# -*- coding: utf-8 -*-
##############################################################################
#
#    OpenERP, Open Source Management Solution
#    Copyright (C) 2004-2010 Tiny SPRL (<http://tiny.be>).
#
#    This program is free software: you can redistribute it and/or modify
#    it under the terms of the GNU Affero General Public License as
#    published by the Free Software Foundation, either version 3 of the
#    License, or (at your option) any later version.
#
#    This program is distributed in the hope that it will be useful,
#    but WITHOUT ANY WARRANTY; without even the implied warranty of
#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
#    GNU Affero General Public License for more details.
#
#    You should have received a copy of the GNU Affero General Public License
#    along with this program.  If not, see <http://www.gnu.org/licenses/>.
#
##############################################################################

import ir
import os, time
import netsvc

import random
import StringIO

import tools
import pooler

from report.render import render
from report.interface import report_int
from pychart import *

theme.use_color = 1
#theme.scale = 2
random.seed(0)

class external_pdf(render):

    """ Generate External PDF """

    def __init__(self, pdf):
        render.__init__(self)
        self.pdf = pdf
        self.output_type = 'pdf'

    def _render(self):
        return self.pdf

class report_custom(report_int):

    """ Create Custom Report """

    def create(self, cr, uid, ids, datas, context={}):

        """ @param cr: the current row, from the database cursor,
            @param uid: the current user’s ID for security checks,
            @param ids: List of IDs
            @param context: A standard dictionary for contextual values """

        assert len(ids), 'You should provide some ids!'
        responsible_data = {}
        responsible_names = {}
        data = []
        minbenef = 999999999999999999999
        maxbenef = 0

        cr.execute('select probability, planned_revenue, planned_cost, user_id,\
                 res_users.name as name from crm_case left join res_users on \
                 (crm_case.user_id=res_users.id) where crm_case.id IN %s order by user_id',(tuple(ids),))

        res = cr.dictfetchall()
        for row in res:
            proba = row['probability'] or 0 / 100.0
            cost = row['planned_cost'] or 0
            revenue = row['planned_revenue'] or 0
            userid = row['user_id'] or 0

            benefit = revenue - cost
            if benefit > maxbenef:
                maxbenef = benefit
            if benefit < minbenef:
                minbenef = benefit

            tuple = (proba * 100,  benefit)
            responsible_data.setdefault(userid, [])
            responsible_data[userid].append(tuple)

            tuple = (proba * 100, cost, benefit)
            data.append(tuple)

            responsible_names[userid] = (row['name'] or '/').replace('/','//')

        minbenef -= maxbenef * 0.05
        maxbenef *= 1.2

        ratio = 0.5
        minmaxdiff2 = (maxbenef - minbenef)/2

        for l in responsible_data.itervalues():
            for i in range(len(l)):
                percent, benef = l[i]
                proba = percent/100

                current_ratio = 1 + (ratio-1) * proba

                newbenef = minmaxdiff2 + ((benef - minbenef - minmaxdiff2) * current_ratio)

                l[i] = (percent, newbenef)

#TODO:
#-group by "categorie de probabilites ds graphe du haut"
#-echelle variable

        pdf_string = StringIO.StringIO()
        can = canvas.init(fname = pdf_string, format = 'pdf')

        chart_object.set_defaults(line_plot.T, line_style=None)

        xaxis = axis.X(label=None, format="%d%%", tic_interval=20)
        yaxis = axis.Y()

        x_range_a, x_range_b = (0, 100)
        y_range_a, y_range_b = (minbenef, maxbenef)
        if y_range_a == 0.0:
            y_range_a += 0.0001

        ar = area.T(
            size = (300,200),
            y_grid_interval = 10000,
            y_grid_style = None,
            x_range = (x_range_a, x_range_b),
            y_range = (y_range_a, y_range_b),
            x_axis = xaxis,
            y_axis = None,
            legend = legend.T()
        )

        #import pydb; pydb.debugger()
        for k, d in responsible_data.iteritems():
            fill = fill_style.Plain(bgcolor=color.T(r=random.random(), g=random.random(), b=random.random()))
            tick = tick_mark.Square(size=6, fill_style=fill)
            ar.add_plot(line_plot.T(label=responsible_names[k], data=d, tick_mark=tick))

        ar.draw(can)

        # second graph (top right)
        ar = area.T(legend = legend.T(),
                    size = (200,100),
                    loc = (100,250),
                    x_grid_interval = lambda min, max: [40,60,80,100],
                    x_grid_style = line_style.gray70_dash1,
                    x_range = (33, 100),
                    x_axis = axis.X(label=None, minor_tic_interval = lambda min,max: [50, 70, 90],\
                                     format=lambda x: ""),
                    y_axis = axis.Y(label="Planned amounts"))

        bar_plot.fill_styles.reset();
        plot1 = bar_plot.T(label="Cost", data=data, fill_style=fill_style.red)
        plot2 = bar_plot.T(label="Revenue", data=data, hcol=2, stack_on = plot1, fill_style=fill_style.blue)

        ar.add_plot(plot1, plot2)

        ar.draw(can)

        # diagonal "pipeline" lines
        can.line(line_style.black, 0, 200, 300, 150)
        can.line(line_style.black, 0, 0, 300, 50)

        # vertical lines
        ls = line_style.T(width=0.4, color=color.gray70, dash=(2, 2))
        for x in range(120, 300, 60):
            can.line(ls, x, 0, x, 250)

        # draw arrows to the right
        a = arrow.fat1
        for y in range(60, 150, 10):
            a.draw([(285, y), (315, y)], can=can)

        # close canvas so that the file is written to "disk"
        can.close()

        self.obj = external_pdf(pdf_string.getvalue())
        self.obj.render()

        pdf_string.close()
        return (self.obj.pdf, 'pdf')

report_custom('report.crm.case')

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