def plot_pop(self):
pop_size, rdm_individuals, populations = self.get_population_data()
#CHART 1
x = range(len(pop_size))
chart1 = pygal.XY(style=DarkStyle,
legend_at_bottom=True,
show_dots=False,
fill=True,
include_x_axis=True)
chart1.title = str('Population size over ' + str(len(pop_size)) +
' generations.')
chart1.add('Population size', list(zip(x, pop_size)))
chart1.render_to_file('charts/Sexual_reproduction_1.svg')
#CHART 2
genes = sorted(self.get_genes_data(rdm_individuals))
x2 = map(str, range(len(genes)))
chart2 = pygal.StackedBar(style=DarkStyle,
legend_at_bottom=True,
truncate_label=-1)
chart2.title = (
'Genome of a random individual from the population over \n ' +
str(len(pop_size)) + ' generations. \n Monogamy: ' +
str(self.population.monogamy) + ', Long term: ' +
str(self.population.long_term))
chart2.x_labels = self.get_x_lables(pop_size)
for x2_, genes_ in genes:
chart2.add(x2_, genes_)
chart2.render_to_file('charts/Sexual_reproduction_2.svg')
#CHART 3
for population in populations:
if populations.index(population) % 50 == 0:
genes = sorted(self.get_genes_data(population))
x2 = map(str, range(len(genes)))
chart2 = pygal.StackedBar(style=DarkStyle,
legend_at_bottom=True,
truncate_label=-1)
chart2.title = ('Gentoype of each individual of generation #' +
str(populations.index(population)) +
'. \n Monogamy: ' +
str(self.population.monogamy) +
', Long term: ' +
str(self.population.long_term))
for x2_, genes_ in genes:
chart2.add(x2_, genes_)
chart2.render_to_file('charts/Genes_' +
str(populations.index(population)) +
'.svg')
def pygal_bar_stacked(data, chartname, file_name):
bar_chart = pygal.StackedBar()
bar_chart = pygal.StackedBar(print_values=True,
style=DefaultStyle(
value_font_family='googlefont:Raleway',
value_font_size=30,
value_colors=('white', )))
bar_chart.title = chartname
for ds in data:
for key, value in ds.items():
bar_chart.add(key, value)
bar_chart.render_to_file(file_name + '.svg')
bar_chart.render_to_png(file_name + '.png')
return True
def prepare_bar_plot():
result, years, no_of_projects = languageStatistic()
my_style = define_style()
my_config = pygal.Config()
my_config.x_label_rotation = 45
my_config.title_font_size = 30
my_config.label_font_size = 25
my_config.major_label_font_size = 20
my_config.truncate_label = 15
my_config.show_y_guides = False
my_config.width = 1300
result.loc[:, result.columns != 'Language'] = (
result.loc[:, result.columns != 'Language'] /
result.loc[:, result.columns != 'Language'].sum()) * 100
bar_plot = pygal.StackedBar(my_config, style=my_style)
bar_plot.title = 'Timeline analysis'
year_start, year_end = min(years), max(years)
bar_plot.x_labels = map(str, range(year_start, year_end + 1))
for i, lang in enumerate(result['Language']):
cut_lang = result.loc[:, result.columns != 'Language']
values_yearly = list(cut_lang.iloc[i])
bar_plot.add(lang, values_yearly)
return bar_plot
def _report_2(request, ctx):
ctx['report_title'] = 'Presupuestos expandidos (en el tiempo)'
chart = pygal.StackedBar(legend_at_bottom=True,
y_title="$",
x_label_rotation=20) # @UndefinedVariable
chart.title = ctx['report_title']
cursor = connection.cursor()
# FIXME: use only accepted quotes! (not canceled, or rejected by customer)
cursor.execute(
"SELECT "
" lsq.created AS \"date_for_report\","
" lsq.cost AS \"orig_cost\","
" lsqa.cost AS \"selected_quote_alternative_cost\","
" c.name AS \"customer\""
" FROM lumina_session AS ls"
" JOIN lumina_sessionquote AS lsq ON lsq.session_id = ls.id"
" JOIN lumina_customer AS c ON ls.customer_id = c.id"
" LEFT OUTER JOIN lumina_sessionquotealternative AS lsqa"
" ON lsq.accepted_quote_alternative_id = lsqa.id"
" WHERE ls.studio_id = %s", [request.user.studio.id])
desc = cursor.description
values_as_dict = [
dict(list(zip([col[0] for col in desc], row)))
for row in cursor.fetchall()
]
# pprint.pprint(values_as_dict)
group_by_date = defaultdict(list)
for item in values_as_dict:
group_by_date[(item['date_for_report'].year,
item['date_for_report'].month)].append(item)
dates = list(group_by_date.keys())
dates.sort()
logger.info("group_by_date: %s", pprint.pformat(group_by_date))
serie_cost = []
serie_alt_quote = []
labels = []
for year, month in dates:
acum_cost = 0.0
acum_alt_quote = 0.0
for item in group_by_date[(year, month)]:
acum_cost += float(item['orig_cost'])
if item['selected_quote_alternative_cost']:
acum_alt_quote += float(
item['selected_quote_alternative_cost'])
labels.append("{}/{}".format(month, year))
serie_cost.append(acum_cost)
serie_alt_quote.append(acum_alt_quote)
chart.x_labels = labels
chart.add('Presupuesto original', serie_cost)
chart.add('Presupuesto expandido', serie_alt_quote)
chart.print_values = False
ctx['svg_chart'] = chart.render()
ctx['show_form_2'] = True
def create_chart(hvgc, hhgc, msw):
""" Create chart """
chart = pygal.StackedBar(truncate_label=5,
style=CleanStyle,
fill=True,
dots_size=1.75,
interpolate='cubic')
chart.x_title = 'Year'
chart.y_title = 'Video Games Amount'
chart.x_labels = [i for i in range(1980, 2017)]
chart.x_labels_major_count = 8
chart.show_minor_x_labels = False
chart.y_labels = [i for i in range(0, 18001, 2000)]
chart.legend_at_bottom = True
chart.legend_at_bottom_columns = 3
chart.legend_box_size = 16
chart.add("Home Video Game Consoles", hvgc)
chart.add("Handheld Game Consoles", hhgc)
chart.add("Microsoft Windows", msw)
chart.render_to_file('growth.svg')
def create_missing_emotions_chart_V2(trusted_src_dict):
custom_style = Style(label_font_size = 14, major_label_font_size=14,value_font_size=14,value_label_font_size=14)
keys = trusted_src_dict.keys()
sadness_vals = []
anger_vals = []
joy_vals = []
disgust_vals = []
fear_vals = []
for key in trusted_src_dict.keys():
sadness_vals.append(trusted_src_dict[key]['sadness'])
anger_vals.append(trusted_src_dict[key]['anger'])
joy_vals.append(trusted_src_dict[key]['joy'])
disgust_vals.append(trusted_src_dict[key]['disgust'])
fear_vals.append(trusted_src_dict[key]['fear'])
line_chart = pygal.StackedBar(x_label_rotation=90,style=custom_style)
line_chart.x_labels = keys
line_chart.add('sadness', sadness_vals)
line_chart.add('anger', anger_vals)
line_chart.add('joy', joy_vals)
line_chart.add('disgust', disgust_vals)
line_chart.add('fear', fear_vals)
line_chart.render_to_png('./example_missing_emotion.png')
def graphSentenceWordUse(sentences, top=0, fileName=args.args.file):
num = len(sentences) + 1
chart = pygal.StackedBar(print_labels=True, show_legend=False)
chart.title = 'Word Use By Sentence'
if top > 0:
chart.title += ' Of Top ' + str(top) + ' Words'
mostUsed = most_used_words.mostUsed(fileName, top=top)
mostUsed = {word['label']: word['value'] \
for word in mostUsed}
chart.x_labels = map(str, range(1, num))
sentencesByWord = [[taxonomy.sanitize(word) for word in sentence.split()] \
for sentence in sentences]
allWords = {}
for sentence in sentencesByWord:
for word in sentence:
allWords[word] = {'label': word, 'value': 0}
wordCounts = [copy.deepcopy(allWords) for sentence in sentencesByWord]
for i in xrange(0, len(sentencesByWord)):
for word in sentencesByWord[i]:
wordCounts[i][word]['value'] += 1
perWord = {}
for i in xrange(0, len(wordCounts)):
for word in wordCounts[i]:
if not word in perWord:
perWord[word] = []
if wordCounts[i][word]['value'] < 1 or \
(top > 0 and not word in mostUsed):
wordCounts[i][word]['label'] = ''
wordCounts[i][word]['value'] = 0
perWord[word].append(wordCounts[i][word])
for word in perWord:
chart.add(word, perWord[word])
fileName = chart.title.lower().replace(' ', '_')
chart.render_to_png(taxonomy.outdir(fileName + '.png'))
def stacked_bar():
chart = pygal.StackedBar()
chart.title = 'starked_bar'
chart.x_labels = map(str, range(size))
chart.add('Number 1 Test one', get_random_data(size))
chart.add('Number 2 Test two', get_random_data(size))
chart.render_to_file(get_file_name(inspect.stack()[0][3]))
def stacked(data, dirname):
data = deepcopy(data)
tasks = sorted(data.keys())
# Use a fixed order of methods in the plot
methods = ("mel", "cmds", "PyMEL", "cmdx")
# [group1 result, group2 result, ... of MEL]
# [group1 result, group2 result, ... of cmds]
# ...
cols = list()
for method in methods:
col = list()
for task in tasks:
col += [data[task].get(method, {}).get("min", 0)]
cols.append(col)
# Normalise along Y-axis
rows = zip(*cols)
for index, row in enumerate(rows[:]):
rows[index] = [100.0 * col / sum(row) for col in row]
cols = zip(*rows)
line_chart = pygal.StackedBar()
line_chart.title = "cmdx performance plot (in %)"
line_chart.x_labels = tasks
for method, col in enumerate(cols):
line_chart.add(methods[method], col)
fname = os.path.join(dirname, "stacked.svg")
line_chart.render_to_file(fname)
def graph(total):
# this is the name of each county and the total votes
print("--- graph test ---")
county_and_votes = {}
county_names = []
county_votes = []
for county_name, d in total.items():
county_names.append(county_name)
total_votes = 0
for party_name, count in total[county_name].items():
total_votes = total_votes + total[county_name][party_name]
county_and_votes[county_name] = total_votes
top_five_names = Nmaxelements(county_and_votes, 5)
my_config = pygal.Config()
my_config.x_label_rotation = 0
my_config.x_label_font_size = 14
my_config.show_legend = True
my_config.truncate_label = 15
my_config.width = 1000
chart = pygal.StackedBar(my_config)
chart.title = 'Parties'
chart.x_labels = top_five_names
chart.add('UNA', [total[x]['UNA'] for x in top_five_names])
chart.add('DEM', [total[x]['DEM'] for x in top_five_names])
chart.add('REP', [total[x]['REP'] for x in top_five_names])
chart.add('LIB', [total[x]['LIB'] for x in top_five_names])
chart.add('GRE', [total[x]['GRE'] for x in top_five_names])
chart.add('CST', [total[x]['CST'] for x in top_five_names])
chart.render_in_browser()
def weekly_users():
# unique active users per week
# Get URL parameters
number_of_weeks = int(request.args.get('weeks', 4))
selected_filter = request.args.get('filter', 'version')
# Create a list with the number of weeks you want to compare
sunday = (
datetime.date.today() - datetime.timedelta(days=datetime.date.today().weekday()) + datetime.timedelta(days=6,
weeks=-1))
week_list = list(reversed([(sunday - datetime.timedelta(days=(x + 1) * 7),
(sunday - datetime.timedelta(days=+1)) - datetime.timedelta(days=(x) * 7)) for x in
range(0, number_of_weeks-1)]))
week_list.append([sunday, datetime.date.today()])
if selected_filter is not None:
filter_list = get_filter_list(selected_filter, week_list[0][0], week_list[-1][1])
users_per_week = []
for filter in filter_list:
filter, = filter
week_data = [filter, []]
for week in week_list:
week_data[1].append(len(get_users_between_dates(week[0], week[1], selected_filter, filter)))
users_per_week.append(week_data)
line_chart = pygal.StackedBar()
line_chart.title = 'Weekly unique users count, segmented by {}'.format(selected_filter)
line_chart.x_labels = [(str(week_list[i][0])+'/'+str(week_list[i][1])) for i in range(0, len(week_list))]
for week in users_per_week:
line_chart.add(week[0], week[1])
return line_chart.render_data_uri()
def stacked_bar(news_src, num_pos, num_neg, num_neut):
totals = [
num_pos[0] + num_neg[0] + num_neut[0],
num_pos[1] + num_neg[1] + num_neut[1],
num_pos[2] + num_neg[2] + num_neut[2],
num_neut[3] + num_pos[3] + num_neg[3],
num_pos[4] + num_neg[4] + num_neut[4],
num_pos[5] + num_neg[5] + num_neut[5]
]
bar_chart = pygal.StackedBar()
bar_chart.title = 'Sentiment Across News Sources'
bar_chart.x_labels = [
news_src[0], news_src[1], news_src[2], news_src[3], news_src[4],
news_src[5]
]
bar_chart.add('Positive', [(num_pos[0] / totals[0]),
(num_pos[1] / totals[1]),
(num_pos[2] / totals[2]),
(num_pos[3] / totals[3]),
(num_pos[4] / totals[4]),
(num_pos[5] / totals[5])])
bar_chart.add('Negative', [(num_neg[0] / totals[0]),
(num_neg[1] / totals[1]),
(num_neg[2] / totals[2]),
(num_neg[3] / totals[3]),
(num_neg[4] / totals[4]),
(num_neg[5] / totals[5])])
bar_chart.add('Neutral', [(num_neut[0] / totals[0]),
(num_neut[1] / totals[1]),
(num_neut[2] / totals[2]),
(num_neut[3] / totals[3]),
(num_neut[4] / totals[4]),
(num_neut[5] / totals[5])])
bar_chart.render_to_file('stacked_bar.svg')
def _generar_grafico_de_barras_de_llamadas_entrantes(self, estadisticas):
grafico = pygal.StackedBar(show_legend=True,
style=ESTILO_VERDE_GRIS_NEGRO)
nombres_campanas = []
atendidas = []
expiradas = []
abandonadas = []
abandonadas_anuncio = []
por_campana = estadisticas['tipos_de_llamada_por_campana'][str(
Campana.TYPE_ENTRANTE)]
for datos_campana in por_campana.values():
nombres_campanas.append(datos_campana['nombre'])
atendidas.append(datos_campana['atendidas'])
abandonadas.append(datos_campana['abandonadas'])
abandonadas_anuncio.append(datos_campana['abandonadas_anuncio'])
expiradas.append(datos_campana['expiradas'])
grafico.x_labels = nombres_campanas
grafico.add(_(u'Atendidas'), atendidas)
grafico.add(_(u'Abandonadas'), abandonadas)
grafico.add(_(u'Abandonadas durante anuncio'), abandonadas_anuncio)
grafico.add(_(u'Expiradas'), expiradas)
self.graficos[
'barra_campana_llamadas_entrantes'] = adicionar_render_unicode(
grafico)
def percent_graph():
hours = int(request.args.get('hours', 24))
since = datetime.now() - timedelta(hours=hours)
stats_query = db.session.query(WorkerStat).filter(
WorkerStat.created > since).with_entities(WorkerStat.created,
WorkerStat.toots,
WorkerStat.tweets,
WorkerStat.instas)
df = pd.read_sql(stats_query.statement, stats_query.session.bind)
df.set_index(['created'], inplace=True)
df.groupby(level=0).sum()
r = df.resample('h').sum()
r = r.fillna(0)
r['total'] = r['toots'] + r['tweets'] + r['instas']
r['tweets_p'] = r['tweets'] / r['total']
r['toots_p'] = r['toots'] / r['total']
r['instas_p'] = r['instas'] / r['total']
toots_p = r['toots_p'].tolist()
tweets_p = r['tweets_p'].tolist()
instas_p = r['instas_p'].tolist()
chart = pygal.StackedBar(
title=f"Ratio of Incoming Messages ({timespan(hours)})",
human_readable=True,
legend_at_bottom=True)
chart.add('Toots', toots_p)
chart.add('Tweets', tweets_p)
chart.add('Instas', instas_p)
return chart.render_response()
def _generar_grafico_de_barras_de_llamadas_dialer(self, estadisticas):
grafico = pygal.StackedBar(show_legend=True,
style=ESTILO_ROJO_VERDE_GRIS_NEGRO)
nombres_campanas = []
no_atendidas = []
conectadas = []
expiradas = []
abandonadas = []
por_campana = estadisticas['tipos_de_llamada_por_campana'][str(
Campana.TYPE_DIALER)]
for datos_campana in por_campana.values():
nombres_campanas.append(datos_campana['nombre'])
no_atendidas.append(datos_campana['efectuadas'] -
datos_campana['atendidas'])
conectadas.append(datos_campana['conectadas'])
abandonadas.append(datos_campana['abandonadas'])
expiradas.append(datos_campana['expiradas'])
grafico.x_labels = nombres_campanas
grafico.add(_(u'No contactadas'), no_atendidas)
grafico.add(_(u'Procesadas'), conectadas)
grafico.add(_(u'Abandonadas'), abandonadas)
grafico.add(_(u'Expiradas'), expiradas)
self.graficos[
'barra_campana_llamadas_dialer'] = adicionar_render_unicode(
grafico)
def __init__(self, start_time, end_time, study_groups, **kwargs):
style = custom_style()
style.colors = ["#4c7e80", "#FC7100", "#FFBC1A", "#B7D500", "#05C6B4"]
self.chart = pygal.StackedBar(style=style, order_min=0, y_title="Number of ratings", x_label_rotation=30, **kwargs)
self.study_groups = study_groups
self.start_time = start_time
self.end_time = end_time
def plot_memory(data):
chart = pygal.StackedBar(CONFIG)
_plot_generic(
data, chart, 'Peakmem', lambda p: p[VALID_ATTRS['peakmem']]
)
return chart.render(is_unicode=True)
def create_issue_classification_chart(domain):
line_chart = pygal.StackedBar(height=200)
selected_domain = Domain.objects.get(name=domain)
libraries = selected_domain.library_set.all()
library_names = []
performance_issues = []
security_issues = []
performance_security_issues = []
no_classification_issues = []
for library in libraries:
library_names.append(library.name)
performance_issues.append(library.issue_set.all().filter(
performance_issue=True, security_issue=False).count())
security_issues.append(library.issue_set.all().filter(
security_issue=True, performance_issue=False).count())
performance_security_issues.append(library.issue_set.all().filter(
security_issue=True, performance_issue=True).count())
no_classification_issues.append(library.issue_set.all().filter(
security_issue=False, performance_issue=False).count())
line_chart.x_labels = library_names
line_chart.add('Performance', performance_issues)
line_chart.add('Security', security_issues)
line_chart.add('Both', performance_security_issues)
line_chart.add('None', no_classification_issues)
data = line_chart.render_data_uri()
saveData(data, domain + '_issue_classification_chart.pkl')
return data
def plot_dist_lengths(lengths, length_limit, x_step, max_x, y_step, max_y, outimg):
"""
Plot a length distribution over sentences
Inputs:
- lengths: list of numerical lenghts
- length_limit: maximum allowed length
- x_step: step in the horizontal axis
- max_x: maximum value in the horizontal axis
- y_step: step in the vertical axis
- max_y: maximum value in the vertical axis
- outimg: output image
"""
# count number of occurrences for each length value
c = Counter(lengths)
max_val = min(max_x, max(max_x, max(c.keys())))
# output in svg format
xdata = list(range(1, max_val + x_step + 1))
ydata_used = [c[k] if k in c and k <= length_limit else 0 for k in xdata]
ydata_unused = [c[k] if k in c and k > length_limit else 0 for k in xdata]
line_chart = pygal.StackedBar(width=1300, height=800, x_label_rotation=-45,
x_title='Number of words', y_title='Number of sentences',
show_minor_x_labels=False)
line_chart.x_labels = xdata
line_chart.x_labels_major = list(set([x // x_step * x_step for x in xdata]))
line_chart.y_labels = range(0, max_y + 1, y_step)
line_chart.add('Truncated data', ydata_unused)
line_chart.add('Unchanged data', ydata_used)
# circumvent potential svg styling problems
line_chart.render_to_file(outimg)
cairosvg.svg2svg(url=outimg, write_to=outimg)
def ia_coverage_histogram(rows):
"""
Note: this returns a raw pygal chart; it does not render it to SVG/PNG
"""
raw_years = [int(r[0]) for r in rows]
years = dict()
for y in range(min(raw_years), max(raw_years)+1):
years[int(y)] = dict(year=int(y), available=0, missing=0)
for r in rows:
if r[1]:
years[int(r[0])]['available'] = r[2]
else:
years[int(r[0])]['missing'] = r[2]
years = sorted(years.values(), key=lambda x: x['year'])
CleanStyle.colors = ("green", "purple")
label_count = len(years)
if len(years) > 20:
label_count = 10
chart = pygal.StackedBar(dynamic_print_values=True, style=CleanStyle,
width=1000, height=500, x_labels_major_count=label_count,
show_minor_x_labels=False)
#chart.title = "Perpetual Access Coverage"
chart.x_title = "Year"
#chart.y_title = "Releases"
chart.x_labels = [str(y['year']) for y in years]
chart.add('via Fatcat', [y['available'] for y in years])
chart.add('Missing', [y['missing'] for y in years])
return chart
def create_issue_classification_chart(domain):
domain_name = domain.name
line_chart = pygal.StackedBar(height=200)
line_chart.title = "Number of issues of each type per library"
selected_domain = Domain.objects.get(name=domain_name)
libraries = selected_domain.libraries.all()
library_names = []
performance_issues = []
security_issues = []
performance_security_issues = []
no_classification_issues = []
for library in libraries:
library_names.append(library.name)
performance_issues.append(
library.issues.filter(performance_issue=True,
security_issue=False).count())
security_issues.append(
library.issues.filter(security_issue=True,
performance_issue=False).count())
performance_security_issues.append(
library.issues.filter(security_issue=True,
performance_issue=True).count())
no_classification_issues.append(
library.issues.filter(security_issue=False,
performance_issue=False).count())
line_chart.x_labels = library_names
line_chart.add('Performance', performance_issues)
line_chart.add('Security', security_issues)
line_chart.add('Both', performance_security_issues)
line_chart.add('None', no_classification_issues)
data = line_chart.render_data_uri()
saveData(data, domain_name + '_issue_classification_chart.pkl')
save_chart_in_db(line_chart, domain, metric_name="issue classification")
def get_trades_chart(self, days=None):
trades = self.bottrade_set.filter(
time__gte=now() - datetime.timedelta(days=60),
profit_usd__isnull=False,
bot_trade=True,
)
chart = pygal.StackedBar(
x_title="Days",
y_title="Value in USD",
legend_at_bottom=True,
style=CleanStyle(font_family="googlefont:Raleway",
value_font_size=10),
dynamic_print_values=True,
)
chart.value_formatter = lambda x: "$%.2f USD" % x
chart.title = "Aggregated profits over time"
if days is None:
days = [1, 3, 7, 14, 30]
chart.x_labels = days
profits = {"buy": [], "sell": []}
if not self.base:
return chart.render_data_uri()
movements = get_price_movement(self.base_price_url, self.base)
for side in ["buy", "sell"]:
running_total = 0
previous_day = 0
for day in days:
profit = trades.filter(
trade_type=side,
time__lt=now() - datetime.timedelta(days=previous_day),
time__gte=now() - datetime.timedelta(days=day),
).aggregate(profit=Sum("profit_usd"))["profit"]
movement_factor = 1
if movements:
movement_factor = (movements.get("number_of_days", {}).get(
str(day), {}).get("movement_factor", 1))
if profit:
adjusted_profit = profit * movement_factor
else:
adjusted_profit = 0
running_total += adjusted_profit
profits[side].append(running_total)
previous_day = day
chart.add("Buy", profits["buy"])
chart.add("Sell", profits["sell"])
return chart.render_data_uri()
def chart(data, label):
want = 10
line_chart = pygal.StackedBar()
line_chart.title = 'skill want top 10'
line_chart.x_labels = label[:want]
for i, j in data:
line_chart.add(i, j[:want])
line_chart.render_to_file('img/allskillwant2.svg')
def _get_bar_chart(self):
return pygal.StackedBar(
self.config,
style=self._get_style(),
no_data_text=self.config.no_data_text,
disable_xml_declaration=True, # for correct svg in web page
explicit_size=True,
show_dots=False)
def create_hybrid_month():
"""create graph"""
bar_chart = pygal.StackedBar(x_label_rotation=90)
bar_chart.title = "ผลรวมของรถยนต์ไฮบริดแต่ละประเภทของแต่ละเดือน"
bar_chart.x_labels = all_months()
for i in np(hybrid_by_month):
bar_chart.add(i[0], i[1:])
bar_chart.render_to_file('All_hybrid_each_month.svg')
def get_trades_chart(self, days=None):
trades = self.bottrade_set.filter(time__gte=now() -
datetime.timedelta(days=60),
profit_usd__isnull=False,
bot_trade=True)
chart = pygal.StackedBar(
x_title='Days',
y_title='Value in USD',
legend_at_bottom=True,
style=CleanStyle(font_family='googlefont:Raleway',
value_font_size=10),
dynamic_print_values=True,
)
chart.value_formatter = lambda x: "$%.2f USD" % x
chart.title = 'Aggregated profits over time'
if days is None:
days = [1, 3, 7, 14, 30]
chart.x_labels = days
profits = {'buy': [], 'sell': []}
if not self.base:
return chart.render_data_uri()
movements = get_price_movement(self.base_price_url, self.base)
for side in ['buy', 'sell']:
running_total = 0
previous_day = 0
for day in days:
profit = trades.filter(
trade_type=side,
time__lt=now() - datetime.timedelta(days=previous_day),
time__gte=now() - datetime.timedelta(days=day)).aggregate(
profit=Sum('profit_usd'))['profit']
movement_factor = 1
if movements:
movement_factor = movements.get('number_of_days', {}).get(
str(day), {}).get('movement_factor', 1)
if profit:
adjusted_profit = profit * movement_factor
else:
adjusted_profit = 0
running_total += adjusted_profit
profits[side].append(running_total)
previous_day = day
chart.add('Buy', profits['buy'])
chart.add('Sell', profits['sell'])
return chart.render_data_uri()
def forecast():
""" render svg graph """
bar_chart = pygal.StackedBar(style=NeonStyle)
bar_chart.title = "Hyderabad Forecast"
lower,higher,days = get_forecast()
bar_chart.add('Kanishtam', lower)
bar_chart.add('Garishtam', higher)
bar_chart.x_labels = days
return Response(response=bar_chart.render(), content_type='image/svg+xml')
def dump_stacked_bar_chart(dirname, filename, title, x_labels, chart_data):
if not os.path.exists(dirname):
os.makedirs(dirname)
filepath = os.path.join(dirname, filename)
chart = pygal.StackedBar(show_y_guides=True, x_label_rotation=20)
chart.title = title
chart.x_labels = x_labels
for name, stuff in chart_data.items():
chart.add(name, stuff)
chart.render_to_file(filepath)
def get_svg_count_by_day(self):
chart = pygal.StackedBar(width=960,
height=480,
explicit_size=True,
show_legend=False)
chart.title = "Registered users by day"
chart.x_labels = map(lambda d: d.strftime('%d'), self.active.index)
chart.add('Activated', self.active['id'])
chart.add('Non-activated', self.nonactive['id'])
return chart.render()
def barChart():
bar_chart= pygal.StackedBar()
datalist = []
proselect = Projectpy.select()
for amountkdj in proselect:
datalist.append(amountkdj.amount)
label1 = 'amount'
bar_chart.add(label1, datalist)
bar_chart = bar_chart.render_data_uri()
return bar_chart