def test_return_type(self):
plot1 = figure()
plot1.circle([], [])
plot2 = figure()
plot2.circle([], [])
# This is a testing artefact, users dont' have to do this in practice
curdoc().add_root(plot1)
curdoc().add_root(plot2)
r = bes.components(plot1)
assert len(r) == 2
_, divs = bes.components((plot1, plot2))
assert isinstance(divs, tuple)
_, divs = bes.components([plot1, plot2])
assert isinstance(divs, tuple)
_, divs = bes.components({"Plot 1": plot1, "Plot 2": plot2})
assert isinstance(divs, dict)
assert all(isinstance(x, string_types) for x in divs.keys())
_, divs = bes.components(OrderedDict([("Plot 1", plot1), ("Plot 2", plot2)]))
assert isinstance(divs, OrderedDict)
assert all(isinstance(x, string_types) for x in divs.keys())
def test_return_type(self) -> None:
plot1 = figure()
plot1.circle([], [])
plot2 = figure()
plot2.circle([], [])
# This is a testing artefact, users don't have to do this in practice
curdoc().add_root(plot1)
curdoc().add_root(plot2)
r = bes.components(plot1)
assert len(r) == 2
_, divs0 = bes.components((plot1, plot2))
assert isinstance(divs0, tuple)
_, divs1 = bes.components([plot1, plot2])
assert isinstance(divs1, tuple)
_, divs2 = bes.components({"Plot 1": plot1, "Plot 2": plot2})
assert isinstance(divs2, dict)
assert all(isinstance(x, str) for x in divs2.keys())
# explict test for OrderedDict (don't replace with dict)
_, divs3 = bes.components(
OrderedDict([("Plot 1", plot1), ("Plot 2", plot2)]))
assert isinstance(divs3, OrderedDict)
assert all(isinstance(x, str) for x in divs3.keys())
def test_return_type(self):
plot1 = figure()
plot1.circle([], [])
plot2 = figure()
plot2.circle([], [])
# This is a testing artefact, users dont' have to do this in practice
curdoc().add_root(plot1)
curdoc().add_root(plot2)
r = bes.components(plot1)
assert len(r) == 2
_, divs = bes.components((plot1, plot2))
assert isinstance(divs, tuple)
_, divs = bes.components([plot1, plot2])
assert isinstance(divs, tuple)
_, divs = bes.components({"Plot 1": plot1, "Plot 2": plot2})
assert isinstance(divs, dict)
assert all(isinstance(x, str) for x in divs.keys())
_, divs = bes.components(
OrderedDict([("Plot 1", plot1), ("Plot 2", plot2)]))
assert isinstance(divs, OrderedDict)
assert all(isinstance(x, str) for x in divs.keys())
def test_plot_dict_returned_when_wrap_plot_info_is_false(
self, mock_make_id: MagicMock) -> None:
doc = Document()
plot1 = figure()
plot1.circle([], [])
doc.add_root(plot1)
plot2 = figure()
plot2.circle([], [])
doc.add_root(plot2)
expected_plotdict_1 = RenderRoot(elementid=ID("ID"), id=ID("ID"))
expected_plotdict_2 = RenderRoot(elementid=ID("ID"), id=ID("ID"))
_, plotdict = bes.components(plot1, wrap_plot_info=False)
assert plotdict == expected_plotdict_1
_, plotids = bes.components((plot1, plot2), wrap_plot_info=False)
assert plotids == (expected_plotdict_1, expected_plotdict_2)
_, plotiddict = bes.components({
'p1': plot1,
'p2': plot2
},
wrap_plot_info=False)
assert plotiddict == {
'p1': expected_plotdict_1,
'p2': expected_plotdict_2
}
def test_output_is_without_script_tag_when_wrap_script_is_false(self, mock_make_id, test_plot):
script, div = bes.components(test_plot)
html = bs4.BeautifulSoup(script, "lxml")
scripts = html.findAll(name='script')
assert len(scripts) == 1
script_content = scripts[0].getText()
rawscript, div = bes.components(test_plot, wrap_script=False)
self.maxDiff = None
assert rawscript.strip() == script_content.strip()
def __init__(self, contents, **kwargs):
"""
Writes out the content as raw text or HTML.
:param contents: Bokeh plotting figure.
:param kwargs: Optional styling arguments. The `style` keyword argument has special
meaning in that it allows styling to be grouped as one argument.
It is also useful in case a styling parameter name clashes with a standard
block parameter.
"""
self.resource_deps = [
JScript(script_string=s, name='bokeh_js')
for s in JSResources().js_raw
]
self.resource_deps += [
Css(css_string=s, name='bokeh_css') for s in CSSResources().css_raw
]
super(BokehPlotBlock, self).__init__(**kwargs)
if not isinstance(contents, BokehFigure):
raise ValueError(
"Expected bokeh.plotting.figure.Figure type but got %s",
type(contents))
script, div = components(contents)
self._contents = script + div
def test_div_attrs(self, test_plot):
script, div = bes.components(test_plot)
html = bs4.BeautifulSoup(div, "lxml")
divs = html.findAll(name='div')
assert len(divs) == 1
div = divs[0]
assert set(div.attrs) == set(['class', 'id'])
assert div.attrs['class'] == ['bk-root']
assert div.text == ''
def test_plot_dict_returned_when_wrap_plot_info_is_false(self, mock_make_id):
plot1 = figure()
plot1.circle([], [])
plot2 = figure()
plot2.circle([], [])
# This is a testing artefact, users dont' have to do this in practice
curdoc().add_root(plot1)
curdoc().add_root(plot2)
expected_plotdict_1 = {"modelid": plot1.ref["id"], "elementid": "ID", "docid": "ID"}
expected_plotdict_2 = {"modelid": plot2.ref["id"], "elementid": "ID", "docid": "ID"}
_, plotdict = bes.components(plot1, wrap_plot_info=False)
assert plotdict == expected_plotdict_1
_, plotids = bes.components((plot1, plot2), wrap_plot_info=False)
assert plotids == (expected_plotdict_1, expected_plotdict_2)
_, plotiddict = bes.components({'p1': plot1, 'p2': plot2}, wrap_plot_info=False)
assert plotiddict == {'p1': expected_plotdict_1, 'p2': expected_plotdict_2}
def test_div_attrs(self, test_plot):
script, div = bes.components(test_plot)
html = bs4.BeautifulSoup(div, "lxml")
divs = html.findAll(name='div')
assert len(divs) == 1
div = divs[0]
assert set(div.attrs) == set(['class', 'id'])
assert div.attrs['class'] == ['bk-root']
assert div.text == ''
def test_plot_dict_returned_when_wrap_plot_info_is_false(self, mock_make_id):
plot1 = figure()
plot1.circle([], [])
plot2 = figure()
plot2.circle([], [])
# This is a testing artefact, users dont' have to do this in practice
curdoc().add_root(plot1)
curdoc().add_root(plot2)
expected_plotdict_1 = {"modelid": plot1.ref["id"], "elementid": "ID", "docid": "ID"}
expected_plotdict_2 = {"modelid": plot2.ref["id"], "elementid": "ID", "docid": "ID"}
_, plotdict = bes.components(plot1, wrap_plot_info=False)
assert plotdict == expected_plotdict_1
_, plotids = bes.components((plot1, plot2), wrap_plot_info=False)
assert plotids == (expected_plotdict_1, expected_plotdict_2)
_, plotiddict = bes.components({'p1': plot1, 'p2': plot2}, wrap_plot_info=False)
assert plotiddict == {'p1': expected_plotdict_1, 'p2': expected_plotdict_2}
def test_plot_dict_returned_when_wrap_plot_info_is_false(self, mock_make_id):
doc = Document()
plot1 = figure()
plot1.circle([], [])
doc.add_root(plot1)
plot2 = figure()
plot2.circle([], [])
doc.add_root(plot2)
expected_plotdict_1 = RenderRoot(elementid="ID", id="ID")
expected_plotdict_2 = RenderRoot(elementid="ID", id="ID")
_, plotdict = bes.components(plot1, wrap_plot_info=False)
assert plotdict == expected_plotdict_1
_, plotids = bes.components((plot1, plot2), wrap_plot_info=False)
assert plotids == (expected_plotdict_1, expected_plotdict_2)
_, plotiddict = bes.components({'p1': plot1, 'p2': plot2}, wrap_plot_info=False)
assert plotiddict == {'p1': expected_plotdict_1, 'p2': expected_plotdict_2}
def test_div_attrs(self, test_plot) -> None:
script, div = bes.components(test_plot)
html = bs4.BeautifulSoup(div, "html.parser")
divs = html.findAll(name='div')
assert len(divs) == 1
div = divs[0]
assert set(div.attrs) == set(['class', 'id', 'data-root-id'])
assert div.attrs['class'] == ['bk-root']
assert div.attrs['id'] == 'ID'
assert div.attrs['data-root-id'] == test_plot.id
assert div.string is None
def test_div_attrs(self, test_plot: figure) -> None:
_, div = bes.components(test_plot)
html = bs4.BeautifulSoup(div, "html.parser")
els = html.find_all(name='div')
assert len(els) == 1
el = els[0]
assert set(el.attrs) == {"class", "id", "data-root-id"}
assert el.attrs["class"] == ["bk-root"]
assert el.attrs["id"] == "ID"
assert el.attrs["data-root-id"] == test_plot.id
assert el.string is None
def test_div_attrs(self, test_plot) -> None:
script, div = bes.components(test_plot)
html = bs4.BeautifulSoup(div, "html.parser")
divs = html.findAll(name='div')
assert len(divs) == 1
div = divs[0]
assert set(div.attrs) == {"class", "id", "data-root-id"}
assert div.attrs["class"] == ["bk-root"]
assert div.attrs["id"] == "ID"
assert div.attrs["data-root-id"] == test_plot.id
assert div.string is None
def product_graph(request, cde):
item = ProductDetailExp.objects.get(code=cde)
c_data = ConsumptionData.objects.filter(productDetail=item)
items_list = []
for p in c_data:
items_list.append([p.consumptionDate, p.consumptionQty])
items_columns = ['consumptionDate', 'consumptionQty']
items_df = pd.DataFrame(items_list, columns=items_columns)
items_df['consumptionQty'] = items_df['consumptionQty'].astype(
float) # Convert from str to float
plt = figure(width=1200,
height=550,
title="CONSUMPTION GRAPH",
x_axis_type="datetime")
plt.line(x=items_df.consumptionDate,
y=items_df.consumptionQty,
line_color='green')
plt.title.text_color = "olive"
plt.title.text_font = "times"
plt.title.text_font_style = "italic"
plt.xaxis.axis_label = "Consumption Quantity"
plt.xaxis.axis_line_width = 1
plt.xaxis.axis_line_color = "red"
plt.xaxis.axis_label_text_color = "brown"
plt.yaxis.axis_label = "Consumption Date"
plt.yaxis.axis_line_width = 1
plt.yaxis.axis_line_color = "yellow"
plt.yaxis.axis_label_text_color = "red"
plt.yaxis.major_label_text_color = "blue"
plt.yaxis.major_label_orientation = "vertical"
plt.toolbar.autohide = True
div, script = components(plt)
context = {
'title': 'ANALYSIS|' + str(cde) + 'GRAPH',
'the_div': div,
'the_script': script,
'resources': INLINE.render(),
}
return render(request, 'analysis/product_graph.html', context)
def test_script_is_utf8_encoded(self, test_plot: figure) -> None:
script, _ = bes.components(test_plot)
assert isinstance(script, str)
def test_result_attrs(self, test_plot: figure) -> None:
script, _ = bes.components(test_plot)
html = bs4.BeautifulSoup(script, "html.parser")
scripts = html.find_all(name='script')
assert len(scripts) == 1
assert scripts[0].attrs == {'type': 'text/javascript'}
def all_current_stock_single_stats(request, cde):
item = ProductDetailExp.objects.get(code=cde)
c_data = ConsumptionData.objects.filter(productDetail=item)
items_list = []
for p in c_data:
items_list.append([p.consumptionDate, p.consumptionQty])
items_columns = ['consumptionDate', 'consumptionQty']
items_df = pd.DataFrame(items_list, columns=items_columns)
items_df['Date'] = pd.to_datetime(items_df['consumptionDate'])
items_df['Year'] = pd.DatetimeIndex(items_df['Date']).year
items_df['Month'] = pd.DatetimeIndex(items_df['Date']).strftime("%b")
items_df['Day'] = pd.DatetimeIndex(items_df['Date']).strftime("%a")
items_df['consumptionQty'] = items_df['consumptionQty'].astype(
float) # Convert from str to float
items_df['Year'] = items_df['Year'].apply(str) # From integer to string
plt = figure(width=500,
height=400,
title="CONSUMPTION GRAPHS",
x_axis_type="datetime")
plt.line(x=items_df.consumptionDate,
y=items_df.consumptionQty,
line_color='green')
plt.title.text_color = "olive"
plt.title.text_font = "times"
plt.title.text_font_style = "italic"
plt.xaxis.axis_label = "Consumption Date"
plt.xaxis.axis_line_width = 1
plt.xaxis.axis_line_color = "red"
plt.xaxis.axis_label_text_color = "brown"
plt.yaxis.axis_label = "Consumption Quantity"
plt.yaxis.axis_line_width = 1
plt.yaxis.axis_line_color = "yellow"
plt.yaxis.axis_label_text_color = "red"
plt.yaxis.major_label_text_color = "blue"
plt.yaxis.major_label_orientation = "vertical"
plt.toolbar.autohide = True
by_year = items_df.groupby('Year')['consumptionQty'].mean()
by_month = items_df.groupby('Month')['consumptionQty'].mean()
by_year_df = pd.DataFrame(by_year).reset_index().sort_values(
by='consumptionQty', ascending=True)
by_month_df = pd.DataFrame(by_month).reset_index().sort_values(
by='consumptionQty', ascending=True)
years = by_year_df['Year'].unique()
source1 = ColumnDataSource(data=by_year_df)
plt1 = figure(title="AVERAGE YEARLY CONSUMPTION",
y_range=by_year_df['Year'],
plot_height=350,
plot_width=500,
toolbar_location="left",
x_axis_label="Mean",
y_axis_label="Year",
tooltips=[("Year", "@Year"), ("Mean", "@consumptionQty")])
plt1.hbar(y='Year',
right='consumptionQty',
height=0.7,
source=source1,
color=factor_cmap('Year', Spectral5, years))
months = by_month_df['Month'].unique()
source2 = ColumnDataSource(data=by_month_df)
plt2 = figure(title="AVERAGE MONTHLY CONSUMPTION",
y_range=by_month_df['Month'],
plot_height=350,
plot_width=500,
toolbar_location="left",
x_axis_label="Mean",
y_axis_label="Months",
tooltips=[("Month", "@Month"), ("Mean", "@consumptionQty")])
plt1.x_range.start = 0
plt1.outline_line_color = "brown"
plt1.xgrid.grid_line_color = None
plt1.ygrid.grid_line_color = None
plt1.toolbar.autohide = True
plt1.outline_line_color = None
plt2.hbar(y='Month',
right='consumptionQty',
height=0.7,
source=source2,
color=factor_cmap('Month', Set3_12, months))
plt2.x_range.start = 0
plt2.outline_line_color = "brown"
plt2.xgrid.grid_line_color = None
plt2.ygrid.grid_line_color = None
plt2.toolbar.autohide = True
plt2.outline_line_color = None
plots = Column(plt, plt2, plt1)
div, script = components(plots)
s_type = 'STATISTICS'
qty_stats = calc_stats(item)
context = {
'title': 'ANALYSIS |STATS|' + str(cde),
'productData': item,
'qty_stats': qty_stats,
's_type': s_type,
'the_div': div,
'the_script': script,
'resources': INLINE.render(),
}
return render(request, 'analysis/visuals_product.html', context)
def product_visual(request):
products = ProductDetailExp.objects.all()
if request.method == 'POST':
var_stat = request.POST['stat']
var_time = request.POST['time']
item = ProductDetailExp.objects.get(code=request.POST['productSelect'])
data = ProductDetailExp.objects.get(code=request.POST['productSelect'])
c_data = ConsumptionData.objects.filter(productDetail=item)
items_list = []
for p in c_data:
items_list.append([p.consumptionDate, p.consumptionQty])
items_columns = ['consumptionDate', 'consumptionQty']
items_df = pd.DataFrame(items_list, columns=items_columns)
items_df['Date'] = pd.to_datetime(items_df['consumptionDate'])
items_df['Year'] = pd.DatetimeIndex(items_df['Date']).year
items_df['Month'] = pd.DatetimeIndex(items_df['Date']).strftime("%b")
items_df['Day'] = pd.DatetimeIndex(items_df['Date']).strftime("%a")
items_df['consumptionQty'] = items_df['consumptionQty'].astype(
float) # Convert from str to float
items_df['Year'] = items_df['Year'].apply(
str) # From integer to string
if var_stat == 'stats':
s_type = 'STATISTICS'
qty_stats = calc_stats(data)
plt = figure(width=400,
height=400,
title="CONSUMPTION GRAPH",
x_axis_type="datetime")
plt.line(x=items_df.consumptionDate,
y=items_df.consumptionQty,
line_color='green')
plt.title.text_color = "olive"
plt.title.text_font = "times"
plt.title.text_font_style = "italic"
plt.xaxis.axis_label = "Consumption Quantity"
plt.xaxis.axis_line_width = 1
plt.xaxis.axis_line_color = "red"
plt.xaxis.axis_label_text_color = "brown"
plt.yaxis.axis_label = "Consumption Date"
plt.yaxis.axis_line_width = 1
plt.yaxis.axis_line_color = "yellow"
plt.yaxis.axis_label_text_color = "red"
plt.yaxis.major_label_text_color = "blue"
plt.yaxis.major_label_orientation = "vertical"
plt.toolbar.autohide = True
div, script = components(plt)
context = {
'title': 'ANALYSIS | PRODUCTS',
'allProducts': products,
'productData': item,
'qty_stats': qty_stats,
's_type': s_type,
'the_div': div,
'the_script': script,
'resources': INLINE.render(),
}
return render(request, 'analysis/visuals.html', context)
elif var_stat == 'Sum':
s_type = 'SUM'
if var_time == 'Year':
v_type = 'Year'
by_group = items_df.groupby('Year')['consumptionQty'].sum()
result_df = pd.DataFrame(by_group).reset_index()
elif var_time == 'YMonth':
v_type = 'YMonth'
by_group = items_df.groupby(['Year',
'Month'])['consumptionQty'].sum()
result_df = pd.DataFrame(by_group).reset_index()
elif var_time == 'Month':
v_type = 'Month'
by_group = items_df.groupby('Month')['consumptionQty'].sum()
result_df = pd.DataFrame(by_group).reset_index()
else:
v_type = 'Day' # For the day
json_records = result_df.to_json(orient='records')
data = []
data = json.loads(json_records)
context = {
'title': 'ANALYSIS | PRODUCTS',
'allProducts': products,
'productData': c_data,
's_type': s_type,
'v_type': v_type,
'data_df': data,
}
return render(request, 'analysis/visuals.html', context)
else:
s_type = 'MEAN'
if var_time == 'Year':
v_type = 'Year'
by_group = items_df.groupby('Year')['consumptionQty'].mean()
result_df = pd.DataFrame(by_group).reset_index()
elif var_time == 'YMonth':
v_type = 'YMonth'
by_group = items_df.groupby(['Year', 'Month'
])['consumptionQty'].mean()
result_df = pd.DataFrame(by_group).reset_index()
elif var_time == 'Month':
v_type = 'Month'
by_group = items_df.groupby('Month')['consumptionQty'].mean()
result_df = pd.DataFrame(by_group).reset_index()
else:
v_type = 'Day'
json_records = result_df.to_json(orient='records')
data = []
data = json.loads(json_records)
context = {
'title': 'ANALYSIS | PRODUCTS',
'allProducts': products,
'productData': c_data,
's_type': s_type,
'v_type': v_type,
'data_df': data,
}
return render(request, 'analysis/visuals.html', context)
context = {
'title': 'ANALYSIS | PRODUCTS',
'allProducts': products,
}
return render(request, 'analysis/visuals.html', context)
def test_output_is_without_script_tag_when_wrap_script_is_false(
self, test_plot):
script, div = bes.components(test_plot)
html = bs4.BeautifulSoup(script, "lxml")
scripts = html.findAll(name='script')
assert len(scripts) == 1
def test_script_is_utf8_encoded(self, test_plot):
script, div = bes.components(test_plot)
assert isinstance(script, str)
def test_result_attrs(self, test_plot):
script, div = bes.components(test_plot)
html = bs4.BeautifulSoup(script, "lxml")
scripts = html.findAll(name='script')
assert len(scripts) == 1
assert scripts[0].attrs == {'type': 'text/javascript'}
def admin_dashboard(request):
products = ProductDetailExp.objects.all()
items = []
items_columns = [
'CODE',
'DESCRIPTION',
'VEN',
'PRICE',
'CURRENT_STOCK',
'STAT',
]
for p in products:
data = get_initial_graphs_data(p)
if data is not None:
items.append([
data['code'], data['description'], data['ven'], data['price'],
data['current_stock'], data['stat']
])
products_df = pd.DataFrame(items, columns=items_columns)
df = get_df_to_make_graphs(products_df)
df1 = df.reset_index()
factors = np.array(df1.CODE)
factors2 = ['V', 'E', 'N']
source = ColumnDataSource(data=df1)
tools = "pan,wheel_zoom, box_zoom,reset,box_select,lasso_select, hover"
p = figure(
title=
"Average Consumption of Drugs At Fort Portal Regional Referral Hospital",
y_range=factors,
plot_height=2000,
plot_width=2000,
tools=tools,
toolbar_location="left",
x_axis_label="MEAN CONSUMPTION",
y_axis_label="PRODUCT CODE",
tooltips=[("PRODUCT CODE", "@CODE"), ("DESCRIPTION", "@DESCRIPTION"),
("VEN", "@VEN"), ("PRICE", "@PRICE"),
("CURRENT STOCK", "@CURRENT_STOCK"),
("MEAN VALUE", "@STAT")])
p.hbar(y='CODE',
right='STAT',
height=0.7,
source=source,
color=factor_cmap('VEN', ['red', 'yellow', 'black'], factors2),
legend_field='VEN')
p.title.text_color = "olive"
p.title.text_font = "times"
p.title.text_font_style = "italic"
p.xaxis.major_label_orientation = 1.5
p.outline_line_color = "brown"
p.xgrid.grid_line_color = None
p.ygrid.grid_line_color = None
p.x_range.start = 0
p.legend.location = "top_center"
div, script = components(p)
context = {
'the_div': div,
'the_script': script,
'resources': INLINE.render(),
}
return render(request, 'analysis/productdashboard.html', context)
def test_output_is_without_script_tag_when_wrap_script_is_false(self, test_plot):
script, div = bes.components(test_plot)
html = bs4.BeautifulSoup(script, "lxml")
scripts = html.findAll(name='script')
assert len(scripts) == 1
def test_script_is_utf8_encoded(self, test_plot):
script, div = bes.components(test_plot)
assert isinstance(script, str)
def test_quoting(self, test_plot: figure) -> None:
script, _ = bes.components(test_plot)
assert """ not in script
assert "'foo'" not in script
assert "'foo'" in script
def get_graphs_1_month_consumption(request):
if request.method == 'GET':
stat = request.GET.get('stat')
else:
stat = 'mean'
products = ProductDetailExp.objects.all()
items = []
items_columns = [
'CODE', 'DESCRIPTION', 'VEN', 'PRICE', 'CURRENT_STOCK', 'STAT'
]
for p in products:
data = get_graphs_consumption_method_1_month_cycle(p, stat)
if data is not None:
items.append([
data['code'], data['description'], data['ven'], data['PRICE'],
data['current_stock'], data['stat']
])
products_df = pd.DataFrame(items, columns=items_columns)
df = get_df_to_make_graphs(products_df)
df1 = df.reset_index()
factors = np.array(df1.CODE)
factors2 = ['V', 'E', 'N']
if stat is None:
stat = 'mean'
source = ColumnDataSource(data=df1)
tools = "pan,wheel_zoom, box_zoom,reset,box_select,lasso_select, hover"
p = figure(title=str(stat),
y_range=factors,
plot_height=2000,
plot_width=2000,
tools=tools,
toolbar_location="left",
x_axis_label=str(stat),
y_axis_label="PRODUCT CODE",
tooltips=[("PRODUCT CODE", "@CODE"),
("DESCRIPTION", "@DESCRIPTION"), ("VEN", "@VEN"),
(str(stat), "@STAT")])
p.hbar(y='CODE',
right='STAT',
height=0.7,
source=source,
color=factor_cmap('VEN', ['red', 'yellow', 'black'], factors2),
legend_field='VEN')
p.title.text_color = "olive"
p.title.text_font = "times"
p.title.text_font_style = "italic"
p.xaxis.major_label_orientation = 1.5
p.outline_line_color = "brown"
p.xgrid.grid_line_color = None
p.ygrid.grid_line_color = None
p.x_range.start = 0
# p.xaxis.visible = False
p.legend.location = "top_center"
div, script = components(p)
context = {
'the_div': div,
'the_script': script,
'resources': INLINE.render(),
}
return render(request, 'analysis/graphs_1_c_method.html', context)
def test_output_is_without_script_tag_when_wrap_script_is_false(
self, test_plot: figure) -> None:
script, _ = bes.components(test_plot)
html = bs4.BeautifulSoup(script, "html.parser")
scripts = html.find_all(name='script')
assert len(scripts) == 1
def test_result_attrs(self, test_plot):
script, div = bes.components(test_plot)
html = bs4.BeautifulSoup(script, "lxml")
scripts = html.findAll(name='script')
assert len(scripts) == 1
assert scripts[0].attrs == {'type': 'text/javascript'}
