diff --git a/pyglance/glance/compare.py b/pyglance/glance/compare.py
index 9c357aa3c342d1ddbc7f40ccbd9ac3c4a5c83a5e..ea3775f4634b128560d4a713acd4f9a8eed1e444 100644
--- a/pyglance/glance/compare.py
+++ b/pyglance/glance/compare.py
@@ -598,12 +598,10 @@ def inspect_library_call (a_path, var_list=None,
# we are always going to want to draw a basic histogram of the data values to tell which
# occur most frequently
plotFunctionGenerationObjects.append(plotcreate.DataHistogramPlotFunctionFactory())
-
+
# if it's vector data with longitude and latitude, quiver plot it on the Earth
if isVectorData and (not do_not_test_with_lon_lat) :
- # TODO replace this at some point
- #plotFunctionGenerationObjects.append(plotcreate.MappedQuiverPlotFunctionFactory())
- pass
+ plotFunctionGenerationObjects.append(plotcreate.InspectMappedQuiverPlotFunctionFactory())
# if the data is one dimensional we can plot it as lines
elif (len(aData.shape) == 1) :
@@ -864,8 +862,7 @@ def reportGen_library_call (a_path, b_path, var_list=None,
do_not_test_with_lon_lat = (not include_images_for_this_variable) or (len(lon_lat_data) <= 0)
# handle vector data
- isVectorData = ( (MAGNITUDE_VAR_NAME_KEY in varRunInfo) and (DIRECTION_VAR_NAME_KEY in varRunInfo) and
- (MAGNITUDE_B_VAR_NAME_KEY in varRunInfo) and (DIRECTION_B_VAR_NAME_KEY in varRunInfo) )
+ isVectorData = (MAGNITUDE_VAR_NAME_KEY in varRunInfo) and (DIRECTION_VAR_NAME_KEY in varRunInfo)
# check if this data can be displayed but
# don't compare lon/lat sizes if we won't be plotting
@@ -943,8 +940,8 @@ def reportGen_library_call (a_path, b_path, var_list=None,
lon_lat_data[A_FILE_KEY][INVALID_MASK_KEY]
if (A_FILE_KEY in lon_lat_data) and (INVALID_MASK_KEY in lon_lat_data[A_FILE_KEY]) else None)
bUData, bVData = get_UV_info_from_magnitude_direction_info (bFile.file_object,
- varRunInfo[MAGNITUDE_B_VAR_NAME_KEY] if (MAGNITUDE_B_VAR_NAME_KEY) in varRunInfo else None,
- varRunInfo[DIRECTION_B_VAR_NAME_KEY] if (DIRECTION_B_VAR_NAME_KEY) in varRunInfo else None,
+ varRunInfo[MAGNITUDE_B_VAR_NAME_KEY] if (MAGNITUDE_B_VAR_NAME_KEY) in varRunInfo else varRunInfo[MAGNITUDE_VAR_NAME_KEY] if (MAGNITUDE_VAR_NAME_KEY) in varRunInfo else None,
+ varRunInfo[DIRECTION_B_VAR_NAME_KEY] if (DIRECTION_B_VAR_NAME_KEY) in varRunInfo else varRunInfo[DIRECTION_VAR_NAME_KEY] if (DIRECTION_VAR_NAME_KEY) in varRunInfo else None,
lon_lat_data[B_FILE_KEY][INVALID_MASK_KEY]
if (B_FILE_KEY in lon_lat_data) and (INVALID_MASK_KEY in lon_lat_data[B_FILE_KEY]) else None)
@@ -958,7 +955,7 @@ def reportGen_library_call (a_path, b_path, var_list=None,
plotFunctionGenerationObjects.append(plotcreate.BinTupleAnalysisFunctionFactory())
else : # if it's not bin/tuple, there are lots of other posibilities
-
+
# if it's vector data with longitude and latitude, quiver plot it on the Earth
if isVectorData and (not do_not_test_with_lon_lat) :
plotFunctionGenerationObjects.append(plotcreate.MappedQuiverPlotFunctionFactory())
diff --git a/pyglance/glance/figures.py b/pyglance/glance/figures.py
index edd0237d16d2096c11dc42f71364d4d7378af3c8..b42d91efffa107c779aae10cd8a184f7494e7627 100644
--- a/pyglance/glance/figures.py
+++ b/pyglance/glance/figures.py
@@ -660,16 +660,15 @@ def create_mapped_figure(data, latitude, longitude, in_projection, out_projectio
return figure_obj
-# create a figure including a quiver plot of our vector data mapped onto a map at the lon/lat
-# given, the colorMap parameter can be used to control the colors the figure is drawn.
-# 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, in_projection, out_projection, boundingAxes, title_str,
- invalidMask=None, tagData=None, uData=None, vData=None, units=None, **kwargs) :
+ invalidMask=None, tagData=None, uData=None, vData=None, units=None, colorMap=None, **kwargs) :
+ """create a figure including a quiver plot of our vector data mapped onto a map at the lon/lat
- if (data is None) or (data.size <= 1) or (invalidMask is not None and data[~invalidMask].size <= 1):
+ if any masks are passed in the tagData list they will be plotted as an overlays set on the existing image
+
+ """
+
+ if (data is None) or (data.size < 1) or (invalidMask is not None and data[~invalidMask].size < 1):
LOG.debug("Not enough data to make a meaningful quiver mapped figure.")
return None
@@ -691,22 +690,21 @@ def create_quiver_mapped_figure(data, latitude, longitude, in_projection, out_pr
# build the plot
figure_obj = plt.figure()
axes_obj = figure_obj.add_subplot(111, projection=out_projection,)
-
+
# draw our data placed on a map
maps.draw_basic_features(in_projection, axes_obj, boundingAxes, )
- img_temp = maps.quiver_plot_on_map(longitudeClean, latitudeClean, axes_obj, in_projection, uDataClean, vDataClean, colordata=colorData, )
+ img_temp = maps.quiver_plot_on_map(longitudeClean, latitudeClean, axes_obj, in_projection, uDataClean, vDataClean,
+ colorMap=colorMap, colordata=colorData, )
# show the title
axes_obj.set_title(title_str)
-
+
# 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(img_temp, format='%.3g')
# add the units to the colorbar
if (str.lower(str(units)) != "none") and (str.lower(str(units)) != "1") :
cbar.set_label(units)
- """
numMismatchPoints = _plot_tag_data_mapped(axes_obj, in_projection, tagDataClean, longitudeClean, latitudeClean, )
diff --git a/pyglance/glance/graphics.py b/pyglance/glance/graphics.py
index 078cd03b29bfb3ce11193079ac2e43946615b752..e5c34eb947170bc447a39e3eb066465125868b77 100644
--- a/pyglance/glance/graphics.py
+++ b/pyglance/glance/graphics.py
@@ -280,7 +280,7 @@ def contourf_on_map(lon, lat, data, axes_object, in_projection, levelsToUse=None
return img_temp
-def quiver_plot_on_map(lon, lat, axes_object, in_projection, uData=None, vData=None, colordata=None, **kwargs) :
+def quiver_plot_on_map(lon, lat, axes_object, in_projection, uData=None, vData=None, colordata=None, colorMap=None, **kwargs) :
"""
Show a quiver plot of the given vector data at the given longitude and latitude
"""
@@ -289,9 +289,9 @@ def quiver_plot_on_map(lon, lat, axes_object, in_projection, uData=None, vData=N
if (uData is not None) and (vData is not None):
if colordata is None:
- img_temp = axes_object.quiver(lon, lat, uData, vData, transform=in_projection, **kwargs)
+ img_temp = axes_object.quiver(lon, lat, uData, vData, transform=in_projection, cmap=colorMap, **kwargs)
else:
- img_temp = axes_object.quiver(lon, lat, uData, vData, colordata, transform=in_projection, **kwargs)
+ img_temp = axes_object.quiver(lon, lat, uData, vData, colordata, transform=in_projection, cmap=colorMap, **kwargs)
return img_temp
diff --git a/pyglance/glance/plotcreatefns.py b/pyglance/glance/plotcreatefns.py
index 92698f186a8e032c1e98fd0d976b35c08703ff3c..97f561c2e4390b9b928b20989bd2e395ed331843 100644
--- a/pyglance/glance/plotcreatefns.py
+++ b/pyglance/glance/plotcreatefns.py
@@ -1488,6 +1488,103 @@ class InspectMappedContourPlotFunctionFactory (PlottingFunctionFactory) :
return functionsToReturn
+class InspectMappedQuiverPlotFunctionFactory(PlottingFunctionFactory):
+ """
+ This class creates quiver plots for a single file mapped onto a region of the earth.
+ Note: the plotting function requires u and v data.
+ """
+
+ def __init__(self):
+ LOG.debug("Creating InspectMappedQuiverPlotFunctionFactory object.")
+
+ def create_plotting_functions(
+ self,
+
+ # the most basic data set needed
+ aData, bData, # bData will not be used
+ variableDisplayName,
+ epsilon,
+ doPlotSettingsDict,
+
+ # where the names of the created figures will be stored
+ original_fig_list, compared_fig_list,
+
+ # parameters that are only needed for geolocated data
+ lonLatDataDict=None,
+
+ # not used in this method (for contour plots)
+ dataRanges=None, dataRangeNames=None, dataColors=None,
+ shouldUseSharedRangeForOriginal=True,
+
+ # not used in this method (for comparison plots)
+ differences=None,
+
+ # only used for plotting quiver data
+ aUData=None, aVData=None,
+ bUData=None, bVData=None, # b versions will not be used
+
+ # not used in this method (only used for line plots)
+ binIndex=None, tupleIndex=None,
+ binName=None, tupleName=None,
+
+ # not used in this method (the optional epsilon for comparison of a percent of A)
+ epsilonPercent=None,
+
+ # the optional units for display
+ units_a=None, units_b=None, # units_b will not be used
+
+ # not used in this method (an optional range for a histogram)
+ histRange=None
+
+ ):
+
+ # FUTURE, for the moment, unpack these values into local variables; FUTURE use the objects directly and as needed
+ goodInAMask = aData.masks.valid_mask
+ aData = aData.data
+
+ # the default for plotting geolocated data
+ mappedPlottingFunction = figures.create_quiver_mapped_figure
+
+ functionsToReturn = {}
+
+ assert (aUData is not None)
+ assert (aVData is not None)
+
+ assert (lonLatDataDict is not None)
+ assert (goodInAMask is not None)
+
+ # figure out where we're going to be plotting and using which projections
+ temp_lonlat = {
+ A_FILE_KEY: lonLatDataDict,
+ }
+ fullAxis, in_proj, out_proj = _get_extents_and_projections(temp_lonlat,
+ goodInAMask, None,
+ variableDisplayName)
+
+ # make the plotting functions
+
+ # make the original data plots
+ if (DO_PLOT_ORIGINALS_KEY not in doPlotSettingsDict) or (doPlotSettingsDict[DO_PLOT_ORIGINALS_KEY]):
+ assert (LAT_KEY in lonLatDataDict)
+ assert (LON_KEY in lonLatDataDict)
+ assert (lonLatDataDict[LAT_KEY].shape == lonLatDataDict[LON_KEY].shape)
+
+ functionsToReturn[ORIG_A_FUNCTION_KEY] = \
+ ((lambda: mappedPlottingFunction(aData,
+ lonLatDataDict[LAT_KEY],
+ lonLatDataDict[LON_KEY],
+ in_proj, out_proj, fullAxis,
+ (variableDisplayName + "\nin File A"),
+ invalidMask=(~goodInAMask),
+ uData=aUData, vData=aVData,
+ units=units_a)),
+ variableDisplayName + " in file a",
+ "A.png", original_fig_list)
+
+ # FUTURE, any additional figures of the original data?
+
+ return functionsToReturn
+
if __name__=='__main__':
import doctest
doctest.testmod()