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 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))
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,
toolbar_location=None, **figure_style_kws)
mid.line('day', 'N', source=source,
