def makeSummary(year, month, day, julianDay, selectedObjects, imageLinks):
headerStuff = [
E.H2("Matsu Analytic Summary Report for {}-{}-{} (Julian day {})".format(year, month, day, julianDay)),
E.TABLE(E.TR(E.TD(E.B("Analysis date:")), E.TD(time.ctime(time.time()))), style="margin-left: 20px;"),
E.H3("Analytic Environment", style="margin-bottom: 5px;"),
E.TABLE(E.TR(E.TD(E.B("Analytic")), E.TD("GMM-KNN")),
E.TR(E.TD(E.B("Noise Correction Enabled")), E.TD("False")),
E.TR(E.TD(E.B("Report Format")), E.TD("GMM-KNN v1")), style="margin-left: 20px;"),
E.H3("Summary", style="margin-bottom: 5px;"),
E.TABLE(E.TR(E.TD(E.B("Number of images:")), E.TD(" " + repr(len(imageLinks)))),
E.TR(E.TD(E.B("Image reports:"), style="min-width: 130px;", valign="top"), E.TD(*[E.SPAN(" ", imageLinks[x]) for x in sorted(imageLinks.keys())])), style="margin-left: 20px;"),
]
if len(selectedObjects) > 0:
selectedObjects.sort(lambda a, b: cmp(a["score"][1], b["score"][1]))
for rank, cluster in enumerate(selectedObjects):
cluster["knnrank"] = rank + 1
selectedObjects.sort(lambda a, b: cmp(a["score"][0], b["score"][0]))
for rank, cluster in enumerate(selectedObjects):
cluster["gmmrank"] = rank + 1
anomalousObjects = E.TABLE(E.TR(E.TD(E.B("Rank (GMM)"), align="center", style="min-width: 100px;"), E.TD(E.B("Rank (KNN)"), align="center", style="min-width: 100px;"), E.TD(E.B("Image"), style="min-width: 230px;"), E.TD(E.B("Object id"), style="min-width: 80px;"), E.TD(E.B("Raw GMM score"), align="center", style="min-width: 120px;"), E.TD(E.B("Raw KNN score"), align="center", style="min-width: 120px;"), E.TD(E.B("Clump size (pixels)"), align="center", style="min-width: 150px;")), style="margin-left: 20px;")
for cluster in selectedObjects:
shortName = cluster["imageName"]
imageLink = E.A(shortName, href=("image_reports/" + shortName + ".html"))
anomalousObjects.append(E.TR(E.TD(repr(cluster["gmmrank"]), align="center", style="min-width: 100px;"), E.TD(repr(cluster["knnrank"]), align="center", style="min-width: 100px;"), E.TD(imageLink, style="min-width: 230px;"), E.TD(cluster["id"], style="min-width: 80px;"), E.TD("{:g}".format(cluster["score"][0]), align="center", style="min-width: 120px;"), E.TD("{:g}".format(math.log10(cluster["score"][1])), align="center", style="min-width: 120px;"), E.TD(repr(cluster["other"]["numPixels"]), align="center", style="min-width: 150px;")))
scoresDistributionGMM = histogram("x", numBins=50, style="fill: darkviolet;", normalized=True, xlabel="Raw GMM score (low is anomalous)", ylabel="normalized histogram", width=1200, height=400).calc({"x": numpy.array([x["score"][0] for x in selectedObjects])})
scoresDistributionGMM["width"] = "600"
scoresDistributionGMM["height"] = "200"
scoresDistributionGMM["style"] = scoresDistributionGMM["style"] + "; margin-left: 20px;"
scoresDistributionKNN = histogram("x", numBins=50, style="fill: darkviolet;", normalized=True, xlabel="Raw KNN score (low is anomalous)", ylabel="normalized histogram", width=1200, height=400).calc({"x": numpy.array([math.log10(x["score"][1]) for x in selectedObjects])})
scoresDistributionKNN["width"] = "600"
scoresDistributionKNN["height"] = "200"
scoresDistributionKNN["style"] = scoresDistributionKNN["style"] + "; margin-left: 20px;"
html = E.HTML(
E.HEAD(),
E.BODY(
*(headerStuff + [
E.H3("Most anomalous objects", style="margin-bottom: 5px;"),
scoresDistributionGMM,
scoresDistributionKNN,
anomalousObjects,
E.P(E.I("See the individual reports for hyperspectral details."))
])))
else:
html = E.HTML(E.HEAD(), E.BODY(*(headerStuff + [E.H3("No anomalous objects today", style="margin-bottom: 5px;")])))
print " /var/www/reports/{}-{}/gmm-knn/summary-report-{}-{}-{}.html".format(year, month, year, month, day); sys.stdout.flush()
open("/var/www/reports/{}-{}/gmm-knn/summary-report-{}-{}-{}.html".format(year, month, year, month, day), "w").write("<!DOCTYPE html>" + htmlToString(html))
E.TABLE(E.TR(E.TD(E.B("Image size:")), E.TD("{}x{} ({} pixels)".format(imageValue["metadata"]["width"], imageValue["metadata"]["height"], imageValue["metadata"]["width"]*imageValue["metadata"]["height"]))),
E.TR(E.TD(E.B("Default RGB:")), E.TD("Bands 5, 4, 3")),
E.TR(E.TD(E.B("Number of bands:")), E.TD(repr(len(wavelengths)))),
E.TR(E.TD(E.B("File type:")), E.TD("GeoTIFF")),
E.TR(E.TD(E.B("Units:")), E.TD("spectral radiance")),
E.TR(E.TD(E.B("Sensor:")), E.TD("ALI")), style="margin-left: 20px;"),
E.H3("Notes", style="margin-bottom: 5px;"),
E.DIV(E.P("Objects are described in terms of four concentric sets of pixels:", style="margin-bottom: 0px;"), E.UL(E.LI(E.B("seeds:"), " extremely anomalous pixels that started the search"), E.LI(E.B("clump:"), " bucket-fill clump of contiguous semi-anomalous pixels"), E.LI(E.B("first border:"), " pixels adjacent to but not included in the clump"), E.LI(E.B("second border:"), " pixels adjacent to the first border"), style="margin-top: 0px;"),
E.P("Selected objects are outlined in the image (at the second border).", style="margin-bottom: 0px;"), style="font-size: 11pt; margin-left: 20px;"))
html = E.HTML(
E.HEAD(),
E.BODY(
E.TABLE(E.TR(E.TD(E.I("(Click image to enlarge.)"), align="center")),
E.TR(E.TD(E.A(E.IMG(src=(shortName + ".svg"), width="400"), href=(shortName + ".svg")), align="center")), style="float: right;"),
imageSummary,
E.H3("Object details", style="margin-bottom: 5px; clear: right;"),
E.P("No objects passed cuts.", style="margin-left: 20px;") if len(tableRows) == 0 else E.TABLE(*tableRows, width="100%", style="margin-left: 20px;")
))
if makingReport:
print " writing /var/www/reports/{}-{}/gmm-knn/image_reports/{}.html".format(year, month, shortName); sys.stdout.flush()
open("/var/www/reports/{}-{}/gmm-knn/image_reports/{}.html".format(year, month, shortName), "w").write("<!DOCTYPE html>" + htmlToString(html))
if lastJulianDay is not None:
year = time.strftime("%Y", time.strptime(lastJulianDay, "%Y %j"))
month = time.strftime("%m", time.strptime(lastJulianDay, "%Y %j"))
day = time.strftime("%d", time.strptime(lastJulianDay, "%Y %j"))
makeSummary(year, month, day, lastJulianDay, selectedObjects, imageLinks)
