#!/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, random

# numpy seems to override random() with something else.  Instantiate our
# own here
randgen = random.Random()
randgen.seed(50)

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):

    #14413824 8192 extent back ref root 5 gen 10 owner 282 num_refs 1
    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])
            root = float(line[6])
            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
            yield root
    X = numpy.fromiter(iter(fh, delimiter, converters), dtype=float)
    return X

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

def shapeit(X):
    lines = len(X) / 4
    X.shape = (lines, 4)

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)

# record the color used for each root the first time we find it
root_colors = {}
# there are lots of good colormaps to choose from
# http://www.scipy.org/Cookbook/Matplotlib/Show_colormaps
#
meta_cmap = get_cmap("gist_ncar")
data_done = False

def plotone(a, xvals, yvals, owner, root, lines, labels):
    global data_done
    add_label = False

    if owner:
        if options.meta_only:
            return
        color = "blue"
        label = "Data"
        if not data_done:
            add_label = True
            data_done = True
    else:
        if options.data_only:
            return
        if root not in root_colors:
            color = meta_cmap(randgen.random())
            label = "Meta %d" % int(root)
            root_colors[root] = (color, label)
            add_label = True
        else:
            color, label = root_colors[root]

    plotlines = a.plot(xvals, yvals, 's', color=color, mfc=color, mec=color,
           markersize=.23, label=label)
    if add_label:
        lines += plotlines
        labels.append(label)
        print "add label %s" % label

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

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 histogram 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 bottom
a = subplot(1, 1, 1)
subplots_adjust(right=0.7)
datai = 0
xvals = []
yvals = []
last_owner = 0
last_root = 0
lines = []
labels = []
while datai < datalen:
    row = data[datai]
    datai += 1
    byte = row[0]
    size = row[1]
    owner = row[2]
    root = row[3]

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

    if len(xvals) and (owner != last_owner or last_root != root):
        plotone(a, xvals, yvals, last_owner, last_root, lines, labels)
        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 = owner
    last_root = root

if xvals:
    plotone(a, xvals, yvals, last_owner, last_root, lines, labels)

# 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')

a.legend(lines, labels, loc=(1.05, 0.8), shadow=True, pad=0.1, 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()