def run(self):
"""
This initialise process called when QGIS started
"""
# create and show the dialog
self.dlg = PlotStatisticsDialog()
# show the dialog
self.dlg.show()
QObject.connect(self.dlg, SIGNAL("okClicked(QString, QString)"), self.readData)
class PlotStatistics:
def __init__(self, iface):
# Save reference to the QGIS interface
self.iface = iface
def initGui(self):
self.canvas = self.iface.mapCanvas()
self.mainWindow = self.iface.mainWindow()
# Create action that will start plugin configuration
self.action = QAction(QIcon(":/plugins/plotstatistics/icon.png"), \
"plot statistics", self.mainWindow)
# connect the action to the run method
QObject.connect(self.action, SIGNAL("triggered()"), self.run)
# Add toolbar button and menu item
self.iface.addToolBarIcon(self.action)
self.iface.addPluginToMenu("&plot statistics", self.action)
def unload(self):
# Remove the plugin menu item and icon
self.iface.removePluginMenu("&plot statistics",self.action)
self.iface.removeToolBarIcon(self.action)
# run method that performs all the real work
def run(self):
"""
This initialise process called when QGIS started
"""
# create and show the dialog
self.dlg = PlotStatisticsDialog()
# show the dialog
self.dlg.show()
QObject.connect(self.dlg, SIGNAL("okClicked(QString, QString)"), self.readData)
def readData(self, layerName, outFile):
"""
selected layer and output file name are passed in from dialog box, from the layer
its attribute values are extracted to plot diagrams.
Note this function currently extract data from Vector layer only.
"""
dateTimeList = []
magList = []
depList = []
vlayer = utils.getVectorLayerByName( layerName )
vprovider = vlayer.dataProvider()
feat = QgsFeature()
allAttrs = vprovider.attributeIndexes()
vprovider.select( allAttrs )
# field description
myFields = vprovider.fields()
while vprovider.nextFeature(feat):
atmap = feat.attributeMap()
for key, value in atmap.iteritems():
if key == 6:
dateTime = "%-22s" % atmap[key].toString()
dateTimeList.append(dateTime)
elif key == 3:
#mag = "%-22s" % atmap[key].toString()
mag = "%-22s" % atmap[key].toString()
magList.append(mag)
elif key == 4:
dep = "%-22s" % atmap[key].toString()
depList.append(dep)
else:
pass
self.plotTimes(dateTimeList,magList, depList, outFile)
def plotTimes(self, dateTimeList,magList, depList, outFile):
"""
This function plots following diagrams calculating Bin/histogram values
- date vs Frequency
- time vs Frequency
- magnitude vs Frequency
- depth vs Frequency
"""
outputfile = str(outFile) + "_date_freq.png"
timeoutputfile = str(outFile) + "_time_freq.png"
magoutputfile = str(outFile) + "_mag_freq.png"
depoutputfile = str(outFile) + "_dep_freq.png"
yearList = []
timeList = []
magOutList = []
depOutList = []
for mag in magList:
mag_en = float(mag)
magOutList.append(mag_en)
for dep in depList:
dep_en = float(dep)
depOutList.append(dep_en)
for dateTime in dateTimeList:
year = dateTime[:4]
time = dateTime[11:13]
year_e = int(year)
time_e = int(time)
yearList.append(year_e)
timeList.append(time_e)
# Frequency vs Year plot
startYear = min(yearList)
endYear = max(yearList)
step = 1 #bin width
bins = np.arange(startYear, endYear, step)
hist, edges = np.histogram(yearList, bins)
plt.figure()
plt.bar(bins[:-1]+0.5,hist, width=1, color='k')
#plt.bar(bins[:-1]+0.02,hist, width=0.8, color='k')
plt.axis([startYear, endYear, 0, 100])
plt.ylabel('Number of Eruptions per Year')
plt.xlabel('Year')
plt.savefig(outputfile)
# Frequency vs Time plot
startTime = min(timeList)
endTime = max(timeList)
step = 1 #bin width
bins = np.arange(startTime, endTime, step)
hist, edges = np.histogram(timeList, bins)
plt.figure()
plt.bar(bins[:-1]+0.5,hist, width=1, color='k')
plt.axis([startTime, endTime, 0, 100])
plt.ylabel('Number of Eruptions per Time')
plt.xlabel('Time')
plt.savefig(timeoutputfile)
# Frequency vs Mag plot
startMag = min(magOutList)
endMag = max(magOutList)
step = 1 #bin width
bins = np.arange(startMag, endMag, step)
hist, edges = np.histogram(magOutList, bins)
plt.figure()
plt.bar(bins[:-1]+0.5,hist, width=0.8, color='k')
plt.axis([startMag, endMag, 0, 50])
plt.ylabel('Number of Eruptions ')
plt.xlabel('Mag')
plt.savefig(magoutputfile)
# Frequency vs Dep plot
startDep = min(depOutList)
endDep = max(depOutList)
step = 1 #bin width
bins = np.arange(startDep, endDep, step)
hist, edges = np.histogram(depOutList, bins)
plt.figure()
plt.bar(bins[:-1]+0.5,hist, width=0.8, color='k')
#plt.bar(bins[:-1]+0.02,hist, width=0.8, color='k')
plt.axis([startDep, endDep, 0, 50])
plt.ylabel('Number of Eruptions')
plt.xlabel('Depth')
plt.savefig(depoutputfile)
