def squarify_size_nodes(path, nodes, x, y, width, height, min_size):
# for n in nodes:
# print "%s -> %s" % (n.name, n.size)
nodes = [n for n in nodes if n.size > min_size]
nodes = sorted(nodes, key=lambda n: n.size, reverse=True)
sizes = [n.size for n in nodes]
sizes = squarify.normalize_sizes(sizes, width, height)
rects = squarify.squarify(sizes, x, y, width, height)
for i in range(len(rects)):
rect = rects[i]
node = nodes[i]
child_path = path + "/" + node.name
# print "[DEBUG] child_path", i, child_path, node.size
# assert rect['x'] >= x, "%s (%s)" % (rect, (x, y, width, height))
# assert rect['y'] >= y, "%s (%s)" % (rect, (x, y, width, height))
# assert rect['dx'] <= width + 1, "%s (%s)" % (rect, (x, y, width, height))
# assert rect['dy'] <= height + 1, "%s (%s)" % (rect, (x, y, width, height))
rect['name'] = node.name
rect['path'] = child_path
rect['size'] = int(node.size)
child_rects = SquareTreeMap.squarify_size_nodes(
child_path, node.name2childs.values(), rect['x'], rect['y'], rect['dx'], rect['dy'], min_size)
rects.extend(child_rects)
return rects
def _plot_otu(self, axis, sizes, colors, max_count, name):
width_and_height = math.sqrt(float(sum(sizes))/max_count*100)
offset = (10 - width_and_height)/2
normed = squarify.normalize_sizes(sizes, width_and_height, width_and_height)
rects = squarify.squarify(normed, offset, offset , width_and_height, width_and_height)
x = [rect['x'] for rect in rects]
y = [rect['y'] for rect in rects]
dx = [rect['dx'] for rect in rects]
dy = [rect['dy'] for rect in rects]
axis.bar(x, dy, width=dx, bottom=y, color=colors, align='edge', edgecolor='black', linewidth=0.2)
axis.set_aspect('equal')
axis.set_ylim(-0.3,10.3) # Add 0.1 so the edges are not truncated.
axis.set_xlim(-0.3,10.3)
axis.set_xticks([])
axis.set_yticks([])
axis.set_axis_off()
if name is not None:
fp = matplotlib.font_manager.FontProperties(size=9)
axis.text(-1, 5,
name,
font_properties=fp,
rotation='vertical',
horizontalalignment='center',
verticalalignment='center')
def tree_layout(id, path=''):
response.content_type = 'application/json'
# get node metadata
tree = get_tree(cache[id]['tree'], path)
children = tree['children'].keys()
sizes = [tree['children'][child]['size'] for child in children]
# filter out zero values
children = filter(lambda child: tree['children'][child]['size'] > 0, children)
sizes = filter(lambda size: size > 0, sizes)
# sort the objects by size, descending
order = argsort(sizes)[::-1]
children = [children[i] for i in order]
sizes = [sizes[i] for i in order]
# compute the treemap layout
sizes = squarify.normalize_sizes(sizes, width, height)
rects = squarify.padded_squarify(sizes, 0, 0, width, height)
# annotate rects with some metadata
for (child, rect) in zip(children, rects):
rect['host'] = cache[id]['meta']['host']
rect['path'] = os.path.join(path, child)
rect['name'] = child
rect['size'] = bytes2human(tree['children'][child]['size'])
if len(tree['children'][child]['children']) == 0:
rect['type'] = 'file'
else:
rect['type'] = 'dir'
# if I am at a leaf node, then rects should be empty
# in that case, add a single rectangle for the whole canvas
if len(rects) == 0:
rects.append({'x': 0, 'y': 0,
'dx': width, 'dy': height,
'host': cache[id]['meta']['host'], 'path': path, 'name': path.split('/')[-1],
'size': bytes2human(tree['size']),
'type': 'file'})
data = {}
data['rects'] = rects
data['size'] = tree['size']
data['humansize'] = bytes2human(tree['size'])
data['date'] = cache[id]['tree']['date']
return json.dumps(data)
def _plot_scale(self, axis, max_total_count):
axis.set_aspect('equal')
axis.set_ylim(-0.3,10.3) # Add 0.1 so the edges are not truncated.
axis.set_xlim(-0.3,10.3)
axis.set_xticks([])
axis.set_yticks([])
axis.set_axis_off()
scale_values = [1]
while sum(scale_values)+scale_values[0]*10 < max_total_count:
scale_values = [scale_values[0]*10] + scale_values
to_normalise = scale_values + [max_total_count-sum(scale_values)]
normalised = squarify.normalize_sizes(to_normalise, 10, 10)
ylim = [0.,10.]
sides = list([math.sqrt(normalised[i]) for i, value in enumerate(scale_values)])
overlap = (ylim[1]-ylim[0]-sum(sides))/(len(sides)-1)
next_bottom = ylim[0]
xoffset = ylim[1]-ylim[0]-sides[0]
fp = matplotlib.font_manager.FontProperties(size=6)
for i, value in enumerate(scale_values):
side = sides[i]
axis.bar(10-side/2-0.1-xoffset,
bottom=next_bottom,
height=side,width=side,
color='0.7',edgecolor='black',linewidth=0.2)
# Add text
if value == 1:
text = "1 read"
else:
text = "%i reads" % value
axis.text(10.2-xoffset, next_bottom+side/2, text,
verticalalignment='center', font_properties=fp)
# Setup for next loop iter
next_bottom += overlap + side
fp = matplotlib.font_manager.FontProperties(size=9)
axis.text(0.2, 10.6, 'OTU count', font_properties=fp)
def gen_chart(title):
x = 0.
y = 0.
width = 100.
height = 100.
values = parties.values()
normed = squarify.normalize_sizes(values, width, height)
rects = squarify.squarify(normed, x, y, width, height)
shapes = []
annotations = []
counter = 0
for r in rects:
shapes.append(
dict(
type ='rect',
x0=r['x'],
y0=r['y'],
x1=r['x']+r['dx'],
y1=r['y']+r['dy'],
line=dict(width=2),
fillcolor=_coalision_col(parties.keys()[counter]),
opacity=_committed(parties.keys()[counter])
)
)
annotations.append(
dict(
x=r['x']+(r['dx']/2),
y=r['y']+(r['dy']/2),
text=parties.keys()[counter],
showarrow=False
)
)
counter = counter + 1
# For hover text
trace0 = go.Scatter(
x=[r['x']+(r['dx']/2) for r in rects],
y=[r['y']+(r['dy']/2) for r in rects],
text=[str(v) for v in values],
mode='text')
layout = dict(
title="{}".format(title),
font=dict(size=18),
height=700,
width=700,
xaxis=dict(showgrid=False, zeroline=False,
ticks='', showticklabels=False),
yaxis=dict(showgrid=False, zeroline=False,
ticks='', showticklabels=False),
shapes=shapes,
annotations=annotations,
hovermode='closest')
# Without hovertext
return dict(data=[go.Scatter()], layout=layout)
def treemap(value):
x = 0.
y = 0.
width = 100.
height = 100.
test_data = {
'BTC': {
'size': '500',
'marketcap': -0.34,
},
'BCH': {
'size': '433',
'marketcap': -0.34,
},
'ETH': {
'size': '78',
'marketcap': -0.34,
},
'XRP': {
'size': '25',
'marketcap': 0.34,
},
'XLM': {
'size': '25',
'marketcap': 0.34,
},
'ADA': {
'size': '25',
'marketcap': -0.34,
},
}
coin_name_list = test_data.keys()
coin_name_list2 = []
for i in coin_name_list:
coin_name_list2.append(i)
values = []
for key in coin_name_list:
values.append(test_data[key]['size'])
values = list(map(int, values)) # string to list
normed = squarify.normalize_sizes(values, width, height)
rects = squarify.squarify(normed, x, y, width, height)
# Choose colors from http://colorbrewer2.org/ under "Export"
color_brewer = ['rgb(255,0,255)', 'rgb(0,255,0)']
shapes = []
annotations = []
counter = 0
for r in rects:
coin_name = coin_name_list2[counter]
if test_data[coin_name]['marketcap'] > 0:
color = 0
else:
color = 1
shapes.append(
dict(type='rect',
x0=r['x'],
y0=r['y'],
x1=r['x'] + r['dx'],
y1=r['y'] + r['dy'],
line=dict(width=2),
fillcolor=color_brewer[color]))
annotations.append(
dict(
x=r['x'] + (r['dx'] / 2),
y=r['y'] + (r['dy'] / 2),
text="<span><a id='hover_info'>" + coin_name_list2[counter] +
"</a><br> <b>" +
str(test_data[coin_name_list2[counter]]['marketcap']) +
"</b></span>",
#text=coin_name_list2[counter],
showarrow=False))
counter = counter + 1
figure = {
'data': [
go.Scatter(
x=[r['x'] + (r['dx'] / 2) for r in rects],
y=[r['y'] + (r['dy'] / 2) for r in rects],
text=[str(v) for v in values],
mode='text',
)
],
'layout':
go.Layout(
height=700,
width=700,
xaxis={
'showgrid': False,
'zeroline': False,
'showticklabels': False
},
yaxis={
'showgrid': False,
'zeroline': False,
'showticklabels': False
},
shapes=shapes,
annotations=annotations,
hovermode=False,
)
}
return figure
import plotly.graph_objects as go
import squarify
fig = go.Figure()
x = 0.
y = 0.
width = 100.
height = 100.
values = [500, 433, 78, 25, 25, 7]
normed = squarify.normalize_sizes(values, width, height)
rects = squarify.squarify(normed, x, y, width, height)
# Choose colors from http://colorbrewer2.org/ under "Export"
color_brewer = [
'rgb(166,206,227)', 'rgb(31,120,180)', 'rgb(178,223,138)',
'rgb(51,160,44)', 'rgb(251,154,153)', 'rgb(227,26,28)'
]
shapes = []
annotations = []
counter = 0
for r, val, color in zip(rects, values, color_brewer):
shapes.append(-dict(type='rect',
x0=r['x'],
y0=r['y'],
x1=r['x'] + r['dx'],
y1=r['y'] + r['dy'],
def update_graph(n_clicks, county, year, age, gender, figure):
selected_data = df[(df['Location'] == county) & (df['Year'] == year) &
(df['Age'] == age) & (df['Sex'] == gender)]
selected_data.set_index(
'Disease', inplace=True
) # set the disease type to be the index to call, not sure if it's a good idea
Year = selected_data['Year'].unique()
Gender = selected_data['Sex'].unique()
Age = selected_data['Age'].unique()
#Dict_data = {}
#for disease in selected_data.index:
# Dict_data[disease] = selected_data.loc[county]
## Put things into the graph.
# NOTE: There will/should be a section that categorize disease type into say three groups.
# A specific color should be assigned to each categoryself.
x = 0.
y = 0.
width = 100.
height = 100.
#values = [500, 433, 78, 25, 25, 7]
values = selected_data['Value']
normed = squarify.normalize_sizes(values, width, height)
rects = squarify.squarify(normed, x, y, width, height)
# Choose colors from http://colorbrewer2.org/ under "Export"
color_brewer = ['rgb(166,206,227)', 'rgb(31,120,180)', 'rgb(227,26,28)']
shapes = []
annotations = []
counter = 0
for r in rects:
shapes.append(
dict(type='rect',
x0=r['x'],
y0=r['y'],
x1=r['x'] + r['dx'],
y1=r['y'] + r['dy'],
line=dict(width=2),
fillcolor=color_brewer[counter]))
annotations.append(
dict(x=r['x'] + (r['dx'] / 2),
y=r['y'] + (r['dy'] / 2),
text=values[counter],
showarrow=False))
counter = counter + 1
if counter >= len(color_brewer):
counter = 0
figure = {
'data': [
go.Scatter(
x=[r['x'] + (r['dx'] / 2) for r in rects],
y=[r['y'] + (r['dy'] / 2) for r in rects],
text=[str(v) for v in values],
mode='text',
)
],
'layout':
go.Layout(
height=700,
width=700,
xaxis={
'showgrid': False,
'zeroline': False,
'showticklabels': False
},
yaxis={
'showgrid': False,
'zeroline': False,
'showticklabels': False
},
shapes=shapes,
annotations=annotations,
hovermode='closest',
)
}
return figure
y = 0.
width = 500.
height = 500.
#values of products or sum of products
#values = [500, 433, 78, 25, 25, 7]
# Determine and collect data for most frequent product. WARNING!: opp has 500 rows only!
product_count=opp.product_id.value_counts()
aisle_name=[]
for e in product_count:
print findProductName(product_count.index[e])
aisle_name.append(findProductName(product_count.index[e]))
allNames=pd.Series(aisle_name)
#normed = squarify.normalize_sizes(values, width, height)
normed1 = squarify.normalize_sizes(allNames, width, height)
#rects = squarify.squarify(normed, x, y, width, height)
rects1 = squarify.squarify(normed1,x,y,width,height)
# Choose colors from http://colorbrewer2.org/ under "Export"
#color_brewer = ['rgb(166,206,227)','rgb(31,120,180)','rgb(178,223,138)',
# 'rgb(51,160,44)','rgb(251,154,153)','rgb(227,26,28)']
color_brewer1 = ['rgb(239,138,98)','rgb(247,247,247)','rgb(103,169,207)']
bupu500 = cl.interp( color_brewer1, 10 )
def findProductName(val):
aNum=products.aisle_id[products.product_id==val]
aNam=aisle.aisle[aisle.aisle_id==int(aNum)].values[0]
return aNam.strip()
def treemap(value):
data = pd.read_csv("../../data/data_levantamientos_diciembre_2018.csv")
data_set = data[['Cadena', 'Tienda', 'Ofertas y precios']]
data_set = data_set.sort_values(by=['Ofertas y precios'], ascending=False)
data_set = data_set.reset_index(drop=True)
dd = data_set[['Tienda', 'Cadena']]
x = 0.
y = 0.
width = 100.
height = 100.
#tiendas= ['SECAGV', 'SCADE', 'SCADE2', 'SEC', 'ZTM', 'ZTC', 'ZES', 'ZE3', 'SN3', 'ZTL', 'STL', 'SAT', 'ZN2', 'ZTN', 'ZNR', 'ZAT', 'SN2', 'ZAN', 'CNA', 'ZEC', 'ZPR', 'ZE2', 'ZLG', 'ZRH']
values = pd.Series(data_set['Ofertas y precios'])
tiendas = pd.Series(data_set['Tienda'])
cadenas = pd.Series(data_set['Cadena'])
#print(data_set)
normed = squarify.normalize_sizes(values, width, height)
rects = squarify.squarify(normed, x, y, width, height)
# Choose colors from http://colorbrewer2.org/ under "Export"
#http://colorbrewer2.org/?type=sequential&scheme=Reds&n=3
color_brewer = ['red', 'blue']
colores = {'Zorro Abarrotero': 0, 'Scorpion': 1}
shapes = []
annotations = []
counter = 0
i = 0
for r in rects:
#print(i)
#print(tiendas[i])
#print(values[i])
#print(cadenas[i])
#print(color_brewer[colores[cadenas[i]]])
shapes.append(
dict(type='rect',
x0=r['x'],
y0=r['y'],
x1=r['x'] + r['dx'],
y1=r['y'] + r['dy'],
line=dict(width=2),
fillcolor=color_brewer[colores[cadenas[i]]]))
annotations.append(
dict(
x=r['x'] + (r['dx'] / 2),
y=r['y'] + (r['dy'] / 2),
#text = tiendas[i] + ': ' + '\n' + str(values[i]),
text=str(values[i]),
showarrow=False))
counter = counter + 1
i = i + 1
if counter >= len(color_brewer):
counter = 0
figure = {
'data': [
go.Scatter(x=[r['x'] + (r['dx'] / 2) for r in rects],
y=[r['y'] + (r['dy'] / 2) for r in rects],
text=['Tienda: ' + str(c) for c in tiendas],
mode='none',
hoverinfo='text')
],
'layout':
go.Layout(title='Treemap de Ofertas y Precios por Tienda',
height=900,
width=1200,
xaxis={
'showgrid': False,
'zeroline': False,
'showticklabels': False
},
yaxis={
'showgrid': False,
'zeroline': False,
'showticklabels': False
},
shapes=shapes,
annotations=annotations,
hovermode='closest',
plot_bgcolor=colors['background'],
paper_bgcolor=colors['background'],
font={'color': colors['text']})
}
return figure
def draw_tree9(vs, n, exp, title_text):
fig = go.Figure()
x = 0.
y = 0.
width = 100.
height = 100.
values = vs
names = n
normed = squarify.normalize_sizes(values, width, height)
rects = squarify.squarify(normed, x, y, width, height)
# Choose colors from http://colorbrewer2.org/ under "Export"
color_brewer = cartocolors.Prism_9.hex_colors
shapes = []
annotations = []
m_names = [nn if vv > 0.5 else '' for nn, vv in zip(names, values)]
for r, val, color, n in zip(rects, values, color_brewer, m_names):
shapes.append(
dict(type='rect',
x0=r['x'],
y0=r['y'],
x1=r['x'] + r['dx'],
y1=r['y'] + r['dy'],
line=dict(width=2),
fillcolor=color))
annotations.append(
dict(x=r['x'] + (r['dx'] / 2),
y=r['y'] + (r['dy'] / 2),
text=n,
showarrow=False,
font=dict(size=18, color='#ebfffb', family='Noto Sans TC')))
# For hover text
fig.add_trace(
go.Scatter(
x=[r['x'] + (r['dx'] / 2) for r in rects],
y=[r['y'] + (r['dy'] / 2) for r in rects],
text=exp,
mode='text',
hoverinfo='text',
textfont=dict(size=16, color='#ebfffb', family='Noto Sans TC'),
))
fig.update_layout(
title=title_text,
#width=500,
#height=500,
xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
yaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
shapes=shapes,
annotations=annotations,
hovermode='closest',
dragmode=False,
# margin=dict(l=10,r=10,b=10,t=10),
margin=dict(l=0, r=0, b=0, t=50),
# plot_bgcolor='#ebfffb',
plot_bgcolor='rgba(0,0,0,0)',
paper_bgcolor='rgba(0,0,0,0)',
font=dict(family='Noto Sans TC')
# paper_bgcolor="#00ff00",
)
# fig.update_xaxes()
# fig.update_yaxes(showticklabels=False)
return fig
def main():
sections = parseSections(sys.stdin)
if sections is None:
print(
'start of memory config not found, did you invoke the compiler/linker with LANG=C?'
)
return
sectionWhitelist = {'.text', '.data', '.bss', '.rodata'}
plots = []
whitelistedSections = list(
filter(lambda x: x.section in sectionWhitelist, sections))
allObjects = list(chain(*map(lambda x: x.children, whitelistedSections)))
allFiles = list(set(map(lambda x: x.basepath, allObjects)))
for s in whitelistedSections:
objects = s.children
groupsize = {}
for k, g in groupby(sorted(objects, key=lambda x: x.basepath),
lambda x: x.basepath):
groupsize[k] = sum(map(lambda x: x.size, g))
objects.sort(reverse=True, key=lambda x: x.size)
values = list(map(lambda x: x.size, objects))
totalsize = sum(values)
x = 0
y = 0
width = 1000
height = 1000
values = squarify.normalize_sizes(values, width, height)
rects = squarify.squarify(values, x, y, width, height)
padded_rects = squarify.padded_squarify(values, x, y, width, height)
# plot with bokeh
output_file('linkermap.html', title='Linker map')
left = list(map(lambda x: x['x'], padded_rects))
top = list(map(lambda x: x['y'], padded_rects))
rectx = list(map(lambda x: x['x'] + x['dx'] / 2, padded_rects))
recty = list(map(lambda x: x['y'] + x['dy'] / 2, padded_rects))
rectw = list(map(lambda x: x['dx'], padded_rects))
recth = list(map(lambda x: x['dy'], padded_rects))
files = list(map(lambda x: x.basepath, objects))
size = list(map(lambda x: x.size, objects))
children = list(
map(
lambda x: ','.join(map(lambda x: x[1], x.children))
if x.children else x.section, objects))
legend = list(
map(lambda x: '{} ({})'.format(x.basepath, groupsize[x.basepath]),
objects))
source = ColumnDataSource(data=dict(
left=left,
top=top,
x=rectx,
y=recty,
width=rectw,
height=recth,
file=files,
size=size,
children=children,
legend=legend,
))
hover = HoverTool(tooltips=[
("size", "@size"),
("file", "@file"),
("symbol", "@children"),
])
p = figure(title='Linker map for section {} ({} bytes)'.format(
s.section, totalsize),
plot_width=width,
plot_height=height,
tools=[hover, 'pan', 'wheel_zoom', 'box_zoom', 'reset'],
x_range=(0, width),
y_range=(0, height))
p.xaxis.visible = False
p.xgrid.visible = False
p.yaxis.visible = False
p.ygrid.visible = False
palette = Category10[10]
mapper = CategoricalColorMapper(palette=palette, factors=allFiles)
p.rect(x='x',
y='y',
width='width',
height='height',
source=source,
color={
'field': 'file',
'transform': mapper
},
legend='legend')
# set up legend, must be done after plotting
p.legend.location = "top_left"
p.legend.orientation = "horizontal"
plots.append(p)
show(column(*plots, sizing_mode="scale_width"))
def updateTreemap(clickData, year):
if clickData is not None:
clickedGraph = clickData['points'][0]['curveNumber']
else:
clickedGraph = 0
if clickedGraph == 0:
sub_df = df_inc[(df_inc['Periodo']) == year]
sub_df_gb = sub_df.groupby(['Periodo', 'NIVEL3'])['Real_amount'].sum()
sub_df = sub_df_gb.reset_index()
elif clickedGraph == 1:
sub_df = df_exp[(df_exp['Periodo']) == year]
sub_df_gb = sub_df.groupby(['Periodo', 'NIVEL3'])['Real_amount'].sum()
sub_df = sub_df_gb.reset_index()
total = sub_df.groupby(['Periodo'], as_index=False)['Real_amount'].sum()
total = total.iloc[0]['Real_amount']
x, y = 0., 0.
width, height = 200., 100.
normed = sq.normalize_sizes(sub_df['Real_amount'], width, height)
rects = sq.squarify(normed, x, y, width, height)
color_brewer = ['rgb(166,206,227)', 'rgb(31,120,180)', 'rgb(178,223,138)',
'rgb(51,160,44)', 'rgb(251,154,153)', 'rgb(227,26,28)',
'rgb(137,45,89)']
shapes = []
annotations = []
counter = 0
df_counter = 0
for r in rects:
shapes.append(dict(
type='rect',
x0=r['x'],
y0=r['y'],
x1=r['x']+r['dx'],
y1=r['y']+r['dy'],
line=dict(width=2),
fillcolor=color_brewer[counter]
))
if r['dx'] < 20 or r['dy'] < 20:
text = ''
else:
text = sub_df.iloc[df_counter]['NIVEL3'].replace(' ', '<br>')
annotations.append(dict(
x=r['x']+(r['dx']/2),
y=r['y']+(r['dy']/2),
text=text,
showarrow=False,
font=dict(size=10, color='#000000')
))
counter += 1
df_counter += 1
if counter >= len(color_brewer):
counter = 0
trace = go.Scatter(
x=[r['x']+(r['dx']/2) for r in rects],
y=[r['y']+(r['dy']/2) for r in rects],
text=[
str(row['NIVEL3']) + '<br>' +
str(round(row['Real_amount'] / total * 100, 2)) +
'%' for (i, row) in sub_df.iterrows()
],
customdata=[],
hoverinfo='text',
textfont=dict(size=2),
mode='text',
)
layout = dict(
height=700,
width=1700,
xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
yaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
shapes=shapes,
annotations=annotations,
hovermode='closest'
)
return go.Figure(data=[trace], layout=layout)
def ST(data, groups, path, dir, file, width, height, use):
# these values define the coordinate system for the returned rectangles
# the values will range from x to x + width and y to y + height
x = 0.
y = 0.
total = 0
groupSize = []
length = len(groups)
for i in range(length):
total += len(groups[i])
for i in range(length):
dic = {}
dic['size'] = (len(groups[i]) / total)
dic['name'] = i
groupSize.append(dic)
groupSize.sort(key=itemgetter('size'), reverse=True)
index = []
values = []
for i in groupSize:
values.append(i['size'])
index.append(i['name'])
# the sum of the values must equal the total area to be laid out
# i.e., sum(values) == width * height
values = squarify.normalize_sizes(values, width, height)
# returns a list of rectangles
rects = squarify.squarify(values, x, y, width, height)
# padded rectangles will probably visualize better for certain cases
# padded_rects = squarify.padded_squarify(values, x, y, width, height)
# print(padded_rects)
for i in range(length):
rects[i]['name'] = index[i]
rects.sort(key=itemgetter('name'))
# for i in range(length):
# del rects[i]['index']
dic = {}
dic['x'] = 0
dic['y'] = 0
dic['dx'] = width
dic['dy'] = height
rects.append(dic)
links = data['links']
nodes = data['nodes']
forWrite = {}
forWrite['nodes'] = nodes
forWrite['links'] = links
forWrite['groups'] = rects
forWrite['groupSize'] = data['groupSize']
forWrite['pgroup'] = data['pgroup']
forWrite['pout'] = data['pout']
forWrite['mostConnected'] = data['mostConnected']
forWrite['nodeSize'] = data['nodeSize']
forWrite['linkSize'] = data['linkSize']
forWrite['nodeMax'] = data['nodeMax']
forWrite['nodeMin'] = data['nodeMin']
forWrite['linkMax'] = data['linkMax']
forWrite['linkMin'] = data['linkMin']
try:
# verify = os.listdir('../data/' + use + '/temp/' + dir)
verify = os.listdir('../data/origin/' + use)
except:
# os.mkdir('../data/' + use + '/temp/' + dir)
os.mkdir('../data/origin/' + use)
# f = open('../data/' + use + '/temp/' + dir + '/' + file, 'w')
f = open('../data/origin/' + use + '/' + file, 'w')
json.dump(forWrite,
f,
ensure_ascii=False,
indent=4,
sort_keys=True,
separators=(',', ': '))
def ft_treemap_figure(percent_dict, percent_tuples):
"""
This method creates the figure attribute for the treemap.
Uses squarify to compute the necessary rectangles.
Arguments
----------
percent_dict: {topic nbr:sum(topic probability over all docs)}
percent_tuples: same as percent_dict but under list of tuples
Return
----------
figure: plotly graph object which results in a treemap when ploted
"""
x = 0.
y = 0.
width = 4.
height = 4.
values = list(percent_dict.values())
values.sort(reverse=True)
normed = squarify.normalize_sizes(values, width, height)
rects = squarify.squarify(normed, x, y, width, height)
# color_brewer = ['#800026', '#bd0026', '#e31a1c', '#fc4e2a',
# '#fd8d3c', '#feb24c', '#fed976', '#ffeda0', '#ffffcc']
shapes = []
annotations = []
# counter = 0
topic_counter = 0
for r in rects:
shapes.append(
dict(
type='rect',
x0=r['x'],
y0=r['y'],
x1=r['x'] + r['dx'],
y1=r['y'] + r['dy'],
line=dict(width=2),
# fillcolor=color_brewer[counter]
))
annotations.append(
dict(x=r['x'] + (r['dx'] / 2),
y=r['y'] + (r['dy'] / 2),
text=percent_tuples[topic_counter][0],
showarrow=False))
# counter += 1
topic_counter += 1
# if counter >= len(color_brewer):
# counter = 0
figure = {
'data':
go.Scatter(
x=[r['x'] + (r['dx'] / 2) for r in rects],
y=[r['y'] + (r['dy'] / 2) for r in rects],
text=[ptuple[0] for ptuple in percent_tuples],
mode='text',
),
'layout':
go.Layout(
height=700,
width=700,
xaxis={
'fixedrange': True,
'showgrid': False,
'zeroline': False,
'showticklabels': False
},
yaxis={
'fixedrange': True,
'showgrid': False,
'zeroline': False,
'showticklabels': False
},
shapes=shapes,
annotations=annotations,
hovermode='closest',
)
}
return figure
def treemap(df):
bs = df
liab = ["totalcurrentliabilities", "totalnoncurrentliabilities"]
ass = ["netppe", "totalcurrentassets", "totalnoncurrentassets"]
equ = [
"totalcommonequity",
]
tras = bs.T[bs.T.index.isin([
"netppe", "totalnoncurrentassets", "totalcurrentassets",
"totalcurrentliabilities", "totalcommonequity",
"totalnoncurrentliabilities"
])]
tras["cat"] = np.where(
tras.index.isin(ass), "asset",
(np.where(tras.index.isin(liab), "liability",
(np.where(tras.index.isin(equ), "equity", np.nan)))))
tras = tras[tras["cat"].isin(["liability", "equity", "asset"])]
tras = tras.sort_values("cat", ascending=True)
lit = list(tras.index.values)
dam = [str(v) for v in ['ppe', 'ca', 'nca', 'ce', 'cl', 'ncl']]
x = 0.
y = 0.
width = 100.
height = 100.
# values = [500, 433, 78, 25, 25, 7]
values = list(tras[6].values)
normed = squarify.normalize_sizes(values, width, height)
rects = squarify.squarify(normed, x, y, width, height)
# Choose colors from http://colorbrewer2.org/ under "Export"
color_brewer = [
'rgb(166,206,227)', '#CAFF70', '#CDB7B5', '#EED5B7', 'pink', '#EBEBEB'
]
shapes = []
annotations = []
counter = 0
for r in rects:
shapes.append(
dict(type='rect',
x0=r['x'],
y0=r['y'],
x1=r['x'] + r['dx'],
y1=r['y'] + r['dy'],
line=dict(width=2),
fillcolor=color_brewer[counter]))
annotations.append(
dict(x=r['x'] + (r['dx'] / 2),
y=r['y'] + (r['dy'] / 2),
text=dam[counter],
textangle=15,
showarrow=False))
counter = counter + 1
if counter >= len(color_brewer):
counter = 0
# For hover text
trace0 = go.Scatter(
x=[r['x'] + (r['dx'] / 2) for r in rects],
y=[r['y'] + (r['dy'] / 2) for r in rects],
text=[str(v) for v in lit],
mode='text',
)
layout = dict(height=350,
width=350,
xaxis=dict(showgrid=False, zeroline=False),
yaxis=dict(showgrid=False, zeroline=False),
shapes=shapes,
annotations=annotations,
hovermode='closest')
# With hovertext
figure = dict(data=[trace0], layout=layout)
# Without hovertext
# figure = dict(data=[Scatter()], layout=layout)
return figure
def create_tree_map(series, title, treeMapColors, negative=False):
hashtagThreshold = 0.03
blankThreshold = 0.01
x = 0.
y = 0.
width = 0.6
height = 1
if negative:
series = series[series < 0]
values = series.values * -1
else:
series = series[series > 0]
values = series.values
normed = squarify.normalize_sizes(values, width, height)
rects = squarify.squarify(normed, x, y, width, height)
df = pd.DataFrame(series, columns=['exposure'])
df['percentage'] = df.exposure.values / df.exposure.sum()
df['label'] = ''
df['label'][df.percentage > hashtagThreshold] = df.index.to_series()[
df.percentage > hashtagThreshold]
df['number'] = df.reset_index().index.values + 1
try:
df['label'][(df.percentage < hashtagThreshold)
& (df.percentage > blankThreshold)] = '#' + df.number[
(df.percentage < hashtagThreshold)
& (df.percentage > blankThreshold)].apply(str)
except:
pass
labels = df['label'].values
color_brewer = [
'#8dd3c7', '#ffffb3', '#bebada', '#fb8072', '#80b1d3', '#fdb462',
'#b3de69', '#fccde5', '#d9d9d9', '#bc80bd', '#ccebc5', '#ffed6f'
]
shapes = []
annotations = []
counter = 0
label_counter = 0
for r in rects:
trade = series.index[counter]
shapes.append(
dict(type='rect',
x0=r['x'],
y0=r['y'],
x1=r['x'] + r['dx'],
y1=r['y'] + r['dy'],
line=dict(width=2),
fillcolor=treeMapColors.color[trade]))
annotations.append(
dict(x=r['x'] + (r['dx'] / 2),
y=r['y'] + (r['dy'] / 2),
text=labels[label_counter],
showarrow=False))
counter = counter + 1
label_counter = label_counter + 1
# For hover text
trace0 = go.Scatter(
x=[r['x'] + (r['dx'] / 2) for r in rects],
y=[r['y'] + (r['dy'] / 2) for r in rects],
text=[
str(index + ': ' + '{0:,.2f}'.format(value))
for (index, value) in series.iteritems()
],
# text=[str(v) for v in values],
mode='none',
hoverinfo='text')
layout = dict(title=title,
xaxis=dict(showgrid=False, zeroline=False),
yaxis=dict(showgrid=False, zeroline=False),
shapes=shapes,
annotations=annotations,
hovermode='closest',
margin=go.layout.Margin(l=0, r=0, b=0, t=25))
# With hovertext
figure = dict(data=[trace0], layout=layout)
return figure
def treemap():
x = 0.
y = 0.
width = 100.
height = 100.
values = [500, 433, 78, 25, 25, 7]
normed = squarify.normalize_sizes(values, width, height)
rects = squarify.squarify(normed, x, y, width, height)
# Choose colors from http://colorbrewer2.org/ under "Export"
color_brewer = [
'rgb(166,206,227)', 'rgb(31,120,180)', 'rgb(178,223,138)',
'rgb(51,160,44)', 'rgb(251,154,153)', 'rgb(227,26,28)'
]
shapes = []
annotations = []
counter = 0
for r in rects:
shapes.append(
dict(type='rect',
x0=r['x'],
y0=r['y'],
x1=r['x'] + r['dx'],
y1=r['y'] + r['dy'],
line=dict(width=2),
fillcolor=color_brewer[counter]))
annotations.append(
dict(x=r['x'] + (r['dx'] / 2),
y=r['y'] + (r['dy'] / 2),
text=values[counter],
showarrow=False))
counter = counter + 1
if counter >= len(color_brewer):
counter = 0
# For hover text
trace0 = go.Scatter(
x=[r['x'] + (r['dx'] / 2) for r in rects],
y=[r['y'] + (r['dy'] / 2) for r in rects],
text=[str(v) for v in values],
mode='text',
)
layout = dict(height=700,
width=700,
xaxis=dict(showgrid=False, zeroline=False),
yaxis=dict(showgrid=False, zeroline=False),
shapes=shapes,
annotations=annotations,
hovermode='closest')
# With hovertext
figure = dict(data=[trace0], layout=layout)
# Without hovertext
# figure = dict(data=[Scatter()], layout=layout)
return div_output(figure)
x = 0.
y = 0.
width = 100.
height = 100.
values = []
values_text = []
for tier_3_format, count in Counter(tier_3_formats).most_common():
# otherwise this gets a little unwieldy...
if tier_3_format != "" and count > 100:
values.append(count)
values_text.append(tier_3_format)
normed = squarify.normalize_sizes(values, width, height)
rects = squarify.squarify(normed, x, y, width, height)
# Choose colors from http://colorbrewer2.org/ under "Export"
color_brewer = ['rgb(166,206,227)','rgb(31,120,180)','rgb(178,223,138)',
'rgb(51,160,44)','rgb(251,154,153)','rgb(227,26,28)',
'rgb(253,191,111)','rgb(255,127,0)','rgb(202,178,214)',
'rgb(106,61,154)','rgb(255,255,153)','rgb(177,89,40)']
shapes = []
annotations = []
color_counter = 0
name_counter = 0
for r in rects:
shapes.append(
def treemap(sizes, diff, labels, x=0, y=0, width=1, height=1, title=None):
# 准备画布
fig, ax = plt.subplots(1, figsize=(15, 15 * height / width))
ax.set_xlim(x, width)
ax.set_ylim(y, height)
# 创造和同比净增长关联的颜色方案
min_diff = min(diff)
max_diff = max(diff)
if min_diff > 0:
cmap = mpl.cm.Blues
norm = mpl.colors.Normalize(vmin=min_diff, vmax=max_diff)
elif max_diff < 0:
cmap = mpl.cm.Reds
norm = mpl.colors.Normalize(vmin=min_diff, vmax=max_diff)
else:
cmap = mpl.cm.bwr_r
norm = mpl.colors.TwoSlopeNorm(
vmin=min_diff, vcenter=0, vmax=max_diff
) # 强制0为中点的正太分布渐变色
colors = [cmap(norm(value)) for value in diff]
# 使用Squarify原生方法画图
# ax = squarify.plot(sizes=sizes,
# label=labels[:label_limit],
# ax=ax,
# bar_kwargs=dict(linewidth=1, edgecolor="#222222"),
# text_kwargs={'fontname': 'SimHei',
# 'fontsize': 20},
# alpha=.8,
# color=colors
# )
# 使用Squarify导出四边形数据，以数据手动画图，可以控制更多元素
sizes.sort(reverse=True) # sizes必须先由大到小排序
sizes = squarify.normalize_sizes(sizes, width, height) # 根据设置的总体宽高正态化数据
rects_data = squarify.squarify(sizes, x, y, width, height) # Squarify算法计算出所有四边形的数据
# 根据数据循环创建矩形并添加标签
for i, r in enumerate(rects_data):
rect = patches.Rectangle(
(r["x"], r["y"]),
r["dx"],
r["dy"],
linewidth=2,
edgecolor="#222222",
facecolor=colors[i],
) # 创建四边形
ax.add_patch(rect) # Add patch到轴
# 动态添加标签并设置标签字体大小
if r["dx"] > 0.02 * (width * height) or r["dx"] * r["dy"] > 0.01 * (
width * height
):
plt.text(
r["x"] + r["dx"] / 2, # rect的水平中心
r["y"] + r["dy"] / 2, # rect的垂直中心
labels[i],
ha="center",
va="center",
multialignment="center",
fontproperties=myfont,
fontsize=80 * r["dx"] / (width * height),
)
# 前十名左上角添加Rank
if i < 10:
plt.text(
r["x"] + r["dx"] * 0.1, # rect的left稍往右偏移
r["y"] + r["dy"] - r["dx"] * 0.1, # rect的Top稍往下偏移
i + 1,
ha="center",
va="center",
multialignment="center",
fontproperties=myfont,
fontsize=80 * r["dx"] / (width * height),
)
# 去除边框的刻度
ax.set_xticks([])
ax.set_yticks([])
# 添加标题
if title is not None:
fig.suptitle(title, fontproperties=myfont)
# 保存到字符串
sio = BytesIO()
plt.savefig(sio, format="png", bbox_inches="tight", transparent=True, dpi=600)
data = base64.encodebytes(sio.getvalue()).decode() # 解码为base64编码的png图片数据
src = "data:image/png;base64," + str(data) # 增加Data URI scheme
# 关闭绘图进程
plt.clf()
plt.cla()
plt.close()
return src
