def make_plot(xname, yname, xax=False, yax=False):
mbl = 40 if yax else 0
mbb = 40 if xax else 0
plot = Plot(
x_range=xdr, y_range=ydr, background_fill_color="#efe8e2",
border_fill_color='white', plot_width=200 + mbl, plot_height=200 + mbb,
min_border_left=2+mbl, min_border_right=2, min_border_top=2, min_border_bottom=2+mbb)
circle = Circle(x=xname, y=yname, fill_color="color", fill_alpha=0.2, size=4, line_color="color")
r = plot.add_glyph(source, circle)
xdr.renderers.append(r)
ydr.renderers.append(r)
xticker = BasicTicker()
if xax:
xaxis = LinearAxis()
xaxis.axis_label = xname
plot.add_layout(xaxis, 'below')
xticker = xaxis.ticker
plot.add_layout(Grid(dimension=0, ticker=xticker))
yticker = BasicTicker()
if yax:
yaxis = LinearAxis()
yaxis.axis_label = yname
yaxis.major_label_orientation = 'vertical'
plot.add_layout(yaxis, 'left')
yticker = yaxis.ticker
plot.add_layout(Grid(dimension=1, ticker=yticker))
plot.add_tools(PanTool(), WheelZoomTool())
return plot
def make_plot(xname, yname, xax=False, yax=False):
mbl = 40 if yax else 0
mbb = 40 if xax else 0
plot = Plot(
x_range=xdr, y_range=ydr, background_fill_color="#efe8e2",
border_fill_color='white', plot_width=200 + mbl, plot_height=200 + mbb,
min_border_left=2+mbl, min_border_right=2, min_border_top=2, min_border_bottom=2+mbb)
circle = Circle(x=xname, y=yname, fill_color="color", fill_alpha=0.2, size=4, line_color="color")
r = plot.add_glyph(source, circle)
xdr.renderers.append(r)
ydr.renderers.append(r)
xticker = BasicTicker()
if xax:
xaxis = LinearAxis()
xaxis.axis_label = xname
plot.add_layout(xaxis, 'below')
xticker = xaxis.ticker
plot.add_layout(Grid(dimension=0, ticker=xticker))
yticker = BasicTicker()
if yax:
yaxis = LinearAxis()
yaxis.axis_label = yname
yaxis.major_label_orientation = 'vertical'
plot.add_layout(yaxis, 'left')
yticker = yaxis.ticker
plot.add_layout(Grid(dimension=1, ticker=yticker))
plot.add_tools(PanTool(), WheelZoomTool())
return plot
def make_scatter(source, data, xname, yname, xax=False, yax=False):
# sets range and borders for plot
xdr = DataRange1d(bounds=None)
ydr = DataRange1d(bounds=None)
mbl = 40 if yax else 0
mbb = 40 if xax else 0
plot = figure(x_range=xdr,
y_range=ydr,
background_fill_color="#efe8e2",
border_fill_color='white',
plot_width=200 + mbl,
plot_height=200 + mbb,
min_border_left=2 + mbl,
min_border_right=2,
min_border_top=2,
min_border_bottom=2 + mbb)
# plots points
circle = Circle(x=xname,
y=yname,
fill_color="blue",
fill_alpha=0.2,
size=4,
line_color="blue")
plot.add_glyph(source, circle)
# calculates and plots regression line
a, b, mse = make_regression_line(data, xname, yname)
mse_mean = mse.mean()
print(xname, yname, mse_mean)
x = data[xname]
plot.line(x, a * x + b, color='red')
plot.axis.visible = False
# makes axis according to place in matrix
xticker = BasicTicker()
if xax:
xaxis = LinearAxis()
xaxis.axis_label = xname
plot.add_layout(xaxis, 'below')
xticker = xaxis.ticker
plot.add_layout(Grid(dimension=0, ticker=xticker))
yticker = BasicTicker()
if yax:
yaxis = LinearAxis()
yaxis.axis_label = yname
yaxis.major_label_orientation = 'vertical'
plot.add_layout(yaxis, 'left')
yticker = yaxis.ticker
plot.add_layout(Grid(dimension=1, ticker=yticker))
return plot
def make_dist(data, xname, xax=False, yax=False):
# sets ranges and borders for plot
xdr = DataRange1d(bounds=None)
ydr = DataRange1d(bounds=None)
mbl = 40 if yax else 0
mbb = 40 if xax else 0
TOOLS = "hover, save, reset"
plot = figure(x_range=xdr,
y_range=ydr,
tools=TOOLS,
x_axis_label="",
y_axis_label="",
background_fill_color="#E8DDCB",
plot_width=200 + mbl,
plot_height=200 + mbb,
min_border_left=2 + mbl,
min_border_right=2,
min_border_top=2,
min_border_bottom=2 + mbb)
# makes histogram
measured = data[xname]
hist, edges = np.histogram(measured, density=True, bins=50)
# plots histogram
plot.quad(top=hist,
bottom=0,
left=edges[:-1],
right=edges[1:],
fill_color="#036564",
line_color="#033649")
# makes axis according to place in matrix
plot.axis.visible = False
xticker = BasicTicker()
if xax:
xaxis = LinearAxis()
xaxis.axis_label = xname
plot.add_layout(xaxis, 'below')
xticker = xaxis.ticker
yticker = BasicTicker()
if yax:
yaxis = LinearAxis()
yaxis.axis_label = xname
yaxis.major_label_orientation = 'vertical'
plot.add_layout(yaxis, 'left')
yticker = yaxis.ticker
plot.legend.location = "center_right"
plot.legend.background_fill_color = "darkgrey"
return plot
def metrix_plot(xname,
yname,
xax=False,
yax=False,
xdr=None,
ydr=None,
source=None):
mbl = 40 if yax else 0
mbb = 40 if xax else 0
plot = Plot(x_range=xdr,
y_range=ydr,
plot_width=200 + mbl,
plot_height=200 + mbb,
min_border_left=1 + mbl,
min_border_right=1,
min_border_top=1,
min_border_bottom=1 + mbb)
circle = Circle(x=xname,
y=yname,
fill_color="color",
size=4,
line_color="color")
r = plot.add_glyph(source, circle)
xdr.renderers.append(r)
ydr.renderers.append(r)
xticker = BasicTicker()
if xax:
xaxis = LinearAxis()
xaxis.axis_label = xname
plot.add_layout(xaxis, 'below')
xticker = xaxis.ticker
plot.add_layout(Grid(dimension=0, ticker=xticker))
yticker = BasicTicker()
if yax:
yaxis = LinearAxis()
yaxis.axis_label = yname
yaxis.major_label_orientation = 'vertical'
plot.add_layout(yaxis, 'left')
yticker = yaxis.ticker
plot.add_layout(Grid(dimension=1, ticker=yticker))
plot.add_tools(PanTool(), WheelZoomTool(), BoxZoomTool(), SaveTool(),
ResetTool())
return plot
def show_coeff(data, xname, yname, xax=False, yax=False):
# sets ranges and borders of plot
xdr = DataRange1d(bounds=None)
ydr = DataRange1d(bounds=None)
mbl = 40 if yax else 0
mbb = 40 if xax else 0
plot = figure(x_range=xdr,
y_range=ydr,
background_fill_color="#efe8e2",
border_fill_color='white',
plot_width=200 + mbl,
plot_height=200 + mbb,
min_border_left=2 + mbl,
min_border_right=2,
min_border_top=2,
min_border_bottom=2 + mbb)
# calculates and plots correlation coefficient
measured1 = data[xname]
measured2 = data[yname]
coeff = np.corrcoef(measured1, measured2)
coeff = round(coeff[0][1], 3)
plot.text(text_align='center',
text_baseline='middle',
text=[coeff],
text_font_size='35pt',
x=0,
y=-5)
# adjust axes according to place in matrix
plot.axis.visible = False
xticker = BasicTicker()
if xax:
xaxis = LinearAxis()
xaxis.axis_label = xname
plot.add_layout(xaxis, 'below')
xticker = xaxis.ticker
yticker = BasicTicker()
if yax:
yaxis = LinearAxis()
yaxis.axis_label = yname
yaxis.major_label_orientation = 'vertical'
plot.add_layout(yaxis, 'left')
yticker = yaxis.ticker
plot.add_layout(Grid(dimension=0, ticker=xticker))
plot.add_layout(Grid(dimension=1, ticker=yticker))
return plot
def init_mention_plot():
cprint('%s: init @ mentios barcharts...' % TAG, 'yellow', attrs=['bold'])
global mention_count
global mention_barplot
mention_count = count_mentions()
y = []
mentions = []
for (mention, freq) in mention_count:
y.append(freq)
mentions.append(mention)
x = np.arange(len(mentions))
source = ColumnDataSource(dict(
x=x,
top=y,
))
glyph = VBar(x='x', top='top', bottom=0, width=0.85, fill_color='#ff7f0e')
mention_barplot.add_glyph(source, glyph)
xaxis = LinearAxis()
xaxis.ticker = x
xaxis.major_label_overrides = {
i: mention
for i, mention in enumerate(mentions)
}
mention_barplot.add_layout(xaxis, 'below')
mention_barplot.xaxis.major_label_orientation = +np.pi / 2
yaxis = LinearAxis()
yaxis.axis_label = 'Overall number of @ mentions'
yaxis.axis_label_text_font_size = '14pt'
yaxis.ticker = np.linspace(0, max(y), 11, dtype=np.int)[1:]
mention_barplot.add_layout(yaxis, 'left')
mention_barplot.add_layout(Grid(dimension=0, ticker=xaxis.ticker))
mention_barplot.add_layout(Grid(dimension=1, ticker=yaxis.ticker))
def add_axes(self, plot, label): xaxis = LinearAxis() yaxis = LinearAxis() yaxis.axis_label = label plot.add_layout(xaxis, 'below') plot.add_layout(yaxis, 'left') plot.add_layout(Grid(dimension=0, ticker=xaxis.ticker)) plot.add_layout(Grid(dimension=1, ticker=yaxis.ticker)) return plot
def add_axes(self, plot, label):
xaxis = LinearAxis()
yaxis = LinearAxis()
yaxis.axis_label = label
plot.add_layout(xaxis, 'below')
plot.add_layout(yaxis, 'left')
plot.add_layout(Grid(dimension=0, ticker=xaxis.ticker))
plot.add_layout(Grid(dimension=1, ticker=yaxis.ticker))
return plot
def init_user_plot():
cprint('%s: init @ users barcharts...' % TAG, 'yellow', attrs=['bold'])
global user_count
global user_barplot
user_count = count_users()
y = []
users = []
for (user, freq) in user_count.items():
y.append(freq)
users.append(user)
x = np.arange(len(users))
wlist = []
for user in users:
prefixes = ['@' + user]
for prefix, freq in sorted(user_tweet_freq[user].items(),
key=lambda kv: kv[1],
reverse=True)[:10]:
prefixes.append(' %s:%d' % (prefix, freq))
wlist.append(list(prefixes))
source = ColumnDataSource(dict(x=x, top=y, wlist=wlist))
glyph = VBar(x='x', top='top', bottom=0, width=0.85, fill_color='#1f77b4')
user_barplot.add_glyph(source, glyph)
xaxis = LinearAxis()
xaxis.ticker = x
xaxis.major_label_overrides = {
i: '@' + user
for i, user in enumerate(users)
}
#xaxis.major_label_standoff = -35
user_barplot.add_layout(xaxis, 'below')
user_barplot.xaxis.major_label_orientation = +np.pi / 2
yaxis = LinearAxis()
yaxis.axis_label = 'Overall number of tweets per @'
yaxis.axis_label_text_font_size = '14pt'
yaxis.ticker = np.linspace(0, max(y), 11, dtype=np.int)[1:]
user_barplot.add_layout(yaxis, 'left')
user_barplot.add_layout(Grid(dimension=0, ticker=xaxis.ticker))
user_barplot.add_layout(Grid(dimension=1, ticker=yaxis.ticker))
def generate_seir_chart(options, series):
# output to static HTML file
# output_file(series.location_name + ".html")
# create a new plot with a title and axis labels
p = figure(title=series.location_name, x_axis_label='Days', y_axis_label='Population')
p.y_range = Range1d(0, 1.1)
plot_seir_series(options, series, p, 'solid', None)
if options.er or options.sr or options.ir0:
p.extra_y_ranges = {"r_range": Range1d(start=0, end=np.max(series.er) * 1.1)}
extra_axis = LinearAxis(y_range_name="r_range")
extra_axis.axis_label = "R"
p.add_layout(extra_axis, 'right')
# Remove initial values for er and ir0
index = 0
for index in range(len(series.i)):
if series.i[index] != 0:
log("Breaking from i at index=", index)
log("Previous values of er: ", series.er[:index])
log("Next values of er: ", series.er[index:index+10])
break
index = index + 1
if options.er:
p.line(range(index, len(series.er)), series.er[index:], legend_label="Effective r", line_width=2, line_color="grey", y_range_name="r_range")
if options.sr:
p.line(range(len(series.sr)), series.sr, legend_label="Standard r", line_width=2, line_color="red", line_dash='dashed', y_range_name="r_range")
if options.ir0:
p.line(range(index, len(series.ir0)), series.ir0[index:], legend_label="Implicit r0", line_width=2, line_color="grey", line_dash='dashed', y_range_name="r_range")
p.legend.location = "top_right"
p.legend.click_policy = "hide"
return p
x_axis_label='wavelength(nm)',
y_axis_label= 'polarizability',
# x_axis_type='linear',
# y_axis_type='linear',
x_axis_type = None,
y_axis_type = None,
tools = "pan,wheel_zoom,box_zoom,zoom_in,zoom_out,save,hover,crosshair"
)
p.x_range=Range1d(500, 1800)
p.y_range=Range1d(-5000, 5000)
ticker = SingleIntervalTicker(interval=100, num_minor_ticks=1100)
xaxis = LinearAxis(ticker=ticker)
# p.xaxis.visible = True
xaxis.axis_label = "wavelength (nm)"
xaxis.axis_line_width = 1
xaxis.axis_label_text_font_style = "italic"
p.add_layout(xaxis, 'below')
tickery = SingleIntervalTicker(interval=1000, num_minor_ticks=-5000)
yaxis = LinearAxis(ticker=tickery)
# Disable scientific notation on yaxis
yaxis.formatter.use_scientific = False
yaxis.axis_label = "polarizability (a.u.)"
yaxis.axis_line_width = 1
yaxis.axis_label_text_font_style = "italic"
p.add_layout(yaxis, 'left')
x_slider = RangeSlider(start=500, end=1800, value=(500,1800), step=.1, title="Wavelength(nm)",width=250 )
y_slider = RangeSlider(start=-5000, end=5000, value=(-5000,5000), step=.1, title="polarizability (a.u.)",width=250 )
def visualize(data, columnName='Mean'):
output_file("%s_trends.html" % columnName)
f = lambda x: str(x)[:10]
data["datetime_s"] = map(f, data.index.date)
cds = ColumnDataSource(data)
print(cds.data.keys())
TOOLS = "crosshair,pan,wheel_zoom,box_zoom,reset,previewsave"
p = figure(plot_width=800,
plot_height=400,
title="BTC %s vs BTC Trend" % columnName,
x_axis_type="datetime",
tools=TOOLS)
r = p.line('Date',
columnName,
line_width=2,
legend="BTC Prices" if columnName == 'Mean' else "BTC %s" %
columnName,
source=cds)
p.extra_y_ranges = {
'Trend': Range1d(data['Trend'].min(), data['Trend'].max())
}
p.line('Date',
'Trend',
color="red",
y_range_name="Trend",
line_width=2,
legend="BTC Trends",
source=cds)
yaxis2 = LinearAxis(y_range_name="Trend")
yaxis2.axis_label = "BTC Trend"
p.add_layout(yaxis2, 'right')
p.xaxis.axis_label = 'Date'
p.yaxis[0].axis_label = 'BTC %s' % columnName
if columnName == "Mean":
p.yaxis[0].formatter = NumeralTickFormatter(format="$0.00")
else:
p.yaxis[0].formatter = NumeralTickFormatter(format="0,0")
if columnName == "Mean":
tool_tip_col = 'Price'
tool_tip_val = '$@Mean{0,0}'
tool_tip_fmt = 'printf'
else:
tool_tip_col = columnName
tool_tip_val = '@%s{0,0}' % columnName
tool_tip_fmt = 'numeral'
p.add_tools(
HoverTool(tooltips=[
("Date", '@datetime_s'),
(tool_tip_col, tool_tip_val),
('Trend', '@Trend'),
],
formatters={
"Date": "datetime",
tool_tip_col: tool_tip_fmt,
"Trend": "numeral"
},
renderers=[r],
mode='vline'))
p.legend.location = "top_left"
show(p)
# Create a new plot and add a renderer
top = Figure(tools=tools, title=None, x_range=day_range,
**figure_style_kws)
top.line('day', 'S', source=source,
line_color=colors[0], line_width=3, line_cap='round')
top.y_range = Range1d(0., 40.)
top.yaxis.axis_label = "Salinity (g/kg)"
top.xaxis.axis_label_text_font_size = label_fontsize
top.yaxis.axis_label_text_font_size = label_fontsize
# overlay volume level chart to salinity
tc = "MediumBlue" # tide color
tide_range = Range1d(start=0, end=15)
tide_axis = LinearAxis(y_range_name="Z")
tide_axis.axis_label = "Tidal Height (m)"
tide_axis.axis_label_text_color = tc
tide_axis.axis_label_text_font_size = label_fontsize
tide_axis.major_tick_line_color = tc
tide_axis.major_label_text_color = tc
tide_axis.minor_tick_line_alpha = 0.
top.extra_y_ranges = {"Z": tide_range}
# top.line('day', 'Z', source=source,
# line_color=tc, line_width=2, line_cap='round')
top.add_layout(tide_axis, "right")
top.line('day', 'Z', source=source,
line_color=tc, line_width=2, line_cap='round',
y_range_name="Z")
mid = Figure(title=None, x_range=top.x_range,
