#!/usr/bin/env python
#
# Copyright (C) 2007 Oracle.  All rights reserved.
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public
# License v2 as published by the Free Software Foundation.
# 
# 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
# General Public License for more details.
# 
# You should have received a copy of the GNU General Public
# License along with this program; if not, write to the
# Free Software Foundation, Inc., 59 Temple Place - Suite 330,
# Boston, MA 021110-1307, USA.
#
import sys, os, signal, time, commands, tempfile
from optparse import OptionParser
from matplotlib import rcParams
from matplotlib.font_manager import fontManager, FontProperties
import numpy

rcParams['numerix'] = 'numpy'
rcParams['backend'] = 'Agg'
rcParams['interactive'] = 'False'
from pylab import *

class AnnoteFinder:
  """
  callback for matplotlib to display an annotation when points are clicked on.  The
  point which is closest to the click and within xtol and ytol is identified.
    
  Register this function like this:
    
  scatter(xdata, ydata)
  af = AnnoteFinder(xdata, ydata, annotes)
  connect('button_press_event', af)
  """

  def __init__(self, axis=None):
    if axis is None:
      self.axis = gca()
    else:
      self.axis= axis
    self.drawnAnnotations = {}
    self.links = []
    
  def clear(self):
    for k in self.drawnAnnotations.keys():
        self.drawnAnnotations[k].set_visible(False)

  def __call__(self, event):
    if event.inaxes:
      if event.button != 1:
        self.clear()
        draw()
        return
      clickX = event.xdata
      clickY = event.ydata
      if (self.axis is None) or (self.axis==event.inaxes):
        self.drawAnnote(event.inaxes, clickX, clickY)
    
  def drawAnnote(self, axis, x, y):
    """
    Draw the annotation on the plot
    """
    if self.drawnAnnotations.has_key((x,y)):
      markers = self.drawnAnnotations[(x,y)]
      markers.set_visible(not markers.get_visible())
      draw()
    else:
      t = axis.text(x,y, "(%3.2f, %3.2f)"%(x,y), bbox=dict(facecolor='red',
                    alpha=0.8))
      self.drawnAnnotations[(x,y)] = t
      draw()

def loaddata(fh,delimiter=None, converters=None):

    def iter(fh, delimiter, converters):
        global total_data
        global total_metadata
        for i,line in enumerate(fh):
            line = line.split(' ')
            start = float(line[0])
            len = float(line[1])
            owner = float(line[10])
            if owner <= 255:
                total_metadata += int(len)
            else:
                total_data += int(len)
            if start < zoommin or (zoommax != 0 and start > zoommax):
                continue
            yield start
            yield len
            yield owner
    X = numpy.fromiter(iter(fh, delimiter, converters), dtype=float)
    return X

def run_debug_tree(device):
    p = os.popen('debug-tree -e ' + device)
    data = loaddata(p)
    return data

def shapeit(X):
    lines = len(X) / 3
    X.shape = (lines, 3)

def line_picker(line, mouseevent):
    if mouseevent.xdata is None: return False, dict()
    print "%d %d\n", mouseevent.xdata, mouseevent.ydata
    return False, dict()

def xycalc(byte):
    byte = byte / bytes_per_cell
    yval = floor(byte / num_cells)
    xval = byte % num_cells
    return (xval, yval + 1)

def plotone(a, xvals, yvals, owner):
    global data_lines
    global meta_lines

    if owner:
        if options.meta_only:
            return
        color = "blue"
        label = "Data"
    else:
        if options.data_only:
            return
        color = "green"
        label = "Metadata"

    lines = a.plot(xvals, yvals, 's', color=color, mfc=color, mec=color,
           markersize=.23, label=label)
    if owner and not data_lines:
        data_lines = lines
    elif not owner and not meta_lines:
        meta_lines = lines


def parse_zoom():
    def parse_num(s):
        mult = 1
        c = s.lower()[-1]
        if c == 't':
            mult = 1024 * 1024 * 1024 * 1024
        elif c == 'g':
            mult = 1024 * 1024 * 1024
        elif c == 'm':
            mult = 1024 * 1024
        elif c == 'k':
            mult = 1024
        else:
            c = None
        if c:
            num = int(s[:-1]) * mult
        else:
            num = int(s)
        return num
        
    if not options.zoom:
        return (0, 0)

    vals = options.zoom.split(':')
    if len(vals) != 2:
        sys.stderr.write("warning: unable to parse zoom %s\n" % options.zoom)
        return (0, 0)
    zoommin = parse_num(vals[0])
    zoommax = parse_num(vals[1])
    return (zoommin, zoommax)

usage = "usage: %prog [options]"
parser = OptionParser(usage=usage)
parser.add_option("-d", "--device", help="Btrfs device", default="")
parser.add_option("-i", "--input-file", help="debug-tree data", default="")
parser.add_option("-o", "--output", help="Output file", default="blocks.png")
parser.add_option("-z", "--zoom", help="Zoom", default=None)
parser.add_option("", "--data-only", help="Only print data blocks",
                  default=False, action="store_true")
parser.add_option("", "--meta-only", help="Only print metadata blocks",
                  default=False, action="store_true")

(options,args) = parser.parse_args()

if not options.device and not options.input_file:
    parser.print_help()
    sys.exit(1)

zoommin, zoommax = parse_zoom()
total_data = 0
total_metadata = 0
data_lines = []
meta_lines = []

if options.device:
    data = run_debug_tree(options.device)
elif options.input_file:
    data = loaddata(file(options.input_file))
shapeit(data)

# try to drop out the least common data points by creating
# a historgram of the sectors seen.
sectors = data[:,0]
sizes = data[:,1]
datalen = len(data)
sectormax = numpy.max(sectors)
sectormin = 0
num_cells = 800
total_cells = num_cells * num_cells
byte_range = sectormax - sectormin
bytes_per_cell = byte_range / total_cells

f = figure(figsize=(8,6))

# Throughput goes at the botoom
a = subplot(1, 1, 1)
datai = 0
xvals = []
yvals = []
last = 0
while datai < datalen:
    row = data[datai]
    datai += 1
    byte = row[0]
    size = row[1]
    owner = row[2]

    if owner <= 255:
        owner = 0
    else:
        owner = 1

    if len(xvals) and owner != last:
        plotone(a, xvals, yvals, last)
        xvals = []
        yvals = []
    cell = 0
    while cell < size:
        xy = xycalc(byte)
        byte += bytes_per_cell
        cell += bytes_per_cell
        if xy:
            xvals.append(xy[0])
            yvals.append(xy[1])
    last = owner

if xvals:
    plotone(a, xvals, yvals, last)

# make sure the final second goes on the x axes
ticks = []
a.set_xticks(ticks)
ticks = a.get_yticks()

first_tick = ticks[1] * bytes_per_cell * num_cells
if first_tick > 1024 * 1024 * 1024 * 1024:
    scale = 1024 * 1024 * 1024 * 1024;
    scalestr = "TB"
elif first_tick > 1024 * 1024 * 1024:
    scale = 1024 * 1024 * 1024;
    scalestr = "GB"
elif first_tick > 1024 * 1024:
    scale = 1024 * 1024;
    scalestr = "MB"
elif first_tick > 1024:
    scale = 1024;
    scalestr = "KB"
else:
    scalestr = "Bytes"
    scale = 1

ylabels = [ str(int((x * bytes_per_cell * num_cells) / scale)) for x in ticks ]
a.set_yticklabels(ylabels)
a.set_ylabel('Disk offset (%s)' % scalestr)
a.set_xlim(0, num_cells)
a.set_title('Blocks')

lines = []
labels = []
if data_lines:
    lines += data_lines
    labels += ["Data"]
if meta_lines:
    lines += meta_lines
    labels += ["Metadata"]

a.legend(lines, labels, loc=(.9, 1.02), shadow=True, pad=0.5, numpoints=1,
              handletextsep = 0.005,
              labelsep = 0.01,
              markerscale=10,
              prop=FontProperties(size='x-small') )

if total_data == 0:
    percent_meta = 100
else:
    percent_meta = (float(total_metadata) / float(total_data)) * 100

print "Total metadata bytes %d data %d ratio %.3f" % (total_metadata,
                                                    total_data, percent_meta)
print "saving graph to %s" % options.output
savefig(options.output, orientation='landscape')
show()