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CSPP_VIIRS_SST_hdf5Plots.py
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CSPP_VIIRS_SST_hdf5Plots.py
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#!/usr/bin/env python
# encoding: utf-8
"""
CSPP_VIIRS_SST_hdf5Plots.py
Purpose: Create swath projection quicklook PNGs from the VIIRS SST EDR HDF5 files.
Images can be created for the EDR product or the associated quality flags.
Minimum commandline...
export CSPP_EDR_HOME=$(readlink -f /path/to/EDR)
source $CSPP_EDR_HOME/cspp_edr_env.sh
python CSPP_VIIRS_SST_hdf5Plots.py -i '/path/to/files/VSSTO*.h5'
or
python CSPP_VIIRS_SST_hdf5Plots.py --input_files=/path/to/files/VSSTO*.h5
Created by Geoff Cureton on 2013-06-04.
Copyright (c) 2013 University of Wisconsin SSEC. All rights reserved.
"""
file_Date = '$Date$'
file_Revision = '$Revision$'
file_Author = '$Author$'
file_HeadURL = '$HeadURL$'
file_Id = '$Id$'
__author__ = 'G.P. Cureton <[email protected]>'
__version__ = '$Id$'
__docformat__ = 'Epytext'
#############
import os, sys
from os import path, uname, mkdir
from glob import glob
import string, logging, traceback
from time import time
import numpy as np
from numpy import ma as ma
import scipy as scipy
import matplotlib
import matplotlib.cm as cm
from matplotlib.colors import ListedColormap
from matplotlib.figure import Figure
matplotlib.use('Agg')
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
# This must come *after* the backend is specified.
import matplotlib.pyplot as ppl
import optparse as optparse
from ViirsData import ViirsTrimTable
import viirs_edr_data
import tables as pytables
from tables import exceptions as pyEx
# every module should have a LOG object
# e.g. LOG.warning('my dog has fleas')
import logging
LOG = logging.getLogger(__file__)
dpi=200
### Moderate and Imager resolution trim table arrays. These are
### bool arrays, and the trim pixels are set to True.
trimObj = ViirsTrimTable()
modTrimMask = trimObj.createModTrimArray(nscans=48,trimType=bool)
SeaSurfaceTempProduct = viirs_edr_data.SeaSurfaceTempProdData.SeaSurfaceTempProd()
cmap = SeaSurfaceTempProduct.cmap
def get_hdf5_dict(hdf5Path,filePrefix):
shortNameDict = {}
hdf5Path = path.abspath(path.expanduser(hdf5Path))
print "hdf5Path = %s" % (hdf5Path)
hdf5Dir = path.dirname(hdf5Path)
hdf5Glob = path.basename(hdf5Path)
print "hdf5Dir = %s" % (hdf5Dir)
print "hdf5Glob = %s" % (hdf5Glob)
if (hdf5Glob == '' or hdf5Glob == '*'):
print "prefix = %s" % (filePrefix)
hdf5Glob = path.join(hdf5Dir,'%s_*.h5'%(filePrefix))
else :
hdf5Glob = path.join(hdf5Dir,'%s'%(hdf5Glob))
print "Final hdf5Glob = %s" % (hdf5Glob)
hdf5Files = glob(hdf5Glob)
if hdf5Files != []:
hdf5Files.sort()
granIdDict = {}
for files in hdf5Files :
# Open the hdf5 file
fileObj = pytables.openFile(files)
# Get a "pointer" to the granules attribute group.
VIIRS_SST_EDR_Gran_0 = fileObj.getNode('/Data_Products/VIIRS-SST-EDR/VIIRS-SST-EDR_Gran_0')
# Retrieve a few attributes
granID = getattr(VIIRS_SST_EDR_Gran_0.attrs,'N_Granule_ID')[0][0]
print 'N_Granule_ID = %s' % (granID)
dayNightFlag = getattr(VIIRS_SST_EDR_Gran_0.attrs,'N_Day_Night_Flag')[0][0]
print 'N_Day_Night_Flag = %s' % (dayNightFlag)
shortName = fileObj.getNodeAttr('/Data_Products/VIIRS-SST-EDR','N_Collection_Short_Name')[0][0]
print 'N_Collection_Short_Name = %s' % (shortName)
# Strip the path from the filename
hdf5File = path.basename(files)
# Add the granule information to the dictionary, keyed with the granule ID...
granIdDict[granID] = [hdf5File,fileObj]
shortNameDict[shortName] = granIdDict
return shortNameDict
class SSTclass():
def __init__(self,hdf5Dir):
self.hdf5Dir = hdf5Dir
self.collShortNames = [
'VIIRS-SST-EDR',
]
self.plotDescr = {}
self.plotDescr['VIIRS-SST-EDR'] = ['Skin Sea Surface Temperature (K)',
'Reference Sea Surface Temperature (K)',
'Bulk Sea Surface Temperature (K)']
self.plotLims = {}
#self.plotLims['VIIRS-SST-EDR'] = [250., 290.]
self.plotLims['VIIRS-SST-EDR'] = [None,None]
self.dataName = {}
self.dataName['VIIRS-SST-EDR'] = ['/All_Data/VIIRS-SST-EDR_All/SkinSST',
'/All_Data/VIIRS-SST-EDR_All/ReferenceSST',
'/All_Data/VIIRS-SST-EDR_All/BulkSST']
self.dataFactors = {}
self.dataFactors['VIIRS-SST-EDR'] = ['/All_Data/VIIRS-SST-EDR_All/SkinSSTFactors',
'/All_Data/VIIRS-SST-EDR_All/ReferenceSSTFactors',
'/All_Data/VIIRS-SST-EDR_All/Bulk-Skin_Offset']
self.hdf5_dict = get_hdf5_dict(hdf5Dir,'VSSTO')
def plot_SST_granules(self,plotProd='EDR',vmin=None,vmax=None,pngDir=None,pngPrefix=None,annotation='',dpi=300):
if pngDir is None :
pngDir = path.abspath(path.curdir)
plotDescr = self.plotDescr
plotLims = self.plotLims
hdf5_dict = self.hdf5_dict
collShortNames = hdf5_dict.keys()
print 'collShortNames = %r' % (collShortNames)
for shortName in collShortNames :
print 'shortName = %s' % (shortName)
if (plotProd == 'EDR'):
dataNames = self.dataName[shortName]
factorsNames = self.dataFactors[shortName]
plotDescrs = plotDescr[shortName]
prodNames = ['SkinSST','BulkSST']
elif (plotProd == 'Skin'):
dataNames = [self.dataName[shortName][0]]
factorsNames = [self.dataFactors[shortName][0]]
plotDescrs = [plotDescr[shortName][0]]
prodNames = ['SkinSST']
elif (plotProd == 'Bulk'):
dataNames = [self.dataName[shortName][1]]
factorsNames = [self.dataFactors[shortName][1]]
plotDescrs = [plotDescr[shortName][1]]
prodNames = ['BulkSST']
granID_list = hdf5_dict[shortName].keys()
granID_list.sort()
for granID in granID_list :
print '%s --> %s ' % (shortName, granID)
hdf5Obj = hdf5_dict[shortName][granID][1]
VIIRS_SST_EDR_Gran_0 = hdf5Obj.getNode('/Data_Products/VIIRS-SST-EDR/VIIRS-SST-EDR_Gran_0')
dayNightFlag = getattr(VIIRS_SST_EDR_Gran_0.attrs,'N_Day_Night_Flag')[0][0]
print 'N_Day_Night_Flag = %s' % (dayNightFlag)
orient = -1 if dayNightFlag == 'Day' else 1
for dataName,factorsName,plotDescr,prodName in zip(dataNames,factorsNames,plotDescrs,prodNames):
data = hdf5Obj.getNode(dataName)[:,:]
factors = hdf5Obj.getNode(factorsName)[:]
data = data*factors[0] + factors[1]
SSTqualFlag = hdf5Obj.getNode('/All_Data/VIIRS-SST-EDR_All/QF1_VIIRSSSTEDR')
SSTqualFlag = np.bitwise_and(SSTqualFlag,3) >> 0
SSTqualFlagMask = ma.masked_equal(SSTqualFlag,0).mask
pixelTrimValue = trimObj.sdrTypeFill['ONGROUND_PT_FILL'][data.dtype.name]
print "pixelTrimValue is %r" % (pixelTrimValue)
# Apply the moderate pixel trim, so that we can properly mask them out at plot time.
data = ma.array(data,mask=modTrimMask,fill_value=trimObj.sdrTypeFill['ONBOARD_PT_FILL'][data.dtype.name])
data = data.filled()
plotTitle = '%s : %s %s' % (shortName,granID,annotation)
cbTitle = plotDescr
# Create figure with default size, and create canvas to draw on
scale=1.5
fig = Figure(figsize=(scale*8,scale*3))
canvas = FigureCanvas(fig)
# Create main axes instance, leaving room for colorbar at bottom,
# and also get the Bbox of the axes instance
ax_rect = [0.05, 0.18, 0.9, 0.75 ] # [left,bottom,width,height]
ax = fig.add_axes(ax_rect)
# Granule axis title
ax_title = ppl.setp(ax,title=plotTitle)
ppl.setp(ax_title,fontsize=12)
ppl.setp(ax_title,family="sans-serif")
# Plot the data
print "%s is of kind %r" % (shortName,data.dtype.kind)
if (data.dtype.kind =='i' or data.dtype.kind =='u'):
fill_mask = ma.masked_greater(data,200).mask
else:
fill_mask = ma.masked_less(data,-800.).mask
# Construct the total mask
totalMask = SSTqualFlagMask + fill_mask
# Mask the aerosol so we only have the retrievals
data = ma.masked_array(data,mask=totalMask)
im = ax.imshow(data[::orient,::orient],interpolation='nearest',vmin=vmin,vmax=vmax)
ppl.setp(ax.get_xticklabels(), visible=False)
ppl.setp(ax.get_yticklabels(), visible=False)
ppl.setp(ax.get_xticklines(),visible=False)
ppl.setp(ax.get_yticklines(),visible=False)
# add a colorbar axis
cax_rect = [0.05 , 0.05, 0.9 , 0.10 ] # [left,bottom,width,height]
cax = fig.add_axes(cax_rect,frameon=False) # setup colorbar axes
# Plot the colorbar.
cb = fig.colorbar(im, cax=cax, orientation='horizontal')
ppl.setp(cax.get_xticklabels(),fontsize=9)
ppl.setp(cax.get_xticklines(),visible=True)
# Colourbar title
cax_title = ppl.setp(cax,title=cbTitle)
ppl.setp(cax_title,fontsize=10)
# Turn off the tickmarks on the colourbar
#ppl.setp(cb.ax.get_xticklines(),visible=False)
#ppl.setp(cb.ax.get_xticklabels(),fontsize=9)
# Redraw the figure
canvas.draw()
# Save the figure to a png file...
pngFile = path.join(pngDir,'%s%s_%s_%s.png' % (pngPrefix,shortName,granID,prodName))
canvas.print_figure(pngFile,dpi=dpi)
print "Writing to %s..." % (pngFile)
ppl.close('all')
hdf5Obj.close()
def plot_SST_pass(self,plotProd='EDR',vmin=None,vmax=None,pngDir=None,
pngPrefix=None,annotation='',dpi=300):
if pngDir is None :
pngDir = path.abspath(path.curdir)
plotDescr = self.plotDescr
plotLims = self.plotLims
hdf5_dict = self.hdf5_dict
collShortNames = hdf5_dict.keys()
print 'collShortNames = %r' % (collShortNames)
for shortName in collShortNames :
print 'shortName = %s' % (shortName)
if (plotProd == 'EDR'):
dataNames = self.dataName[shortName]
factorsNames = self.dataFactors[shortName]
plotDescrs = plotDescr[shortName]
prodNames = ['SkinSST','ReferenceSST','BulkSST']
elif (plotProd == 'Skin'):
dataNames = [self.dataName[shortName][0]]
factorsNames = [self.dataFactors[shortName][0]]
plotDescrs = [plotDescr[shortName][0]]
prodNames = ['SkinSST']
elif (plotProd == 'Reference'):
dataNames = [self.dataName[shortName][1]]
factorsNames = [self.dataFactors[shortName][1]]
plotDescrs = [plotDescr[shortName][1]]
prodNames = ['ReferenceSST']
elif (plotProd == 'Bulk'):
dataNames = [self.dataName[shortName][2]]
factorsNames = [self.dataFactors[shortName][2]]
plotDescrs = [plotDescr[shortName][2]]
prodNames = ['BulkSST']
granID_list = hdf5_dict[shortName].keys()
granID_list.sort()
for dataName,factorsName,plotDescr,prodName in zip(dataNames,factorsNames,plotDescrs,prodNames):
# Read in the data from the granules and concatenate
for granID in granID_list :
print '%s --> %s ' % (shortName, granID)
hdf5Obj = hdf5_dict[shortName][granID][1]
VIIRS_SST_EDR_Gran_0 = hdf5Obj.getNode('/Data_Products/VIIRS-SST-EDR/VIIRS-SST-EDR_Gran_0')
dayNightFlag = getattr(VIIRS_SST_EDR_Gran_0.attrs,'N_Day_Night_Flag')[0][0]
orbitNumber = getattr(VIIRS_SST_EDR_Gran_0.attrs,'N_Beginning_Orbit_Number')[0][0]
print 'N_Day_Night_Flag = %s' % (dayNightFlag)
print 'N_Beginning_Orbit_Number = %s' % (orbitNumber)
orient = -1 if dayNightFlag == 'Day' else 1
dataGranule = hdf5Obj.getNode(dataName)[:,:]
factors = hdf5Obj.getNode(factorsName)[:]
dataGranule = dataGranule*factors[0] + factors[1]
SSTqualFlagGranule = hdf5Obj.getNode('/All_Data/VIIRS-SST-EDR_All/QF1_VIIRSSSTEDR')
SSTqualFlagGranule = np.bitwise_and(SSTqualFlagGranule,3) >> 0
SSTqualFlagMaskGranule = ma.masked_equal(SSTqualFlagGranule,0).mask
# Concatenate the granules.
try :
data = np.vstack((data,dataGranule))
SSTqualFlagMask = np.vstack((SSTqualFlagMask,SSTqualFlagMaskGranule))
print "data shape = {}".format(data.shape)
print "SSTqualFlagMask shape = {}\n".format(SSTqualFlagMask.shape)
except :
data = dataGranule[:,:]
SSTqualFlagMask = SSTqualFlagMaskGranule[:,:]
print "data shape = {}".format(data.shape)
print "SSTqualFlagMask shape = {}\n".format(SSTqualFlagMask.shape)
print "Final data shape = {}".format(data.shape)
print "Final SSTqualFlagMask shape = {}\n".format(SSTqualFlagMask.shape)
# What value are the bowtie deletion pixels
onboardPixelTrimValue = trimObj.sdrTypeFill['ONBOARD_PT_FILL'][data.dtype.name]
LOG.info("Onboard Pixel Trim value is {}".format(onboardPixelTrimValue))
ongroundPixelTrimValue = trimObj.sdrTypeFill['ONGROUND_PT_FILL'][data.dtype.name]
LOG.info("Onground Pixel Trim value is {}".format(ongroundPixelTrimValue))
# Create onboard and onground pixel trim mask arrays, for the total number of
# scans in the pass...
numGranules = len(granID_list)
numScans = numGranules * 48
onboardTrimMask = trimObj.createOnboardModTrimArray(nscans=numScans,trimType=bool)
ongroundTrimMask = trimObj.createOngroundModTrimArray(nscans=numScans,trimType=bool)
# Apply the On-board pixel trim
data = ma.array(data,mask=onboardTrimMask,fill_value=onboardPixelTrimValue)
data = data.filled() # Substitute for the masked values with ongroundPixelTrimValue
# Apply the On-ground pixel trim
data = ma.array(data,mask=ongroundTrimMask,fill_value=ongroundPixelTrimValue)
data = data.filled() # Substitute for the masked values with ongroundPixelTrimValue
plotTitle = '%s : orbit %s %s' % (shortName,orbitNumber,annotation)
cbTitle = plotDescr
# Create figure with default size, and create canvas to draw on
passRows = float(data.shape[0])
passCols = float(data.shape[1])
aspect = passRows/passCols
scale = 5.
fig = Figure(figsize=(scale*1.,scale*aspect))
canvas = FigureCanvas(fig)
# Create main axes instance, leaving room for colorbar at bottom,
# and also get the Bbox of the axes instance
ax_rect = [0.05, 0.18, 0.9, 0.75 ] # [left,bottom,width,height]
ax = fig.add_axes(ax_rect,axis_bgcolor='lightgray')
# Granule axis title
ax_title = ppl.setp(ax,title=plotTitle)
ppl.setp(ax_title,fontsize=12)
ppl.setp(ax_title,family="sans-serif")
# Remove the ticks and ticklabels on the main axis
ppl.setp(ax.get_xticklabels(), visible=False)
ppl.setp(ax.get_yticklabels(), visible=False)
ppl.setp(ax.get_xticklines(),visible=False)
ppl.setp(ax.get_yticklines(),visible=False)
# Plot the data
print "%s is of kind %r" % (shortName,data.dtype.kind)
if (data.dtype.kind =='i' or data.dtype.kind =='u'):
fill_mask = ma.masked_greater(data,200).mask
else:
fill_mask = ma.masked_less(data,-800.).mask
# Construct the total mask
totalMask = SSTqualFlagMask + fill_mask
# Mask the aerosol so we only have the retrievals
data = ma.masked_array(data,mask=totalMask)
# Flip the pass depending on whether this is an ascending or decending pass
data = data[::orient,::orient]
im = ax.imshow(data,interpolation='nearest',
vmin=vmin,vmax=vmax,cmap=cmap)
# add a colorbar axis
cax_rect = [0.05 , 0.05, 0.9 , 0.08 ] # [left,bottom,width,height]
cax = fig.add_axes(cax_rect,frameon=False) # setup colorbar axes
# Plot the colorbar.
cb = fig.colorbar(im, cax=cax, orientation='horizontal')
ppl.setp(cax.get_xticklabels(),fontsize=9)
ppl.setp(cax.get_xticklines(),visible=True)
# Colourbar title
cax_title = ppl.setp(cax,title=cbTitle)
ppl.setp(cax_title,fontsize=10)
# Turn off the tickmarks on the colourbar
#ppl.setp(cb.ax.get_xticklines(),visible=False)
#ppl.setp(cb.ax.get_xticklabels(),fontsize=9)
# Redraw the figure
canvas.draw()
# Save the figure to a png file...
pngFile = path.join(pngDir,'%s%s_b%s_%s.png' % (pngPrefix,shortName,orbitNumber,prodName))
canvas.print_figure(pngFile,dpi=dpi)
print "Writing to %s..." % (pngFile)
ppl.close('all')
del(data)
del(SSTqualFlagMask)
def plot_SST_tests(self,plotProd='QF',pngDir=None,pngPrefix=None,annotation='',dpi=300):
if pngDir is None :
pngDir = path.abspath(path.curdir)
hdf5_dict = self.hdf5_dict
collShortNames = hdf5_dict.keys()
if (plotProd == 'QF'):
byteList = [0,1,2,3]
else :
byteList = [int(plotProd.strip('QF'))]
print 'collShortNames = %r' % (collShortNames)
CMD = viirs_edr_data.SeaSurfaceTempProdData
for shortName in collShortNames :
print 'shortName = %s' % (shortName)
granID_list = hdf5_dict[shortName].keys()
granID_list.sort()
for granID in granID_list :
print '%s --> %s ' % (shortName, granID)
hdf5Obj = hdf5_dict[shortName][granID][1]
VIIRS_SST_EDR_Gran_0 = hdf5Obj.getNode('/Data_Products/VIIRS-SST-EDR/VIIRS-SST-EDR_Gran_0')
dayNightFlag = getattr(VIIRS_SST_EDR_Gran_0.attrs,'N_Day_Night_Flag')[0][0]
print 'N_Day_Night_Flag = %s' % (dayNightFlag)
orient = -1 if dayNightFlag == 'Day' else 1
for byte in byteList :
print ""
plots = list(CMD.ViirsSSTqualBitMaskNames[byte])
for item in plots:
if item == 'Spare':
plots.remove(item)
numPlots = len(plots)
numRows = np.ceil(float(numPlots)/2.)
figWidth = 15. # inches
figHeight = 3. * numPlots/2. # inches
fig = Figure(figsize=((figWidth,figHeight)))
canvas = FigureCanvas(fig)
Ax = []
Im = []
Txt = []
Cb = []
plotIdx = 1
for dSet in range(np.shape(CMD.ViirsSSTqualBitMasks[byte])[0]):
print '\ndSet = %d' %(dSet)
dSetName = '/All_Data/VIIRS-SST-EDR_All/QF%s_VIIRSSSTEDR'%(str(byte+1))
byteData = hdf5Obj.getNode(dSetName)[:,:]
plotTitle = '%s : %s %s (Byte %d)' % (shortName,granID,annotation,byte)
fig.text(0.5, 0.95, plotTitle, fontsize=16, color='black', ha='center', va='bottom', alpha=1.0)
if (CMD.ViirsSSTqualBitMaskNames[byte][dSet] == 'Spare') :
print "Skipping dataset with byte = %d, dSet = %d" % (byte, dSet)
else :
print "byte = %d, dSet = %d" % (byte, dSet)
byteMask = CMD.ViirsSSTqualBitMasks[byte][dSet]
byteShift = CMD.ViirsSSTqualBitShift[byte][dSet]
print "byteMask = %d, byteShift = %d, dSetName = %s" % (byteMask, byteShift, dSetName)
data = np.bitwise_and(byteData,byteMask) >> byteShift
vmin,vmax = CMD.ViirsSSTqualvalues[byte][dSet][0], CMD.ViirsSSTqualvalues[byte][dSet][-1]
print "vmin = %d, vmax = %d" % (vmin, vmax)
cmap = ListedColormap(CMD.ViirsSSTqualFillColours[byte][dSet])
numCats = np.array(CMD.ViirsSSTqualFillColours[byte][dSet]).size
numBounds = numCats + 1
tickPos = np.arange(float(numBounds))/float(numCats)
tickPos = tickPos[0 :-1] + tickPos[1]/2.
print "numCats = ",numCats
print "tickPos = ",tickPos
titleStr = CMD.ViirsSSTqualBitMaskNames[byte][dSet]
print "titleStr = %s" % (titleStr)
Ax.append(fig.add_subplot(numRows,2,plotIdx))
print "data.dtype.__str__() = %s" % (data.dtype.__str__())
Im.append(Ax[dSet].imshow(data.astype('int')[::orient,::orient], vmin=vmin, vmax=vmax, interpolation='nearest',cmap=cmap))
Txt.append(Ax[dSet].set_title(titleStr))
ppl.setp(Txt[dSet],fontsize=10)
ppl.setp(Ax[dSet].get_xticklines(), visible=False)
ppl.setp(Ax[dSet].get_yticklines(), visible=False)
ppl.setp(Ax[dSet].get_xticklabels(), visible=False)
ppl.setp(Ax[dSet].get_yticklabels(), visible=False)
Cb.append(fig.colorbar(Im[dSet], orientation='horizonal', pad=0.05))
print "Cb byte = %d, dSet = %d" % (byte, dSet)
print "CMD.ViirsSSTqualTickNames[%d][%d] = %s" % \
(byte,dSet,CMD.ViirsSSTqualTickNames[byte][dSet])
print "CMD.ViirsSSTqualFillColours[%d][%d] = %s" % \
(byte,dSet,CMD.ViirsSSTqualFillColours[byte][dSet])
Cb[dSet].set_ticks(vmax*tickPos)
ppl.setp(Cb[dSet].ax,xticklabels=CMD.ViirsSSTqualTickNames[byte][dSet])
ppl.setp(Cb[dSet].ax.get_xticklabels(),fontsize=6)
ppl.setp(Cb[dSet].ax.get_xticklines(),visible=False)
plotIdx += 1
pngFile = path.join(pngDir,'%s%s_%s_QF%s.png' % (pngPrefix,shortName,granID,str(byte+1)))
print "Writing to %s..." % (pngFile)
canvas.draw()
canvas.print_figure(pngFile,dpi=dpi)
ppl.close('all')
hdf5Obj.close()
def plot_SST_pass_tests(self,plotProd='QF',pngDir=None,pngPrefix=None,annotation='',dpi=300):
if pngDir is None :
pngDir = path.abspath(path.curdir)
hdf5_dict = self.hdf5_dict
collShortNames = hdf5_dict.keys()
if (plotProd == 'QF'):
byteList = [0,1,2,3]
else :
byteList = [int(plotProd.strip('QF'))-1]
print 'collShortNames = %r' % (collShortNames)
CMD = viirs_edr_data.SeaSurfaceTempProdData
for shortName in collShortNames :
print 'shortName = %s' % (shortName)
dataName = self.dataName[shortName]
granID_list = hdf5_dict[shortName].keys()
granID_list.sort()
for byte in byteList :
print ""
plots = list(CMD.ViirsSSTqualBitMaskNames[byte])
for item in plots:
if item == 'Spare':
plots.remove(item)
print "plots = ",plots
if (plots == []):
print "There are no valid datasets in this byte array, skipping..."
else :
for dSet in range(np.shape(CMD.ViirsSSTqualBitMasks[byte])[0]):
print '\ndSet = %d' %(dSet)
for granID in granID_list :
print '%s --> %s ' % (shortName, granID)
hdf5Obj = hdf5_dict[shortName][granID][1]
VIIRS_SST_EDR_Gran_0 = hdf5Obj.getNode('/Data_Products/VIIRS-SST-EDR/VIIRS-SST-EDR_Gran_0')
dayNightFlag = getattr(VIIRS_SST_EDR_Gran_0.attrs,'N_Day_Night_Flag')[0][0]
orbitNumber = getattr(VIIRS_SST_EDR_Gran_0.attrs,'N_Beginning_Orbit_Number')[0][0]
print 'N_Day_Night_Flag = %s' % (dayNightFlag)
print 'N_Beginning_Orbit_Number = %s' % (orbitNumber)
orient = -1 if dayNightFlag == 'Day' else 1
dSetName = '/All_Data/VIIRS-SST-EDR_All/QF%s_VIIRSSSTEDR'%(str(byte+1))
byteDataGranule = hdf5Obj.getNode(dSetName)[:,:]
# Concatenate the granules.
try :
byteData = np.vstack((byteData,byteDataGranule))
print "byteData shape = %s\n" %(str(byteData.shape))
except :
byteData = byteDataGranule[:,:]
print "byteData shape = %s\n" %(str(byteData.shape))
# What value are the bowtie deletion pixels
ongroundPixelTrimValue = trimObj.sdrTypeFill['ONGROUND_PT_FILL'][byteData.dtype.name]
print "Onground Pixel Trim value is {}".format(ongroundPixelTrimValue)
onboardPixelTrimValue = trimObj.sdrTypeFill['ONBOARD_PT_FILL'][byteData.dtype.name]
print "Onboard Pixel Trim value is {}\n".format(onboardPixelTrimValue)
# Create onboard and onground pixel trim mask arrays, for the total number of
# scans in the pass...
numGranules = len(granID_list)
numScans = numGranules * 48
onboardTrimMask = trimObj.createOnboardModTrimArray(nscans=numScans,trimType=bool)
ongroundTrimMask = trimObj.createModTrimArray(nscans=numScans,trimType=bool)
# Apply the On-board pixel trim
byteData = ma.array(byteData,mask=onboardTrimMask,fill_value=ongroundPixelTrimValue)
#byteData = byteData.filled() # Substitute for the masked values with ongroundPixelTrimValue
# Apply the On-board pixel trim
byteData = ma.array(byteData,mask=ongroundTrimMask,fill_value=onboardPixelTrimValue)
#byteData = byteData.filled() # Substitute for the masked values with onboardPixelTrimValue
# Flip the pass depending on whether this is an ascending or decending pass
byteData = byteData[::orient,::orient]
if (CMD.ViirsSSTqualBitMaskNames[byte][dSet] == 'Spare') :
print "Skipping dataset with byte = %d, dSet = %d" % (byte, dSet)
else :
print "byte = %d, dSet = %d" % (byte, dSet)
byteMask = CMD.ViirsSSTqualBitMasks[byte][dSet]
byteShift = CMD.ViirsSSTqualBitShift[byte][dSet]
print "byteMask = %d, byteShift = %d, dSetName = %s" % (byteMask, byteShift, dSetName)
data = np.bitwise_and(byteData,byteMask) >> byteShift
vmin,vmax = CMD.ViirsSSTqualvalues[byte][dSet][0], CMD.ViirsSSTqualvalues[byte][dSet][-1]
print "vmin = %d, vmax = %d" % (vmin, vmax)
cmap = ListedColormap(CMD.ViirsSSTqualFillColours[byte][dSet])
numCats = np.array(CMD.ViirsSSTqualFillColours[byte][dSet]).size
numBounds = numCats + 1
tickPos = np.arange(float(numBounds))/float(numCats)
tickPos = tickPos[0 :-1] + tickPos[1]/2.
print "numCats = ",numCats
print "tickPos = ",tickPos
# Set the plot and colourbar titles...
plotTitle = '%s : orbit %s %s (Byte %d)' % (shortName,orbitNumber,annotation,byte)
cbTitle = CMD.ViirsSSTqualBitMaskNames[byte][dSet]
# Create figure with default size, and create canvas to draw on
passRows = float(data.shape[0])
passCols = float(data.shape[1])
aspect = passRows/passCols
scale = 5.
fig = Figure(figsize=(scale*1.,scale*aspect))
canvas = FigureCanvas(fig)
# Create main axes instance, leaving room for colorbar at bottom,
# and also get the Bbox of the axes instance
ax_rect = [0.05, 0.18, 0.9, 0.75 ] # [left,bottom,width,height]
ax = fig.add_axes(ax_rect,axis_bgcolor='lightgray')
# Granule axis title
ax_title = ppl.setp(ax,title=plotTitle)
ppl.setp(ax_title,fontsize=12)
ppl.setp(ax_title,family="sans-serif")
# Remove the ticks and ticklabels on the main axis
ppl.setp(ax.get_xticklabels(), visible=False)
ppl.setp(ax.get_yticklabels(), visible=False)
ppl.setp(ax.get_xticklines(),visible=False)
ppl.setp(ax.get_yticklines(),visible=False)
# Mask the data
if (data.dtype.kind =='i' or data.dtype.kind =='u'):
print "%s is of kind %r" % (shortName,data.dtype.kind)
data = ma.masked_greater(data,247)
else:
print "%s is of kind %r" % (shortName,data.dtype.kind)
data = ma.masked_less(data,-800.)
# Plot the dataset on the main plotting axis
im = ax.imshow(data,interpolation='nearest',vmin=vmin,vmax=vmax,cmap=cmap)
# add a colorbar axis
cax_rect = [0.05 , 0.05, 0.9 , 0.08 ] # [left,bottom,width,height]
cax = fig.add_axes(cax_rect,frameon=False) # setup colorbar axes
# Plot the colorbar.
cb = fig.colorbar(im, cax=cax, orientation='horizontal')
ppl.setp(cax.get_xticklabels(),fontsize=9)
ppl.setp(cax.get_xticklines(),visible=False)
# Set the colourbar tick locations and ticklabels
#ppl.setp(cb.ax,xticks=CMD.ViirsCMTickPos) # In colorbar axis coords (0..1)
cb.set_ticks(vmax*tickPos) # In data coords (0..3)
ppl.setp(cb.ax,xticklabels=CMD.ViirsSSTqualTickNames[byte][dSet])
# Colourbar title
cax_title = ppl.setp(cax,title=cbTitle)
ppl.setp(cax_title,fontsize=10)
# Turn off the tickmarks on the colourbar
ppl.setp(cb.ax.get_xticklines(),visible=False)
ppl.setp(cb.ax.get_xticklabels(),fontsize=7)
# Redraw the figure
canvas.draw()
# Save the figure to a png file...
pngFile = path.join(pngDir,'%s%s_b%s_QF%s_%d.png' % (pngPrefix,shortName,orbitNumber,str(byte+1),dSet))
canvas.print_figure(pngFile,dpi=dpi)
print "Writing to %s..." % (pngFile)
ppl.close('all')
del(byteData)
###################################################
# Main Function #
###################################################
def main():
prodChoices=['EDR','QF','Skin','Reference','Bulk','QF1','QF2','QF3','QF4']
description = \
'''
This is a brief description of %prog
'''
usage = "usage: %prog [mandatory args] [options]"
version = version="%prog"
parser = optparse.OptionParser(description=description,usage=usage,version=version)
# Mandatory arguments
mandatoryGroup = optparse.OptionGroup(parser, "Mandatory Arguments",
"At a minimum these arguments must be specified")
mandatoryGroup.add_option('-i','--input_files',
action="store",
dest="hdf5Files" ,
type="string",
help="The fully qualified path to the input VSSTO HDF5 files. May be a directory or a file glob.")
parser.add_option_group(mandatoryGroup)
# Optional arguments
optionalGroup = optparse.OptionGroup(parser, "Extra Options",
"These options may be used to customize plot characteristics.")
optionalGroup.add_option('-r','--svn_revision',
action="store",
dest="svnRevision",
default=string.split(__version__," ")[2],
type="string",
help="The Subversion revision number/tag of this script")
optionalGroup.add_option('--pass',
action="store_true",
dest="plotPass",
help="Concatenate the granules")
optionalGroup.add_option('--plotMin',
action="store",
type="float",
dest="plotMin",
help="Minimum value to plot.")
optionalGroup.add_option('--plotMax',
action="store",
type="float",
dest="plotMax",
help="Maximum value to plot.")
optionalGroup.add_option('-d','--dpi',
action="store",
dest="dpi",
default='200.',
type="float",
help="The resolution in dots per inch of the output png file. [default: %default]")
optionalGroup.add_option('-a','--map_annotation',
action="store",
dest="mapAnn",
#default='',
type="string",
help="The map legend describing the dataset being shown. [default: IPPROD]")
optionalGroup.add_option('-p','--product',
action="store",
dest="plotProduct",
type="choice",
choices=prodChoices,
help='''The VIIRS SST EDR or QF datasets to plot.\n\n
Possible values are...
%s
''' % (prodChoices.__str__()[1:-1]))
optionalGroup.add_option('--png_dir',
action="store",
dest="pngDir" ,
type="string",
help="The directory where png files will be written.")
optionalGroup.add_option('-o','--output_file_prefix',
action="store",
dest="outputFilePrefix",
default="",
type="string",
help="""String to prefix to the automatically generated
png names, which are of the form
<N_Collection_Short_Name>_<N_Granule_ID>_<dset>.png.
[default: %default]""")
optionalGroup.add_option('-v', '--verbose',
dest='verbosity',
action="count",
default=2,
help="""each occurrence increases verbosity 1 level from
ERROR: -v=WARNING -vv=INFO -vvv=DEBUG""")
parser.add_option_group(optionalGroup)
# Parse the arguments from the command line
(options, args) = parser.parse_args()
# Set up the logging
console_logFormat = '%(asctime)s : (%(levelname)s):%(filename)s:%(funcName)s:%(lineno)d: %(message)s'
dateFormat = '%Y-%m-%d %H:%M:%S'
levels = [logging.ERROR, logging.WARN, logging.INFO, logging.DEBUG]
logging.basicConfig(level = levels[options.verbosity],
format = console_logFormat,
datefmt = dateFormat)
# Check that all of the mandatory options are given. If one or more
# are missing, print error message and exit...
mandatories = ['hdf5Files']
mand_errors = ["Missing mandatory argument [-i HDF5FILES | --input_files=HDF5FILES]"
]
isMissingMand = False
for m,m_err in zip(mandatories,mand_errors):
if not options.__dict__[m]:
isMissingMand = True
print m_err
if isMissingMand :
parser.error("Incomplete mandatory arguments, aborting...")
vmin = options.plotMin
vmax = options.plotMax
hdf5Path = path.abspath(path.expanduser(options.hdf5Files))
print "hdf5Path = %s" % (hdf5Path)
pngDir = '.' if (options.pngDir is None) else options.pngDir
pngDir = path.abspath(path.expanduser(pngDir))
print "pngDir = %s" % (pngDir)
if not path.isdir(pngDir):
print "Output image directory %s does not exist, creating..." % (pngDir)
try:
mkdir(pngDir,0755)
except Exception, err :
print "%s" % (err)
print "Creating directory %s failed, aborting..." % (pngDir)
sys.exit(1)
pngPrefix = options.outputFilePrefix
dpi = options.dpi
plotProduct = options.plotProduct
plotPass = options.plotPass
plotEDR = False
plotQF = False
if (plotProduct is None):
plotEDR = True
plotQF = True
edrPlotProduct = 'EDR'
qfPlotProduct = 'QF'
else :
if ('EDR' in plotProduct) \
or ('Skin' in plotProduct) \
or ('Reference' in plotProduct) \
or ('Bulk' in plotProduct) :
plotEDR = True
edrPlotProduct = plotProduct
if ('QF' in plotProduct) :
plotQF = True
qfPlotProduct = plotProduct
if plotEDR :
try :
SSTobj = SSTclass(hdf5Path)
if plotPass :
SSTobj.plot_SST_pass(plotProd=edrPlotProduct,vmin=vmin,vmax=vmax,pngDir=pngDir,pngPrefix=pngPrefix,dpi=dpi)
else:
SSTobj.plot_SST_granules(plotProd=edrPlotProduct,vmin=vmin,vmax=vmax,pngDir=pngDir,pngPrefix=pngPrefix,dpi=dpi)
pytables.file.close_open_files()
except Exception, err:
traceback.print_exc(file=sys.stdout)
pytables.file.close_open_files()
if plotQF :
try :
SSTobj = SSTclass(hdf5Path)
if plotPass :