I'm trying to convert numbers that were previously percentages to a decimal format by dividing them by 100 in Google Sheets. Basically, I have:
<polygon points="48, 6, 43, 7, 38, 9, 34, 12, 29, 16, 24, 22, 22, 30, 22, 44, 23, 50, 23, 65, 25, 72, 28, 77, 32, 82, 35, 86, 40, 90, 43, 92, 50, 93, 55, 91, 62, 87, 70, 76, 74, 69, 75, 64, 75, 54, 74, 49, 74, 40, 74, 32, 71, 23, 66, 15, 59, 9, 53, 6" />
And I want:
<polygon points=".48, .06, .43, .07, .38, .09, .34, .12, .29, .16, .24, .22, .22, .30, .22, .44, .23, .50, .23, .65, .25, .72, .28, .77, .32, .82, .35, .86, .40, .90, .43, .92, .50, .93, .55, .91, .62, .87, .70, .76, .74, .69, .75, .64, .75, .54, .74, .49, .74, .40, .74, .32, .71, .23, .66, .15, .59, .09, .53, .06" />
Is there any way to extract numbers, do an operation on them, then replace them in the previous string? I tried to use a regex token in REGEXREPLACE but it doesn't seem to be supported.
=(REGEXREPLACE(A2,"[^[:digit:]]",($/10)))
You cannot apply any function to the string replacement pattern in REGEXREPLACE. In this concrete case, you may simply append a 0 before single-digit numbers and then add dots before each sequence of 1 or more digits:
=REGEXREPLACE(REGEXREPLACE(A1,"\b\d\b", "0$0"), "\d+", ".$0")
See screenshot:
NOTES:
REGEXREPLACE(A1,"\b\d\b", "0$0") - finds a digit not preceded nor followed with a letter/digit/_, and adds a 0 in front of it ($0 is the placeholder for the whole match)
REGEXREPLACE(..., "\d+", ".$0") - prepends one or more digit chunks with a dot.
Related
i have a data structure of a flat array of numbers
[145, 46, 200, 3, 178, 206, 73, 228, 165, 65, 6, 141, 73, 90, 181, 100]
i need to make an array of arrays with a max of 3 items per sub array. So i look at some examples, and Enum.chunk(arr, n) seems like a candidate
so .chuck(arr, 3) says its deprecated, use chuck_every(arr, 3) instead, so i did that and it produces a strange result vs chunk
for example: chunk returns
[[145, 46, 200], [3, 178, 206], [73, 228, 165], [65, 6, 141], [73, 90, 181]]
while chunk_every returns
[145, 46, 200],
[3, 178, 206],
[73, 228, 165],
[65, 6, 141],
[73, 90, 181],
'p']
the main difference being an extra random element which is a string???
it's almost like it converted the element that chunk cuts off and converts it to a string?
Naturally I am expecting the replacement method would have the same output given the same input. Right?
Look at last element: 100. chunk seems to discard that value while chunk_every add it at last element alone. That is the p character you see. Elixir try to show as chars arrays of numbers in the console, as that is its internal representation.
As you can see in the documentation, you can pass :discard as leftover parameter to behave as deprecated chunk function.
https://hexdocs.pm/elixir/Enum.html#chunk_every/2
Enum.chunk_every/4 was designed by this,
actually its a number if you do like this:
[145, 46, 200, 3, 178, 206, 73, 228, 165, 65, 6, 141, 73, 90, 181, 100]
|> Enum.chunk_every(3, 3, [])
|> Enum.each(fn item ->
IO.inspect item, charlists: false
end)
you can find more detail from official discussion:
https://github.com/elixir-lang/elixir/issues/7260
Sometimes it makes sense to implement basic functionality ourselves, instead of looking up the standard library, for the precisely controlled result.
Here is a recursive implementation, that discards the tail.
input =
[145, 46, 200, 3, 178, 206, 73, 228,
165, 65, 6, 141, 73, 90, 181, 100]
defmodule MyEnum do
def chunk_3(input), do: do_chunk_3(input, [])
defp do_chunk_3([e1, e2, e3 | rest], acc),
do: do_chunk_3(rest, [[e1, e2, e3] | acc])
defp do_chunk_3(_, acc), do: Enum.reverse(acc)
end
MyEnum.chunk_3(input)
#⇒ [[145, 46, 200],
# [3, 178, 206],
# [73, 228, 165],
# [65, 6, 141],
# [73, 90, 181]]
This is my training function:
def train(input_layer_data, output_layer_data, dnn, stn):
ds = SupervisedDataSet(len(input_layer_data), len(output_layer_data))
ds.addSample(input_layer_data, output_layer_data)
if 'network' in dnn[stn]:
net_dumped = dnn[stn]['network']
net = pickle.loads(net_dumped)
else:
net = buildNetwork(len(input_layer_data), 50, len(output_layer_data), hiddenclass=SigmoidLayer, outclass = SigmoidLayer)
trainer = BackpropTrainer(net, ds)
trainer.trainEpochs(1)
trnresult = percentError( trainer.testOnClassData(), input_layer_data )
print "epoch: %4d" % trainer.totalepochs, \
" train error: %5.2f%%" % trnresult
return net
I call this function with a single input and output data repeatedly.
And this is the output it generates,
inp=[48, 48, 8, 69, 69, 8, 57, 57, 8, 67, 67, 8, 71, 71, 8, 75, 75, 8, 71, 71, 8]
out=[27, 27, 8, 71, 71, 8, 75, 75, 8, 71, 71, 8, 67, 67, 8, 57, 57, 8, 69, 69, 8]
epoch: 0 train error: 2100.00%
FeedForwardNetwork-152
Modules:
[<BiasUnit 'bias'>, <LinearLayer 'in'>, <SigmoidLayer 'hidden0'>, <SigmoidLayer 'out'>]
Connections:
[<FullConnection 'FullConnection-148': 'bias' -> 'out'>, <FullConnection 'FullConnection-149': 'bias' -> 'hidden0'>, <FullConnection 'FullConnection-150': 'in' -> 'hidden0'>, <FullConnection 'FullConnection-151': 'hidden0' -> 'out'>]
I don't understand such huge error.
The error continues through the whole program(this is for just one call).
How do I reduce the error?
I have a list of the numbers 1,2,3 and 4.
I wish to print them out in the following manner:
1
2
3
4
11
12
13
14
21
22
23
24
31
..and so on.
How is it possible to do?
Thanks
from itertools import product
maximumDigits = 2
digits = '1234'
for l in range(1, maximumDigits + 1):
for n in product(digits, repeat=l):
print(''.join(n))
Gives you:
1
2
3
4
11
12
13
14
21
22
23
24
31
32
33
34
41
42
43
44
Non-itertools solution:
>>> digits = (1, 2, 3, 4)
>>> nums = newNums = list(digits)
# calculate 2-digit numbers
>>> newNums = [n * 10 + m for n in newNums for m in digits]
>>> nums.extend(newNums)
>>> nums
[1, 2, 3, 4, 11, 12, 13, 14, 21, 22, 23, 24, 31, 32, 33, 34, 41, 42, 43, 44]
# calculate 3-digit numbers
>>> newNums = [n * 10 + m for n in newNums for m in digits]
>>> nums.extend(newNums)
>>> nums
[1, 2, 3, 4, 11, 12, 13, 14, 21, 22, 23, 24, 31, 32, 33, 34, 41, 42, 43, 44, 111, 112, 113, 114, 121, 122, 123, 124, 131, 132, 133, 134, 141, 142, 143, 144, 211, 212, 213, 214, 221, 222, 223, 224, 231, 232, 233, 234, 241, 242, 243, 244, 311, 312, 313, 314, 321, 322, 323, 324, 331, 332, 333, 334, 341, 342, 343, 344, 411, 412, 413, 414, 421, 422, 423, 424, 431, 432, 433, 434, 441, 442, 443, 444]
# this repeats for each new digit you want
The relationship between Foo and Bar is through Baz as follows:
class Foo(Model):
# stuff
class Bar(Model)
# stuff
class Baz(Model):
foos = ManyToManyField("Foo")
bar = ForeignKey("Bar")
I basically need to generate the following dict representing the Bars that are related to each Foo through Baz (in dict comprehension pseudo-code):
{ foo.id: [list of unique bars related to the foo through any baz] for foo in all foos}
I can currently generate my data structure with O(N) queries (1 query per Foo), but with lots of data this is a bottleneck, and I need it optimized to O(1) (not a single query per se, but a fixed number of queries irrespective of data size of any of the models), while also minimizing iterations of the data in python.
If you can drop to SQL, you could use the single query (the appname should prefix all the tables names):
select distinct foo.id, bar.id
from baz_foos
join baz on baz_foos.baz_id = baz.id
join foo on baz_foos.foo_id = foo.id
join bar on baz.bar_id = bar.id
baz_foos is the many-to-many table Django creates.
#Alasdair's solution is possibly/probably more readable (although if you're doing this for performance reasons that might not be most important). His solution uses exactly two queries (which is hardly a difference). The only problem I see is if you have a large number of Baz objects since the generated sql looks like this:
SELECT "foobar_baz"."id", "foobar_baz"."bar_id", "foobar_bar"."id"
FROM "foobar_baz"
INNER JOIN "foobar_bar" ON ("foobar_baz"."bar_id" = "foobar_bar"."id")
SELECT
("foobar_baz_foos"."baz_id") AS "_prefetch_related_val",
"foobar_foo"."id"
FROM "foobar_foo"
INNER JOIN "foobar_baz_foos" ON ("foobar_foo"."id" = "foobar_baz_foos"."foo_id")
WHERE "foobar_baz_foos"."baz_id" IN (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34,
35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54,
55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74,
75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94,
95, 96, 97, 98, 99, 100, 101)
If you have only a few Bar's and a few hundred Foo's, I would do:
from django.db import connection
from collections import defaultdict
# foos = {f.id: f for f in Foo.objects.all()}
bars = {b.id: b for b in Bar.objects.all()}
c = connection.cursor()
c.execute(sql) # from above
d = defaultdict(set)
for f_id, b_id in c.fetchall():
d[f_id].add(bars[b_id])
Using select_related and prefetch_related, I think you can build the required data structure with 2 queries:
out = {}
bazes = Baz.objects.select_related('bar').prefetch_related('foos')
for baz in bazes:
for foo in baz.foos.all():
out.setdefault(foo.id, set()).add(baz.bar)
The values of the output dictionary are sets, not lists as in your question, to ensure uniqueness.
Hi i have a bar chart made with g.raphael
The 47 in brackets in bold i am looking to place an if else statement in there. it seems to cause errors if i do so. Any help?
paper.barchart(-5, -20, 480, 260, [(47), 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52], {colors:["RGB(45,58,65)","RGB(217,31,53)","RGB(217,31,53)","RGB(217,31,53)","RGB(217,31,53)","RGB(217,31,53)","RGB(205,148,43)","RGB(205,148,43)","RGB(205,148,43)","RGB(205,148,43)","RGB(73,102,20)","RGB(73,102,20)","RGB(73,102,20)","RGB(73,102,20)","RGB(73,102,20)","RGB(0,99,186)","RGB(0,99,186)","RGB(0,99,186)","RGB(0,99,186)"]})
I've never tried a nested if block there, but you can define your data array outside of the instantiation, using if statements to build that according to your conditions, and then using your array variable in the call:
var dataArray = [...];
var colorArray = [...];
paper.barchart(-5, -20,
480, 260,
dataArray,
{
colors : colorArray
});