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authorThomas Preud'homme <thomasp@graphcore.ai>2019-09-25 07:58:52 +0000
committerThomas Preud'homme <thomasp@graphcore.ai>2019-09-25 07:58:52 +0000
commit99f5df118a790da133f33965cc5f6590285b8b39 (patch)
tree6b2aae36524d2d263a84a57c833de2d02da3f5da
parent65d5ffa9872da4a2800fe3ec098b084363321c60 (diff)
[LNT] Python 3 support: adapt to map returning an iterator
Adapt calls to map() to the fact it returns an iterator in Python 3 when necessary. This was produced by running futurize's stage2 lib2to3.fixes.fix_map, with manual clean up to remove unecessary list wrapping and simplify the code. Reviewers: cmatthews, hubert.reinterpretcast, kristof.beyls Reviewed By: hubert.reinterpretcast Subscribers: llvm-commits Differential Revision: https://reviews.llvm.org/D67817 git-svn-id: https://llvm.org/svn/llvm-project/lnt/trunk@372821 91177308-0d34-0410-b5e6-96231b3b80d8
-rw-r--r--lnt/external/stats/pstat.py21
-rw-r--r--lnt/external/stats/stats.py32
-rw-r--r--lnt/server/ui/views.py2
-rw-r--r--lnt/testing/__init__.py2
-rw-r--r--lnt/testing/util/valgrind.py4
-rw-r--r--lnt/tests/nt.py2
6 files changed, 24 insertions, 39 deletions
diff --git a/lnt/external/stats/pstat.py b/lnt/external/stats/pstat.py
index 2beb130..46237f4 100644
--- a/lnt/external/stats/pstat.py
+++ b/lnt/external/stats/pstat.py
@@ -216,16 +216,16 @@ Returns: a list-of-lists corresponding to the columns from listoflists
column = 0
if isinstance(cnums, (list, tuple)): # if multiple columns to get
index = cnums[0]
- column = map(lambda x: x[index], listoflists)
+ column = [x[index] for x in listoflists]
for col in cnums[1:]:
index = col
- column = abut(column,map(lambda x: x[index], listoflists))
+ column = abut(column, [x[index] for x in listoflists])
elif isinstance(cnums, str): # if an 'x[3:]' type expr.
- evalstring = 'map(lambda x: x'+cnums+', listoflists)'
+ evalstring = 'list(map(lambda x: x'+cnums+', listoflists))'
column = eval(evalstring)
else: # else it's just 1 col to get
index = cnums
- column = map(lambda x: x[index], listoflists)
+ column = [x[index] for x in listoflists]
return column
@@ -463,8 +463,8 @@ the string.join function.
Usage: list2string (inlist,delimit=' ')
Returns: the string created from inlist
"""
- stringlist = map(makestr,inlist)
- return string.join(stringlist,delimit)
+ stringlist = map(makestr, inlist)
+ return delimit.join(stringlist)
def makelol(inlist):
@@ -510,8 +510,7 @@ Returns: None
maxsize = [0]*len(list2print[0])
for col in range(len(list2print[0])):
items = colex(list2print,col)
- items = map(makestr,items)
- maxsize[col] = max(map(len,items)) + extra
+ maxsize[col] = max(map(lambda item: len(makestr(item)), items)) + extra
for row in lst:
if row == ['\n'] or row == '\n' or row == '' or row == ['']:
print()
@@ -614,7 +613,7 @@ returned ... map(lambda x: 'criterion',listoflists).
Usage: remap(listoflists,criterion) criterion=string
Returns: remapped version of listoflists
"""
- function = 'map(lambda x: '+criterion+',listoflists)'
+ function = 'list(map(lambda x: '+criterion+',listoflists))'
lines = eval(function)
return lines
@@ -963,7 +962,7 @@ Returns: an array of equal length containing 1s where the two rows had
"""
return
if row1.dtype.char=='O' or row2.dtype=='O':
- cmpvect = N.logical_not(abs(N.array(map(cmp,row1,row2)))) # cmp fcn gives -1,0,1
+ cmpvect = N.logical_not(abs(N.array(list(map(cmp, row1, row2))))) # cmp fcn gives -1,0,1
else:
cmpvect = N.equal(row1,row2)
return cmpvect
@@ -1023,7 +1022,7 @@ Usage: aunique (inarray)
for item in inarray[1:]:
newflag = 1
for unq in uniques: # NOTE: cmp --> 0=same, -1=<, 1=>
- test = N.sum(abs(N.array(map(cmp,item,unq))))
+ test = N.sum(abs(N.array(list(map(cmp, item, unq)))))
if test == 0: # if item identical to any 1 row in uniques
newflag = 0 # then not a novel item to add
break
diff --git a/lnt/external/stats/stats.py b/lnt/external/stats/stats.py
index baa4a89..89ecf9d 100644
--- a/lnt/external/stats/stats.py
+++ b/lnt/external/stats/stats.py
@@ -842,8 +842,8 @@ Returns: Pearson's r value, two-tailed p-value
if len(x) != len(y):
raise ValueError('Input values not paired in pearsonr. Aborting.')
n = len(x)
- x = map(float,x)
- y = map(float,y)
+ x = list(map(float, x))
+ y = list(map(float, y))
xmean = mean(x)
ymean = mean(y)
r_num = n*(summult(x,y)) - sum(x)*sum(y)
@@ -971,8 +971,8 @@ Returns: slope, intercept, r, two-tailed prob, sterr-of-estimate
if len(x) != len(y):
raise ValueError('Input values not paired in linregress. Aborting.')
n = len(x)
- x = map(float,x)
- y = map(float,y)
+ x = list(map(float, x))
+ y = list(map(float, y))
xmean = mean(x)
ymean = mean(y)
r_num = float(n*(summult(x,y)) - sum(x)*sum(y))
@@ -1235,7 +1235,7 @@ Returns: a t-statistic, two-tail probability estimate
if diff != 0:
d.append(diff)
count = len(d)
- absd = map(abs,d)
+ absd = list(map(abs, d))
absranked = rankdata(absd)
r_plus = 0.0
r_minus = 0.0
@@ -1265,7 +1265,7 @@ Returns: H-statistic (corrected for ties), associated p-value
args = list(args)
n = [0]*len(args)
all = []
- n = map(len,args)
+ n = list(map(len, args))
for i in range(len(args)):
all = all + args[i]
ranked = rankdata(all)
@@ -1562,14 +1562,7 @@ Usage: F_oneway(*lists) where *lists is any number of lists, one per
Returns: F value, one-tailed p-value
"""
a = len(lists) # ANOVA on 'a' groups, each in it's own list
- means = [0]*a
- vars = [0]*a
- ns = [0]*a
alldata = []
- tmp = map(N.array,lists)
- means = map(amean,tmp)
- vars = map(avar,tmp)
- ns = map(len,lists)
for i in range(len(lists)):
alldata = alldata + lists[i]
alldata = N.array(alldata)
@@ -1629,8 +1622,8 @@ Returns: None
maxsize = [0]*len(list2print[0])
for col in range(len(list2print[0])):
items = pstat.colex(list2print,col)
- items = map(pstat.makestr,items)
- maxsize[col] = max(map(len,items)) + extra
+ maxsize[col] = (max(map(lambda item: len(pstat.makestr(item)), items))
+ + extra)
for row in listoflists:
if row == ['\n'] or row == '\n':
outfile.write('\n')
@@ -3640,7 +3633,7 @@ Returns: H-statistic (corrected for ties), associated p-value
assert len(args) == 3, "Need at least 3 groups in stats.akruskalwallish()"
args = list(args)
n = [0]*len(args)
- n = map(len,args)
+ n = list(map(len, args))
all = []
for i in range(len(args)):
all = all + args[i].tolist()
@@ -4045,14 +4038,7 @@ Usage: aF_oneway (*args) where *args is 2 or more arrays, one per
Returns: f-value, probability
"""
na = len(args) # ANOVA on 'na' groups, each in it's own array
- means = [0]*na
- vars = [0]*na
- ns = [0]*na
alldata = []
- tmp = map(N.array,args)
- means = map(amean,tmp)
- vars = map(avar,tmp)
- ns = map(len,args)
alldata = N.concatenate(args)
bign = len(alldata)
sstot = ass(alldata)-(asquare_of_sums(alldata)/float(bign))
diff --git a/lnt/server/ui/views.py b/lnt/server/ui/views.py
index a94577a..40a7786 100644
--- a/lnt/server/ui/views.py
+++ b/lnt/server/ui/views.py
@@ -1330,7 +1330,7 @@ def v4_global_status():
def get_machine_keys(m):
m.css_name = m.name.replace('.', '-')
return m
- recent_machines = map(get_machine_keys, recent_machines)
+ recent_machines = list(map(get_machine_keys, recent_machines))
# For each machine, build a table of the machine, the baseline run, and the
# most recent run. We also computed a list of all the runs we are reporting
diff --git a/lnt/testing/__init__.py b/lnt/testing/__init__.py
index 5161eb4..f82eb7f 100644
--- a/lnt/testing/__init__.py
+++ b/lnt/testing/__init__.py
@@ -380,7 +380,7 @@ class MetricSamples:
"""Add samples for this metric, converted to float by calling
function conv_f.
"""
- self.data.extend(list(map(conv_f, new_samples)))
+ self.data.extend(map(conv_f, new_samples))
def render(self):
"""Return info from this instance in a dictionary that respects
diff --git a/lnt/testing/util/valgrind.py b/lnt/testing/util/valgrind.py
index 65e7c71..51414be 100644
--- a/lnt/testing/util/valgrind.py
+++ b/lnt/testing/util/valgrind.py
@@ -74,7 +74,7 @@ class CalltreeData(object):
# Check if this is the closing summary line.
if ln.startswith('summary'):
key, value = ln.split(':', 1)
- summary_samples = map(int, value.split())
+ summary_samples = list(map(int, value.split()))
break
# Check if this is an update to the current file or function.
@@ -84,7 +84,7 @@ class CalltreeData(object):
current_function = ln[3:-1]
else:
# Otherwise, this is a data record.
- samples = map(int, ln.split())
+ samples = list(map(int, ln.split()))
if len(samples) != num_samples:
raise CalltreeParseError(
"invalid record line, unexpected sample count")
diff --git a/lnt/tests/nt.py b/lnt/tests/nt.py
index 3eac505..cf4d634 100644
--- a/lnt/tests/nt.py
+++ b/lnt/tests/nt.py
@@ -1305,7 +1305,7 @@ def _execute_test_again(config, test_name, test_path, test_relative_path,
def _unix_quote_args(s):
- return map(pipes.quote, shlex.split(s))
+ return list(map(pipes.quote, shlex.split(s)))
# When set to true, all benchmarks will be rerun.