def calculateHanziData(self, graphwindow, days):
log.info("Calculating %d days worth of Hanzi graph data", days)
# NB: must lazy-load matplotlib to give Anki a chance to set up the paths
# to the data files, or we get an error like "Could not find the matplotlib
# data files" as documented at <http://www.py2exe.org/index.cgi/MatPlotLib>
try:
from matplotlib.figure import Figure
except UnicodeEncodeError:
# Haven't tracked down the cause of this yet, but reloading fixes it
log.warn("UnicodeEncodeError loading matplotlib - trying again")
from matplotlib.figure import Figure
# Use the statistics engine to generate the data for graphing.
# NB: should add one to the number of days because we want to
# return e.g. 8 days of data for a 7 day plot (the extra day is "today").
xs, _totaly, gradeys = pinyin.statistics.hanziDailyStats(
self.hanziData(), days + 1)
# Set up the figure into which we will add all our graphs
figure = Figure(figsize=(graphwindow.dg.width, graphwindow.dg.height),
dpi=graphwindow.dg.dpi)
self.addLegend(figure)
self.addGraph(figure, graphwindow, days, xs, gradeys)
return figure
def chooseField(candidateFieldNames, targetkeys):
# Find the first field that is present in the fact
for candidateField in candidateFieldNames:
for factfieldname in [factfieldname for factfieldname in targetkeys if factfieldname.lower() == candidateField.lower()]:
return factfieldname
# No suitable field found!
log.warn("No field matching %s in the fact", candidateFieldNames)
return None
def chooseField(candidateFieldNames, targetkeys):
# Find the first field that is present in the fact
for candidateField in candidateFieldNames:
for factfieldname in [factfieldname for factfieldname in targetkeys if factfieldname.lower() == candidateField.lower()]:
return factfieldname
# No suitable field found!
log.warn("No field matching %s in the fact", candidateFieldNames)
return None
def chooseField(candidateFieldNames, fact):
# Find the first field that is present in the fact
for candidateField in candidateFieldNames:
for factfieldname in [factfieldname for factfieldname in fact.keys() if factfieldname.lower() == candidateField.lower()]:
log.info("Choose %s as a field name from the fact for %s", factfieldname, candidateField)
return factfieldname
# No suitable field found!
log.warn("No field matching %s in the fact", candidateFieldNames)
return None
def chooseField(candidateFieldNames, fact):
# Find the first field that is present in the fact
for candidateField in candidateFieldNames:
for factfieldname in [
factfieldname for factfieldname in fact.keys()
if factfieldname.lower() == candidateField.lower()
]:
log.info("Choose %s as a field name from the fact for %s",
factfieldname, candidateField)
return factfieldname
# No suitable field found!
log.warn("No field matching %s in the fact", candidateFieldNames)
return None
def calculateHanziData(self, graphwindow, days):
log.info("Calculating %d days worth of Hanzi graph data", days)
# NB: must lazy-load matplotlib to give Anki a chance to set up the paths
# to the data files, or we get an error like "Could not find the matplotlib
# data files" as documented at <http://www.py2exe.org/index.cgi/MatPlotLib>
try:
from matplotlib.figure import Figure
except UnicodeEncodeError:
# Haven't tracked down the cause of this yet, but reloading fixes it
log.warn("UnicodeEncodeError loading matplotlib - trying again")
from matplotlib.figure import Figure
# Use the statistics engine to generate the data for graphing.
# NB: should add one to the number of days because we want to
# return e.g. 8 days of data for a 7 day plot (the extra day is "today").
xs, _totaly, gradeys = pinyin.statistics.hanziDailyStats(self.hanziData(), days + 1)
# Set up the figure into which we will add all our graphs
figure = Figure(figsize=(graphwindow.dg.width, graphwindow.dg.height), dpi=graphwindow.dg.dpi)
self.addLegend(figure)
self.addGraph(figure, graphwindow, days, xs, gradeys)
return figure
