def project_um():
with open('Bangsai.csv', encoding="utf-8") as csvfile:
test = csv.reader(csvfile)
list_date = []
list_do = []
list_ec = []
list_temp = []
for i in test:
data = i[0].split(';')
list_date.append(data[1])
list_do.append(data[2])
list_ec.append(data[3])
list_temp.append(data[4])
list_do = change_value_to_float(list_do)
list_ec = change_value_to_float(list_ec)
list_temp = change_value_to_float(list_temp)
#created HTML
output_file = open('test-Project.html', 'w')
chart = lineChart(name="lineChart Bangsai D.O.", width=1244)
xdata = range(8708)
ydata = list_do
extra_serie = {"tooltip": {"y_start": "There are ", "y_end": " calls"}}
chart.add_serie(y=ydata, x=xdata, name='D.O.', extra=extra_serie)
chart.buildhtml()
output_file.write(chart.htmlcontent)
# close Html file
output_file.close()
def pamok():
""" """
list_date, list_do, list_ec, list_temp, ave_do_pamok, ave_ec_pamok, ave_temp_pamok = riverside_pamok.data_split()
list_mean_ec_in_aday = average_per_day(list_ec, list_date)
#created HTML
output_file = open('Chart mean EC in a day of Pamok.html', 'w')
chart = lineChart(name="lineChart Pamok E.C.", width = 1244)
xdata = range(1, 32)
ydata1 = list_mean_ec_in_aday[:30]
ydata2 = list_mean_ec_in_aday[30:61]
ydata3 = list_mean_ec_in_aday[61:91]
ydata4 = list_mean_ec_in_aday[91:122]
ydata5 = list_mean_ec_in_aday[122:153]
ydata6 = list_mean_ec_in_aday[153:]
chart.add_serie(y=ydata1, x=xdata, name='เม.ย.')
chart.add_serie(y=ydata2, x=xdata, name='พ.ค.')
chart.add_serie(y=ydata3, x=xdata, name='มิ.ย.')
chart.add_serie(y=ydata4, x=xdata, name='ก.ค.')
chart.add_serie(y=ydata5, x=xdata, name='ส.ค.')
chart.add_serie(y=ydata6, x=xdata, name='ก.ย.')
chart.buildhtml()
output_file.write(chart.htmlcontent)
# close Html file
output_file.close()
def linechart(x, y):
chart = nvd3.lineChart(name=y.name, height=200, width=350)
chart.add_serie(y=y.tolist(), x=np.arange(len(y)), name=y.name)
chart.buildcontent()
chart_html = chart.htmlcontent
return chart_html
def project_um():
with open('Bangsai.csv', encoding="utf-8") as csvfile:
test = csv.reader(csvfile)
list_date = []
list_do = []
for i in test:
data = i[0].split(';')
list_date.append(data[1])
list_do.append(data[2])
list_do = change_value_to_float(list_do)
list_mean_do_in_aday = average_per_day(list_do, list_date)
#created HTML
output_file = open('DO-Bangsai.html', 'w')
chart = lineChart(name="lineChart Bangsai DO", width=1244)
xdata = range(1, 32)
ydata = list_mean_do_in_aday[:30]
ydata2 = list_mean_do_in_aday[30:61]
ydata3 = list_mean_do_in_aday[61:91]
ydata4 = list_mean_do_in_aday[91:122]
ydata5 = list_mean_do_in_aday[122:153]
ydata6 = list_mean_do_in_aday[153:]
chart.add_serie(y=ydata, x=xdata, name='เม.ย.')
chart.add_serie(y=ydata2, x=xdata, name='พ.ค.')
chart.add_serie(y=ydata3, x=xdata, name='มิ.ย.')
chart.add_serie(y=ydata4, x=xdata, name='ก.ค.')
chart.add_serie(y=ydata5, x=xdata, name='ส.ค.')
chart.add_serie(y=ydata6, x=xdata, name='ก.ย.')
chart.buildhtml()
output_file.write(chart.htmlcontent)
# close Html file
output_file.close()
def visualize_print_log(filename):
try:
data = np.loadtxt(filename)
if data.ndim == 1:
data = data[:, np.newaxis]
except Error as e:
return 'Cannot load file {}: {}'.format(filename, str(e))
chart_name = os.path.splitext(os.path.basename(filename))[0]
chart = nvd3.lineChart(name=chart_name + '_log_chart',
height=args.chart_height,
y_axis_format='.03g')
if args.sample < 0:
step = max(data.shape[0] / -args.sample, 1)
else:
step = args.sample
xdata = np.arange(0, data.shape[0], step)
# if there is only one curve, we also show the running min and max
if data.shape[1] == 1:
# We also print the running min and max for the steps.
trunc_size = data.shape[0] / step
running_mat = data[:trunc_size * step].reshape((trunc_size, step))
chart.add_serie(x=xdata[:trunc_size], y=running_mat.min(axis=1),
name='running_min')
chart.add_serie(x=xdata[:trunc_size], y=running_mat.max(axis=1),
name='running_max')
chart.add_serie(x=xdata, y=data[xdata, 0], name=chart_name)
else:
for i in range(0, min(data.shape[1], args.max_curves)):
# data should have 4 dimensions.
chart.add_serie(x=xdata, y=data[xdata, i],
name='{}[{}]'.format(chart_name, i))
return jsonify_nvd3(chart)
def draw(handle, type, logs, **kwargs):
kwparams = {
'name': "lineChart",
'width': 1000,
'height': 500,
'chart_attr': {
'forceX': x_axis_scale(logs),
'forceY': y_axis_scale(logs),
# 'yAxis.scale': y_axis_scale(logs),
'xAxis.axisLabel': ('"%s"' % kwargs['xlabel']),
'yAxis.axisLabel': ('"%s"' % kwargs['ylabel']),
'useInteractiveGuideline': 'true',
# 'x2Axis.scale': xAxisScale(logs),
# 'y2Axis.scale': yAxisScale(logs),
},
}
chart = None
if type == LINE_CHART:
chart = lineChart(**kwparams)
elif type == LINE_WITH_FOCUS_CHART:
chart = lineWithFocusChart(**kwparams)
chart.show_labels = True
count = 0
for alg in logs:
extra_serie = {
"tooltip": {"y_start": kwargs['ylabel'] + "is ", "y_end": "!"},
}
chart.add_serie(y=logs[alg]['y'], x=logs[alg]['x'], color=COLOR_LIST[count], extra=extra_serie, name=alg)
count += 1
chart.buildhtml()
handle.write(str(chart))
def samlae():
""" """
list_date, list_do, list_ec, list_temp, ave_do_samlae, ave_ec_samlae, ave_temp_samlae = (
riverside_samlae.data_split()
)
list_mean_ec_in_aday = average_per_day(list_ec, list_date)
# created HTML
output_file = open("Chart mean EC in a day of Samlae.html", "w")
chart = lineChart(name="lineChart Samlae E.C.", width=1244)
xdata = range(1, 32)
xdata1 = range(17, 32)
ydata1 = list_mean_ec_in_aday[:30]
ydata2 = list_mean_ec_in_aday[30:43]
ydata4 = list_mean_ec_in_aday[43:57]
ydata5 = list_mean_ec_in_aday[57:82]
ydata6 = list_mean_ec_in_aday[82:]
chart.add_serie(y=ydata1, x=xdata, name="เม.ย.")
chart.add_serie(y=ydata2, x=xdata, name="พ.ค.")
chart.add_serie(y=ydata4, x=xdata1, name="ก.ค.")
chart.add_serie(y=ydata5, x=xdata, name="ส.ค.")
chart.add_serie(y=ydata6, x=xdata, name="ก.ย.")
chart.buildhtml()
output_file.write(chart.htmlcontent)
# close Html file
output_file.close()
def plotData(self, getTickerData):
output_file = open('ticker.html', 'w')
type = "lineChart"
chart = lineChart(name=type,
x_is_date=True,
x_axis_format="%Y-%m-%d",
height=450,
width=1300)
extra_serie = {"tooltip": {"y_start": "There is ", "y_end": " calls"}}
# Get Timestamp and Y-Values
for idx, ticker in enumerate(self.ticker):
print ticker
df = getTickerData(ticker)
timestamp = []
xdata = [time.mktime(s.timetuple()) * 1000 for s in df.index]
tickerData = df['Open']
color = "#%06x" % random.randint(0, 0xFFFFFF)
print color
chart.add_serie(y=tickerData,
x=xdata,
name=ticker,
extra=extra_serie,
**{'color': color})
chart.buildhtml()
output_file.write(chart.htmlcontent)
output_file.close()
def draw(handle, type, logs, **kwargs):
kwparams = {
'name': "lineChart",
'width': 1000,
'height': 500,
'chart_attr': {
'forceY': yAxisScale(logs),
'forceX': xAxisScale(logs),
'xAxis.axisLabel': ('"%s"' % kwargs['xlabel']),
'yAxis.axisLabel': ('"%s"' % kwargs['ylabel']),
},
}
chart = None
if type == LINE_CHART:
chart = lineChart(**kwparams)
elif type == LINE_WITH_FOCUS_CHART:
chart = lineWithFocusChart(**kwparams)
chart.show_labels = True
for alg in logs:
extra_serie = {
"tooltip": {
"y_start": kwargs['ylabel'] + "is ",
"y_end": "!"
}
}
chart.add_serie(y=logs[alg]['y'],
x=logs[alg]['x'],
extra=extra_serie,
name=alg)
chart.buildhtml()
handle.write(str(chart))
def nakhonsawan():
""" """
list_date, list_do, list_ec, list_temp, ave_do_nakhonsawan, ave_ec_nakhonsawan, ave_temp_nakhonsawan = riverside_nakhonsawan.data_split()
list_mean_ec_in_aday = average_per_day(list_ec, list_date)
#created HTML
output_file = open('Chart mean EC in a day of Nakhonsawan.html', 'w')
chart = lineChart(name="lineChart Nakhonsawan E.C.", width = 1244)
xdata = range(1, 32)
xdata1 = range(23, 32)
ydata1 = list_mean_ec_in_aday[23:31]
ydata2 = list_mean_ec_in_aday[31:61]
ydata3 = list_mean_ec_in_aday[61:91]
ydata4 = list_mean_ec_in_aday[91:122]
ydata5 = list_mean_ec_in_aday[122:152]
ydata6 = list_mean_ec_in_aday[152:]
chart.add_serie(y=ydata1, x=xdata1, name='เม.ย.')
chart.add_serie(y=ydata2, x=xdata, name='พ.ค.')
chart.add_serie(y=ydata3, x=xdata, name='มิ.ย.')
chart.add_serie(y=ydata4, x=xdata, name='ก.ค.')
chart.add_serie(y=ydata5, x=xdata, name='ส.ค.')
chart.add_serie(y=ydata6, x=xdata, name='ก.ย.')
chart.buildhtml()
output_file.write(chart.htmlcontent)
# close Html file
output_file.close()
def getCaseData(self,selectData):
"""Method to do plot Cases for DueDate counts from df"""
df = selectData()
df_DueDate = df['RHZ'].value_counts()
print df_DueDate
values = []
labels = []
for idx, item in enumerate(df_DueDate):
values.append(int(df_DueDate[idx]))
labels.append(df_DueDate.index[idx])
output_file = open('casesDueDate.html', 'w')
type = "lineChart"
chart = lineChart(name=type, x_is_date=True,
width=1000, height=300,
show_legend=False)
# lissajous parameters of a/b
"""delta = pi / 2
t = linspace(-pi, pi, 300)
for i in range(0, 4):
x = sin(a[i] * t + delta)
y = sin(b[i] * t)"""
chart.add_serie(y=values, x=labels, name='jeoma', color='red')
chart.buildhtml()
output_file.write(chart.htmlcontent)
output_file.close()
def data_split():
with open("Data/Pamok.csv") as csvfile:
test = csv.reader(csvfile)
list_date = []
list_do = []
for i in test:
list_date.append(i[1])
list_do.append(i[2])
list_do = change_value_to_float(list_do)
list_mean_do_in_aday = average_per_day(list_do, list_date)
# created HTML
output_file = open("DO-Pamok.html", "w")
chart = lineChart(name="lineChart Pamok DO", width=1244)
xdata = range(1, 32)
ydata = list_mean_do_in_aday[:30]
ydata2 = list_mean_do_in_aday[30:61]
ydata3 = list_mean_do_in_aday[61:91]
ydata4 = list_mean_do_in_aday[91:122]
ydata5 = list_mean_do_in_aday[122:153]
ydata6 = list_mean_do_in_aday[153:]
chart.add_serie(y=ydata, x=xdata, name="เม.ย.")
chart.add_serie(y=ydata2, x=xdata, name="พ.ค.")
chart.add_serie(y=ydata3, x=xdata, name="มิ.ย.")
chart.add_serie(y=ydata4, x=xdata, name="ก.ค.")
chart.add_serie(y=ydata5, x=xdata, name="ส.ค.")
chart.add_serie(y=ydata6, x=xdata, name="ก.ย.")
chart.buildhtml()
output_file.write(chart.htmlcontent)
# close Html file
output_file.close()
def test_lineChart_tooltip(self):
"""Test Line Chart"""
type = "lineChart"
chart = lineChart(name=type, date=True, height=350)
nb_element = 100
xdata = list(range(nb_element))
xdata = [1365026400000 + x * 100000 for x in xdata]
ydata = [i + random.randint(1, 10) for i in range(nb_element)]
ydata2 = [x * 2 for x in ydata]
kwargs1 = {'color': 'green'}
kwargs2 = {'color': 'red'}
extra_serie = {
"tooltip": {
"y_start": "There is ",
"y_end": " random values"
}
}
chart.add_serie(name="Random X-Axis",
y=ydata,
x=xdata,
extra=extra_serie,
**kwargs1)
extra_serie = {"tooltip": {"y_start": "", "y_end": " double values"}}
chart.add_serie(name="Double X-Axis",
y=ydata2,
x=xdata,
extra=extra_serie,
**kwargs2)
chart.buildhtml()
def chainat():
""" """
list_date, list_do, list_ec, list_temp, ave_do_chainat, ave_ec_chainat, ave_temp_chainat = (
riverside_chainat.data_split()
)
list_mean_ec_in_aday = average_per_day(list_ec, list_date)
# created HTML
output_file = open("Chart mean EC in a day of Chainat.html", "w")
chart = lineChart(name="lineChart Chainat E.C.", width=1244)
xdata = range(1, 32)
ydata1 = list_mean_ec_in_aday[:30]
ydata2 = list_mean_ec_in_aday[30:61]
ydata3 = list_mean_ec_in_aday[61:91]
ydata4 = list_mean_ec_in_aday[91:122]
ydata5 = list_mean_ec_in_aday[122:153]
ydata6 = list_mean_ec_in_aday[153:]
chart.add_serie(y=ydata1, x=xdata, name="เม.ย.")
chart.add_serie(y=ydata2, x=xdata, name="พ.ค.")
chart.add_serie(y=ydata3, x=xdata, name="มิ.ย.")
chart.add_serie(y=ydata4, x=xdata, name="ก.ค.")
chart.add_serie(y=ydata5, x=xdata, name="ส.ค.")
chart.add_serie(y=ydata6, x=xdata, name="ก.ย.")
chart.buildhtml()
output_file.write(chart.htmlcontent)
# close Html file
output_file.close()
def data_split():
with open('Data/Samlae.csv', encoding="utf-8") as csvfile:
test = csv.reader(csvfile)
list_date = []
list_do = []
for i in test:
data = i[0].split(';')
list_date.append(data[1])
list_do.append(data[2])
list_do = change_value_to_float(list_do)
list_mean_do_in_aday = average_per_day(list_do, list_date)
#created HTML
output_file = open('DO-Samlae.html', 'w')
chart = lineChart(name="lineChart Samlae DO", width=1244)
xdata = range(1, 32)
xdata2 = range(17, 32)
ydata = list_mean_do_in_aday[:30]
ydata2 = list_mean_do_in_aday[30:43]
ydata4 = list_mean_do_in_aday[43:58]
ydata5 = list_mean_do_in_aday[58:83]
ydata6 = list_mean_do_in_aday[83:]
chart.add_serie(y=ydata, x=xdata, name='เม.ย.')
chart.add_serie(y=ydata2, x=xdata, name='พ.ค.')
chart.add_serie(y=ydata4, x=xdata2, name='ก.ค.')
chart.add_serie(y=ydata5, x=xdata, name='ส.ค.')
chart.add_serie(y=ydata6, x=xdata, name='ก.ย.')
chart.buildhtml()
output_file.write(chart.htmlcontent)
# close Html file
output_file.close()
def project_um():
with open('Data/Ayuthaya.csv', encoding="utf-8") as csvfile:
test = csv.reader(csvfile)
list_date = []
list_do = []
list_ec = []
list_temp = []
for i in test:
data = i[0].split(';')
list_date.append(data[1])
list_do.append(data[2])
list_do = change_value_to_float(list_do)
list_mean_do_in_aday = average_per_day(list_do, list_date)
#created HTML
output_file = open('DO-Ayuthaya.html', 'w')
chart = lineChart(name="lineChart Ayuthaya D.O.", width=1244)
xdata = range(1, 32)
ydata = list_mean_do_in_aday[:31]
ydata2 = list_mean_do_in_aday[31:62]
ydata3 = list_mean_do_in_aday[62:]
chart.add_serie(y=ydata, x=xdata, name='ก.ค.')
chart.add_serie(y=ydata2, x=xdata, name='ส.ค.')
chart.add_serie(y=ydata3, x=xdata, name='ก.ย.')
chart.buildhtml()
output_file.write(chart.htmlcontent)
# close Html file
output_file.close()
def getCaseData(self, selectData):
"""Method to do plot Cases for DueDate counts from df"""
df = selectData()
df_DueDate = df['RHZ'].value_counts()
print df_DueDate
values = []
labels = []
for idx, item in enumerate(df_DueDate):
values.append(int(df_DueDate[idx]))
labels.append(df_DueDate.index[idx])
output_file = open('casesDueDate.html', 'w')
type = "lineChart"
chart = lineChart(name=type,
x_is_date=True,
width=1000,
height=300,
show_legend=False)
# lissajous parameters of a/b
"""delta = pi / 2
t = linspace(-pi, pi, 300)
for i in range(0, 4):
x = sin(a[i] * t + delta)
y = sin(b[i] * t)"""
chart.add_serie(y=values, x=labels, name='jeoma', color='red')
chart.buildhtml()
output_file.write(chart.htmlcontent)
output_file.close()
def data_split():
with open('Dowkanong.csv', encoding="utf-8") as csvfile:
test = csv.reader(csvfile)
list_date = []
list_do = []
for i in test:
data = i[0].split(';')
list_date.append(data[1])
list_do.append(data[2])
list_do = change_value_to_float(list_do)
list_mean_do_in_aday = average_per_day(list_do, list_date)
#created HTML
output_file = open('DO-Dowkanong.html', 'w')
chart = lineChart(name="lineChart Dowkanong DO", width=1244)
xdata = range(1, 32)
xdata2 = range(14, 32)
ydata = list_mean_do_in_aday[:18]
ydata2 = list_mean_do_in_aday[18:43]
ydata3 = list_mean_do_in_aday[43:]
chart.add_serie(y=ydata, x=xdata2, name='ก.ค.')
chart.add_serie(y=ydata2, x=xdata, name='ส.ค.')
chart.add_serie(y=ydata3, x=xdata, name='ก.ย.')
chart.buildhtml()
output_file.write(chart.htmlcontent)
# close Html file
output_file.close()
def data_split():
with open('Nakhonsawan.csv', encoding="utf-8") as csvfile:
test = csv.reader(csvfile)
list_date = []
list_do = []
for i in test:
data = i[0].split(';')
list_date.append(data[2])
list_do.append(data[4])
list_do = change_value_to_float(list_do)
list_mean_do_in_aday = average_per_day(list_do, list_date)
#created HTML
output_file = open('DO-Nakhonsawan.html', 'w')
chart = lineChart(name="lineChart Nakhonsawan DO", width=1244)
xdata = range(1, 32)
xdata2 = range(23, 32)
ydata = list_mean_do_in_aday[:8]
ydata2 = list_mean_do_in_aday[8:38]
ydata3 = list_mean_do_in_aday[38:68]
ydata4 = list_mean_do_in_aday[68:99]
ydata5 = list_mean_do_in_aday[99:129]
ydata6 = list_mean_do_in_aday[129:]
chart.add_serie(y=ydata, x=xdata2, name='เม.ย.')
chart.add_serie(y=ydata2, x=xdata, name='พ.ค.')
chart.add_serie(y=ydata3, x=xdata, name='มิ.ย.')
chart.add_serie(y=ydata4, x=xdata, name='ก.ค.')
chart.add_serie(y=ydata5, x=xdata, name='ส.ค.')
chart.add_serie(y=ydata6, x=xdata, name='ก.ย.')
chart.buildhtml()
output_file.write(chart.htmlcontent)
# close Html file
output_file.close()
def chart_line(ydata,xdata,filename):
output_file = open(filename, 'w')
type = 'lineChart'
chart = lineChart(name=type, x_is_date=True, color_category='category20c', height=450, width=900)
chart.set_containerheader("\n\n<h2>" + type + "</h2>\n\n")
chart.add_serie(y=ydata, x=xdata)
chart.buildhtml()
output_file.write(chart.htmlcontent)
def line_chart():
content = read_data('/var/www/html/assignment5/static/dataset_chart1.csv')
station, ydata = validate_data(content)
kwargs1 = {'height':'3000'}
chart = lineChart(name="lineChart",height=900,width=1800,margin_bottom=20, margin_top=40, margin_left=60, margin_right=10)
xdata = list(range(1,13))
for it in range(0, len(station)-1):
chart.add_serie(y=ydata[it],x=xdata,name=station[it])
chart.buildhtml()
return chart.htmlcontent
def test_lineChart(self):
"""Test Line Chart"""
type = "lineChart"
chart = lineChart(name=type, date=True, height=350)
nb_element = 100
xdata = list(range(nb_element))
xdata = [1365026400000 + x * 100000 for x in xdata]
ydata = [i + random.randint(1, 10) for i in range(nb_element)]
ydata2 = [x * 2 for x in ydata]
chart.add_serie(y=ydata, x=xdata)
chart.add_serie(y=ydata2, x=xdata)
chart.buildhtml()
def test_lineChart(self):
"""Test Line Chart"""
type = "lineChart"
chart = lineChart(name=type, date=True, height=350)
nb_element = 100
xdata = list(range(nb_element))
xdata = [1365026400000 + x * 100000 for x in xdata]
ydata = [i + random.randint(1, 10) for i in range(nb_element)]
ydata2 = [x * 2 for x in ydata]
chart.add_serie(y=ydata, x=xdata)
chart.add_serie(y=ydata2, x=xdata)
chart.buildhtml()
def __init__(self, size=None, theme=None):
global _INITED
if not _INITED:
initialize_javascript()
_INITED = True
self.size = size or (700, 400)
self._lines = lineChart(name='lineChart',
x_is_date=True,
x_axis_format='%Y-%m-%d',
height=self.size[1],
width=self.size[0])
def test_lineChart(self):
"""Test Line Chart"""
type = "lineChart"
chart = lineChart(name=type, date=True, height=350)
nb_element = 100
xdata = range(nb_element)
xdata = map(lambda x: 1365026400000 + x * 100000, xdata)
ydata = [i + random.randint(1, 10) for i in range(nb_element)]
ydata2 = map(lambda x: x * 2, ydata)
chart.add_serie(y=ydata, x=xdata)
chart.add_serie(y=ydata2, x=xdata)
chart.buildhtml()
def test_lineChart(self):
"""Test Line Chart"""
type = "lineChart"
chart = lineChart(name=type, date=True, height=350)
nb_element = 100
xdata = range(nb_element)
xdata = map(lambda x: 1365026400000 + x * 100000, xdata)
ydata = [i + random.randint(1, 10) for i in range(nb_element)]
ydata2 = map(lambda x: x * 2, ydata)
chart.add_serie(y=ydata, x=xdata)
chart.add_serie(y=ydata2, x=xdata)
chart.buildhtml()
def index_chart(request):
"""
lineChart page
"""
today = datetime.date.today()
year = today.year
kwargs2 = {'color': 'red'}
stock_list = CproChart.objects.filter(chart_in_hm_choices=u'STOCK',chart_time__year=year)
xdata = [int(calendar.timegm(t.chart_time.timetuple()))*1000 for t in stock_list]
ydata = [float("%.2f"%v.chart_value) for v in stock_list]
chart = lineChart(name='lineChart', container='lineChart',height=400, width=400, x_is_date=True, x_axis_format="%d %b %Y")
#xdata = [1365026400000000, 1365026500000000, 1365026600000000]
#ydata = [-6, 5, -1]
#tooltip_str = "'<center><b>'+key+'</b></center>' + y + ' 增长 ' + x;"
extra_serie = {"tooltip": {"y_start": "净值", "y_end": ""},
"date_format": "%Y年%m月%d日",
#"tooltip_str": tooltip_str,
}
chart.add_serie(name=u"股票净值", y=ydata, x=xdata, extra=extra_serie,**kwargs2)
chart.buildhtml()
chart_html = chart.jschart
#--------------------------------------------------------------
chart2 = lineChart(name='lineChart2',container='lineChart2',height=400, width=400, x_is_date=True, x_axis_format="%d %b %Y")
fund_list = CproChart.objects.filter(chart_in_hm_choices=u'FUND',chart_time__year=year)
xdata2 = [int(calendar.timegm(t.chart_time.timetuple()))*1000 for t in fund_list]
ydata2 = [float("%.2f"%v.chart_value) for v in fund_list]
#xdata2 = [1365988400000000, 1365026500000000, 1365026600000000]
#ydata2 = [8, 5, 3]
extra_serie2 = {"tooltip": {"y_start": "净值", "y_end": ""},
"date_format": "%Y年%m月%d日"}
chart2.add_serie(name=u"期货净值", y=ydata2, x=xdata2, extra=extra_serie2,**kwargs2)
chart2.buildhtml()
chart_html2 = chart2.jschart
adimg = CproadManager.objects.all()
return chart_html,chart_html2
def d3js_htmls(self):
""" visualize data using D3.js(wrapped by python-nvd3)
"""
global html_lineChart, html_pieChart
if self.vars_dict.get('LINE_CHART'):
chart_name = self.vars_dict.get('TABULATE_FILE')
height = 768
width = 1366
line_chart = lineChart(name='[line]'+chart_name,
height=height,
width=width)
line_data = self.get_tabulate_data(self.vars_dict.get('LAST_DAYS'))
# x_data = [each[0].strip() for each in line_data][1:]
# x_data = map(lambda x: mktime(datetime.strptime(x, '%Y-%m-%d').timetuple()), x_data)
x_data = list(range(-30, 0))
name_list = line_data[0][1:]
y_data_list = []
for i in range(1, len(line_data[0])):
y_data_list.append([each[i] for each in line_data[1:]])
extra_serie = {
'tooltip': {
'y_start': '',
'y_end': 'counts'
}
}
for name, y_data in zip(name_list, y_data_list):
line_chart.add_serie(y=y_data, x=x_data, name=name, extra=extra_serie)
line_chart.buildhtml()
html_lineChart = line_chart.htmlcontent
if self.vars_dict.get('PIE_CHART'):
rows = self.res_counts
xdata, ydata = zip(*rows)
extra_serie = {
'tooltip': {
'y_start': '',
'y_end': 'counts'
}
}
chart_name = self.vars_dict.get('FILE_PATH')
height = 768
width = 1366
pie_chart = pieChart(name='[pie]'+chart_name, color_category='category20c', height=height, width=width)
pie_chart.set_containerheader("\n\n<h2>" + chart_name + "</h2>\n\n")
pie_chart.add_serie(y=ydata, x=xdata, extra=extra_serie)
pie_chart.buildhtml()
html_pieChart = pie_chart.htmlcontent
return html_lineChart, html_pieChart
def hello():
input_data = list(
csv.reader(open('dateCrimeOutput.txt', 'rb'), delimiter='\t'))
chart = lineChart(name="lineChart",
x_is_date=False,
height=800,
width=1800,
margin_bottom=200,
margin_top=40,
margin_left=60,
margin_right=60)
crimes = []
for row in input_data:
crimes.append([row[0], row[1], int(row[2])])
crimes = sorted(crimes, key=lambda crimes: ([crimes[0], crimes[1]]))
xdata = []
current_crime = None
i = 0
for crime in crimes:
if str(crime[0]) == current_crime:
xdata.append(crime[1])
globals()['ydata%s' % i].append(crime[2])
else:
current_crime = crime[0]
i = i + 1
globals()['name%s' % i] = str(crime[0])
globals()['ydata%s' % i] = []
xdata.append(str(crime[1]))
globals()['ydata%s' % i].append(crime[2])
kwargs1 = {'shape': 'circle', 'size': '20'}
# kwargs2 = {'shape': 'cross', 'size': '4'}
i = 1
while True:
try:
chart.add_serie(name=globals()['name%s' % i],
y=globals()['ydata%s' % i],
x=xdata,
**kwargs1)
i = i + 1
except:
break
chart.buildhtml()
print chart.htmlcontent
return chart.htmlcontent
def probe(probe_id):
probe = probe_storage.get_probe(probe_id)
chart = None
if(probe['type'] == "PingProbe" and
'result' in probe):
chart = lineChart(name="lineChart",
x_is_date=True,
x_axis_format="%d-%m-%y %H:%M:%S",
height=250)
xdata = []
min_data = []
avg_data = []
max_data = []
for result in probe['result']:
if 'error' in result:
# TODO, need to take into account that some probes
# give an error and some don't This just assumes
# all probes have errors
break
# TODO, Convert timestamp to format using function
xdata.append(int(result['timestamp'])*1000)
min_data.append(result['min'])
avg_data.append(result['avg'])
max_data.append(result['max'])
extra_serie = {"tooltip": {"y_start": "There are ", "y_end": " calls"}}
chart.add_serie(y=min_data, x=xdata, name='min rtt(ms)',
extra=extra_serie)
extra_serie = {"tooltip": {"y_start": "", "y_end": " min"}}
chart.add_serie(y=avg_data, x=xdata, name='avg rtt(ms)',
extra=extra_serie)
extra_serie = {"tooltip": {"y_start": "", "y_end": " min"}}
chart.add_serie(y=max_data, x=xdata, name='max rtt(ms)',
extra=extra_serie)
chart.buildcontent()
chart = chart.htmlcontent
# convert timestamps for pretty printing
for item in probe['result']:
item['timestamp'] = format(datetime.fromtimestamp(item['timestamp']),
'%d-%b-%y - %H:%M:%S')
return render_template("probe.html", probe=probe, chart=chart)
def plot(filename):
array=fileParser_json(filename)
filename = 'plot.html'
fw = open(filename, "w")
type='lineChart'
# for a date v/s frequency graph
chart = lineChart(name=type, x_is_date=False, x_axis_format="AM_PM", height=600, width=1000)
time_dict_days = {}
for item in array:
item_json = json.loads(item)
# print item_json['id']
created_at = item_json['created_at']
time_stamp = time.strftime('%s', time.strptime(created_at, '%a %b %d %H:%M:%S +0000 %Y'))
date_time = datetime.fromtimestamp(float(time_stamp))
# date_time = date_time+timedelta(hours=-5, minutes=30)
day = date_time.day
if str(day) in time_dict_days.keys():
list = time_dict_days.get(str(day))
list.append(date_time)
else:
list = []
list.append(date_time)
time_dict_days[str(day)] = list
print time_dict_days.keys()
for key in time_dict_days.keys():
list = time_dict_days.get(key)
time_dict = {}
for item in list:
hour = item.hour
if str(hour) in time_dict.keys():
time_dict[str(hour)] = time_dict[str(hour)] + 1
else:
time_dict[str(hour)] = 1
time_dict=collections.OrderedDict(sorted(time_dict.items()))
xdata = []
ydata = []
for k in time_dict.keys():
xdata.append(k)
ydata.append(time_dict[k])
chart.add_serie(name=key, y=ydata, x=xdata)
chart.buildhtml()
fw.write(chart.htmlcontent)
fw.close()
def test_lineChart_tooltip(self):
"""Test Line Chart"""
type = "lineChart"
chart = lineChart(name=type, date=True, height=350)
nb_element = 100
xdata = list(range(nb_element))
xdata = [1365026400000 + x * 100000 for x in xdata]
ydata = [i + random.randint(1, 10) for i in range(nb_element)]
ydata2 = [x * 2 for x in ydata]
kwargs1 = {'color': 'green'}
kwargs2 = {'color': 'red'}
extra_serie = {"tooltip": {"y_start": "There is ", "y_end": " random values"}}
chart.add_serie(name="Random X-Axis", y=ydata, x=xdata, extra=extra_serie, **kwargs1)
extra_serie = {"tooltip": {"y_start": "", "y_end": " double values"}}
chart.add_serie(name="Double X-Axis", y=ydata2, x=xdata, extra=extra_serie, **kwargs2)
chart.buildhtml()
def ayuthaya():
""" """
list_date, list_do, list_ec, list_temp, ave_do_ayuthaya, ave_ec_ayuthaya, ave_temp_ayuthaya = riverside_ayuthaya.data_split()
list_mean_ec_in_aday = average_per_day(list_ec, list_date)
#created HTML
output_file = open('Chart mean EC in a day of Ayuthaya.html', 'w')
chart = lineChart(name="lineChart Ayuthaya E.C.", width = 1244)
xdata = range(1, 32)
ydata4 = list_mean_ec_in_aday[:31]
ydata5 = list_mean_ec_in_aday[31:62]
ydata6 = list_mean_ec_in_aday[62:]
chart.add_serie(y=ydata4, x=xdata, name='ก.ค.')
chart.add_serie(y=ydata5, x=xdata, name='ส.ค.')
chart.add_serie(y=ydata6, x=xdata, name='ก.ย.')
chart.buildhtml()
output_file.write(chart.htmlcontent)
# close Html file
output_file.close()
def dowkanong():
""" """
list_date, list_do, list_ec, list_temp, ave_do_dowkanong, ave_ec_dowkanong, ave_temp_dowkanong = riverside_dowkanong.data_split()
list_mean_ec_in_aday = average_per_day(list_ec, list_date)
#created HTML
output_file = open('Chart mean EC in a day of Dowkanong.html', 'w')
chart = lineChart(name="lineChart Dowkanong E.C.", width = 1244)
xdata = range(1, 32)
ydata4 = list_mean_ec_in_aday[14:31]
ydata5 = list_mean_ec_in_aday[31:56]
ydata6 = list_mean_ec_in_aday[56:]
chart.add_serie(y=ydata4, x=xdata, name='ก.ค.')
chart.add_serie(y=ydata5, x=xdata, name='ส.ค.')
chart.add_serie(y=ydata6, x=xdata, name='ก.ย.')
chart.buildhtml()
output_file.write(chart.htmlcontent)
# close Html file
output_file.close()
def plotData(self,getTickerData):
output_file = open('ticker.html', 'w')
type = "lineChart"
chart = lineChart(name=type, x_is_date=True, x_axis_format="%Y-%m-%d", height=450, width=1300)
extra_serie = {"tooltip": {"y_start": "There is ", "y_end": " calls"}}
# Get Timestamp and Y-Values
for idx,ticker in enumerate(self.ticker):
print ticker
df = getTickerData(ticker)
timestamp = []
xdata = [time.mktime(s.timetuple()) * 1000 for s in df.index]
tickerData = df['Open']
color = "#%06x" % random.randint(0, 0xFFFFFF)
print color
chart.add_serie(y=tickerData, x=xdata, name=ticker, extra=extra_serie, **{'color': color})
chart.buildhtml()
output_file.write(chart.htmlcontent)
output_file.close()
def visualize_summary(filename):
try:
data = np.loadtxt(filename)
except Error as e:
return 'Cannot load file {}: {}'.format(filename, str(e))
chart_name = os.path.splitext(os.path.basename(filename))[0]
chart = nvd3.lineChart(name=chart_name + '_summary_chart',
height=args.chart_height,
y_axis_format='.03g')
if args.sample < 0:
step = max(data.shape[0] / -args.sample, 1)
else:
step = args.sample
xdata = np.arange(0, data.shape[0], step)
# data should have 4 dimensions.
chart.add_serie(x=xdata, y=data[xdata, 0], name='min')
chart.add_serie(x=xdata, y=data[xdata, 1], name='max')
chart.add_serie(x=xdata, y=data[xdata, 2], name='mean')
chart.add_serie(x=xdata, y=data[xdata, 2] + data[xdata, 3], name='m+std')
chart.add_serie(x=xdata, y=data[xdata, 2] - data[xdata, 3], name='m-std')
return jsonify_nvd3(chart)
def visualize_summary(filename):
try:
data = np.loadtxt(filename)
except Exception as e:
return 'Cannot load file {}: {}'.format(filename, str(e))
chart_name = os.path.splitext(os.path.basename(filename))[0]
chart = nvd3.lineChart(name=chart_name + '_summary_chart',
height=args.chart_height,
y_axis_format='.03g')
if args.sample < 0:
step = max(data.shape[0] / -args.sample, 1)
else:
step = args.sample
xdata = np.arange(0, data.shape[0], step)
# data should have 4 dimensions.
chart.add_serie(x=xdata, y=data[xdata, 0], name='min')
chart.add_serie(x=xdata, y=data[xdata, 1], name='max')
chart.add_serie(x=xdata, y=data[xdata, 2], name='mean')
chart.add_serie(x=xdata, y=data[xdata, 2] + data[xdata, 3], name='m+std')
chart.add_serie(x=xdata, y=data[xdata, 2] - data[xdata, 3], name='m-std')
return jsonify_nvd3(chart)
def plot_multiple_entitytimeseries_dbhandle(entities = [], output_file = 'immigration.html'):
'''Plots timeseries for multiple entities.
'''
db_conn = pm.Connection()
dbhandle = db_conn['news']
from nvd3 import lineChart
chart = lineChart(name='lineChart', height=400, width=700, date=True)
for entity in entities:
edges_with_entity = find_edges_with_entity(entity=entity, dbhandle=dbhandle)
ts_dict = dd(int)
for e in edges_with_entity: ts_dict[strtodate(e['date']).strftime('%s')] += 1
ts_list = [(ts_dict[k], int(k)*1000) for k in ts_dict]
ts_list.sort(tcmp)
xdata = [i[1] for i in ts_list]
ydata = [i[0] for i in ts_list]
extra_serie = {"tooltip": {"y_start": "", "y_end": " mentions"}}
chart.add_serie(name=entity, y=ydata, x=xdata, extra=extra_serie)
of = open(output_file, 'w')
chart.buildhtml()
of.write(chart.htmlcontent)
of.close()
def testgraphic(request):
if request.POST:
type = 'lineChart'
chart = lineChart(name=type, x_is_date=False)
#
xdata = range(100)
ydata = [x ** 3 + 234 for x in range(100)]
chart.add_serie(y=ydata,x=xdata,name='sas')
# chartdata = {'x': xdata, 'y': ydata}
# charttype = "lineChart"
# chartcontainer = 'piechart_container'
# data = {
# 'charttype': charttype,
# 'chartdata': chartdata,
# 'chartcontainer': chartcontainer,
# 'extra': {
# 'x_is_date': False,
# 'x_axis_format': '',
# 'tag_script_js': True,
# 'jquery_on_ready': False,
# }
# }
return HttpResponse(chart.htmlcontent)
def hello():
input_data = list(csv.reader(open('dateCrimeOutput.txt', 'rb'), delimiter='\t'))
chart = lineChart(name="lineChart", x_is_date=False, height=800, width=1800, margin_bottom=200, margin_top=40, margin_left=60, margin_right=60)
crimes = []
for row in input_data:
crimes.append([row[0], row[1], int(row[2])])
crimes = sorted(crimes, key=lambda crimes: ([crimes[0],crimes[1]]))
xdata = []
current_crime = None
i = 0
for crime in crimes:
if str(crime[0]) == current_crime:
xdata.append(crime[1])
globals()['ydata%s' % i].append(crime[2])
else:
current_crime = crime[0]
i = i+1
globals()['name%s' % i] = str(crime[0])
globals()['ydata%s' % i] = []
xdata.append(str(crime[1]))
globals()['ydata%s' % i].append(crime[2])
kwargs1 = {'shape': 'circle', 'size': '20'}
# kwargs2 = {'shape': 'cross', 'size': '4'}
i = 1
while True:
try:
chart.add_serie(name=globals()['name%s' % i], y=globals()['ydata%s' % i], x=xdata, **kwargs1)
i = i + 1
except:
break
chart.buildhtml()
print chart.htmlcontent
return chart.htmlcontent
def test_chartWithBadName(self):
name = "Chart with spaces"
chart = lineChart(name=name, date=True, height=350)
chart.buildhtml()
assert (" " not in chart.name)
assert ("spaces" in chart.name)
def make_graphs(tag_name, values=False, tofile=False):
import sqlite3 as sql
# import matplotlib.pyplot as p
# from bokeh.plotting import figure, output_file, show
from datetime import date
from nvd3 import lineChart
import time
ch_name = change_name(tag_name)
connection = sql.connect("db\\tagstats.db")
c = connection.cursor()
base = '''SELECT alles,nodes,ways,relations,used_by,data FROM "{0}" ORDER BY data ASC'''
key_db = c.execute(base.format(ch_name)).fetchall()
# list of tuple [(1,2,3), (1,2,3) ]
alles = []
n = []
w = []
r = []
u = []
d = []
value_list = []
for i in key_db:
alles.append(i[0])
n.append(i[1])
w.append(i[2])
r.append(i[3])
u.append(i[4])
d_n = str(i[5])
d_r = int(d_n[:4])
d_m = int(d_n[4:6])
d_d = int(d_n[6:])
# d_str = "{0}-{1}-{2}".format(d_n[:4], d_n[4:6], d_n[6:])
# d.append(d_str)
# print(d_str)
data_obj = date(d_r, d_m, d_d)
new_d = time.mktime(data_obj.timetuple()) * 1000
d.append(new_d)
# d.append(i[5])
# d.append("{0},{1},{2}".format(d_n[:4], d_n[4:6], d_n[6:]))
chart = lineChart(name=ch_name,
height="400",
width="800",
x_is_date=True,
x_axis_format="%d-%m",
use_interactive_guideline=True)
chart.add_serie(x=d, y=alles, name="All")
chart.add_serie(x=d, y=n, name="Nodes")
chart.add_serie(x=d, y=w, name="Ways")
chart.add_serie(x=d, y=r, name="Relations")
chart.add_serie(x=d, y=u, name="Users used")
# chart.create_x_axis(
# name=x_Axis, label="Data", date=True, format="%Y%m%d")
if tofile == True:
out_f = open("{0}.html".format(ch_name), 'w')
chart.buildhtml()
out_f.write(chart.htmlcontent)
out_f.close()
else:
chart.buildcontent()
tag_data = chart.htmlcontent
# make_graphs("area:highway")
connection.close()
if values == True:
# make_graphs("area:highway",True)
connection = sql.connect("db\\tagstats_values.db")
c = connection.cursor()
distinct = '''SELECT DISTINCT value FROM "{0}"'''
dist_db = c.execute(distinct.format(ch_name)).fetchall()
for i in dist_db:
# clear tables
alles.clear()
n.clear()
w.clear()
r.clear()
d.clear()
vals = '''SELECT alles,nodes,ways,relations,data FROM "{0}" WHERE value="{1}" ORDER BY data ASC'''
value_name = i[0]
val_db = c.execute(vals.format(ch_name, value_name)).fetchall()
for i in val_db:
alles.append(i[0])
n.append(i[1])
w.append(i[2])
r.append(i[3])
d_n = str(i[4])
d_r = int(d_n[:4])
d_m = int(d_n[4:6])
d_d = int(d_n[6:])
data_obj = date(d_r, d_m, d_d)
new_d = time.mktime(data_obj.timetuple()) * 1000
d.append(new_d)
# change this shit...it will makes problems with file names
chart_name = ch_name + "-" + value_name
chart = lineChart(name=chart_name,
height="400",
width="800",
x_is_date=True,
x_axis_format="%d-%m",
use_interactive_guideline=True)
chart.add_serie(x=d, y=alles, name="All")
chart.add_serie(x=d, y=n, name="Nodes")
chart.add_serie(x=d, y=w, name="Ways")
chart.add_serie(x=d, y=r, name="Relations")
if tofile == True:
out_f = open("{0}.html".format(chart_name), 'w')
chart.buildhtml()
out_f.write(chart.htmlcontent)
out_f.close()
else:
# val_div = chart.buildcontainer()
# val_js = chart.buildjschart()
chart.buildcontent()
val_data = chart.htmlcontent
sm_dict = {"name": value_name, "graph": val_data}
value_list.append(sm_dict)
connection.close()
# print(values)
# print(value_list)
return (tag_name, values, tag_data, value_list, ch_name)
"""
Examples for Python-nvd3 is a Python wrapper for NVD3 graph library.
NVD3 is an attempt to build re-usable charts and chart components
for d3.js without taking away the power that d3.js gives you.
Project location : https://github.com/areski/python-nvd3
"""
from nvd3 import lineChart
import math
#Open File for test
output_file = open('test_lineChart.html', 'w')
#---------------------------------------
type = "lineChart"
chart = lineChart(name=type, date=False, height='100%')
xdata = []
ydata = []
ydata2 = []
for i in range(0, 101):
xdata.append(i)
x = i * 0.1
ydata.append(math.sin(math.pi * x))
ydata2.append(0.5 * math.cos(math.pi * x))
kwargs1 = {'color': 'black'}
kwargs2 = {'color': 'red'}
extra_serie = {"tooltip": {"y_start": "There is ", "y_end": " calls"}}
chart.add_serie(y=ydata, x=xdata, name='sine', extra=extra_serie, **kwargs1)
# print humidity
cur = c.cursor()
cur.execute("SELECT hum from data")
hum = cur.fetchall()
print hum
# print unixtime
cur = c.cursor()
cur.execute("SELECT ut from data")
ut = cur.fetchall()
print ut
# Open File to write the D3 Graph
output_file = open('html/index.html', 'w')
chart = lineChart(name="lineChart", x_is_date=False, x_axis_format="AM_PM")
xdata = range(24)
ydata = [
25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 24, 25, 25, 25, 25, 25, 25, 25,
25, 25, 25, 25, 25
]
ydata2 = [
18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18,
18, 18, 18, 18, 18
]
extra_serie = {"tooltip": {"y_start": "There are ", "y_end": " calls"}}
chart.add_serie(
y=ydata,
x=xdata,
width=400, jquery_on_ready=True)
chart.set_containerheader("\n\n<h2>" + type + "</h2>\n\n")
color_list = ['orange', 'yellow', '#C5E946', '#95b43f', 'red', '#FF2259', '#F6A641']
extra_serie = {"tooltip": {"y_start": "", "y_end": " cal"}, "color_list": color_list}
xdata = ["Orange", "Banana", "Pear", "Kiwi", "Apple", "Strawberry", "Pineapple"]
ydata = [3, 4, 2, 1, 5, 7, 3]
chart.add_serie(y=ydata, x=xdata, extra=extra_serie)
chart.buildcontent()
output_file.write(chart.htmlcontent)
# ---------------------------------------
name = "lineChart-different-x-axis"
type = "lineChart"
chart = lineChart(name=name, height=400, width=800, x_is_date=False,
jquery_on_ready=True)
chart.set_containerheader("\n\n<h2>" + name + "</h2>\n\n")
xdata = [1 + x * 2 for x in list(range(nb_element))]
xdata10 = [0 + x * 2 for x in list(range(nb_element))]
ydata = [i + random.randint(1, 10) for i in range(nb_element)]
ydata2 = [x * 2 for x in ydata]
#Configure a color for a specific serie
kwargs1 = {'color': 'green'}
kwargs2 = {'color': 'red'}
extra_serie = {"tooltip": {"y_start": "There is ", "y_end": " odd"}}
chart.add_serie(name="Odd X-Axis", y=ydata, x=xdata, extra=extra_serie, **kwargs1)
extra_serie = {"tooltip": {"y_start": "", "y_end": " even"}}
chart.add_serie(name="Even X-Axis", y=ydata2, x=xdata10, extra=extra_serie, **kwargs2)
def index_chart(request):
"""
lineChart page
"""
today = datetime.date.today()
year = today.year
stock_list = HmChart.objects.filter(chart_in_hm_choices=u'STOCK',
chart_time__year=year)
xdata = [
int(calendar.timegm(t.chart_time.timetuple())) * 1000
for t in stock_list
]
ydata = [float("%.2f" % v.chart_value) for v in stock_list]
chart = lineChart(name='lineChart',
container='lineChart',
height=400,
width=400,
x_is_date=True,
x_axis_format="%d %b %Y")
#xdata = [1365026400000000, 1365026500000000, 1365026600000000]
#ydata = [-6, 5, -1]
#tooltip_str = "'<center><b>'+key+'</b></center>' + y + ' 增长 ' + x;"
extra_serie = {
"tooltip": {
"y_start": "净值",
"y_end": ""
},
"date_format": "%Y年%m月%d日",
#"tooltip_str": tooltip_str,
}
chart.add_serie(
name=u"股票净值",
y=ydata,
x=xdata,
extra=extra_serie,
)
chart.buildhtml()
chart_html = chart.jschart
#--------------------------------------------------------------
chart2 = lineChart(name='lineChart2',
container='lineChart2',
height=400,
width=400,
x_is_date=True,
x_axis_format="%d %b %Y")
fund_list = HmChart.objects.filter(chart_in_hm_choices=u'FUND',
chart_time__year=year)
xdata2 = [
int(calendar.timegm(t.chart_time.timetuple())) * 1000
for t in fund_list
]
ydata2 = [float("%.2f" % v.chart_value) for v in fund_list]
#xdata2 = [1365988400000000, 1365026500000000, 1365026600000000]
#ydata2 = [8, 5, 3]
extra_serie2 = {
"tooltip": {
"y_start": "净值",
"y_end": ""
},
"date_format": "%Y年%m月%d日"
}
chart2.add_serie(name=u"期货净值", y=ydata2, x=xdata2, extra=extra_serie2)
chart2.buildhtml()
chart_html2 = chart2.jschart
adimg = HmadManager.objects.all()
return chart_html, chart_html2
"color_list": color_list
}
xdata = [
"Orange", "Banana", "Pear", "Kiwi", "Apple", "Strawberry", "Pineapple"
]
ydata = [3, 4, 2, 1, 5, 7, 3]
chart.add_serie(y=ydata, x=xdata, extra=extra_serie)
chart.buildcontent()
output_file.write(chart.htmlcontent)
#---------------------------------------
type = "lineChart"
chart = lineChart(name=type,
height=350,
date=True,
x_axis_format="%d %b %Y %H",
jquery_on_ready=True)
chart.set_containerheader("\n\n<h2>" + type + "</h2>\n\n")
xdata = list(range(nb_element))
xdata = [start_time + x * 1000000000 for x in xdata]
ydata = [i + random.randint(1, 10) for i in range(nb_element)]
ydata2 = [x * 2 for x in ydata]
#Configure a color for a specific serie
kwargs1 = {'color': 'green'}
kwargs2 = {'color': 'red'}
extra_serie = {
"tooltip": {
"color_list": color_list
}
xdata = [
"Orange", "Banana", "Pear", "Kiwi", "Apple", "Strawberry", "Pineapple"
]
ydata = [3, 4, 2, 1, 5, 7, 3]
chart.add_serie(y=ydata, x=xdata, extra=extra_serie)
chart.buildcontent()
output_file.write(chart.htmlcontent)
#---------------------------------------
type = "lineChart"
chart = lineChart(name=type,
height=350,
date=True,
x_axis_format="%d %b %Y %H",
jquery_on_ready=True)
chart.set_containerheader("\n\n<h2>" + type + "</h2>\n\n")
xdata = list(range(nb_element))
xdata = [start_time + x * 1000000000 for x in xdata]
ydata = [i + random.randint(1, 10) for i in range(nb_element)]
ydata2 = [x * 2 for x in ydata]
#Configure a color for a specific serie
kwargs1 = {'color': 'green'}
kwargs2 = {'color': 'red'}
extra_serie = {
"tooltip": {
type = "pieChart"
chart = pieChart(name=type, color_category='category20c', height=400, width=400)
chart.set_containerheader("\n\n<h2>" + type + "</h2>\n\n")
color_list = ['orange', 'yellow', '#C5E946', '#95b43f', 'red', '#FF2259', '#F6A641']
extra_serie = {"tooltip": {"y_start": "", "y_end": " cal"}, "color_list": color_list}
xdata = ["Orange", "Banana", "Pear", "Kiwi", "Apple", "Strawberry", "Pineapple"]
ydata = [3, 4, 2, 1, 5, 7, 3]
chart.add_serie(y=ydata, x=xdata, extra=extra_serie)
chart.buildhtml()
output_file.write(chart.htmlcontent)
#---------------------------------------
type = "lineChart"
chart = lineChart(name=type, height=350, date=True, x_axis_date_format="%d %b %Y %H")
chart.set_containerheader("\n\n<h2>" + type + "</h2>\n\n")
xdata = list(range(nb_element))
xdata = [start_time + x * 1000000000 for x in xdata]
ydata = [i + random.randint(1, 10) for i in range(nb_element)]
ydata2 = [x * 2 for x in ydata]
#Configure a color for a specific serie
kwargs1 = {'color': 'green'}
kwargs2 = {'color': 'red'}
extra_serie = {"tooltip": {"y_start": "There is ", "y_end": " calls"},
"date_format": "%d %b %Y %I:%M:%S %p"}
chart.add_serie(name="Count", y=ydata, x=xdata, extra=extra_serie, **kwargs1)
extra_serie = {"tooltip": {"y_start": "", "y_end": " min"}}
chart.add_serie(name="Duration", y=ydata2, x=xdata, extra=extra_serie, **kwargs2)
NVD3 is an attempt to build re-usable charts and chart components
for d3.js without taking away the power that d3.js gives you.
Project location : https://github.com/areski/python-nvd3
"""
from nvd3 import lineChart
import math
from numpy import sin, pi, linspace
output_file = open('test_lineChartXY.html', 'w')
chart = lineChart(name="lineChart",
date=False,
x_format="f",
y_format="f",
width=500,
height=500,
show_legend=False)
#lissajous parameters of a/b
a = [1, 3, 5, 3]
b = [1, 5, 7, 4]
delta = pi / 2
t = linspace(-pi, pi, 300)
for i in range(0, 4):
x = sin(a[i] * t + delta)
y = sin(b[i] * t)
chart.add_serie(y=y,
import pandas as pd
import nvd3
from IPython.display import Image
from IPython.core.display import display, HTML
from nvd3 import lineChart
#
df = pd.read_excel(r"lg_apple.xlsx")
df = pd.DataFrame(df)
#
output_file = open('apple.html', 'w')
chart = lineChart(width=1000,
name="lineChart",
x_is_date=False,
x_axis_format=None)
#
xdata = df['features']
y1 = df['SVM_7']
y2 = df['SVM_37']
y3 = df['NN_7']
y4 = df['NN_37']
#
extra_serie = {"tooltip": {"y_start": "There are ", "y_end": " calls"}}
chart.add_serie(y=y1, x=xdata, name='SVM 7 years', extra=extra_serie)
extra_serie = {"tooltip": {"y_start": "", "y_end": " min"}}
chart.add_serie(y=y2, x=xdata, name='SVM 37 years', extra=extra_serie)
extra_serie = {"tooltip": {"y_start": "There are ", "y_end": " calls"}}
chart.add_serie(y=y3,
x=xdata,
name='Neural Network 7 years',
extra=extra_serie)
extra_serie = {"tooltip": {"y_start": "There are ", "y_end": " calls"}}
NVD3 is an attempt to build re-usable charts and chart components
for d3.js without taking away the power that d3.js gives you.
Project location : https://github.com/areski/python-nvd3
"""
from nvd3 import lineChart
from numpy import sin, pi, linspace
output_file = open('test_lineChartXY.html', 'w')
type = "lineChart"
chart = lineChart(name=type,
x_is_date=False,
x_axis_format=".1f",
y_axis_format=".1f",
width=500,
height=500,
show_legend=False)
#lissajous parameters of a/b
a = [1, 3, 5, 3]
b = [1, 5, 7, 4]
delta = pi / 2
t = linspace(-pi, pi, 300)
for i in range(0, 4):
x = sin(a[i] * t + delta)
y = sin(b[i] * t)
chart.add_serie(y=y,
x=x,
"""
Examples for Python-nvd3 is a Python wrapper for NVD3 graph library.
NVD3 is an attempt to build re-usable charts and chart components
for d3.js without taking away the power that d3.js gives you.
Project location : https://github.com/areski/python-nvd3
"""
from nvd3 import lineChart
import math
#Open File for test
output_file = open('test_lineChart.html', 'w')
#---------------------------------------
type = "lineChart"
chart = lineChart(name=type, date=False, x_axis_format="AM_PM")
xdata = []
ydata = []
ydata2 = []
ydata = [
0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 4, 3, 3, 5, 7, 5, 3, 16, 6, 9, 15, 4, 12
]
ydata2 = [
9, 8, 11, 8, 3, 7, 10, 8, 6, 6, 9, 6, 5, 4, 3, 10, 0, 6, 3, 1, 0, 0, 0, 1
]
#ydata3 = [0, 0, 1, 1, 0, 2, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0]
for i in range(0, 24):
xdata.append(i)
from nvd3 import lineWithFocusChart
from nvd3 import stackedAreaChart
#TODO: demo_all.py should have an example for all charts
from nvd3 import multiBarHorizontalChart
from nvd3 import linePlusBarChart
from nvd3 import cumulativeLineChart
import random
import datetime
import time
#Open File for test
output_file = open('test.html', 'w')
#---------------------------------------
type = "lineChart"
chart = lineChart(name=type, date=True, height=350)
chart.set_containerheader("\n\n<h2>" + type + "</h2>\n\n")
start_time = int(time.mktime(datetime.datetime(2012, 6, 1).timetuple()) * 1000)
nb_element = 100
xdata = range(nb_element)
xdata = map(lambda x: start_time + x * 1000000000, xdata)
ydata = [i + random.randint(1, 10) for i in range(nb_element)]
ydata2 = map(lambda x: x * 2, ydata)
chart.add_serie(y=ydata, x=xdata)
chart.add_serie(y=ydata2, x=xdata)
chart.buildhtml()
output_file.write(chart.htmlcontent)
},
"color_list": color_list
}
xdata = [
"Orange", "Banana", "Pear", "Kiwi", "Apple", "Strawberry", "Pineapple"
]
ydata = [3, 4, 2, 1, 5, 7, 3]
chart.add_serie(y=ydata, x=xdata, extra=extra_serie)
chart.buildcontent()
output_file.write(chart.htmlcontent)
#---------------------------------------
type = "lineChart"
chart = lineChart(height=350,
x_is_date=True,
x_axis_format="%d %b %Y %H",
jquery_on_ready=True)
chart.set_containerheader("\n\n<h2>" + type + "</h2>\n\n")
xdata = list(range(nb_element))
xdata = [start_time + x * 1000000000 for x in xdata]
ydata = [i + random.randint(1, 10) for i in range(nb_element)]
ydata2 = [x * 2 for x in ydata]
#Configure a color for a specific serie
kwargs1 = {'color': 'green'}
kwargs2 = {'color': 'red'}
extra_serie = {
"tooltip": {
"y_start": "There is ",
def draw(handle, workload):
x_data = range(0, len(workload))
chart = lineChart(name="lineChart", width=1000, height=500)
chart.add_serie(y=workload, x=x_data, name='Workload')
chart.buildhtml()
handle.write(str(chart))
