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How to apply a function to every foreach result?


How to apply a function to every foreach result?

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How to apply a function to every foreach result?
Tag : php , By : user98986
Date : November 23 2020, 01:01 AM

it helps some times I think that array_walk is what you need: http://php.net/manual/en/function.array-walk.php
array_walk($blocks, 'some_function');

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PHP- Get each value of an associative array in a foreach loop, then apply a function and echo the result


Tag : php , By : Alex Bartzas
Date : March 29 2020, 07:55 AM
will be helpful for those in need In this context, foreach($list_links as $link), $link is not the url, it is an array of urls. Try a nested foreach instead:
foreach ($list_link as $link_array) {
    foreach ($link_array as $link) {
        DoWork($link, $db_connect);
    }
}
foreach ($list_link as $key=>$link_array) {
    foreach ($link_array as $link) {
        DoWork($link, $db_connect);
        echo 'this url is from the '.$key.' list';
    }
}
$list_links = array(
    0 => array
        (
            "http://test.com/1/",
            "http://test.com/2/"
        ),
    1 => array
        (
            "http://test.com/3/",
            "http://test.com/4/"
        )
);
$array = array ('key' => 'value')
$list_links = array(
    array("http://test.com/1/", "http://test.com/2/"),
    array("http://test.com/3/", "http://test.com/4/")
);

Apply Function foreach Pixel in Numpy Array


Tag : python , By : Brian
Date : March 29 2020, 07:55 AM
I wish did fix the issue. I have a function like: , Code:
import math
import numpy as np
np.random.seed(1)

# FAKE-DATA
img = np.random.randint(0,255,size=(4,4,3))
print(img)

# LOOP APPROACH
def calcChromaFromPixel(red, green, blue):
    r = int(red)
    g = int(green)
    b = int(blue)
    return math.sqrt(math.pow(r - g, 2) +
                     math.pow(r - b, 2) +
                     math.pow(g - b, 2))

bla = np.zeros(img.shape[:2])
for a in range(img.shape[0]):
    for b in range(img.shape[1]):
        bla[a,b] = calcChromaFromPixel(*img[a,b])
print('loop')
print(bla)

# VECTORIZED APPROACH
print('vectorized')
res = np.linalg.norm(np.stack(
        (img[:,:,0] - img[:,:,1],
         img[:,:,0] - img[:,:,2],
         img[:,:,1] - img[:,:,2])), axis=0)
print(res)
[[[ 37 235 140]
  [ 72 137 203]
  [133  79 192]
  [144 129 204]]

 [[ 71 237 252]
  [134  25 178]
  [ 20 254 101]
  [146 212 139]]

 [[252 234 156]
  [157 142  50]
  [ 68 215 215]
  [233 241 247]]

 [[222  96  86]
  [141 233 137]
  [  7  63  61]
  [ 22  57   1]]]
loop
[[ 242.56545508  160.44313634  138.44132331   97.21111048]
 [ 246.05283985  192.94040531  291.07730932   98.66103588]
 [ 124.99599994  141.90842117  207.88939367   17.20465053]
 [ 185.66636744  133.02631319   77.82030583   69.29646456]]
vectorized
[[ 242.56545508  160.44313634  138.44132331   97.21111048]
 [ 246.05283985  192.94040531  291.07730932   98.66103588]
 [ 124.99599994  141.90842117  207.88939367   17.20465053]
 [ 185.66636744  133.02631319   77.82030583   69.29646456]]

How can I apply the Result.withDefault function to a function that produces a Result


Tag : json , By : Adam May
Date : March 29 2020, 07:55 AM
should help you out Given that you have a function which returns an empty Item, for example emptyItem, you just need to perform the steps you've described:
Wrap the output of decodeItem with a Result.withDefault The empty Item would be the first argument to Result.withDefault
decodeItem : D.Value -> Item
decodeItem value =
    Result.withDefault emptyItem (D.decodeValue itemDecoder value)
emptyItem : Item
emptyItem = Item "" "" 0 ""

Apply forEach function for array like object


Tag : javascript , By : Dean
Date : March 29 2020, 07:55 AM
it fixes the issue files is of type File‚ÄčList and it doesn't have a forEach extension method. You could spread it within an [] to convert it to an array of files:
[...files].forEach(file => { /* do something */ })
const filesToStore = [...files]

How can I iterate through all rows of a dataframe to apply a look up function to a string value and apply the result to


Tag : python , By : Alan Little
Date : March 29 2020, 07:55 AM
seems to work fine First off, apply and iterrows are slow, so try not to use them, ever.
What I usually do in this situation is to create a pair of forward and backward dicts:
forward = {'east': east,
           'west': west,
           'south': south}

backward = {x:k for k,v in forward.items() for x in v}
df1['Region'] = (df1['State'].map(backward)
                    .fillna(df1['City'].map(backward))
                    .fillna('other')
                )
  Last Name First Name  Code    Deparment           City State Region
0     SMITH        TOM    12     Research       NEW YORK    NY   east
1     JONES       DICK    34   Management         BOSTON    MA   east
2    WILSON      HARRY    56  Maintenance  SAN FRANCISCO    CA   west
3     DOYLE    MICHAEL    78    Marketing         DALLAS    TX  south
4  ANDERSON      KEVIN    90           IT        DETROIT    MI  other
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