diff --git a/pyglance/glance/compare.py b/pyglance/glance/compare.py
index 9f534a17133cd92b977d67f7367fa9beb6e96b92..5fbcb307608e3d8f94918475981667ccf53005fe 100644
--- a/pyglance/glance/compare.py
+++ b/pyglance/glance/compare.py
@@ -477,7 +477,7 @@ def _check_lon_lat_equality(longitudeADataObject, latitudeADataObject,
latitudeDiffInfo = dataobj.DiffInfoObject(latitudeADataObject, latitudeBDataObject, epsilonValue=llepsilon)
# how much difference is there between the two sets?
- lon_lat_not_equal_mask = longitudeDiffInfo.diff_data_object.masks.trouble_mask | latitudeDiffInfo.diff_data_object.masks.trouble_mask
+ lon_lat_not_equal_mask = longitudeDiffInfo.diff_data_object.masks.mismatch_mask | latitudeDiffInfo.diff_data_object.masks.mismatch_mask
lon_lat_not_equal_points_count = sum(lon_lat_not_equal_mask)
lon_lat_not_equal_points_percent = (float(lon_lat_not_equal_points_count) / float(lon_lat_not_equal_mask.size)) * 100.0
@@ -491,23 +491,23 @@ def _check_lon_lat_equality(longitudeADataObject, latitudeADataObject,
if ((len(longitudeADataObject.data[~longitudeADataObject.masks.ignore_mask]) > 0) and
(len( latitudeADataObject.data[~ latitudeADataObject.masks.ignore_mask]) > 0)) :
- plot.plot_and_save_spacial_trouble(longitudeADataObject, latitudeADataObject,
+ plot.plot_and_save_spacial_mismatch(longitudeADataObject, latitudeADataObject,
lon_lat_not_equal_mask,
"A", "Lon./Lat. Points Mismatched between A and B\n" +
"(Shown in A)",
"LonLatMismatch",
outputPath, True,
- fullDPI=fullDPI, thumbDPI=thumbDPI)
+ fullDPI=fullDPI, thumbDPI=thumbDPI, units="degrees")
if ((len(longitudeBDataObject.data[~longitudeBDataObject.masks.ignore_mask]) > 0) and
(len( latitudeBDataObject.data[~ latitudeBDataObject.masks.ignore_mask]) > 0)) :
- plot.plot_and_save_spacial_trouble(longitudeBDataObject, latitudeBDataObject,
+ plot.plot_and_save_spacial_mismatch(longitudeBDataObject, latitudeBDataObject,
lon_lat_not_equal_mask,
"B", "Lon./Lat. Points Mismatched between A and B\n" +
"(Shown in B)",
"LonLatMismatch",
outputPath, True,
- fullDPI=fullDPI, thumbDPI=thumbDPI)
+ fullDPI=fullDPI, thumbDPI=thumbDPI, units="degrees")
# setup our return data
returnInfo = {}
@@ -560,22 +560,22 @@ def _compare_spatial_invalidity(longitude_a_object, longitude_b_object,
if ((spatial_info['file A']['numInvPts'] > 0) and (do_include_images) and
(len(longitude_a_object.data[~invalid_in_a_mask]) > 0) and
(len( latitude_a_object.data[~invalid_in_a_mask]) > 0)) :
- plot.plot_and_save_spacial_trouble(longitude_a_object, latitude_a_object,
+ plot.plot_and_save_spacial_mismatch(longitude_a_object, latitude_a_object,
valid_only_in_mask_a,
"A", "Points only valid in\nFile A\'s longitude & latitude",
"SpatialMismatch",
output_path, True,
- fullDPI=fullDPI, thumbDPI=thumbDPI)
+ fullDPI=fullDPI, thumbDPI=thumbDPI, units="degrees")
if ((spatial_info['file B']['numInvPts'] > 0) and (do_include_images) and
(len(longitude_b_object.data[~invalid_in_b_mask]) > 0) and
(len( latitude_b_object.data[~invalid_in_b_mask]) > 0)
) :
- plot.plot_and_save_spacial_trouble(longitude_b_object, latitude_b_object,
+ plot.plot_and_save_spacial_mismatch(longitude_b_object, latitude_b_object,
valid_only_in_mask_b,
"B", "Points only valid in\nFile B\'s longitude & latitude",
"SpatialMismatch",
output_path, True,
- fullDPI=fullDPI, thumbDPI=thumbDPI)
+ fullDPI=fullDPI, thumbDPI=thumbDPI, units="degrees")
return invalid_in_common_mask, spatial_info, longitude_common, latitude_common
@@ -1471,7 +1471,9 @@ def reportGen_library_call (a_path, b_path, var_list=[ ],
tupleName= varRunInfo['tupleName'] if 'tupleName' in varRunInfo else 'tuple',
epsilonPercent=varRunInfo['epsilon_percent'] if 'epsilon_percent' in varRunInfo else None,
fullDPI= runInfo['detail_DPI'],
- thumbDPI= runInfo['thumb_DPI'])
+ thumbDPI= runInfo['thumb_DPI'],
+ units_a= varRunInfo['units_a'] if 'units_a' in varRunInfo else None,
+ units_b= varRunInfo['units_b'] if 'units_b' in varRunInfo else None)
print("\tfinished creating figures for: " + explanationName)
diff --git a/pyglance/glance/data.py b/pyglance/glance/data.py
index 74015cbf27231756b9a9ab1cde96f392016a19ce..4f9f0adca19830088378e280b0e89f851ae95837 100644
--- a/pyglance/glance/data.py
+++ b/pyglance/glance/data.py
@@ -61,15 +61,15 @@ class DiffMaskSetObject (BasicMaskSetObject) :
masks are used to capture information about where data should be
ignored/valid/non-finite in the compared data.
- Additionally, masks describing trouble points and points outside
+ Additionally, masks describing mismatch points and points outside
of the epsilon analysis tolerances are included.
- trouble_mask - a mask of data points which may indicate issues in the data
+ mismatch_mask - a mask of data points which may indicate issues in the data
outside_epsilon_mask - a mask of points which did not pass the epsilon
tolerance testing
"""
- def __init__(self, ignoreMask, validInBothMask, troubleMask, epsilonMask) :
+ def __init__(self, ignoreMask, validInBothMask, mismatchMask, epsilonMask) :
"""
create a more complex mask, including additional difference information
"""
@@ -77,7 +77,7 @@ class DiffMaskSetObject (BasicMaskSetObject) :
self.ignore_mask = ignoreMask
self.valid_mask = validInBothMask
- self.trouble_mask = troubleMask
+ self.mismatch_mask = mismatchMask
self.outside_epsilon_mask = epsilonMask
class DataObject (object) :
@@ -265,15 +265,15 @@ class DiffInfoObject (object) :
if (epsilonPercent is not None) :
outside_epsilon_mask |= (abs(raw_diff) > abs(aDataObject.data * (float(epsilonPercent) / 100.0))) & valid_in_both
- # trouble points = mismatched nans, mismatched missing-values, differences that are too large
- trouble_pt_mask = ( (aDataObject.masks.non_finite_mask ^ bDataObject.masks.non_finite_mask) |
+ # mismatch points = mismatched nans, mismatched missing-values, differences that are too large
+ mismatch_pt_mask = ( (aDataObject.masks.non_finite_mask ^ bDataObject.masks.non_finite_mask) |
(aDataObject.masks.missing_mask ^ bDataObject.masks.missing_mask) |
outside_epsilon_mask )
# make our diff data object
diff_data_object = DataObject(raw_diff, fillValue=fill_data_value)
diff_data_object.masks = DiffMaskSetObject(ignore_in_both, valid_in_both,
- trouble_pt_mask, outside_epsilon_mask)
+ mismatch_pt_mask, outside_epsilon_mask)
return diff_data_object
diff --git a/pyglance/glance/exconfig.py b/pyglance/glance/exconfig.py
index 8aaf2d8b12ac4628b96cac2b584081f4b14ef5b6..22a930383893324d8fe3a67b03ee8407bcfb1ae5 100644
--- a/pyglance/glance/exconfig.py
+++ b/pyglance/glance/exconfig.py
@@ -207,8 +207,8 @@ setOfVariables['Total Precipitable Water, Low'] = {
'do_plot_scatter': True,
# should the histogram be plotted?
'do_plot_histogram': True,
- # should the trouble plot be plotted?
- 'do_plot_trouble': True
+ # should the mismatch plot be plotted?
+ 'do_plot_mismatch': True
}
setOfVariables['Total Precipitable Water, Mid'] = {
'variable_name': 'imager_prof_retr_abi_total_precipitable_water_mid',
diff --git a/pyglance/glance/figures.py b/pyglance/glance/figures.py
index 715eecefa9ce451c2c20ce93bbeb011ddc1e028f..93f6eefdab4b2f5a95b23b36d1045a365e57a18f 100644
--- a/pyglance/glance/figures.py
+++ b/pyglance/glance/figures.py
@@ -80,21 +80,21 @@ def _plot_tag_data_simple(tagData) :
-1 if no valid tagData was given.
"""
- numTroublePoints = -1
+ numMismatchPoints = -1
# if there are "tag" masks, plot them over the existing map
if not (tagData is None) :
- numTroublePoints = sum(tagData)
+ numMismatchPoints = sum(tagData)
- # if we have trouble points, we need to show them
- if numTroublePoints > 0:
+ # if we have mismatch points, we need to show them
+ if numMismatchPoints > 0:
# figure out how many bad points there are
totalNumPoints = tagData.size # the number of points
- percentBad = (float(numTroublePoints) / float(totalNumPoints)) * 100.0
- LOG.debug('\t\tnumber of trouble points: ' + str(numTroublePoints))
- LOG.debug('\t\tpercent of trouble points: ' + str(percentBad))
+ percentBad = (float(numMismatchPoints) / float(totalNumPoints)) * 100.0
+ LOG.debug('\t\tnumber of mismatch points: ' + str(numMismatchPoints))
+ LOG.debug('\t\tpercent of mismatch points: ' + str(percentBad))
new_kwargs = {}
new_kwargs['cmap'] = greenColorMap
@@ -102,14 +102,14 @@ def _plot_tag_data_simple(tagData) :
p = contourf(cleanTagData, **new_kwargs)
# TODO, need to incorporate plot for small numbers of pts
- # display the number of trouble points on the report if we were passed a set of tag data
- troublePtString = '\n\nShowing ' + str(numTroublePoints) + ' Trouble Points'
+ # display the number of mismatch points on the report if we were passed a set of tag data
+ mismatchPtString = '\n\nShowing ' + str(numMismatchPoints) + ' Mismatch Points'
# if our plot is more complex, add clarification
- if numTroublePoints > 0 :
- troublePtString = troublePtString + ' in Green'
- plt.xlabel(troublePtString)
+ if numMismatchPoints > 0 :
+ mismatchPtString = mismatchPtString + ' in Green'
+ plt.xlabel(mismatchPtString)
- return numTroublePoints
+ return numMismatchPoints
def _plot_tag_data_mapped(bMap, tagData, x, y, addExplinationLabel=True) :
"""
@@ -122,19 +122,19 @@ def _plot_tag_data_mapped(bMap, tagData, x, y, addExplinationLabel=True) :
The return will be the number of points plotted or
-1 if no valid tagData was given.
- numTroublePoints = _plot_tag_data_mapped(bMap, tagData, x, y)
+ numMismatchPoints = _plot_tag_data_mapped(bMap, tagData, x, y)
"""
- numTroublePoints = -1
+ numMismatchPoints = -1
# if there are "tag" masks, plot them over the existing map
if (tagData is not None) and (tagData.size > 0) :
- # look at how many trouble points we have
- numTroublePoints = sum(tagData)
+ # look at how many mismatch points we have
+ numMismatchPoints = sum(tagData)
neededHighlighting = False
- if numTroublePoints > 0 :
+ if numMismatchPoints > 0 :
# pick out the cooridinates of the points we want to plot
newX = np.array(x[tagData])
@@ -142,9 +142,9 @@ def _plot_tag_data_mapped(bMap, tagData, x, y, addExplinationLabel=True) :
# figure out how many bad points there are
totalNumPoints = x.size # the number of points
- percentBad = (float(numTroublePoints) / float(totalNumPoints)) * 100.0
- LOG.debug('\t\tnumber of trouble points: ' + str(numTroublePoints))
- LOG.debug('\t\tpercent of trouble points: ' + str(percentBad))
+ percentBad = (float(numMismatchPoints) / float(totalNumPoints)) * 100.0
+ LOG.debug('\t\tnumber of mismatch points: ' + str(numMismatchPoints))
+ LOG.debug('\t\tpercent of mismatch points: ' + str(percentBad))
# if there are very few points, make them easier to notice
# by plotting some colored circles underneath them
@@ -155,8 +155,8 @@ def _plot_tag_data_mapped(bMap, tagData, x, y, addExplinationLabel=True) :
neededHighlighting = True
p = bMap.plot(newX, newY, 'o', color='#993399', markersize=3)
- # if there are way too many trouble points, we can't use plot for this
- if (numTroublePoints > 1000000) :
+ # if there are way too many mismatch points, we can't use plot for this
+ if (numMismatchPoints > 1000000) :
new_kwargs = {}
new_kwargs['cmap'] = greenColorMap
p = maps.show_x_y_data(x, y, bMap, data=tagData, **new_kwargs)
@@ -165,21 +165,21 @@ def _plot_tag_data_mapped(bMap, tagData, x, y, addExplinationLabel=True) :
p = bMap.plot(newX, newY, '.', color='#00FF00', markersize=1)
if addExplinationLabel :
- # display the number of trouble points on the report if we were passed a set of tag data
+ # display the number of mismatch points on the report if we were passed a set of tag data
# I'm not thrilled with this solution for getting it below the labels drawn by the basemap
# but I don't think there's a better one at the moment given matplotlib's workings
- troublePtString = '\n\nShowing ' + str(numTroublePoints) + ' Trouble Points'
+ mismatchPtString = '\n\nShowing ' + str(numMismatchPoints) + ' Mismatch Points'
# if our plot is more complex, add clarification
- if numTroublePoints > 0 :
- troublePtString = troublePtString + ' in Green'
+ if numMismatchPoints > 0 :
+ mismatchPtString = mismatchPtString + ' in Green'
if neededHighlighting :
- troublePtString = troublePtString + '\nwith Purple Circles for Visual Clarity'
- plt.xlabel(troublePtString)
+ mismatchPtString = mismatchPtString + '\nwith Purple Circles for Visual Clarity'
+ plt.xlabel(mismatchPtString)
- return numTroublePoints
+ return numMismatchPoints
# build a scatter plot of the x,y points
-def create_scatter_plot(dataX, dataY, title, xLabel, yLabel, badMask=None, epsilon=None) :
+def create_scatter_plot(dataX, dataY, title, xLabel, yLabel, badMask=None, epsilon=None, units_x=None, units_y=None) :
"""
build a scatter plot of the data
if a bad mask is given the points selected by that mask will be plotted in a different color
@@ -191,9 +191,9 @@ def create_scatter_plot(dataX, dataY, title, xLabel, yLabel, badMask=None, epsil
return create_complex_scatter_plot ([(dataX, dataY, badMask,
'b', 'r',
'within\nepsilon', 'outside\nepsilon')],
- title, xLabel, yLabel, epsilon=epsilon)
+ title, xLabel, yLabel, epsilon=epsilon, units_x=units_x, units_y=units_y)
-def create_complex_scatter_plot(dataList, title, xLabel, yLabel, epsilon=None) :
+def create_complex_scatter_plot(dataList, title, xLabel, yLabel, epsilon=None, units_x=None, units_y=None) :
"""
build a scatter plot with multiple data sets in different colors
the dataList parameter should be in the form:
@@ -231,11 +231,11 @@ def create_complex_scatter_plot(dataList, title, xLabel, yLabel, epsilon=None) :
axes.plot(dataX, dataY, ',', color=goodColor, label=goodLabel)
# plot the bad data
- numTroublePts = 0
+ numMismatchPts = 0
if (badX is not None) and (badY is not None) and (badMask is not None) :
- numTroublePts = badX.size
- LOG.debug('\t\tplotting ' + str(numTroublePts) + ' trouble points in scatter plot.' )
- if numTroublePts > 0 :
+ numMismatchPts = badX.size
+ LOG.debug('\t\tplotting ' + str(numMismatchPts) + ' mismatch points in scatter plot.' )
+ if numMismatchPts > 0 :
axes.plot(badX, badY, ',', color=badColor, label=badLabel)
# draw some extra informational lines
@@ -245,10 +245,18 @@ def create_complex_scatter_plot(dataList, title, xLabel, yLabel, epsilon=None) :
# as long as things have been plotted with proper labels they should show up here
axes.legend(loc=0, markerscale=3.0) # Note: at the moment markerscale doesn't seem to work
+ # add the units to the x and y labels
+ tempXLabel = xLabel
+ tempYLabel = yLabel
+ if str.lower(str(units_x)) != "none" :
+ tempXLabel = tempXLabel + " in " + units_x
+ if str.lower(str(units_y)) != "none" :
+ tempYLabel = tempYLabel + " in " + units_y
+
# and some informational stuff
axes.set_title(title)
- plt.xlabel(xLabel)
- plt.ylabel(yLabel)
+ plt.xlabel(tempXLabel)
+ plt.ylabel(tempYLabel)
# format our axes so they display gracefully
yFormatter = FormatStrFormatter("%4.4g")
@@ -259,12 +267,17 @@ def create_complex_scatter_plot(dataList, title, xLabel, yLabel, epsilon=None) :
return figure
# build a hexbin plot of the x,y points and show the density of the point distribution
-def create_hexbin_plot(dataX, dataY, title, xLabel, yLabel, epsilon=None) :
+def create_hexbin_plot(dataX, dataY, title, xLabel, yLabel, epsilon=None, units_x=None, units_y=None) :
# make the figure
figure = plt.figure()
axes = figure.add_subplot(111)
+ # for some reason, if you give the hexplot a data set that's all the same number it dies horribly
+ if ( ((dataX is None) or (len(dataX) <= 0)) or ((dataY is None) or (len(dataY) <= 0)) or
+ ((dataX.max() == dataX.min()) and (dataY.max() == dataY.min())) ):
+ return figure
+
# the hexbin plot of the good data
plt.hexbin(dataX, dataY, bins='log', cmap=cm.jet)
plt.axis([dataX.min(), dataX.max(), dataY.min(), dataY.max()])
@@ -276,10 +289,18 @@ def create_hexbin_plot(dataX, dataY, title, xLabel, yLabel, epsilon=None) :
# draw some extra informational lines
_draw_x_equals_y_line(axes, color='w', epsilon=epsilon, epsilonColor='k')
+ # add the units to the x and y labels
+ tempXLabel = xLabel
+ tempYLabel = yLabel
+ if str.lower(str(units_x)) != "none" :
+ tempXLabel = tempXLabel + " in " + units_x
+ if str.lower(str(units_y)) != "none" :
+ tempYLabel = tempYLabel + " in " + units_y
+
# and some informational stuff
axes.set_title(title)
- plt.xlabel(xLabel)
- plt.ylabel(yLabel)
+ plt.xlabel(tempXLabel)
+ plt.ylabel(tempYLabel)
# format our axes so they display gracefully
yFormatter = FormatStrFormatter("%4.4g")
@@ -320,7 +341,7 @@ def _draw_x_equals_y_line(axes, color='k', style='--', epsilon=None, epsilonColo
axes.set_ybound(ybounds)
# build a histogram figure of the given data with the given title and number of bins
-def create_histogram(data, bins, title, xLabel, yLabel, displayStats=False) :
+def create_histogram(data, bins, title, xLabel, yLabel, displayStats=False, units=None) :
# make the figure
figure = plt.figure()
@@ -330,7 +351,7 @@ def create_histogram(data, bins, title, xLabel, yLabel, displayStats=False) :
return figure
# the histogram of the data
- n, bins, patches = plt.hist(data, bins)
+ n, outBins, patches = plt.hist(data, bins)
# format our axes so they display gracefully
yFormatter = FormatStrFormatter("%3.3g")
@@ -338,9 +359,14 @@ def create_histogram(data, bins, title, xLabel, yLabel, displayStats=False) :
xFormatter = FormatStrFormatter("%.4g")
axes.xaxis.set_major_formatter(xFormatter)
+ # add the units to the x and y labels
+ tempXLabel = xLabel
+ if str.lower(str(units)) != "none" :
+ tempXLabel = tempXLabel + " in " + units
+
# and some informational stuff
axes.set_title(title)
- plt.xlabel(xLabel)
+ plt.xlabel(tempXLabel)
plt.ylabel(yLabel)
# if stats were passed in, put some of the information on the graph
@@ -356,7 +382,7 @@ def create_histogram(data, bins, title, xLabel, yLabel, displayStats=False) :
# info on the display of our statistics
xbounds = axes.get_xbound()
- numBinsToUse = len(bins)
+ numBinsToUse = bins
xrange = xbounds[1] - xbounds[0]
binSize = xrange / float(numBinsToUse)
@@ -365,8 +391,8 @@ def create_histogram(data, bins, title, xLabel, yLabel, displayStats=False) :
statText = statText + '\n' + 'mean: ' + report.make_formatted_display_string(meanVal)
statText = statText + '\n' + 'median: ' + report.make_formatted_display_string(medianVal)
statText = statText + '\n' + 'std: ' + report.make_formatted_display_string(stdVal)
- statText = statText + '\n\n' + 'bins: ' + report.make_formatted_display_string(numBinsToUse)
- statText = statText + '\n' + 'bin size ' + report.make_formatted_display_string(binSize)
+ statText = statText + '\n\n' + 'intervals: ' + report.make_formatted_display_string(numBinsToUse)
+ statText = statText + '\n' + 'interval size ' + report.make_formatted_display_string(binSize)
# figure out where to place the text and put it on the figure
centerOfDisplay = xbounds[0] + (float(xrange) / 2.0)
@@ -384,7 +410,7 @@ def create_histogram(data, bins, title, xLabel, yLabel, displayStats=False) :
# set on the existing image
def create_mapped_figure(data, latitude, longitude, baseMapInstance, boundingAxes, title,
invalidMask=None, colorMap=None, tagData=None,
- dataRanges=None, dataRangeNames=None, dataRangeColors=None, **kwargs) :
+ dataRanges=None, dataRangeNames=None, dataRangeColors=None, units=None, **kwargs) :
# make a clean version of our lon/lat
latitudeClean = ma.array(latitude, mask=~invalidMask)
@@ -422,7 +448,7 @@ def create_mapped_figure(data, latitude, longitude, baseMapInstance, boundingAxe
axes.set_title(title)
# show a generic color bar
doLabelRanges = False
- if not (data is None) :
+ if data is not None :
cbar = colorbar(format='%.3g')
# if there are specific requested labels, add them
if not (dataRangeNames is None) :
@@ -434,12 +460,16 @@ def create_mapped_figure(data, latitude, longitude, baseMapInstance, boundingAxe
else : # we will want to label the ranges themselves
cbar.ax.set_yticklabels(dataRangeNames) # todo, this line is temporary
doLabelRanges = True
+ else :
+ # add the units to the colorbar
+ if str.lower(str(units)) != "none" :
+ cbar.set_label(units)
- numTroublePoints = _plot_tag_data_mapped(bMap, tagData, x, y)
+ numMismatchPoints = _plot_tag_data_mapped(bMap, tagData, x, y)
- print ('number of trouble points: ' + str(numTroublePoints))
+ LOG.debug ('number of mismatch points: ' + str(numMismatchPoints))
- # if we still need to label the ranges, do it now that our fake axis won't mess the trouble points up
+ # if we still need to label the ranges, do it now that our fake axis won't mess the mismatch points up
if doLabelRanges :
""" TODO get this working properly
fakeAx = plt.axes ([0.77, 0.05, 0.2, 0.9], frameon=False)
@@ -457,8 +487,9 @@ def create_mapped_figure(data, latitude, longitude, baseMapInstance, boundingAxe
# if any masks are passed in the tagData list they will be plotted as an overlays
# set on the existing image
# TODO, this method has not been throughly tested
+# TODO, this method needs an input colormap so the mismatch plot can be the right color
def create_quiver_mapped_figure(data, latitude, longitude, baseMapInstance, boundingAxes, title,
- invalidMask=None, tagData=None, uData=None, vData=None, **kwargs) :
+ invalidMask=None, tagData=None, uData=None, vData=None, units=None, **kwargs) :
# make a clean version of our lon/lat/data
latitudeClean = latitude[~invalidMask]
@@ -486,14 +517,23 @@ def create_quiver_mapped_figure(data, latitude, longitude, baseMapInstance, boun
# show the title
axes.set_title(title)
- numTroublePoints = _plot_tag_data_mapped(bMap, tagDataClean, x, y)
+ # make a color bar if we have color data
+ """ todo, currently this crashes glance because of an error in matplot lib
+ if colorData is not None :
+ cbar = plt.colorbar(format='%.3g')
+ # add the units to the colorbar
+ if str.lower(str(units)) != "none" :
+ cbar.set_label(units)
+ """
+
+ numMismatchPoints = _plot_tag_data_mapped(bMap, tagDataClean, x, y)
return figure
-def create_simple_figure(data, figureTitle, invalidMask=None, tagData=None, colorMap=None, colorbarLimits=None) :
+def create_simple_figure(data, figureTitle, invalidMask=None, tagData=None, colorMap=None, colorbarLimits=None, units=None) :
"""
create a simple figure showing the data given masked by the invalid mask
- any tagData passed in will be interpreted as trouble points on the image and plotted as a
+ any tagData passed in will be interpreted as mismatch points on the image and plotted as a
filled contour overlay in green on the image
if a colorMap is given it will be used to plot the data,
if not the default colorMap for imshow will be used
@@ -521,11 +561,14 @@ def create_simple_figure(data, figureTitle, invalidMask=None, tagData=None, colo
clim(vmin=colorbarLimits[0], vmax=colorbarLimits[-1])
# make a color bar
cbar = colorbar(format='%.3g')
+ # add the units to the colorbar
+ if str.lower(str(units)) != "none" :
+ cbar.set_label(units)
# and some informational stuff
axes.set_title(figureTitle)
- numTroublePoints = _plot_tag_data_simple(tagData)
+ numMismatchPoints = _plot_tag_data_simple(tagData)
return figure
@@ -535,7 +578,7 @@ def create_line_plot_figure(dataList, figureTitle) :
if tagData is given, under-label those points with green circles
Each entry in the dataList should be a tupple containing:
- (data, invalidMask, colorString, labelName, tagData)
+ (data, invalidMask, colorString, labelName, tagData, units)
The color string describes a color for plotting in matplotlib.
The label names will be used for the legend, which will be shown if there is
@@ -544,6 +587,8 @@ def create_line_plot_figure(dataList, figureTitle) :
will be masked and a default label of "data#" (where # is an arbitrary
unique counter) will be used.
tagData may also be passed as None if tagging is not desired in the output.
+ units describes the units used to measure the data (such as mm or degrees)
+ and will be used to label the plot. units may be passed as None.
"""
# build the plot
@@ -555,7 +600,7 @@ def create_line_plot_figure(dataList, figureTitle) :
minTagPts = -1
maxTagPts = -1
plottedTagData = False
- for dataSet, invalidMask, colorString, labelName, tagData in dataList :
+ for dataSet, invalidMask, colorString, labelName, tagData, units in dataList :
# if we don't have these, set them to defaults
if invalidMask is None :
@@ -579,34 +624,37 @@ def create_line_plot_figure(dataList, figureTitle) :
if tagData is not None :
plottedTagData = True
- numTroublePoints = sum(tagData)
- LOG.debug('\t\tnumber of trouble points: ' + str(numTroublePoints))
- if numTroublePoints < minTagPts:
- minTagPts = numTroublePoints
- if numTroublePoints > maxTagPts :
- maxTagPts = numTroublePoints
+ numMismatchPoints = sum(tagData)
+ LOG.debug('\t\tnumber of mismatch points: ' + str(numMismatchPoints))
+ if numMismatchPoints < minTagPts:
+ minTagPts = numMismatchPoints
+ if numMismatchPoints > maxTagPts :
+ maxTagPts = numMismatchPoints
- # if we have trouble points, we need to show them
- if numTroublePoints > 0:
+ # if we have mismatch points, we need to show them
+ if numMismatchPoints > 0:
cleanTagData = ma.array(dataSet, mask=~tagData | invalidMask)
- axes.plot(indexData, cleanTagData, 'yo', label='trouble point')
+ axes.plot(indexData, cleanTagData, 'yo', label='mismatch point')
+
+ if str.lower(str(units)) !="none" :
+ labelName = labelName + " in " + units
axes.plot(indexData, cleanData, '-' + colorString, label=labelName)
- # display the number of trouble points on the report if we were passed
+ # display the number of mismatch points on the report if we were passed
# a set of tag data and we were able to compare it to some actual data
if (plottedTagData and (minTagPts >= 0) and (maxTagPts >=0)) :
- troublePtString = '\nMarking '
+ mismatchPtString = '\nMarking '
if (minTagPts == maxTagPts) :
- troublePtString = troublePtString + str(minTagPts) + ' Trouble Points with Yellow Circles'
+ mismatchPtString = mismatchPtString + str(minTagPts) + ' Mismatch Points with Yellow Circles'
else :
- troublePtString = (troublePtString + 'between ' + str(minTagPts) + ' and ' + str(maxTagPts) + ' Trouble Points'
+ mismatchPtString = (mismatchPtString + 'between ' + str(minTagPts) + ' and ' + str(maxTagPts) + ' Mismatch Points'
+ '\non the various data sets (using Yellow Circles)')
- plt.xlabel(troublePtString)
+ plt.xlabel(mismatchPtString)
if (len(dataList) > 1) or plottedTagData :
# make a key to explain our plot
diff --git a/pyglance/glance/mainreport.txt b/pyglance/glance/mainreport.txt
index 0354923ac1cc5da773d2f724a44fd93688811e66..199505e9415df15e09700be0f0dc7f4c67dc8e69 100644
--- a/pyglance/glance/mainreport.txt
+++ b/pyglance/glance/mainreport.txt
@@ -9,7 +9,7 @@ Copyright (c) 2009 University of Wisconsin SSEC. All rights reserved.
import glance.report as report
%>
-<title>Spacial File Comparison</title>
+<title>File Comparison</title>
</head>
<body>
diff --git a/pyglance/glance/plot.py b/pyglance/glance/plot.py
index 8248a2764c9b722cf6bf48ea02aa6c21ae39c259..42a02b7b636b61f33fc7a76241bbe7b67f13d8a3 100644
--- a/pyglance/glance/plot.py
+++ b/pyglance/glance/plot.py
@@ -106,11 +106,11 @@ def _log_spawn_and_wait_if_needed (imageDescription, childPids,
return
-def plot_and_save_spacial_trouble(longitudeObject, latitudeObject, spacialTroubleMask,
+def plot_and_save_spacial_mismatch(longitudeObject, latitudeObject, spacialMismatchMask,
fileNameDiscriminator, title, fileBaseName, outputPath, makeSmall=False,
- fullDPI=fullSizeDPI, thumbDPI=thumbSizeDPI) :
+ fullDPI=fullSizeDPI, thumbDPI=thumbSizeDPI, units=None) :
"""
- given information on spatially placed trouble points in A and B, plot only those points in a very obvious way
+ given information on spatially placed mismatch points in A and B, plot only those points in a very obvious way
on top of a background plot of a's data shown in grayscale, save this plot to the output path given
if makeSmall is passed as true a smaller version of the image will also be saved
"""
@@ -118,27 +118,28 @@ def plot_and_save_spacial_trouble(longitudeObject, latitudeObject, spacialTroubl
# get the bounding axis and make a basemap
boundingAxes = plotfns.get_visible_axes(longitudeObject.data, latitudeObject.data, ~spaciallyInvalidMask)
- LOG.debug("Visible axes for lon/lat trouble figure are: " + str(boundingAxes))
+ LOG.debug("Visible axes for lon/lat mismatch figure are: " + str(boundingAxes))
baseMapInstance, boundingAxes = maps.create_basemap(longitudeObject.data, latitudeObject.data,
boundingAxes, plotfns.select_projection(boundingAxes))
# make the figure
- LOG.info("Creating spatial trouble image")
- spatialTroubleFig = figures.create_mapped_figure(None, latitudeObject.data, longitudeObject.data, baseMapInstance, boundingAxes,
- title, invalidMask=spaciallyInvalidMask, tagData=spacialTroubleMask)
+ LOG.info("Creating spatial mismatch image")
+ spatialMismatchFig = figures.create_mapped_figure(None, latitudeObject.data, longitudeObject.data, baseMapInstance,
+ boundingAxes, title, invalidMask=spaciallyInvalidMask,
+ tagData=spacialMismatchMask, units=units)
# save the figure
- LOG.info("Saving spatial trouble image")
- spatialTroubleFig.savefig(outputPath + "/" + fileBaseName + "." + fileNameDiscriminator + ".png", dpi=fullDPI)
+ LOG.info("Saving spatial mismatch image")
+ spatialMismatchFig.savefig(outputPath + "/" + fileBaseName + "." + fileNameDiscriminator + ".png", dpi=fullDPI)
# we may also save a smaller versions of the figure
if (makeSmall) :
- spatialTroubleFig.savefig(outputPath + "/" + fileBaseName + "." + fileNameDiscriminator + ".small.png", dpi=thumbDPI)
+ spatialMismatchFig.savefig(outputPath + "/" + fileBaseName + "." + fileNameDiscriminator + ".small.png", dpi=thumbDPI)
# get rid of the figure
- spatialTroubleFig.clf()
- plt.close(spatialTroubleFig)
- del(spatialTroubleFig)
+ spatialMismatchFig.clf()
+ plt.close(spatialMismatchFig)
+ del(spatialMismatchFig)
return
@@ -164,7 +165,8 @@ def plot_and_save_comparison_figures (aData, bData,
binIndex=None, tupleIndex=None,
binName='bin', tupleName='tuple',
epsilonPercent=None,
- fullDPI=None, thumbDPI=None) :
+ fullDPI=None, thumbDPI=None,
+ units_a=None, units_b=None) :
"""
Plot images for a set of figures based on the data sets and settings
passed in. The images will be saved to disk according to the settings.
@@ -239,16 +241,16 @@ def plot_and_save_comparison_figures (aData, bData,
spaciallyInvalidMaskA = lonLatDataDict['a']['inv_mask']
spaciallyInvalidMaskB = lonLatDataDict['b']['inv_mask']
- # compare the two data sets to get our difference data and trouble info
+ # compare the two data sets to get our difference data and mismatch info
aDataObject = dataobj.DataObject(aData, fillValue=missingValue, ignoreMask=spaciallyInvalidMaskA)
bDataObject = dataobj.DataObject(bData, fillValue=missingValueAltInB, ignoreMask=spaciallyInvalidMaskB)
diffInfo = dataobj.DiffInfoObject(aDataObject, bDataObject, epsilonValue=epsilon, epsilonPercent=epsilonPercent)
#TODO, for the moment, unpack these values into local variables
- rawDiffData = diffInfo.diff_data_object.data
- goodMask = diffInfo.diff_data_object.masks.valid_mask
- goodInAMask = diffInfo.a_data_object.masks.valid_mask
- goodInBMask = diffInfo.b_data_object.masks.valid_mask
- troubleMask = diffInfo.diff_data_object.masks.trouble_mask
+ rawDiffData = diffInfo.diff_data_object.data
+ goodMask = diffInfo.diff_data_object.masks.valid_mask
+ goodInAMask = diffInfo.a_data_object.masks.valid_mask
+ goodInBMask = diffInfo.b_data_object.masks.valid_mask
+ mismatchMask = diffInfo.diff_data_object.masks.mismatch_mask
outsideEpsilonMask = diffInfo.diff_data_object.masks.outside_epsilon_mask
aNotFiniteMask = diffInfo.a_data_object.masks.non_finite_mask
bNotFiniteMask = diffInfo.b_data_object.masks.non_finite_mask
@@ -292,7 +294,7 @@ def plot_and_save_comparison_figures (aData, bData,
# point by point
absDiffData=absDiffData, rawDiffData=rawDiffData,
goodInBothMask=goodMask,
- troubleMask=troubleMask, outsideEpsilonMask=outsideEpsilonMask,
+ mismatchMask=mismatchMask, outsideEpsilonMask=outsideEpsilonMask,
# only used for plotting quiver data
aUData=aUData, aVData=aVData,
@@ -301,7 +303,10 @@ def plot_and_save_comparison_figures (aData, bData,
# only used for line plots
binIndex=binIndex, tupleIndex=tupleIndex,
binName=binName, tupleName=tupleName,
- epsilonPercent=epsilonPercent
+ epsilonPercent=epsilonPercent,
+
+ # used for display in several types of plots
+ units_a=units_a, units_b=units_b
)
plottingFunctions.update(moreFunctions)
diff --git a/pyglance/glance/plotcreatefns.py b/pyglance/glance/plotcreatefns.py
index 2d9367e7bcfd5e8175423d1075a1fa2bd6aaf63e..d421a8fbbed8f59dcb4dfea21bfaa47b4a0697d0 100644
--- a/pyglance/glance/plotcreatefns.py
+++ b/pyglance/glance/plotcreatefns.py
@@ -182,7 +182,7 @@ class PlottingFunctionFactory :
# point by point
absDiffData=None, rawDiffData=None,
goodInBothMask=None,
- troubleMask=None, outsideEpsilonMask=None,
+ mismatchMask=None, outsideEpsilonMask=None,
# only used for plotting quiver data
aUData=None, aVData=None,
@@ -193,7 +193,9 @@ class PlottingFunctionFactory :
binName=None, tupleName=None,
# the optional epsilon for comparison of a percent of A
- epsilonPercent=None
+ epsilonPercent=None,
+ # the optional units for display
+ units_a=None, units_b=None
) : _abstract
@@ -226,7 +228,7 @@ class BasicComparisonPlotsFunctionFactory (PlottingFunctionFactory) :
# point by point
absDiffData=None, rawDiffData=None,
goodInBothMask=None,
- troubleMask=None, outsideEpsilonMask=None,
+ mismatchMask=None, outsideEpsilonMask=None,
# only used for plotting quiver data
aUData=None, aVData=None,
@@ -237,7 +239,9 @@ class BasicComparisonPlotsFunctionFactory (PlottingFunctionFactory) :
binName=None, tupleName=None,
# the optional epsilon for comparison of a percent of A
- epsilonPercent=None
+ epsilonPercent=None,
+ # the optional units for display
+ units_a=None, units_b=None
) :
@@ -255,7 +259,7 @@ class BasicComparisonPlotsFunctionFactory (PlottingFunctionFactory) :
("Difference in\n" + variableDisplayName),
('Value of (Data File B - Data File A) at a Data Point'),
('Number of Data Points with a Given Difference'),
- True)),
+ True, units=units_a)),
"histogram of the amount of difference in " + variableDisplayName,
"Hist.png", compared_fig_list)
# make the scatter plot
@@ -270,7 +274,7 @@ class BasicComparisonPlotsFunctionFactory (PlottingFunctionFactory) :
"Value in File A vs Value in File B",
"File A Value", "File B Value",
outsideEpsilonMask[goodInBothMask],
- epsilon)),
+ epsilon, units_x=units_a, units_y=units_b)),
"scatter plot of file a values vs file b values for " + variableDisplayName,
"Scatter.png", compared_fig_list)
@@ -282,7 +286,8 @@ class BasicComparisonPlotsFunctionFactory (PlottingFunctionFactory) :
functionsToReturn['scatterD'] = ((lambda : figures.create_hexbin_plot(aData[goodInBothMask], bData[goodInBothMask],
"Value in File A vs Value in File B",
- "File A Value", "File B Value", epsilon)),
+ "File A Value", "File B Value", epsilon,
+ units_x=units_a, units_y=units_b)),
"density of file a values vs file b values for " + variableDisplayName,
"Hex.png", compared_fig_list)
@@ -316,7 +321,7 @@ class MappedContourPlotFunctionFactory (PlottingFunctionFactory) :
# point by point
absDiffData=None, rawDiffData=None,
goodInBothMask=None,
- troubleMask=None, outsideEpsilonMask=None,
+ mismatchMask=None, outsideEpsilonMask=None,
# only used for plotting quiver data
aUData=None, aVData=None,
@@ -327,7 +332,9 @@ class MappedContourPlotFunctionFactory (PlottingFunctionFactory) :
binName=None, tupleName=None,
# the optional epsilon for comparison of a percent of A
- epsilonPercent=None
+ epsilonPercent=None,
+ # the optional units for display
+ units_a=None, units_b=None
) :
@@ -366,7 +373,8 @@ class MappedContourPlotFunctionFactory (PlottingFunctionFactory) :
invalidMask=(~goodInAMask),
dataRanges=dataRanges or sharedRange,
dataRangeNames=dataRangeNames,
- dataRangeColors=dataColors)),
+ dataRangeColors=dataColors,
+ units=units_a)),
variableDisplayName + " in file a",
"A.png", original_fig_list)
@@ -383,7 +391,8 @@ class MappedContourPlotFunctionFactory (PlottingFunctionFactory) :
invalidMask=(~goodInBMask),
dataRanges=dataRanges or sharedRange,
dataRangeNames=dataRangeNames,
- dataRangeColors=dataColors)),
+ dataRangeColors=dataColors,
+ units=units_b)),
variableDisplayName + " in file b",
"B.png", original_fig_list)
@@ -403,7 +412,8 @@ class MappedContourPlotFunctionFactory (PlottingFunctionFactory) :
baseMapInstance, fullAxis,
("Absolute value of difference in\n"
+ variableDisplayName),
- invalidMask=(~goodInBothMask))),
+ invalidMask=(~goodInBothMask),
+ units=units_a)),
"absolute value of difference in " + variableDisplayName,
"AbsDiff.png", compared_fig_list)
# make the subtractive difference plot
@@ -422,11 +432,12 @@ class MappedContourPlotFunctionFactory (PlottingFunctionFactory) :
baseMapInstance, fullAxis,
("Value of (Data File B - Data File A) for\n"
+ variableDisplayName),
- invalidMask=(~goodInBothMask))),
+ invalidMask=(~goodInBothMask),
+ units=units_a)),
"the difference in " + variableDisplayName,
"Diff.png", compared_fig_list)
- # make the trouble data plot
- if ('do_plot_trouble' not in doPlotSettingsDict) or (doPlotSettingsDict['do_plot_trouble']) :
+ # make the mismatch data plot
+ if ('do_plot_mismatch' not in doPlotSettingsDict) or (doPlotSettingsDict['do_plot_mismatch']) :
assert(aData.shape == bData.shape)
assert(goodInAMask.shape == goodInBMask.shape)
@@ -441,17 +452,18 @@ class MappedContourPlotFunctionFactory (PlottingFunctionFactory) :
bDataCopy = bData[:]
tempMask = goodInAMask & (~goodInBMask)
bDataCopy[tempMask] = aData[tempMask]
- functionsToReturn['trouble'] = ((lambda : mappedPlottingFunction(bDataCopy,
+ functionsToReturn['mismatch'] = ((lambda : mappedPlottingFunction(bDataCopy,
lonLatDataDict['common']['lat'],
lonLatDataDict['common']['lon'],
baseMapInstance, fullAxis,
- ("Areas of trouble data in\n" + variableDisplayName),
+ ("Areas of mismatch data in\n" + variableDisplayName),
invalidMask=(~(goodInAMask | goodInBMask)),
- colorMap=mediumGrayColorMap, tagData=troubleMask,
+ colorMap=mediumGrayColorMap, tagData=mismatchMask,
dataRanges=dataRanges,
- dataRangeNames=dataRangeNames)), # TODO, does this need modification?
- "trouble data in " + variableDisplayName,
- "Trouble.png", compared_fig_list)
+ dataRangeNames=dataRangeNames,
+ units=units_a)), # TODO, does this need modification?
+ "mismatch data in " + variableDisplayName,
+ "Mismatch.png", compared_fig_list)
return functionsToReturn
@@ -488,7 +500,7 @@ class MappedQuiverPlotFunctionFactory (PlottingFunctionFactory) :
# point by point
absDiffData=None, rawDiffData=None,
goodInBothMask=None,
- troubleMask=None, outsideEpsilonMask=None,
+ mismatchMask=None, outsideEpsilonMask=None,
# only used for plotting quiver data
aUData=None, aVData=None,
@@ -499,7 +511,9 @@ class MappedQuiverPlotFunctionFactory (PlottingFunctionFactory) :
binName=None, tupleName=None,
# the optional epsilon for comparison of a percent of A
- epsilonPercent=None
+ epsilonPercent=None,
+ # the optional units for display
+ units_a=None, units_b=None
) :
@@ -537,7 +551,8 @@ class MappedQuiverPlotFunctionFactory (PlottingFunctionFactory) :
baseMapInstance, fullAxis,
(variableDisplayName + "\nin File A"),
invalidMask=(~goodInAMask),
- uData=aUData, vData=aVData)),
+ uData=aUData, vData=aVData,
+ units=units_a)),
variableDisplayName + " in file a",
"A.png", original_fig_list)
@@ -552,7 +567,8 @@ class MappedQuiverPlotFunctionFactory (PlottingFunctionFactory) :
baseMapInstance, fullAxis,
(variableDisplayName + "\nin File B"),
invalidMask=(~ goodInBMask),
- uData=bUData, vData=bVData)),
+ uData=bUData, vData=bVData,
+ units=units_b)),
variableDisplayName + " in file b",
"B.png", original_fig_list)
@@ -582,7 +598,8 @@ class MappedQuiverPlotFunctionFactory (PlottingFunctionFactory) :
("Absolute value of difference in\n"
+ variableDisplayName),
invalidMask=(~ goodInBothMask),
- uData=diffUData, vData=diffVData)),
+ uData=diffUData, vData=diffVData,
+ units=units_a)),
"absolute value of difference in " + variableDisplayName,
"AbsDiff.png", compared_fig_list)
# make the subtractive difference plot
@@ -602,11 +619,12 @@ class MappedQuiverPlotFunctionFactory (PlottingFunctionFactory) :
("Value of (Data File B - Data File A) for\n"
+ variableDisplayName),
invalidMask=(~ goodInBothMask),
- uData=diffUData, vData=diffVData)),
+ uData=diffUData, vData=diffVData,
+ units=units_a)),
"the difference in " + variableDisplayName,
"Diff.png", compared_fig_list)
- # make the trouble data plot
- if ('do_plot_trouble' not in doPlotSettingsDict) or (doPlotSettingsDict['do_plot_trouble']) :
+ # make the mismatch data plot
+ if ('do_plot_mismatch' not in doPlotSettingsDict) or (doPlotSettingsDict['do_plot_mismatch']) :
assert(aData.shape == bData.shape)
assert(goodInAMask.shape == goodInBMask.shape)
@@ -621,19 +639,20 @@ class MappedQuiverPlotFunctionFactory (PlottingFunctionFactory) :
bDataCopy = bData[:]
tempMask = goodInAMask & (~goodInBMask)
bDataCopy[tempMask] = aData[tempMask]
- functionsToReturn['trouble'] = ((lambda : mappedPlottingFunction(bDataCopy,
+ functionsToReturn['mismatch'] = ((lambda : mappedPlottingFunction(bDataCopy,
lonLatDataDict['common']['lat'],
lonLatDataDict['common']['lon'],
baseMapInstance, fullAxis,
- ("Areas of trouble data in\n" + variableDisplayName),
+ ("Areas of mismatch data in\n" + variableDisplayName),
invalidMask=(~(goodInAMask | goodInBMask)),
- colorMap=mediumGrayColorMap, tagData=troubleMask,
+ colorMap=mediumGrayColorMap, tagData=mismatchMask,
dataRanges=dataRanges,
dataRangeNames=dataRangeNames,
# TODO, does this need modification?
- uData=bUData, vData=bVData)),
- "trouble data in " + variableDisplayName,
- "Trouble.png", compared_fig_list)
+ uData=bUData, vData=bVData,
+ units=units_a)),
+ "mismatch data in " + variableDisplayName,
+ "Mismatch.png", compared_fig_list)
return functionsToReturn
@@ -666,7 +685,7 @@ class LinePlotsFunctionFactory (PlottingFunctionFactory) :
# point by point
absDiffData=None, rawDiffData=None,
goodInBothMask=None,
- troubleMask=None, outsideEpsilonMask=None,
+ mismatchMask=None, outsideEpsilonMask=None,
# only used for plotting quiver data
aUData=None, aVData=None,
@@ -677,7 +696,9 @@ class LinePlotsFunctionFactory (PlottingFunctionFactory) :
binName=None, tupleName=None,
# the optional epsilon for comparison of a percent of A
- epsilonPercent=None
+ epsilonPercent=None,
+ # the optional units for display
+ units_a=None, units_b=None
) :
"""
@@ -694,13 +715,13 @@ class LinePlotsFunctionFactory (PlottingFunctionFactory) :
assert(aData.shape == bData.shape)
# make all our data sets for plotting ahead of time for simplicity
- aList = [(aData, ~goodInAMask, 'r', 'A data', None)]
- bList = [(bData, ~goodInBMask, 'b', 'B data', None)]
- absDiffList = [(absDiffData, ~goodInBothMask, '', 'abs. diff. data', None)]
- subDiffList = [(rawDiffData, ~goodInBothMask, '', 'sub. diff. data', None)]
+ aList = [(aData, ~goodInAMask, 'r', 'A data', None, units_a)]
+ bList = [(bData, ~goodInBMask, 'b', 'B data', None, units_b)]
+ absDiffList = [(absDiffData, ~goodInBothMask, '', 'abs. diff. data', None, units_a)] # todo, should this be a units?
+ subDiffList = [(rawDiffData, ~goodInBothMask, '', 'sub. diff. data', None, units_a)] # todo, should this be a units?
- troubleList = [(aData, ~goodInAMask, 'r', 'A data', troubleMask),
- (bData, ~goodInBMask, 'b', 'B data', troubleMask)]
+ mismatchList = [(aData, ~goodInAMask, 'r', 'A data', mismatchMask, units_a),
+ (bData, ~goodInBMask, 'b', 'B data', mismatchMask, units_b)]
functionsToReturn = { }
@@ -730,16 +751,17 @@ class LinePlotsFunctionFactory (PlottingFunctionFactory) :
# make the subtractive difference plot
if ('do_plot_sub_diff' not in doPlotSettingsDict) or (doPlotSettingsDict['do_plot_sub_diff']) :
functionsToReturn['diffSub'] = ((lambda: figures.create_line_plot_figure(subDiffList,
- "Value of (Data File B - Data File A) for\n" + variableDisplayName)),
+ "Value of (Data File B - Data File A) for\n"
+ + variableDisplayName)),
"the difference in " + variableDisplayName,
"Diff.png", compared_fig_list)
- # make the trouble data plot
- if ('do_plot_trouble' not in doPlotSettingsDict) or (doPlotSettingsDict['do_plot_trouble']) :
- functionsToReturn['trouble'] = ((lambda: figures.create_line_plot_figure(troubleList,
- "Areas of trouble data in\n" + variableDisplayName)),
- "trouble data in " + variableDisplayName,
- "Trouble.png", compared_fig_list)
+ # make the mismatch data plot
+ if ('do_plot_mismatch' not in doPlotSettingsDict) or (doPlotSettingsDict['do_plot_mismatch']) :
+ functionsToReturn['mismatch'] = ((lambda: figures.create_line_plot_figure(mismatchList,
+ "Areas of mismatch data in\n" + variableDisplayName)),
+ "mismatch data in " + variableDisplayName,
+ "Mismatch.png", compared_fig_list)
return functionsToReturn
@@ -768,7 +790,7 @@ class BinTupleAnalysisFunctionFactory (PlottingFunctionFactory) :
# point by point
absDiffData=None, rawDiffData=None,
goodInBothMask=None,
- troubleMask=None, outsideEpsilonMask=None,
+ mismatchMask=None, outsideEpsilonMask=None,
# only used for plotting quiver data
aUData=None, aVData=None,
@@ -779,7 +801,9 @@ class BinTupleAnalysisFunctionFactory (PlottingFunctionFactory) :
binName=None, tupleName=None,
# the optional epsilon for comparison of a percent of A
- epsilonPercent=None
+ epsilonPercent=None,
+ # the optional units for display
+ units_a=None, units_b=None
) :
"""
@@ -815,7 +839,7 @@ class BinTupleAnalysisFunctionFactory (PlottingFunctionFactory) :
absDiffData = reorderMapObject.reorder_for_bin_tuple(absDiffData)
rawDiffData = reorderMapObject.reorder_for_bin_tuple(rawDiffData)
goodInBothMask = reorderMapObject.reorder_for_bin_tuple(goodInBothMask)
- troubleMask = reorderMapObject.reorder_for_bin_tuple(troubleMask)
+ mismatchMask = reorderMapObject.reorder_for_bin_tuple(mismatchMask)
outsideEpsilonMask = reorderMapObject.reorder_for_bin_tuple(outsideEpsilonMask)
# our list of functions that will later create the plots
@@ -835,7 +859,7 @@ class BinTupleAnalysisFunctionFactory (PlottingFunctionFactory) :
functionsToReturn['multi-scatter'] = ((lambda : figures.create_complex_scatter_plot(scatterPlotList,
"Value in File A vs Value in File B, Colored by Bin",
"File A Value", "File B Value",
- epsilon)),
+ epsilon, units_x=units_a, units_y=units_b)),
"scatter plot of file a values vs file b values for " + variableDisplayName + " by bin",
"MultiScatter.png", compared_fig_list)
@@ -861,7 +885,7 @@ class BinTupleAnalysisFunctionFactory (PlottingFunctionFactory) :
"\nfor " + binName + " # " + str(binNumber + 1)),
('RMS Difference across ' + tupleName + ' dimension'),
('Number of Cases with a Given RMS Diff.'),
- True)
+ True, units=units_a)
functionsToReturn[str(binNumber + 1) + 'histogram'] = (make_histogram,
"histogram of rms differences in " + variableDisplayName,
str(binNumber + 1) + "Hist.png", new_list)
@@ -903,8 +927,8 @@ class BinTupleAnalysisFunctionFactory (PlottingFunctionFactory) :
caseNumText = ''
for caseIndex in caseIndexes :
caseNumText = caseNumText + str(caseIndex)
- dataList = [(aData[binNumber][caseNumber], ~goodInAMask[binNumber][caseNumber], 'r', 'A case', None),
- (bData[binNumber][caseNumber], ~goodInBMask[binNumber][caseNumber], 'b', 'B case', None)]
+ dataList = [(aData[binNumber][caseNumber], ~goodInAMask[binNumber][caseNumber], 'r', 'A case', None, units_a),
+ (bData[binNumber][caseNumber], ~goodInBMask[binNumber][caseNumber], 'b', 'B case', None, units_b)]
def make_lineplot(data=dataList, binNumber=binNumber, caseNumberText=caseNumText):
return figures.create_line_plot_figure(data,
variableDisplayName + " in both files" + "\n" + "for "
@@ -912,8 +936,8 @@ class BinTupleAnalysisFunctionFactory (PlottingFunctionFactory) :
+ caseNumberText)
dataDiff = aData[binNumber][caseNumber] - bData[binNumber][caseNumber]
maskDiff = ~goodInAMask[binNumber][caseNumber] | ~goodInBMask[binNumber][caseNumber]
- def make_diffplot(data=dataDiff, badMask=maskDiff, binNumber=binNumber, caseNumberText=caseNumText):
- return figures.create_line_plot_figure([(data, badMask, 'm', 'A - B', None)],
+ def make_diffplot(data=dataDiff, badMask=maskDiff, binNumber=binNumber, caseNumberText=caseNumText, units=units_a):
+ return figures.create_line_plot_figure([(data, badMask, 'm', 'A - B', None, units)],
"Value of " + variableDisplayName + " in File A - the value in File B\n" +
"for " + binName + " # " + str(binNumber + 1) + " and case # " + caseNumberText)
@@ -956,7 +980,7 @@ class IMShowPlotFunctionFactory (PlottingFunctionFactory) :
# point by point
absDiffData=None, rawDiffData=None,
goodInBothMask=None,
- troubleMask=None, outsideEpsilonMask=None,
+ mismatchMask=None, outsideEpsilonMask=None,
# only used for plotting quiver data
aUData=None, aVData=None,
@@ -967,7 +991,9 @@ class IMShowPlotFunctionFactory (PlottingFunctionFactory) :
binName=None, tupleName=None,
# the optional epsilon for comparison of a percent of A
- epsilonPercent=None
+ epsilonPercent=None,
+ # the optional units for display
+ units_a=None, units_b=None
) :
"""
@@ -995,7 +1021,8 @@ class IMShowPlotFunctionFactory (PlottingFunctionFactory) :
assert(aData.shape == goodInAMask.shape)
functionsToReturn['originalA'] = ((lambda: figures.create_simple_figure(aData, variableDisplayName + "\nin File A",
- invalidMask=~goodInAMask, colorbarLimits=sharedRange)),
+ invalidMask=~goodInAMask, colorbarLimits=sharedRange,
+ units=units_a)),
variableDisplayName + " in file a",
"A.png", original_fig_list)
@@ -1003,7 +1030,8 @@ class IMShowPlotFunctionFactory (PlottingFunctionFactory) :
assert(bData.shape == goodInBMask.shape)
functionsToReturn['originalB'] = ((lambda: figures.create_simple_figure(bData, variableDisplayName + "\nin File B",
- invalidMask=~goodInBMask, colorbarLimits=sharedRange)),
+ invalidMask=~goodInBMask, colorbarLimits=sharedRange,
+ units=units_b)),
variableDisplayName + " in file b",
"B.png", original_fig_list)
@@ -1016,7 +1044,7 @@ class IMShowPlotFunctionFactory (PlottingFunctionFactory) :
functionsToReturn['diffAbs'] = ((lambda: figures.create_simple_figure(absDiffData,
"Absolute value of difference in\n" + variableDisplayName,
- invalidMask=~goodInBothMask)),
+ invalidMask=~goodInBothMask, units=units_a)),
"absolute value of difference in " + variableDisplayName,
"AbsDiff.png", compared_fig_list)
# make the subtractive difference plot
@@ -1028,19 +1056,19 @@ class IMShowPlotFunctionFactory (PlottingFunctionFactory) :
functionsToReturn['diffSub'] = ((lambda: figures.create_simple_figure(rawDiffData,
"Value of (Data File B - Data File A) for\n" + variableDisplayName,
- invalidMask=~goodInBothMask)),
+ invalidMask=~goodInBothMask, units=units_a)),
"the difference in " + variableDisplayName,
"Diff.png", compared_fig_list)
- # make the trouble data plot
- if ('do_plot_trouble' not in doPlotSettingsDict) or (doPlotSettingsDict['do_plot_trouble']) :
+ # make the mismatch data plot
+ if ('do_plot_mismatch' not in doPlotSettingsDict) or (doPlotSettingsDict['do_plot_mismatch']) :
assert(goodInAMask is not None)
assert(goodInBMask is not None)
assert(goodInAMask.shape == goodInBMask.shape)
assert(aData.shape == bData.shape)
assert(aData.shape == goodInAMask.shape)
- assert(troubleMask is not None)
- assert(troubleMask.shape == aData.shape)
+ assert(mismatchMask is not None)
+ assert(mismatchMask.shape == aData.shape)
# this is not an optimal solution, but we need to have at least somewhat valid data at any mismatched points so
@@ -1048,11 +1076,11 @@ class IMShowPlotFunctionFactory (PlottingFunctionFactory) :
bDataCopy = bData[:]
tempMask = goodInAMask & (~goodInBMask)
bDataCopy[tempMask] = aData[tempMask]
- functionsToReturn['trouble'] = ((lambda: figures.create_simple_figure(bDataCopy, "Areas of trouble data in\n" + variableDisplayName,
- invalidMask=~(goodInAMask | goodInBMask), tagData=troubleMask,
- colorMap=mediumGrayColorMap)),
- "trouble data in " + variableDisplayName,
- "Trouble.png", compared_fig_list)
+ functionsToReturn['mismatch'] = ((lambda: figures.create_simple_figure(bDataCopy, "Areas of mismatch data in\n" + variableDisplayName,
+ invalidMask=~(goodInAMask | goodInBMask), tagData=mismatchMask,
+ colorMap=mediumGrayColorMap, units=units_a)),
+ "mismatch data in " + variableDisplayName,
+ "Mismatch.png", compared_fig_list)
return functionsToReturn
diff --git a/pyglance/glance/stats.py b/pyglance/glance/stats.py
index d75921ac5fa7ffaf18aedb59f080392082f7cea8..4d72ecaa56cdb74bde6717c4e6d9c03ad34aedc1 100644
--- a/pyglance/glance/stats.py
+++ b/pyglance/glance/stats.py
@@ -411,8 +411,8 @@ class NumericalComparisonStatistics (StatisticalData) :
diff_outside_epsilon_fraction - the fraction of points that fall outside the acceptable epsilon settings
perfect_match_count - the number of points that match perfectly between the sets
perfect_match_fraction - the fraction of points that match perfectly between the sets
- trouble_points_count - the number of points that have possible issues according to the current analysis
- trouble_points_fraction - the fraction of points that have possible issues according to the current analysis
+ mismatch_points_count - the number of points that have possible issues according to the current analysis
+ mismatch_points_fraction - the fraction of points that have possible issues according to the current analysis
It may also contain additional statistics. This is indicated by the does_include_simple boolean.
The possible additional statistics include:
@@ -442,9 +442,9 @@ class NumericalComparisonStatistics (StatisticalData) :
'rms_diff': "root mean square (RMS) difference of finite values",
'r-squared correlation': "the square of the r correlation (see correlation)",
'std_diff': "standard deviation of difference of finite values",
- 'trouble_points_count': 'number of points that differ in finite/missing status between the input data sets A and B,' +
+ 'mismatch_points_count': 'number of points that differ in finite/missing status between the input data sets A and B,' +
' or are unacceptable when compared according to the current epsilon definitions',
- 'trouble_points_fraction': 'fraction of points that differ in finite/missing status between the input data sets A and B,' +
+ 'mismatch_points_fraction': 'fraction of points that differ in finite/missing status between the input data sets A and B,' +
' or are unacceptable when compared according to the current epsilon definitions',
}
@@ -461,13 +461,13 @@ class NumericalComparisonStatistics (StatisticalData) :
# pull out some info we will use later
valid_in_both = diffInfoObject.diff_data_object.masks.valid_mask
outside_epsilon_mask = diffInfoObject.diff_data_object.masks.outside_epsilon_mask
- trouble_mask = diffInfoObject.diff_data_object.masks.trouble_mask
+ mismatch_mask = diffInfoObject.diff_data_object.masks.mismatch_mask
aData = diffInfoObject.a_data_object.data
bData = diffInfoObject.b_data_object.data
assert (valid_in_both.shape == outside_epsilon_mask.shape)
- assert (outside_epsilon_mask.shape == trouble_mask.shape)
- assert (trouble_mask.shape == aData.shape)
+ assert (outside_epsilon_mask.shape == mismatch_mask.shape)
+ assert (mismatch_mask.shape == aData.shape)
assert (aData.shape == bData.shape)
# fill in some simple statistics
@@ -476,13 +476,13 @@ class NumericalComparisonStatistics (StatisticalData) :
goodMask=valid_in_both)
self.correlation = delta.compute_correlation(aData, bData, valid_in_both)
self.r_squared_correlation = self.correlation * self.correlation
- self.trouble_points_count = np.sum(trouble_mask)
+ self.mismatch_points_count = np.sum(mismatch_mask)
# we actually want the total number of _finite_ values rather than all the data
total_num_finite_values = np.sum(valid_in_both)
# calculate some more complex statistics
- self.trouble_points_fraction = float(self.trouble_points_count) / float(aData.size)
+ self.mismatch_points_fraction = float(self.mismatch_points_count) / float(aData.size)
# be careful not to divide by zero if we don't have finite data
if total_num_finite_values > 0 :
self.diff_outside_epsilon_fraction = float(self.diff_outside_epsilon_count) / float(total_num_finite_values)
@@ -522,8 +522,8 @@ class NumericalComparisonStatistics (StatisticalData) :
'diff_outside_epsilon_fraction': self.diff_outside_epsilon_fraction,
'perfect_match_count': self.perfect_match_count,
'perfect_match_fraction': self.perfect_match_fraction,
- 'trouble_points_count': self.trouble_points_count,
- 'trouble_points_fraction': self.trouble_points_fraction
+ 'mismatch_points_count': self.mismatch_points_count,
+ 'mismatch_points_fraction': self.mismatch_points_fraction
}
toReturn.update(self.temp_analysis)