source.on_change('data', clear_message)
hover.callback = CustomJS(args=dict(cb=checkbox),
code="""
if(!cb.active.includes(%d)) {
document.getElementsByClassName('bk-tooltip')[%d].style.display = 'none';
}
""" % (1, 0))
checkbox.callback = CustomJS(args=dict(
p0=circle,
p1=line_regr,
p2=circle_fit,
),
code="""
//Toggle glyph visibility based on checkbox status
p0.visible = cb_obj.active.includes(0);
p1.visible = cb_obj.active.includes(1);
p2.visible = cb_obj.active.includes(2);
""")
click_reset_tool = CustomJS(args=dict(p=plot),
code="""
p.toolbar.tools[""" + util.reset_tool_index(g.TOOLS3) +
"""].trigger('do');
""")
device_slc.on_change('value', device_slc_callback)
device_slc.js_on_change(
'value',
def templateAcceptedLoanPerRegion():
LABELS = ["Central", "Mid - Atlantic", "NorthEast", "NorthWest", "South", "SouthEast", "SouthWest"]
colors = ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#17becf']
data = pd.read_csv(DATA + 'perc_acc_loan_per_region_date_compact.csv')
central = data['Central'] / 100
midatl = data['Mid-Atlantic'] / 100
northe = data['Northeast'] / 100
northw = data['Northwest'] / 100
south = data['South'] / 100
southe = data['Southeast'] / 100
southw = data['Southwest'] / 100
date = data['date']
source = ColumnDataSource(data=dict(x=[datetime.strptime(d, '%b-%Y') for d in date.values],
Central=central,
MidAtlantic=midatl,
Northeast=northe,
Northwest=northw,
South=south,
Southeast=southe,
Southwest=southw
))
props = dict(line_width=4, line_alpha=0.8)
p = Figure(x_axis_type="datetime", width=1200, height=380)
p0 = p.line('x', 'Central', source=source, legend="Central", line_color=colors[0], **props)
p1 = p.line('x', 'MidAtlantic', source=source, legend="Mid - Atlantic", line_color=colors[1], **props)
p2 = p.line('x', 'Northeast', source=source, legend="NorthEast", line_color=colors[2], **props)
p3 = p.line('x', 'Northwest', source=source, legend="NorthWest", line_color=colors[3], **props)
p4 = p.line('x', 'South', source=source, legend="South", line_color=colors[4], **props)
p5 = p.line('x', 'Southeast', source=source, legend="SouthEast", line_color=colors[5], **props)
p6 = p.line('x', 'Southwest', source=source, legend="SouthWest", line_color=colors[6], **props)
p.yaxis.axis_label = 'Percentage of accepted loans'
p.yaxis[0].formatter = NumeralTickFormatter(format="0.0%")
p.border_fill_color = LIGHT_GREEN
p.background_fill_color = LIGHT_GREEN
p.legend.background_fill_color = LIGHT_GREEN
p.legend.background_fill_alpha = 0.5
checkbox = CheckboxGroup(
labels=LABELS,
inline=True,
active=[0, 1, 2, 3, 4, 5, 6],
width=800)
code = """
//console.log(cb_obj.active);
p0.visible = false;
p1.visible = false;
p2.visible = false;
p3.visible = false;
p4.visible = false;
p5.visible = false;
p6.visible = false;
for (i in checkbox.active) {
//console.log(cb_obj.active[i]);
if (checkbox.active[i] == 0) {
p0.visible = true;
} else if (checkbox.active[i] == 1) {
p1.visible = true;
} else if (checkbox.active[i] == 2) {
p2.visible = true;
} else if (checkbox.active[i] == 3) {
p3.visible = true;
} else if (checkbox.active[i] == 4) {
p4.visible = true;
} else if (checkbox.active[i] == 5) {
p5.visible = true;
} else if (checkbox.active[i] == 6) {
p6.visible = true;
}
}
"""
checkbox.callback = CustomJS(args=dict(p0=p0, p1=p1, p2=p2, p3=p3, p4=p4, p5=p5, p6=p6, checkbox=checkbox),
code=code)
boundaries = open(DATA + 'boundaries.json').read()
states = json.loads(boundaries)
region_state = pd.read_csv(DATA + 'region-state.csv', header=0)
region_state = region_state.set_index('state')
state_xs = [states[code]["lons"] for code in states]
state_ys = [states[code]["lats"] for code in states]
name = states.keys()
colors_state = []
for i in name:
if i != 'AK' and i != 'HI':
reg = region_state.loc[i]['region']
if reg == "Central":
colors_state.append(colors[0])
elif reg == "Mid-Atlantic":
colors_state.append(colors[1])
elif reg == "Northeast":
colors_state.append(colors[2])
elif reg == "Northwest":
colors_state.append(colors[3])
elif reg == "South":
colors_state.append(colors[4])
elif reg == "Southeast":
colors_state.append(colors[5])
elif reg == "Southwest":
colors_state.append(colors[6])
source = ColumnDataSource(data=dict(
x=state_xs,
y=state_ys,
name=name,
colors=colors_state,
))
q = figure(title="",
toolbar_location=None,
plot_width=300,
plot_height=160
)
q.xaxis.visible = False
q.yaxis.visible = False
q.xgrid.grid_line_color = None
q.ygrid.grid_line_color = None
q.min_border_left = False
q.min_border_right = False
q.min_border_top = False
q.min_border_bottom = False
q.border_fill_color = LIGHT_GREEN
q.background_fill_color = LIGHT_GREEN
q.patches('x', 'y', source=source,
fill_color='colors',
fill_alpha=0.9, line_color="white", line_width=0.1)
layout = VBox(q, checkbox, p)
# show(layout)
script, div = components(layout)
return script, div
checkbox1 = CheckboxGroup(labels=["", "", "", "", "", "", "", ""],
active=[0, 1, 2, 3, 4, 5, 6, 7, 8],
sizing_mode='scale_both',
width=200,
height=200)
checkbox1.height = 200
checkbox1.callback = CustomJS.from_coffeescript(args=dict(l0=l_mon,
l1=l_tue,
l2=l_wed,
l3=l_thu,
l4=l_fri,
l5=l_sat,
l6=l_sun,
l7=l_std,
checkbox=checkbox1),
code="""
l0.visible = 0 in checkbox.active;
l1.visible = 1 in checkbox.active;
l2.visible = 2 in checkbox.active;
l3.visible = 3 in checkbox.active;
l4.visible = 4 in checkbox.active;
l5.visible = 5 in checkbox.active;
l6.visible = 6 in checkbox.active;
l7.visible = 7 in checkbox.active;
""")
checkbox2 = CheckboxGroup(labels=["", "", ""], active=[0, 1, 2])
checkbox2.callback = CustomJS.from_coffeescript(args=dict(l0=l_14,
l1=l_15,
l2=l_16,
checkbox=checkbox2),
def plot_density_onegame(df, name, feat_plot):
bandwidth = 5
range_start = -100
range_end = 180
r = len(df.groupby(name).count().index)
l = list(df.groupby(name).count().index)
l = sorted(l)
def style(p):
# Title
p.title.align = 'center'
p.title.text_font_size = '20pt'
p.title.text_font = 'serif'
# Axis titles
p.xaxis.axis_label_text_font_size = '14pt'
p.xaxis.axis_label_text_font_style = 'bold'
p.yaxis.axis_label_text_font_size = '14pt'
p.yaxis.axis_label_text_font_style = 'bold'
# Tick labels
p.xaxis.major_label_text_font_size = '12pt'
p.yaxis.major_label_text_font_size = '12pt'
return p
x = np.linspace(range_start, range_end, 100)
source_dict = dict(x=x)
line_dict = dict()
line_colors = Category20_16
line_colors.sort()
for i in range(0, r):
tmp_df = df[df[name] == l[i]]
tmp_kde = gaussian_kde(tmp_df[feat_plot], bw_method=bandwidth)
tmp_y = tmp_kde.pdf(x)
#y_number = "y%s" % i
y_number = l[i]
source_dict[y_number] = tmp_y
source = ColumnDataSource(data=source_dict)
p = figure(plot_width=600, plot_height=400)
for i in range(0, r):
#y_number = "y%s" % i
y_number = l[i]
line_number = "line%s" % i
line = p.line('x',
y_number,
source=source,
line_width=3,
line_alpha=0.6,
line_color=line_colors[i])
line_dict[line_number] = line
hover = HoverTool(tooltips=[(feat_plot, '$x'), ('Density', '$y')],
line_policy='next')
p.add_tools(hover)
p = style(p)
checkbox = CheckboxGroup(labels=l, active=list(range(r)))
checkbox.callback = CustomJS(args=line_dict,
code="""
//console.log(cb_obj.active);
line0.visible = false;
line1.visible = false;
line2.visible = false;
line3.visible = false;
line4.visible = false;
line5.visible = false;
line6.visible = false;
line7.visible = false;
line8.visible = false;
line9.visible = false;
line10.visible = false;
line11.visible = false;
for (i in cb_obj.active) {
//console.log(cb_obj.active[i]);
if (cb_obj.active[i] == 0) {
line0.visible = true;
} else if (cb_obj.active[i] == 1) {
line1.visible = true;
}
else if (cb_obj.active[i] == 2) {
line2.visible = true;
}
else if (cb_obj.active[i] == 3) {
line3.visible = true;
}
else if (cb_obj.active[i] == 4) {
line4.visible = true;
}
else if (cb_obj.active[i] == 5) {
line5.visible = true;
}
else if (cb_obj.active[i] == 6) {
line6.visible = true;
}
else if (cb_obj.active[i] == 7) {
line7.visible = true;
}
else if (cb_obj.active[i] == 8) {
line8.visible = true;
}
else if (cb_obj.active[i] == 9) {
line9.visible = true;
}
else if (cb_obj.active[i] == 10) {
line10.visible = true;
}
else if (cb_obj.active[i] == 11) {
line11.visible = true;
}
}
""")
controls = WidgetBox(checkbox)
layout = row(controls, p)
tab = Panel(child=layout, title="Density Plot of " + feat_plot)
return tab
def make_timeline_html(input_dir_path: str, output_path: str) -> None:
# Load Data
path = Path(input_dir_path) / 'pep_graph.gpickle'
pep_graph = nx.read_gpickle(path)
path = Path(input_dir_path) / 'python_release_info.csv'
release_df = pd.read_csv(path,
encoding='utf-8',
parse_dates=['release_date'])
release_df = release_df[release_df.micro == 0]
release_df['color'] = release_df.major.apply(lambda x: PYTHON_YELLOW_COLOR_CODE if x == 2 else PYTHON_BLUE_COLOR_CODE) # 2, 3以外が出てきたら再考すること
node_dict = dict(pep_graph.nodes(data=True))
date_list = [value['Created_dt'] for key, value in node_dict.items()]
min_date = datetime.datetime(min(date_list).year, 1, 1)
py2_release_label_data_source = tl_compo.generate_release_label_source(release_df,
major_version=2,
pos_x=min_date)
py3_release_label_data_source = tl_compo.generate_release_label_source(release_df,
major_version=3,
pos_x=min_date)
py2_release_line_data_source = tl_compo.generate_release_line_data_source(release_df,
major_version=2)
py3_release_line_data_source = tl_compo.generate_release_line_data_source(release_df,
major_version=3)
release_source_dict = {'py2_release_label_source': py2_release_label_data_source,
'py3_release_label_source': py3_release_label_data_source,
'py2_release_line_source': py2_release_line_data_source,
'py3_release_line_source': py3_release_line_data_source
}
all_pep_data_source = compo.generate_node_data_source(pep_graph)
# DataTable用のデータソースを用意する
linked_from_table_source = table_compo.generate_data_table_data_source(pep_graph)
link_to_table_source = table_compo.generate_data_table_data_source(pep_graph)
linked_from_data_table = table_compo.generate_data_table(linked_from_table_source)
link_to_data_table = table_compo.generate_data_table(link_to_table_source)
linked_from_table_title_div = Div(text='<strong>PEP N is linked from ...</strong>',
style={'color': BASE_FONT_COLOR})
link_to_table_title_div = Div(text='<strong>PEP N links to ...</strong>',
style={'color': BASE_FONT_COLOR})
# Timeline用のデータソースを用意する
timeline_display_circle_source = tl_compo.generate_timeline_data_source(pep_graph)
timeline_label_source = tl_compo.generate_timeline_label_data_source(pep_graph)
desc_start_date, _ = tl_compo.get_timeline_plot_range(pep_graph)
desc_start_date = desc_start_date + datetime.timedelta(days=30)
timeline_desc_label_source = tl_compo.generate_timeline_desc_data_source(xs=[desc_start_date, desc_start_date],
ys=[1.7, 0.1],
font_size=15)
# 入力ボックス用のデータソース生成
error_message_div = Div(width=300, height=8, style={'color': 'red'}, text='')
title_div = Div(width=700,
style={'font-size': 'large',
'line-height': '1.5',
'color': BASE_FONT_COLOR})
title_div.text = """
Let's enter the PEP number in the left text box.<br>
Then you can see the following information.
<li>Which PEPs do link that PEP?</li>
<li>Which PEPs are linked from that PEP?</li>
"""
checkbox_group = CheckboxGroup(labels=["Show Python 2 release dates",
"Show Python 3 release dates"],
active=[0, 1])
def callback_input_pep_number(all_pep_data_source=all_pep_data_source,
link_to_table_source=link_to_table_source,
linked_from_table_source=linked_from_table_source,
link_to_table_title_div=link_to_table_title_div,
linked_from_table_title_div=linked_from_table_title_div,
timeline_display_circle_source=timeline_display_circle_source,
timeline_label_source=timeline_label_source,
timeline_desc_source=timeline_desc_label_source,
title_div=title_div,
error_message_div=error_message_div) -> None:
"""
テキストボックスに文字入力されたときに実行される関数。
PyScriptを使ってJavaScriptに変換される。
参考: https://bokeh.pydata.org/en/latest/docs/user_guide/interaction/callbacks.html#customjs-with-a-python-function
* このパラメータの設定の仕方以外にもあるかもしれない
:param all_pep_data_source:
:param link_to_table_source:
:param linked_from_table_source:
:param link_to_table_title_div:
:param linked_from_table_title_div:
:param timeline_display_circle_source:
:param timeline_label_source:
:param timeline_desc_source:
:param title_div:
:param error_message_div:
:param debug_div:
:return:
"""
inputed_text = cb_obj['value']
# PyScriptで変換するときに自分の外側の関数の呼び方がわからないので、
# 暫定で関数内関数で定義する。
def create_header_text(pep_dict: dict) -> str:
if not pep_dict:
return 'Not Found.'
# .formatを使うとJavaScript変換後に実行時エラーになるので、
# +演算子で連結している
description_text = "<span>Created: " \
+ pep_dict['Created_str'] \
+ " Type: " \
+ pep_dict['Type'] \
+ "<br>"
link_text = "<a href='https://www.python.org/dev/peps/pep-" \
+ pep_dict['index'] \
+ "/' target='_blank'>PEP " \
+ pep_dict['PEP'] \
+ "</a>"
title_text = "<span style='font-size : xx-large;'>" \
+ link_text \
+ "<br>" \
+ pep_dict['Title'] \
+ " (" + pep_dict['Status'] + ")" \
+ "</span>"
return description_text + title_text
def search_index_by_pep_number(text: str) -> int:
index = 0
for pep_number in all_pep_data_source['data']['PEP']:
if text == str(pep_number):
return index
index += 1
return -1 # Not Found
def get_inputed_pep_dict(text: int) -> dict:
selected_index = search_index_by_pep_number(text)
if selected_index == -1:
return {}
pep_dict = {}
for key, value in all_pep_data_source.data.items():
pep_dict[key] = value[selected_index]
return pep_dict
def get_pep_info(list_index: int) -> dict:
pep_dict = {}
for key, value in all_pep_data_source['data'].items():
pep_dict[key] = value[list_index]
return pep_dict
def get_neighbor_node_info(pep_dict: dict,
neighbor_type: str) -> dict:
neighbors = dict()
for key, value in all_pep_data_source.data.items():
neighbors[key] = []
for pep_id in pep_dict[neighbor_type]:
index = search_index_by_pep_number(int(pep_id))
work_pep_dict = get_pep_info(index)
for key in neighbors.keys():
neighbors[key].append(work_pep_dict[key])
return neighbors
def generate_timeline_source_dict(pep_dict: dict) -> dict:
in_edge_nodes_dict = get_neighbor_node_info(pep_dict,
'in_edge_nodes')
out_edge_nodes_dict = get_neighbor_node_info(pep_dict,
'out_edge_nodes')
in_edge_nodes_dict['y'] = [1.5] * len(in_edge_nodes_dict['PEP'])
out_edge_nodes_dict['y'] = [0.5] * len(out_edge_nodes_dict['PEP'])
timeline_source_dict = in_edge_nodes_dict
del timeline_source_dict['in_degree']
del timeline_source_dict['in_edge_nodes']
del timeline_source_dict['out_degree']
del timeline_source_dict['out_edge_nodes']
for key, value in timeline_source_dict.items():
timeline_source_dict[key] += out_edge_nodes_dict[key]
if key == 'y':
timeline_source_dict[key].append(1)
else:
timeline_source_dict[key].append(pep_dict[key])
return timeline_source_dict
def update_data_table(pep_dict: dict) -> None:
linked_from_table_title_div.text = '<strong>PEP ' \
+ pep_dict['PEP'] \
+ ' is linked from ...</strong>'
link_to_table_title_div.text = '<strong>PEP ' \
+ pep_dict['PEP'] \
+ ' links to ...</strong>'
in_edge_nodes_dict = get_neighbor_node_info(pep_dict,
'in_edge_nodes')
linked_from_table_source.data = in_edge_nodes_dict
linked_from_table_source.change.emit()
out_edge_nodes_dict = get_neighbor_node_info(pep_dict,
'out_edge_nodes')
link_to_table_source.data = out_edge_nodes_dict
link_to_table_source.change.emit()
def update_timeline(pep_dict: dict) -> None:
timeline_circle_dict = generate_timeline_source_dict(pep_dict)
timeline_display_circle_source.data = timeline_circle_dict
timeline_display_circle_source.change.emit()
timeline_label_dict = generate_timeline_source_dict(pep_dict)
timeline_label_dict['displayed_text'] = timeline_label_dict['PEP']
timeline_label_source.data = timeline_label_dict
timeline_label_source.change.emit()
texts = ['PEP ' + pep_dict['PEP'] + ' is linked from...',
'PEP ' + pep_dict['PEP'] + ' links to...', ]
timeline_desc_dict = dict(x=timeline_desc_source.data['x'],
y=timeline_desc_source.data['y'],
text=texts,
size=timeline_desc_source.data['size'],
)
timeline_desc_source.data = timeline_desc_dict
timeline_desc_source.change.emit()
# 正規表現でタグを除去したいけど、JS変換後にreを呼べないので、暫定で<と>を外す
inputed_text = inputed_text.replace('<', '')
inputed_text = inputed_text.replace('>', '')
inputed_text = inputed_text.strip()
# 入力文字のチェック
if not inputed_text:
error_message_div.text = 'Please enter the number of PEP' + inputed_text
return
inputed_text = inputed_text.lstrip('0')
# 表示の更新
selected_pep_dict = get_inputed_pep_dict(inputed_text)
if selected_pep_dict:
title_div.text = create_header_text(selected_pep_dict)
update_data_table(selected_pep_dict)
update_timeline(selected_pep_dict)
error_message_div.text = ""
else:
error_message_div.text = "Not Found: PEP " + inputed_text
def callback_change_checkbox(py2_label_source=py2_release_label_data_source,
py2_line_source=py2_release_line_data_source,
py3_label_source=py3_release_label_data_source,
py3_line_source=py3_release_line_data_source):
def switch_show_or_hide(label_source, line_source, major_version):
label_data = label_source.data
line_data = line_source.data
check_box_index_map = {2: 0, 3: 1}
if check_box_index_map[major_version] in cb_obj.active:
label_data['alpha'] = [1] * len(label_data['alpha'])
line_data['alpha'] = [1] * len(line_data['alpha'])
else:
label_data['alpha'] = [0] * len(label_data['alpha'])
line_data['alpha'] = [0] * len(line_data['alpha'])
label_source.data = label_data
label_source.change.emit()
line_source.data = line_data
line_source.change.emit()
switch_show_or_hide(py2_label_source, py2_line_source, 2)
switch_show_or_hide(py3_label_source, py3_line_source, 3)
# Header Component
pep_textinput = TextInput(title='PEP:',
placeholder='Please enter the PEP number.',
callback=CustomJS.from_py_func(callback_input_pep_number),
width=190)
info_div = Div(width=200, height=20,
style={'background-color': '#175A89',
'padding': '5px',
'color': '#FFFFFF'})
info_div.text = "<li>" \
"<a href='https://github.com/komo-fr/pep_map_site'><font color='#FFFFFF'>repository</font></a>" \
"</li>"
inputbox_component = column(pep_textinput, error_message_div)
color_desc_component = compo.generate_color_description_component()
header_component = row(column(inputbox_component, color_desc_component),
title_div,
info_div)
# Timeline Component
checkbox_group.callback = CustomJS.from_py_func(callback_change_checkbox)
timeline_plot = tl_compo.generate_timeline_plot(pep_graph,
timeline_display_circle_source,
timeline_label_source,
timeline_desc_label_source,
release_source_dict)
as_of_date_div = Div(width=200, height=8, style={'color': 'red'})
# TODO: fetch_start_datetimeを持っていないときの対応について決める
fetch_datetime = pep_graph.graph['fetch_start_datetime'].strftime('%Y/%m/%d') \
if 'fetch_start_datetime' in pep_graph.graph else 'Unknown'
as_of_date_div.text = '* Data as of {}'.format(fetch_datetime) # データ取得日
timeline_component = column(timeline_plot, as_of_date_div)
# Table Component
margin_div = Div(width=50)
link_to_table_component = column(link_to_table_title_div, link_to_data_table)
linked_from_table_component = column(linked_from_table_title_div, linked_from_data_table)
table_component = row(linked_from_table_component, margin_div, link_to_table_component)
# TODO: ここでshowしなくても出力できる方法はないか？
output_file(output_path, 'PEP Map | Timeline')
show(column(header_component, checkbox_group, timeline_component, table_component))
def basic_TS_plot(fullDataset):
# Init values
ticker = ""
yLabel = ""
descLine = ""
plotX = []
plotXLabel = []
plotY = []
legendList = []
# BollingerBands
all_top_bollingers = []
all_bot_bollingers = []
all_mid_bollingers = []
all_bollinger_dates = []
# Quartiles
firstQuartiles = []
medians = []
thirdQuartiles = []
# SETUP DATA
for element in fullDataset:
try:
elementX = []
elementXLabel = []
elementY = []
# Extract x and y's from the pairs provided in each element of the dataset
if element["dataset"]["data"]:
for e in range(0, len(element["dataset"]["data"])):
elementX.append(
datetime.strptime(element["dataset"]["data"][e][0],
'%Y-%m-%d').date())
elementXLabel.append(str(element["dataset"]["data"][e][0]))
elementY.append(element["dataset"]["data"][e][1])
databaseCode = "[" + element["dataset"]["database_code"] + "] "
name = element["dataset"]["name"]
if len(elementX) > 0:
# Reverse the incoming data if it starts with the closest-to-present data. We want it list to start with the oldest data
if len(elementX) > 1:
if elementX[0] > elementX[1]:
elementX.reverse()
elementY.reverse()
plotX.append(elementX)
plotXLabel.append(elementXLabel)
plotY.append(elementY)
# Bollinger Band Info prepare
date_b, top_b, bot_b, mid_b = bollinger_bands(
2, elementX, elementY, 20)
all_top_bollingers.append(top_b)
all_mid_bollingers.append(mid_b)
all_bot_bollingers.append(bot_b)
# all_bollinger_dates.append(date_b)
all_bollinger_dates.append(elementX)
if element["dataset"]["data"]:
if len(name) > 15:
legendList.append("Show/Hide: " + name[:30] + "...")
else:
legendList.append(name)
if element["dataset"]["data"]:
# Prepare Quartiles
numpyY = np.array(elementY)
first_q = np.percentile(numpyY, 25)
medi = np.percentile(numpyY, 50)
third_q = np.percentile(numpyY, 75)
firstQuartiles.append(first_q)
medians.append(medi)
thirdQuartiles.append(third_q)
except Exception as e:
logger.debug("ERROR: element in fullDataset could not be added")
logger.debug(element)
logger.debug(e)
all_quartiles = [[]] * len(plotX)
quartiles_names = [["First Quartile", "Median", "Third Quartile"]
] * len(plotX)
for i in range(len(plotX)):
all_quartiles[i] = [firstQuartiles[i], medians[i], thirdQuartiles[i]]
# If only one item is available from the fullDataset, the report can be tailored to that time-series only
if len(fullDataset) == 1:
titleLong = fullDataset[0]["dataset"]["name"]
if len(titleLong) > 20:
titleShort = titleLong[:10] + "..."
else:
titleShort = titleLong
descLong = "Long description placeholder."
descLine = '<abbr title="' + descLong + '">' + ticker + '</abbr>'
yLabel = fullDataset[0]["dataset"]["column_names"][1]
# generic title for multiple data sets
else:
titleShort = "Time-series for: " + fullDataset[0]["dataset"][
"start_date"] + " to " + fullDataset[0]["dataset"]["end_date"]
descLine = ticker
yLabel = "Value(s)" # The table below will be used to show the units. Ideally it should also figure in the legend
# Prepare column data sources for the graphs. This is also where hover tool and other widgets get their information
source = []
# 'color' is created specifically for lasso tool - for the invisible, but selectable circle glyphs
for i in range(len(plotX)):
color = ["navy"] * len(plotX[i])
source.append(
ColumnDataSource(data=dict(x=plotX[i],
y=plotY[i],
color=color,
topx=all_bollinger_dates[i],
topy=all_top_bollingers[i],
midx=all_bollinger_dates[i],
midy=all_mid_bollingers[i],
botx=all_bollinger_dates[i],
boty=all_bot_bollingers[i])))
PLOT_OPTIONS = dict(plot_width=400, plot_height=170)
crosshair = CrosshairTool(dimensions="height")
TOOLS = ['pan,wheel_zoom,box_zoom,reset,save,lasso_select'] + [crosshair]
plot = figure(title=titleShort,
x_axis_type="datetime",
tools=TOOLS,
toolbar_location="above",
sizing_mode='scale_width',
**PLOT_OPTIONS)
plot.xaxis.formatter = DatetimeTickFormatter(
hours=["%d %B %Y"],
days=["%d %B %Y"],
months=["%d %B %Y"],
years=["%d %B %Y"],
)
plot.xaxis.axis_label = 'Date(s)'
plot.yaxis.axis_label = yLabel
# Magma color palette is: black - purple - orange - tan - light tan
# Viridis is a color paledtte: dark blue - greenblue - green - yellow
# More palettes @
# http://bokeh.pydata.org/en/latest/docs/reference/palettes.html
colors_list = Viridis256
shuffle(colors_list)
# visible lines on graph creation
plot_line_list = []
bollinger_band_list = []
for i in range(len(plotX)):
# circles created for lasso average finding tool
plot.circle("x", "y", color='color', size=1, source=source[i], alpha=0)
# visible graph:
plot_line_list.append(
plot.line("x",
"y",
color=colors_list[i],
line_width=4,
name='standard',
source=source[i]))
shuffle(colors_list)
bollinger_band_list.append(
plot.line("topx",
"topy",
color=colors_list[i],
line_width=1,
name='top',
source=source[i]))
bollinger_band_list.append(
plot.line("midx",
"midy",
color=colors_list[i],
line_width=1,
line_dash="dashed",
name='mid',
source=source[i]))
bollinger_band_list.append(
plot.line("botx",
"boty",
color=colors_list[i],
line_width=1,
name='bot',
source=source[i]))
# Bollinger bands are initially off
for i in range(len(bollinger_band_list)):
bollinger_band_list[i].visible = True
# A hover tool for each line (standard, top, mid, lower)
hover = HoverTool(
names=['standard'],
tooltips=[
("Value", "@y{0,0.0000}"), # FRED REMOVED comma HERE
("Date", "@x{%F}")
],
formatters={"x": "datetime"},
mode='vline')
hover2 = HoverTool(names=['top'],
tooltips=[("Upper Band", "@topy{0,0.0000}"),
("Date", "@x{%F}")],
formatters={"x": "datetime"},
mode='vline')
hover3 = HoverTool(names=['mid'],
tooltips=[("SMA", "@midy{0,0.0000}"),
("Date", "@x{%F}")],
formatters={"x": "datetime"},
mode='vline')
hover4 = HoverTool(names=['bot'],
tooltips=[("Lower Band", "@boty{0,0.0000}"),
("Date", "@x{%F}")],
formatters={"x": "datetime"},
mode='vline')
plot.add_tools(hover, hover2, hover3, hover4)
# Set-up the multi-line representation (not using bokeh's multi-line) and the checkboxes
list_active = []
dictArgs = {}
button_titles = []
for i in range(0, len(plotX)):
button_titles.append("Graph " + str(i + 1) + ": " + legendList[i])
# Generate the JS code for checkbox group - show/hide graphs
dynamicJS = '//console.log(cb_obj.active);'
for line in range(0, len(plot_line_list)):
dynamicJS += '\nline' + str(line * 4) + '.visible = false; '
for i in range(3):
dynamicJS += '\nline' + str(line * 4 + i +
1) + '.visible = false; '
dynamicJS += """
for (i in cb_obj.active)
{
//console.log(cb_obj.active[i]);
if (cb_obj.active[i] == 0)
{
line0.visible = true;
if (bollToggle.active == true)\n"""
dynamicJS += "{\n"
for i in range(3):
dynamicJS += 'line' + str(i + 1) + '.visible = true;\n'
dynamicJS += '}}'
for line in range(1, len(plot_line_list)):
dynamicJS += '\nelse if (cb_obj.active[i] == ' + str(line) + ') {\n'
dynamicJS += 'line' + str(line * 4) + '.visible = true;\n'
dynamicJS += 'if (bollToggle.active == true) {\n'
for i in range(3):
dynamicJS += 'line' + str(line * 4 + i + 1) + '.visible = true;\n'
dynamicJS += '\n}}'
dynamicJS += '\nelse if (cb_obj.active[i] == ' + str(
len(plot_line_list)) + ') {\n'
for t in range(0, len(plot_line_list)):
dynamicJS += 'if (bollToggle.active == true) {\n'
for i in range(3):
dynamicJS += 'line' + str(t * 4 + i + 1) + '.visible = true;\n'
dynamicJS += '}\n'
dynamicJS += '\n}'
dynamicJS += '\n}'
logger.debug("DEBUG: DynamicJS")
logger.debug(dynamicJS)
# list_active means the buttons initially ON at page load
for line in range(0, len(plot_line_list)):
list_active.append(line)
key = "line" + str(line * 4)
dictArgs.update({key: plot_line_list[line]})
for i in range(3):
key = "line" + str(line * 4 + i + 1)
dictArgs.update({key: bollinger_band_list[line * 3 + i]})
bollButton = Toggle(label='Bollinger On/Off', button_type='success')
key = "bollToggle"
dictArgs.update({key: bollButton})
checkboxColor = ''
if len(plotY) > 9:
checkboxColor += '#E4E4E4;'
else:
checkboxColor += 'white;'
checkbox = CheckboxGroup(labels=button_titles,
active=list_active,
width=450,
height=210)
checkbox.callback = CustomJS(args=dictArgs, code=dynamicJS)
# checkbox is 210 pixels high(max), with a vertical scrollbar and grey background color
checkbox.css_classes = ["checkbox-scrollbar"]
key = "checkbox"
dictArgs.update({key: checkbox})
selectAllJS = ''
selectAllJS += "checkbox.active = ["
for i in range(len(plotY)):
if i != len(plotY) - 1:
selectAllJS += str(i) + ', '
else:
selectAllJS += str(i)
selectAllJS += "];\n"
for i in range(len(plotY)):
selectAllJS += 'line' + str(i * 4) + '.visible = true;\n'
selectAllJS += 'if (bollToggle.active == true) {\n'
for i in range(len(plotY)):
for t in range(3):
selectAllJS += 'line' + str(i * 4 + t + 1) + '.visible = true;\n'
selectAllJS += '}'
selectAllCallback = CustomJS(args=dictArgs, code=selectAllJS)
selectAllButton = Button(label='Select All',
button_type='warning',
callback=selectAllCallback)
deselectAllJS = "checkbox.active = [];\n"
for i in range(len(plotY) * 4):
deselectAllJS += 'line' + str(i) + '.visible = false;\n'
deselectAllCallback = CustomJS(args=dictArgs, code=deselectAllJS)
deselectAllButton = Button(label='Deselect All',
button_type='warning',
callback=deselectAllCallback)
plotScript, plotDiv = components(plot)
# printPlotJS = """
# var div = plot;
# console.log(plot);
# var data=divID.innerHTML;
# var myWindow = window.open('', 'my div', 'height=400,width=600');
# myWindow.document.write(div);
# myWindow.document.close(); // necessary for IE >= 10
#
# myWindow.onload=function(){ // necessary if the div contain images
#
# myWindow.focus(); // necessary for IE >= 10
# myWindow.print();
# myWindow.close();
# };
# """
# logger.debug("DEBUG: DynamicJS")
# logger.debug(dynamicJS)
sliderJS = """
var window = cb_obj.value
var sources = ["""
for i in range(len(source)):
if i != len(source) - 1:
sliderJS += 'source' + str(i) + ', '
else:
sliderJS += 'source' + str(i)
sliderJS += '];'
sliderJS += """
for (var i = 0, len=sources.length; i < len; i++) {
var data = sources[i].data;
var y = data['y']
topy = data['topy']
midy = data['midy']
boty = data['boty']
function StandardDeviation(numbersArr) {
//--CALCULATE AVERAGE--
var total = 0;
for(var key in numbersArr)
total += numbersArr[key];
var meanVal = total / numbersArr.length;
//--CALCULATE AVERAGE--
//--CALCULATE STANDARD DEVIATION--
var SDprep = 0;
for(var key in numbersArr)
SDprep += Math.pow((parseFloat(numbersArr[key]) - meanVal),2);
var SDresult = Math.sqrt(SDprep/numbersArr.length);
//--CALCULATE STANDARD DEVIATION--
return SDresult;
}
function standardDev(window, y) {
var sd = [];
var x = window;
while (x <= y.length) {
var a2c = y.slice(x - window, x);
var standev = StandardDeviation(a2c);
sd.push(standev);
x += 1;
}
return sd;
}
//moving average calc
function movingAvg(array, count, qualifier){
// calculate average for subarray
var avg = function(array, qualifier){
var sum = 0, count = 0, val;
for (var i in array){
val = array[i];
if (!qualifier || qualifier(val)){
sum += val;
count++;
}
}
return sum / count;
};
var result = [], val;
// pad beginning of result with null values
for (var i=0; i < count-1; i++)
result.push(NaN);
// calculate average for each subarray and add to result
for (var i=0, len=array.length - count; i <= len; i++){
val = avg(array.slice(i, i + count), qualifier);
if (isNaN(val))
result.push(NaN);
else
result.push(val);
}
return result;
}
//end moving avg
var top_band = [];
var mid_band = [];
var bot_band = [];
var x = window;
while (x < y.length) {
var sma_array = movingAvg(y.slice(x - window, x), window);
var sma_last = sma_array[sma_array.length - 1];
var curSD = standardDev(window, y.slice(0, window));
var curSD_last = curSD[curSD.length - 1];
var tb = sma_last + curSD_last * 2;
var bb = sma_last - curSD_last * 2;
top_band.push(tb);
mid_band.push(sma_last);
bot_band.push(bb);
x+=1;
}
if (top_band < topy) {
shift_amt = topy.length - top_band.length;
for (var q=0; q < shift_amt; q++) {
top_band.unshift(NaN);
mid_band.unshift(NaN);
bot_band.unshift(NaN);
}
}
//for (var t=0; t < y.length; t++) {
// if (isNaN(top_band[0]) == true) {
// topy[t] = top_band[t + 1];
// boty[t] = bot_band[t + 1];
// midy[t] = mid_band[t + 1];
// }
// else {
// topy[t] = top_band[t];
// boty[t] = bot_band[t];
// midy[t] = mid_band[t];
// }
//}
for (var t=0; t < y.length; t++) {
topy[t] = top_band[t];
boty[t] = bot_band[t];
midy[t] = mid_band[t];
}
console.log(sources[i]);
sources[i].change.emit();
}
"""
sourceArgs = {}
for i in range(0, len(plot_line_list)):
key = "source" + str(i)
sourceArgs.update({key: source[i]})
print(sourceArgs)
SMAcallback = CustomJS(args=sourceArgs, code=sliderJS)
SMAwindow_slider = Slider(start=1,
end=100,
value=20,
step=1,
title="SMA Window(period)",
callback=SMAcallback)
# for space between checkboxes and buttons
spacer = Spacer(height=100, width=50)
# for temporary space when slider is invisible
no_slider = Spacer(height=75, width=100)
SMAwindow_slider.height = 65
bollColumn = Column()
bollColumn.width = 175
bollColumn.children = [
bollButton, no_slider, selectAllButton, deselectAllButton
]
bollRow = Row(checkbox, spacer, bollColumn)
# --------------------------------------------------------------
# Allow bollinger button to turn on/off the slider
# dynamicJSboll = '\ncolumn.children = [no_slider];'
#
# dynamicJSboll += """
# if (cb_obj.active == true)
# {
# column.children = [boll_button, slider, select_all, deselect_all]
# }
# else if (cb_obj.active == false)
# {
# column.children = [boll_button, no_slider, select_all, deselect_all];
# }"""
key = "column"
dictArgs.update({key: bollColumn})
key = "boll_button"
dictArgs.update({key: bollButton})
key = "slider"
dictArgs.update({key: SMAwindow_slider})
key = "no_slider"
dictArgs.update({key: no_slider})
key = "select_all"
dictArgs.update({key: selectAllButton})
key = "deselect_all"
dictArgs.update({key: deselectAllButton})
# javascript for bollinger toggle button
dynamicJSboll = """
//console.log(cb_obj.active);
if (cb_obj.active == true) {\n"""
# slider is made visible
dynamicJSboll += 'column.children = [boll_button, slider, select_all, deselect_all];\n'
for t in range(0, len(plot_line_list)):
dynamicJSboll += 'if (line' + str(t * 4) + '.visible == true) {\n'
for i in range(3):
dynamicJSboll += 'line' + str(t * 4 + i + 1) + '.visible = true;\n'
dynamicJSboll += "}\n"
dynamicJSboll += "}\n"
dynamicJSboll += "else if (cb_obj.active == false) {\n"
# slider is turned invisible
dynamicJSboll += 'column.children = [boll_button, no_slider, select_all, deselect_all];\n'
for t in range(0, len(plot_line_list)):
for i in range(3):
dynamicJSboll += 'line' + str(t * 4 + i +
1) + '.visible = false;\n'
dynamicJSboll += "}\n"
bollButton.callback = CustomJS(args=dictArgs, code=dynamicJSboll)
# --------------------------------------------------------------
'''
# display data tables only if there are 10 or less data sets
if len(plotY) < 11:
doc_layout = layout([
[Column((plot), sizing_mode='scale_width')],
[bollRow],
[Row(children=data_table, sizing_mode='scale_width')],
], sizing_mode='scale_width')
'''
doc_layout = layout([[Column(plot)], [bollRow]], sizing_mode='scale_width')
plots = [plot, [bollRow]]
scripts, div = components(plot)
cssCode = """
<style type="text/css">
svg {
font-family: 'Helvetica Neue', Helvetica;
}
.line {
fill: none;
stroke: #000;
stroke-width: 2px;
}
body {
height: 100%;
overflow: hidden;
margin: 0px;
display: flex;
box-sizing: border-box;
}
h1 {
font-family: 'Helvetica Neue', Helvetica;
color: #ffc800;
text-align: center;
}
h2 {
font-family: 'Helvetica Neue', Helvetica;
color: grey;
text-align: center;
}
p {
font-family: 'Helvetica Neue', Helvetica;
font-size: 14px;
color: dark-grey;
text-align: justify;
}
metric {
font-family: 'Helvetica Neue', Helvetica;
font-size: 20px;
color: dark-grey;
text-decoration: underline;
text-align: center;
}
cop {
font-family: 'Helvetica Neue', Helvetica;
font-size: 10px;
color: black;
text-align: center;
}
#main {
transition: margin-left .5s;
padding: 16px;
margin-top: 70px;
flex-grow: 1;
display: flex;
overflow-y: auto; /*adds scroll to this container*/
max-width: 100%;
}
.navbar {
overflow: hidden;
background-color: #ffc800;
position: fixed;
top: 0;
width: 100%;
}
.navbar a {
float: left;
display: block;
color: black;
text-align: center;
padding: 14px 16px;
text-decoration: none;
font-size: 15px;
}
.sidenav {
max-height: 82%;
width: 0;
position: fixed;
z-index: 1;
top: 0;
left: 0;
background-color: #DCDCDC;
overflow-x: hidden;
overflow-y: auto;
transition: 0.5s;
padding-top: 30px;
margin-top: 68px;
}
.sidenav a {
padding: 8px 8px 8px 32px;
text-decoration: none;
font-size: 25px;
color: white;
display: block;
transition: 0.3s;
}
.sidenav a:hover, .offcanvas a:focus{
color: #ffc800;
}
.sidenav .closebtn {
color: black;
position: absolute;
top: 0;
right: 25px;
color: black;
font-size: 36px;
margin-left: 50px;
}
.table-custom {
border:1px;
border-style: solid;
border-color:#ffc800;
padding: 3em;
border-radius: 6px;
text-align:center;
margin: auto;
max-width: 100%;
max-height: 100%;
display: block;
}
.checkbox-scrollbar {
overflow: auto;
background-color: """ + str(checkboxColor) + """
}
@media screen and (max-height: 450px) {
.sidenav {padding-top: 15px;}
.sidenav a {font-size: 18px;}
</style>
"""
metrics_shown = ""
reportId = fullDataset[0]["reportId"]
counter = 1
for element in fullDataset:
if counter == 1:
metrics_shown += "<b>Graph " + str(
counter) + "</b><br>" + element["dataset"]["name"] + "<br>"
else:
metrics_shown += "<b><br>Graph " + str(
counter) + "</b><br>" + element["dataset"]["name"] + "<br>"
counter += 1
redirect_head_script = """
<script type="text/javascript">
<!--
if (screen.width <= 1200) {"""
redirect_head_script += 'window.location = "https://s3.amazonaws.com/reports.tools.neonrisk.com/' + reportId + '/mobile_bokeh_report.html";'
redirect_head_script += """}
//-->
</script>
"""
toolbar_scripts = """
<script>
window.onload = function(){
var pr = document.getElementById('print');
pr.onclick = printReport;
function printReport() {
window.print();
return false;
}};
</script>
<script>
window.onload = function(){
var el = document.getElementById('email');
el.onclick = createEmail;
function createEmail() {
var subject = "See the enclosed report"
var link = "http://www.neonrisk.com"
var body = "Please click here to access the report: " + link
window.open('mailto:?subject=' + subject + '&body=' + body);
return false;
}};
</script>
<script>
window.onload = function(){
var sa = document.getElementById('saveAs');
sa.onclick = saveAs;
function saveAs() {
alert("Please use the SaveAs function of your browser to save the document locally. Note however, that viewing the document always requires a connection.")
return false;
}};
</script>
<script>
jQuery(function($) {
$('#bookmark-this').click(function(e) {
var bookmarkURL = window.location.href;
var bookmarkTitle = document.title;
if ('addToHomescreen' in window && addToHomescreen.isCompatible) {
// Mobile browsers
addToHomescreen({ autostart: false, startDelay: 0 }).show(true);
} else if (window.sidebar && window.sidebar.addPanel) {
// Firefox <=22
window.sidebar.addPanel(bookmarkTitle, bookmarkURL, '');
} else if ((window.sidebar && /Firefox/i.test(navigator.userAgent)) || (window.opera && window.print)) {
// Firefox 23+ and Opera <=14
$(this).attr({
href: bookmarkURL,
title: bookmarkTitle,
rel: 'sidebar'
}).off(e);
return true;
} else if (window.external && ('AddFavorite' in window.external)) {
// IE Favorites
window.external.AddFavorite(bookmarkURL, bookmarkTitle);
} else {
// Other browsers (mainly WebKit & Blink - Safari, Chrome, Opera 15+)
alert('Press ' + (/Mac/i.test(navigator.userAgent) ? 'Cmd' : 'Ctrl') + '+D to bookmark this page.');
}
return false;
});
});
</script>
"""
infoCol = """
</head>
<body>
<div class="navbar">
<a style="font-size:30px;cursor:pointer" onclick="openNav()">☰</a>
<a id="bookmark-this" href="#"><img src="https://s3.amazonaws.com/www.neonrisk.com/icons/bookmark.png" alt="Bookmark" width=30 height=30></a>
<a href="#" title="Save this report as .pdf" id="saveAs">
<img src="https://s3.amazonaws.com/www.neonrisk.com/icons/save.png" alt="Save this report as pdf" width=30 height=30></a>
<a href="#" title="Print this report" id="print">
<img src="https://s3.amazonaws.com/www.neonrisk.com/icons/print.png" alt="Print" width=30 height=30></a>"""
linkToReport = 'https://s3.amazonaws.com/reports.tools.neonrisk.com/' + reportId + '/bokeh_report.html'
infoCol += '<a href="mailto:?subject=Please%20see%20the%20enclosed%20report&body=Link%20to%20the%20report' + linkToReport + '">'
infoCol += """<img src="https://s3.amazonaws.com/www.neonrisk.com/icons/email.png" alt="Email a link" width=30 height=30></a>
<a href="http://www.neonrisk.com"><img src="https://s3.amazonaws.com/www.neonrisk.com/icons/help.png" alt="Open Online Help" width=30 height=30></a>
<a href="https://www.linkedin.com/company/neon-risk"><img src="https://s3.amazonaws.com/www.neonrisk.com/icons/linkedin.png" alt="Find us on LinkedIn" width=30 height=30></a>
<a href="https://twitter.com/NeonRisk"><img src="https://s3.amazonaws.com/www.neonrisk.com/icons/twitter.png" alt="Find us on Twitter" width=30 height=30></a>
</div>
<div id="mySidenav" class="sidenav">
<a href="javascript:void(0)" class="closebtn" onclick="closeNav()">×</a>
<p><img src="http://www.neonrisk.com/uploads/6/9/5/2/69527361/hi-res-fpe-phat-flat-x4.png" alt="logo" align="left"></p>
<metric>Metrics shown</metric>"""
infoCol += '<p>' + metrics_shown + '</p><br>'
infoCol += '<p>Report # ' + reportId + '</p>'
infoCol += """<p>Thank you for using Neon Risk Tools.
For support, please contact <a href="mailto:[email protected]">[email protected]</a></p>
<cop>copyright Neon Risk, Inc. 2017</cop>
</div>
<div id="main">
"""
closeTableHTML = """
</div>
<script>
function openNav() {
document.getElementById("mySidenav").style.width = "250px";
document.getElementById("main").style.marginLeft = "250px";
document.getElementById("main").style.maxWidth = "87%";
}
function closeNav() {
document.getElementById("mySidenav").style.width = "0";
document.getElementById("main").style.marginLeft= "0";
document.getElementById("main").style.maxWidth = "100%";
}
</script>
</body>
</html>
"""
bokehCode = '<link href="https://cdnjs.cloudflare.com/ajax/libs/bokeh/1.0.2/bokeh.min.css" rel="stylesheet" type="text/css">'
bokehCode += '<link href="https://cdnjs.cloudflare.com/ajax/libs/bokeh/1.0.2/bokeh-widgets.min.css" rel="stylesheet" type="text/css">'
bokehCode += '<script src="https://cdnjs.cloudflare.com/ajax/libs/bokeh/1.0.2/bokeh.min.js"></script>'
bokehCode += '<script src="https://cdnjs.cloudflare.com/ajax/libs/bokeh/1.0.2/bokeh-widgets.min.js"></script>'
# -- NOW generate page
reportBodyDataHTML_bokeh = '<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">'
reportBodyDataHTML_bokeh += '<html xmlns="http://www.w3.org/1999/xhtml" style="height:100%;width:100%;font-size:100%">'
reportBodyDataHTML_bokeh += '<head><meta content="text/html; charset=US-ASCII" http-equiv="Content-Type">'
reportBodyDataHTML_bokeh += cssCode
reportBodyDataHTML_bokeh += redirect_head_script + bokehCode + scripts + toolbar_scripts
reportBodyDataHTML_bokeh += infoCol
reportBodyDataHTML_bokeh += div
reportBodyDataHTML_bokeh += closeTableHTML
html_file = open("testing.html", "w")
html_file.write(reportBodyDataHTML_bokeh)
html_file.close()
print(reportBodyDataHTML_bokeh)
