest/docs/user_guide/embedding.html#components
    html = flask.render_template(
        'embed.html',
        scripts = scripts,
        divs=divs,
        js_resources=js_resources,
        css_resources=css_resources,
    )
    return encode_utf8(html)

# 需要导入模块: from bokeh.resources import INLINE [as 别名]
# 或者: from bokeh.resources.INLINE import render_css [as 别名]
def index():
    if request.method == 'GET':
        return render_template('index.html')
    else:
        app.vars['Company_Name'] = request.form['ticker']
        if not app.vars['Company_Name']:
            return render_template('error.html')
        app.vars['features'] = request.form.getlist('features')        
        Company_Name=app.vars['Company_Name']
        API_url='https://www.quandl.com/api/v3/datasets/WIKI/%s.csv?api_key=a5-JLQBhNfxLnwxfXoUE' % Company_Name
        r = requests.get(API_url)
        if r.status_code == 404:
            return render_template('error.html')
        data = pd.read_csv(API_url,parse_dates=['Date'])
        Colors=["blue","green","yellow","red"]
        Color_index=0
        target_data=data.ix[:,['Open','Adj. Open','Close','Adj. Close']]
        p=figure(x_axis_type="datetime")
        p.xaxis.axis_label = 'Date'
        p.title = 'Data from Quandle WIKI set'
        if 'Close' in app.vars['features']:
            p.line(x=data['Date'],y=target_data['Close'],legend="%s:Close" % Company_Name, line_color=Colors[Color_index])
            Color_index = Color_index +1
        if 'Adj. Close' in app.vars['features']:
            p.line(x=data['Date'],y=target_data['Adj. Close'],legend="%s:Adj. Close" % Company_Name, line_color=Colors[Color_index])
            Color_index = Color_index +1
        if 'Open' in app.vars['features']:
            p.line(x=data['Date'],y=target_data['Open'],legend="%s:Open" % Company_Name, line_color=Colors[Color_index])
            Color_index = Color_index +1
        if 'Adj. Open' in app.vars['features']:
            p.line(x=data['Date'],y=target_data['Adj. Open'],legend="%s:Adj. Open" % Company_Name, line_color=Colors[Color_index])


        js_resources = INLINE.render_js()
        css_resources = INLINE.render_css()
        script, div = components(p, INLINE)
        html = flask.render_template(
            'embed.html',
            plot_script=script,
            plot_div=div,
            js_resources=js_resources,
            css_resources=css_resources,
            Company_Name= Company_Name
        )
        return encode_utf8(html)

# 需要导入模块: from bokeh.resources import INLINE [as 别名]
# 或者: from bokeh.resources.INLINE import render_css [as 别名]
def index():

    if request.method == 'POST':
        # Get the entered keywords
        keywords = request.form["keywords"]
        #keywords = [keyword.strip() for keyword in keywords.split(',') if len(keyword) > 0]
        keywords = [keyword.strip() for keyword in keywords.split(',') if len(keyword.strip()) > 0]
        keywords = keywords[:len(COLORS)] # prevent too many keywords
        
        # Get the location data
        user_location = (request.form['latitude'], request.form['longitude'])

        logger.info('{} | {}'.format(user_location, keywords))

        fig = make_fig(keywords)
        
        # Build the bokeh plot resources
        # https://github.com/bokeh/bokeh/tree/master/examples/embed/simple
        js_resources = INLINE.render_js()
        css_resources = INLINE.render_css()
        script, div = components(fig, INLINE)
        
        # Get recent comments matching the keywords
        recent_comments = get_matching_comments_2(keywords, user_location)
        
        # special case if no keywords entered - show 'All' comment counts
        if not keywords:
            keywords = ['All']

        # Build the web page
        html = render_template(
            'index.html',
            keywords = ', '.join(keyword.title() for keyword in keywords),
            plot_script=script,
            plot_div=div,
            js_resources=js_resources,
            css_resources=css_resources,
            jobs=recent_comments,
        )
        return html
    return render_template('index.html')

# 需要导入模块: from bokeh.resources import INLINE [as 别名]
# 或者: from bokeh.resources.INLINE import render_css [as 别名]
def plot(content, data=[]):
    x = list(range(0, 100 + 1))
    fig = figure(title="Polynomial")
    print(dir(fig))
    #fig.line(x, [i ** 2 for i in x], line_width=2)
    #fig.hbar(data['requested_by_name'], data['usage'])
    p=Bar(data, 'requested_by_name', values='usage')

    js_resources = INLINE.render_js()
    css_resources = INLINE.render_css()

    script, div = components(p)
    html = render_template(
        'overview.html',
        plot_script=script,
        plot_div=div,
        js_resources=js_resources,
        css_resources=css_resources,
        content=content,
    )
    return encode_utf8(html)

# 需要导入模块: from bokeh.resources import INLINE [as 别名]
# 或者: from bokeh.resources.INLINE import render_css [as 别名]
def bokeh_bild(range=4800):
    data = bk_plot_timeline(
        LoadFromSQL(
            range,
            app.config['DATABASE_LOCATION'],
            'VS1_GT1',
            'VS1_GT3',
            'VS1_GT2',
            'VS1_Setpoint'
            )
        )
    print(data)
    plot_script, plot_div = components(data, INLINE)
    js_resources = INLINE.render_js()
    css_resources = INLINE.render_css()

    return render_template(
        'bild.html',
        script=plot_script,
        div=plot_div,
        js_resources=js_resources,
        css_resources=css_resources)

# 需要导入模块: from bokeh.resources import INLINE [as 别名]
# 或者: from bokeh.resources.INLINE import render_css [as 别名]
def polynomial():
    """ Very simple embedding of a polynomial chart

    """

    # Grab the inputs arguments from the URL
    # This is automated by the button
    args = flask.request.args

    # Get all the form arguments in the url with defaults
    color = colors[getitem(args, 'color', 'Black')]
    _from = int(getitem(args, '_from', 0))
    to = int(getitem(args, 'to', 10))

    # Create a polynomial line graph
    x = list(range(_from, to + 1))
    fig = figure(title="Polynomial")
    fig.line(x, [i ** 2 for i in x], color=color, line_width=2)

    # Configure resources to include BokehJS inline in the document.
    # For more details see:
    #   http://bokeh.pydata.org/en/latest/docs/reference/resources_embedding.html#bokeh-embed
    js_resources = INLINE.render_js()
    css_resources = INLINE.render_css()

    # For more details see:
    #   http://bokeh.pydata.org/en/latest/docs/user_guide/embedding.html#components
    script, div = components(fig, INLINE)
    html = flask.render_template(
        'embed.html',
        plot_script=script,
        plot_div=div,
        js_resources=js_resources,
        css_resources=css_resources,
        color=color,
        _from=_from,
        to=to
    )
    return encode_utf8(html)