def forecast():
#tam & sas
sales = request.form['sales']
price = request.form['price']
sas = request.form['sas']
growth = request.form['growth']
total = Market(sales, price, sas, growth)
calc_tam = total.tam()
calc_tam_c = '{:,.2f}'.format(calc_tam)
calc_sas = total.sas()
calc_sas_c = '{:,.2f}'.format(calc_sas)
#forecast P&L inputs
salesm1 = request.form['salesm1']
pricem1 = request.form['pricem1']
sgmom = request.form['sgmom']
cmgrowth = request.form['cmgrowth']
pindex = request.form['pindex']
cogs = request.form['cogs']
opex = request.form['opex']
fixed = request.form['fixed']
#forecast P&L class constructor
fpl = Forecastpl(salesm1, pricem1, sgmom, cmgrowth, pindex, cogs, opex,
fixed)
#x chart axis
x = np.arange(1, 13)
#forecast P&L growth and percentages
fpl.sales_growth()
fpl.cm_growth()
fpl.price_growth()
fpl.cogs_pc()
fpl.opex_pc()
fpl.fixed_pc()
#forecast P&L pre-plot calculations
fpl.units_mom()
fpl.price_mom()
fpl_rev = fpl.revenue_profile()
fpl.cm_calc_initial()
fpl.cm_adjusted()
fpl_cmadj = fpl.cm_calc()
fpl.fixed_calc()
fpl_op = fpl.fpl_op_profit()
#forecast P&L cumulative
fpl_rev_cum = np.cumsum(fpl_rev)
fpl_cmadj_cum = np.cumsum(fpl_cmadj)
fpl_op_cum = np.cumsum(fpl_op)
#sas and fp&l comparison
fpl_sas = round(np.sum(fpl_rev, dtype=np.float64), 2)
fpl_sas_c = '{:,.2f}'.format(fpl_sas)
fpl_sas_delta = round(float(fpl_sas - calc_sas), 2)
fpl_sas_delta_c = '{:,.2f}'.format(fpl_sas_delta)
fpl_sas_delta_pc = round(float((fpl_sas / calc_tam) * 100), 2)
#plot parameters
plt.plot(x, fpl_rev_cum, label='revenue')
plt.plot(x, fpl_cmadj_cum, label='cm')
plt.plot(x, fpl_op_cum, label='op profit')
plt.xlabel('month')
plt.ylabel('£')
plt.title('Forecast P&L cumulative ')
plt.legend()
plt.xticks(x)
plt.savefig(img_path)
plt.close()
return render_template('forecast.html',
sales=sales,
price=price,
sas=sas,
growth=growth,
calc_tam_c=calc_tam_c,
calc_sas_c=calc_sas_c,
name='Forecast P&L cumulative',
fpl_sas_c=fpl_sas_c,
fpl_sas_delta_c=fpl_sas_delta_c,
fpl_sas_delta_pc=fpl_sas_delta_pc,
fileName=fileName,
fileExt=fileExt)
