Update r.meb.py

bugfixes

src/raster/r.meb/r.meb.py

@@ -1,6 +1,5 @@
 #!/usr/bin/env python
 
-
 ########################################################################
 #
 # MODULE:       r.meb
@@ -19,7 +18,7 @@
 #               and median of MES values in B (MESb), divided by the median of
 #               the absolute deviations of MESb from the median of MESb (MAD)
 #
-# COPYRIGHT: (C) 2014-2019 by Paulo van Breugel and the GRASS Development Team
+# COPYRIGHT: (C) 2014-2022 by Paulo van Breugel and the GRASS Development Team
 #
 #            This program is free software under the GNU General Public
 #            License (>=v2). Read the file COPYING that comes with GRASS
@@ -113,20 +112,16 @@
 # import libraries
 import os
 import sys
-import csv
-import numpy as np
-import uuid
-import operator
 import atexit
+import uuid
 import tempfile
-import string
+import operator
+from subprocess import PIPE
+import csv
+import numpy as np
 import grass.script as gs
+from grass.pygrass.modules import Module
 
-# for Python 3 compatibility
-try:
-    xrange
-except NameError:
-    xrange = range
 
 # Rules
 COLORS_MES = """\
@@ -158,14 +153,14 @@ def tmpname(prefix):
     Use only for raster maps.
     """
     tmpf = prefix + str(uuid.uuid4())
-    tmpf = string.replace(tmpf, "-", "_")
+    tmpf = tmpf.replace("-", "_")
     CLEAN_RAST.append(tmpf)
     return tmpf
 
 
 def raster_exists(envlay):
     """Check if the raster map exists, call GRASS fatal otherwise"""
-    for chl in xrange(len(envlay)):
+    for chl in range(len(envlay)):
         ffile = gs.find_file(envlay[chl], element="cell")
         if not ffile["fullname"]:
             gs.fatal(_("The layer {} does not exist").format(envlay[chl]))
@@ -179,11 +174,11 @@ def EB(simlay, reflay):
     CLEAN_RAST.append(tmpf4)
     d = gs.read_command("r.quantile", quiet=True, input=simlay, percentiles="50")
     d = d.split(":")
-    d = float(string.replace(d[2], "\n", ""))
+    d = float(d[2].replace("\n", ""))
     gs.mapcalc("$tmpf4 = abs($map - $d)", map=simlay, tmpf4=tmpf4, d=d, quiet=True)
     mad = gs.read_command("r.quantile", quiet=True, input=tmpf4, percentiles="50")
     mad = mad.split(":")
-    mad = float(string.replace(mad[2], "\n", ""))
+    mad = float(mad[2].replace("\n", ""))
     gs.run_command("g.remove", quiet=True, flags="f", type="raster", name=tmpf4)
 
     # Median and mad for reference layer
@@ -198,7 +193,7 @@ def EB(simlay, reflay):
     )
     e = gs.read_command("r.quantile", quiet=True, input=tmpf5, percentiles="50")
     e = e.split(":")
-    e = float(string.replace(e[2], "\n", ""))
+    e = float(e[2].replace("\n", ""))
     EBstat = abs(d - e) / mad
 
     # Print results to screen and return results
@@ -255,8 +250,8 @@ def main(options, flags):
         )
 
     # Text for history in metadata
-    opt2 = dict((k, v) for k, v in options.iteritems() if v)
-    hist = " ".join("{!s}={!r}".format(k, v) for (k, v) in opt2.iteritems())
+    opt2 = dict((k, v) for k, v in options.items() if v)
+    hist = " ".join("{!s}={!r}".format(k, v) for (k, v) in opt2.items())
     hist = "r.meb {}".format(hist)
     unused, tmphist = tempfile.mkstemp()
     text_file = open(tmphist, "w")
@@ -273,7 +268,7 @@ def main(options, flags):
     gs.run_command("g.copy", quiet=True, raster=(ref, tmpref0))
 
     ipi = []
-    for j in xrange(len(ipl)):
+    for j in range(len(ipl)):
         # Calculate the frequency distribution
         tmpf1 = tmpname("reb1")
         CLEAN_RAST.append(tmpf1)
@@ -288,14 +283,20 @@ def main(options, flags):
                 dignum=digits2,
                 quiet=True,
             )
-        p = gs.pipe_command(
-            "r.stats", quiet=True, flags="cn", input=tmpf1, sort="asc", sep=";"
-        )
+        stats_out = Module(
+            "r.stats",
+            flags="cn",
+            input=tmpf1,
+            sort="asc",
+            separator=";",
+            stdout_=PIPE,
+        ).outputs.stdout
         stval = {}
-        for line in p.stdout:
-            [val, count] = line.strip(os.linesep).split(";")
+        stats_outlines = stats_out.replace("\r", "").split("\n")
+        stats_outlines = [_f for _f in stats_outlines if _f]
+        for z in stats_outlines:
+            [val, count] = z.split(";")
             stval[float(val)] = float(count)
-        p.wait()
         sstval = sorted(stval.items(), key=operator.itemgetter(0))
         sstval = np.matrix(sstval)
         a = np.cumsum(np.array(sstval), axis=0)
@@ -332,7 +333,6 @@ def main(options, flags):
             "g.remove", quiet=True, flags="f", type="raster", name=(tmpf2, tmpf1)
         )
         os.close(fd2)
-        os.remove(tmprule)
         ipi.append(tmpf3)
 
     # ----------------------------------------------------------------------
@@ -410,7 +410,7 @@ def main(options, flags):
     # EB individual layers
     if flag_i:
         ebi = {}
-        for mm in xrange(len(ipi)):
+        for mm in range(len(ipi)):
             nmn = "{}_{}".format(tmpf0, ipn[mm])
             if not out:
                 CLEAN_RAST.append(nmn)
@@ -429,11 +429,12 @@ def main(options, flags):
                 description="Environmental similarity (ES) for " "{}".format(ipn[mm]),
                 loadhistory=tmphist,
             )
+
     else:
         gs.run_command("g.remove", quiet=True, flags="f", type="raster", name=ipi)
 
     if filename:
-        with open(filename, "wb") as csvfile:
+        with open(filename, "wt") as csvfile:
             fieldnames = ["variable", "median_region", "median_reference", "mad", "eb"]
             writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
             writer.writeheader()