plt.close (fig)
#do seeing x all correlations
for index, days in enumerate ([days0, days1]):
bigMatrix = makeBigMatrix (correlations)
for p in ambient.parameterBasenames [1:]:
otherDays = ambient.Days (os.path.join (args.indir, p + ".orig"), args.start_date, args.stop_date, allSeeingDays)
#for each day in the seeing correlations tuple, compute the pc seeing vs a non-seeing sensor
for row, day in enumerate (days):
otherDay = otherDays.getDay (day)
pc = (0,(0,0,0))
if otherDay:
f0, f1 = [d.periodFilter (args.start_minutes * 60, args.stop_minutes * 60, args.past_midnight) for d in (day, otherDay)]
m0, m1 = day.matchMeasurements (otherDay, f0, f1)
pc = (ambient.pearsonFromMeasurements (m0, m1, args.min_points), (len (day.measurements), len (otherDay.measurements), len (m0)))
bigMatrix [row].append (pc)
#strip out nonsense correlations
strippedMatrix = [t for t in bigMatrix if t[-1][0] <= 1.0]
scatterPC ([t [0] for t in strippedMatrix],
[t [-1][0] for t in strippedMatrix],
os.path.join (args.outdir, "{}x{}.{}.png".format (p, ambient.parameterBasenames [0], index)),
"{} vs {} ({})".format (ambient.parameterBasenames [0], p, index),
"rank",
"pearson's correlation coefficient",
Axis.y)
utils.dumpList(os.path.join (args.outdir, "{}xAll.{}.corr".format(ambient.parameterBasenames[0], index)), bigMatrix,
lambda out, r: out.write("{} {:%m/%d/%y} {:%m/%d/%y} {:.5f} {:.5f} ({:d},{:d},{:d}) {:.5f} ({:d},{:d},{:d}) {:.5f} ({:d},{:d},{:d}) {:.5f} ({:d},{:d},{:d}) {:.5f} ({:d},{:d},{:d}) {:.5f} ({:d},{:d},{:d}) {:.5f} ({:d},{:d},{:d})\n".format
def plotSites (basename, correlations):
assert (args.best_plots <= args.best_count)
#load in days for every non seeing sensor for both sites in "sites"
#sites [i][j] is sensor j Days for site i
#set the goodness of each day to intersect the goodness for the
#corresponding day in seeing
sites = []
for i in range (2):
sites.append ([])
for p in ambient.parameterBasenames [1:]:
sites [-1].append (ambient.Days (os.path.join (args.indirs [i].path, p + ".orig"), args.start_date, args.stop_date))
sites [-1][-1].setGoodness (allSeeing [i])
row = 0
for correlation in correlations:
if row >= args.best_plots: break
if correlation [2] >= 1.0: continue
pdfPages = PdfPages (os.path.join (args.outdir, "{}.{}.pdf".format (basename, row)))
numPlotted = 0
fig = None
def checkPage (last=False):
nonlocal pdfPages
nonlocal numPlotted
nonlocal fig
numPlotted += 1
if numPlotted >= 4 or last:
numPlotted = 0
fig.subplots_adjust (wspace=0.5, hspace=0.3)
pdfPages.savefig (fig)
plt.close (fig)
if not last:
fig = plt.figure ()
else:
fig = None
fig = plt.figure ()
if correlation [1]:
# Upper Left: Seeing for both sites
ax = fig.add_subplot (2, 2, numPlotted + 1)
ax.set_xlabel ("Time")
setSeeingY (ax)
ax.set_title ("{:%m/%d/%y},{:%m/%d/%y} pc={:0.3f}".format (correlation [0].datetime, correlation [1].datetime, correlation [2]))
plotDay (correlation [0], ax, 'red', 'none', 'none', 'o')
plotDay (correlation [1], ax, 'blue', 'none', 'none', 'v')
checkPage ()
assert (len (ambient.parameterBasenames) == len (ambient.parameterLimits))
for i in range (1, len (ambient.parameterBasenames)):
p = ambient.parameterBasenames [i]
limits = ambient.parameterLimits [i]
otherDays0 = sites [0][i -1]
otherDays1 = sites [1][i -1]
otherDay0 = otherDays0.getDay (correlation [0])
otherDay1 = otherDays1.getDay (correlation [0])
ax = fig.add_subplot (2, 2, numPlotted + 1)
ax.set_ylabel ("{}".format (p))
ax.set_ylim (*limits)
ax.set_xlabel ("Time")
if otherDay0 and otherDay1:
f0, f1 = [d.goodPeriodFilter () for d in (otherDay0, otherDay1)]
m0, m1 = otherDay0.matchMeasurements (otherDay1, f0, f1)
pc = ambient.pearsonFromMeasurements (m0, m1, args.min_points)
if (pc <= 1):
ax.set_title ("pc={:0.3f}".format (pc))
plotDay (otherDay0, ax, 'red', 'none', 'none', 'o')
plotDay (otherDay1, ax, 'blue', 'none', 'none', 'v')
checkPage (i == len (ambient.parameterBasenames) - 1)
pdfPages.close ()
row += 1
