Selecting inputs within groups - arcpy

Question

I need help with some python in selecting correct input and near feature classes in Near Table analysis.

The project aim is to run Near Table Analysis (distance) on point locations collected at time 1[day] and time2[night].

I have managed to group the files I want to input into each iteration of the model based on filename and Year using groupby with the first 0:26 characters in the file name ​(all files are in the same directory).

My problem is I need to separate the inputs for the GenerateNearTable Tool into in_features (Day) and near_features (Night). So split each group again into Day and Night files.

Here is my code.

import arcpy, itertools, os

# Define the input and output workspaces
arcpy.env.workspace = r"C:\Users\Jenny\roos"
outws = r"C:\Users\Jenny\roos\gmehome.gdb"

# List the fcs in your workspace
my_pts = arcpy.ListFeatureClasses()

# Group the items based on first 26 characters
grouped = [list(g) for _, g in itertools.groupby(sorted(my_pts), lambda x: x[0:26])]

# Loop over the groups and perform the NearTable operation
for group in grouped:
    groupedDay = ?
    groupedNight = ?
    outname = group[0][:26] + "_DayNightDist"
    arcpy.GenerateNearTable_analysis(in_features=groupedDay, near_features=groupedNight, out_table= outname, search_radius="", location="NO_LOCATION", angle="NO_ANGLE", closest="ALL", closest_count="0", method="PLANAR")

Other useful information is the file names

[[Jenxxx_Annual_HR_Poly_Yr1Day_SCV, Jenxxx_Annual_HR_Poly_Yr1Night_SCV] [Jenxxx_Annual_HR_Poly_Yr2Day_SCV, Jenxxx_Annual_HR_Poly_Yr2Night_SCV], [Barry_Annual_HR_Poly_Yr1Day_SCV, Barry_Annual_HR_Poly_Yr1Night_SCV]] (and so on)

UPDATE: SCREENSHOT OF ITERATION ISSUE

Answer 1

I think this is what you're trying to do:

import arcpy, itertools, os

# Define the input and output workspaces
arcpy.env.workspace = r"C:\Users\Jenny\roos"
outws = r"C:\Users\Jenny\roos\gmehome.gdb"

# List the fcs in your workspace
my_pts = arcpy.ListFeatureClasses()

DayList = [] # a shiny new empty list..

for ThisFC in my_pts:
    if ThisFC.upper().find('DAY_SCV') > 0: # edited here
        # This is a 'day' feature class
        NightFC = ThisFC.upper().replace("DAY_SCV","NIGHT_SCV") # we'll do this again..

        if not arcpy.Exists(os.path.join(arcpy.env.workspace,NightFC)):
            # do something here if there is no matching night to your day
            arcpy.AddWarning("Oh dear, {0} has no matching night".format(ThisFC))
        else:
            # a 'night' matches a 'day'
            DayList.append(ThisFC) # add it to the list of days to process.

# Group the items based on first 26 characters
# I don't know what you're trying to do here..
# grouped = [list(g) for _, g in itertools.groupby(sorted(my_pts), lambda x: x[0:26])]

# Loop over the groups and perform the NearTable operation
for groupedDay in DayList:
    #groupedDay = ?
    groupedNight = groupedDay.upper().replace("DAY_SCV","NIGHT_SCV") 
    outname = groupedDay[:26] + "_DayNightDist" # I don't like this method, try outname = groupedDay.split('_')[0] to get the first part, not a fixed length
    # you don't need to supply parameters that are 'as default'
    arcpy.GenerateNearTable_analysis(groupedDay,
                                    groupedNight,
                                    outname,
                                    closest = "ALL")#, the rest of this isn't required because they're default

##                                   search_radius="",
##                                   location="NO_LOCATION",
##                                   angle="NO_ANGLE",
##                                   closest="ALL",
##                                   closest_count="0",
##                                   method="PLANAR")

When specifying parameters for a function you only need the parameter name if you're going to skip optional parameters or putting them in a different sequence.. Have a close look at how I edited your Generate Near Table, the only parameter that is implicitly specified is closest = "ALL", that is because I skip 3 optional parameters, accepting the default values.