def category_budget_left_pie(c, category, h, w):
my_data = []
for x in range(1, month + 1):
my_data.append(data.category_data(category, x, year))
labels = month_name[1:month + 1]
labels.append('Budget')
my_data.append(data.category_budget(category) - sum(my_data))
d = Drawing()
pie = Pie()
pie.sideLabels = 1
pie._seriesCount = 10
#if legend:
# add_legend(d, pie, data)
pie.x = 0
pie.y = 0
pie.width = 100
pie.height = pie.width
pie.data = my_data
pie.slices.fontName = serif_font
pie.slices.fontSize = 11
pie.labels = labels
pie.slices.strokeWidth = 0.5
#pie.slices[3].popout = 20
d.add(pie)
d.drawOn(c, h, w)
def category_predicted_spending(c, category, h, w):
"""
Creates a bar graph in a PDF
"""
my_data = []
for i in range(1, month + 1):
my_data.append(round(data.category_data(category, i, year)))
budget = data.category_budget(category)
re_budget = (budget - sum(my_data)) / (12 - month)
for x in range(month, 12):
my_data.append(re_budget)
d = Drawing(0, 0)
bar = VerticalBarChart()
bar.x = 150
bar.y = 150
bar.data = [my_data]
bar.valueAxis.valueMin = 0
bar.categoryAxis.categoryNames = [
'Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct',
'Nov', 'Dec'
]
bar.categoryAxis.labels.fontName = serif_font
bar.valueAxis.labels.fontName = serif_font
bar.categoryAxis.labels.boxAnchor = 'n'
bar.categoryAxis.labels.angle = 90
bar.categoryAxis.labels.dy = -15
bar.categoryAxis.labels.dx = -10
#below change monnth number based upon current month
bar.bars[0].fillColor = PCMYKColor(150, 150, 150, 150, alpha=85)
for i in range(month, 12):
bar.bars[(0, i)].fillColor = PCMYKColor(0, 150, 150, 0, alpha=85)
d.add(bar, '')
d.drawOn(c, h, w)
def monthly_spending_bar(c, category, h, w):
"""
Creates a bar graph in a PDF
"""
my_data = []
for i in range(1, 12 + 1):
my_data.append(data.category_data(category.lower(), i, year))
for i in range(month, 12):
my_data[i] = 0
#d = Drawing(300, 250)
d = Drawing(0, 0)
bar = VerticalBarChart()
bar.x = 150
bar.y = 150
bar.data = [my_data]
bar.valueAxis.valueMin = 0
bar.categoryAxis.categoryNames = [
'Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct',
'Nov', 'Dec'
]
bar.categoryAxis.labels.fontName = serif_font
bar.valueAxis.labels.fontName = serif_font
bar.categoryAxis.labels.boxAnchor = 'n'
bar.categoryAxis.labels.angle = 90
bar.categoryAxis.labels.dy = -15
bar.categoryAxis.labels.dx = -10
#below change monnth number based upon current month
bar.bars[0].fillColor = PCMYKColor(150, 150, 150, 150, alpha=85)
bar.bars[(0, month - 1)].fillColor = PCMYKColor(150, 0, 0, 0, alpha=85)
d.add(bar, '')
d.drawOn(c, 200, 480)
def overview_month_spending_breakdown_pie(c, h, w):
categories = [
'Clothing', 'Transport', 'Insurance', 'Food', 'Medical and Dental',
'Housing', 'Utilities', 'Education', 'Gifts', 'Entertainment'
]
d = Drawing()
pie = Pie()
pie.sideLabels = 1
pie._seriesCount = 10
my_data = []
for x in categories:
my_data.append(data.category_data(x.lower(), month, 2019))
pie.x = 0
pie.y = 0
pie.width = 100
pie.height = pie.width
pie.data = my_data
pie.slices.fontName = serif_font
pie.slices.fontSize = 11
pie.labels = tuple(categories)
pie.slices.strokeWidth = 0.5
#pie.slices[3].popout = 20
d.add(pie)
d.drawOn(c, h, w)
def get_data(source='movies', target=None):
data = None
if '{}{}'.format(source,
target) not in listdir('{}/processedData/'.format(ROOT)):
data = category_data(source, target=target)
pickle.dump(
data,
open('{}/processedData/{}{}'.format(ROOT, source, target), 'w'))
else:
data = pickle.load(
open('{}/processedData/{}{}'.format(ROOT, source, target)))
return data
def get_data():
source, target = 'electronics', 'movies'
data = None
if '{}{}'.format(source,
target) not in listdir('{}/processedData/'.format(ROOT)):
data = category_data(source, autoencoder=False, target=target)
pickle.dump(
data,
open('{}/processedData/{}{}'.format(ROOT, source, target), 'w'))
else:
data = pickle.load(
open('{}/processedData/{}{}'.format(ROOT, source, target)))
return data
def main(args):
mode, src, dest = None, None, None
if len(args) == 2: mode, preload = args
elif len(args) == 4: mode, preload, src, dest = args
else: raise ValueError('Incorrect number of args.')
if preload == 'none': preload = None
if mode == 'vis':
data = get_data()
model = init_model(
data=[data['embedding_matrix'], data['len_word_index']])
return visualizer(model)
if mode == 'train':
return runner(50)
if mode == 'confusion':
model = init_model(preload=preload, declare=False)
data = category_data(src, target=dest)
y_true = data['y_val']
y_pred = model.predict(data['x_val'])
print get_confusion_matrix(y_true, y_pred)
else:
raise ValueError('Incorrect mode')