Python Spread

Python Spread

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# Import Image from wand.image module
# Read image using Image() function
with Image(filename = "koala.jpeg" ) as img:
    # Generate spread image using spread() function
    img.save(filename = "spreadkoala.jpg" )
# Import Image from wand.image module
# Read image using Image() function
with Image(filename = "koala.jpeg" ) as img:
    # Generate spread image using spread() function
    img.save(filename = "spreadkoala2.jpg" )
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Got It !
Spread replaces each pixel with the random pixel value found nearby. spread() function is used to apply Spread effect to the image. The size of the area to search for a new pixel can be controlled by defining a radius.
Example 2: Increase radius value in spread() method.
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Distance a pixel can be displaced from source. Default value is 0.0, which will allow ImageMagick to auto select a radius.
Interpolation method. Only available with ImageMagick-7. Optional parameter.

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Statistical Functions in Python | Set 2 ( Measure of Spread)
Difficulty Level :
Easy Last Updated :
10 Feb, 2020
# Python code to demonstrate the working of
# importing statistics to handle statistical operations
li = [ 1.5 , 2.5 , 2.5 , 3.5 , 3.5 , 3.5 ]
# using variance to calculate variance of data
print ( "The variance of data is : " ,end = "")
# using pvariance to calculate population variance of data
print ( "The population variance of data is : " ,end = "")
# Python code to demonstrate the working of
# importing statistics to handle statistical operations
li = [ 1.5 , 2.5 , 2.5 , 3.5 , 3.5 , 3.5 ]
# using stdev to calculate standard deviation of data
print ( "The standard deviation of data is : " ,end = "")
# using pstdev to calculate population standard deviation of data
print ( "The population standard deviation of data is : " ,end = "")
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Measure of spread functions of statistics are discussed in this article.
1. variance() :- This function calculates the variance i.e measure of deviation of data, more the value of variance, more the data values are spread . Sample variance is computed in this function, assuming data is of a part of population. If passed argument is empty, StatisticsError is raised.
2. pvariance() :- This function computes the variance of the entire population . The data is interpreted as it is of the whole population. If passed argument is empty, StatisticsError is raised.
3. stdev() :- This function returns the standard deviation ( square root of sample variance ) of the data. If passed argument is empty, StatisticsError is raised.
4. pstdev() :- This function returns the population standard deviation ( square root of population variance ) of the data. If passed argument is empty, StatisticsError is raised.
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October 15, 2021 March 17, 2019 by jbencook
const oldObject = { hello : 'world' , foo : 'bar' }
const newObject = { ... oldObject , foo : 'baz' }
old_dict = { 'hello' : 'world' , 'foo' : 'bar' }
new_dict = { ** old_dict , 'foo' : 'baz' }

new_dict

# Expected result
# {'hello': 'world', 'foo': 'baz'}
const oldArray = [ 1 , 2 , 3 ]
const newArray = [ ... oldArray , 4 , 5 ]
old_list = [ 1 , 2 , 3 ]
new_list = [ * old_list , 4 , 5 ]

new_list

# Expected result
# [1, 2, 3, 4, 5]

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Say you have a dictionary that you want to both copy and update. In JavaScript, this is a common pattern that gets its own syntax, called the object spread operator :
After running this snippet, newObject will be { hello: 'world', foo: 'baz' } . Turns out, you can also do this in Python since version 3.5:
You can refer to the double asterisk ** as “dictionary unpacking”. You sometimes see it for passing extra keyword arguments into a function.
In JavaScript, you can also use spread operators in arrays to make updated copies:
This would make newArray an updated copy with [ 1, 2, 3, 4, 5 ] .
We can replicate the behavior for lists in Python:
This is somewhat less useful since you can also write old_list + [4, 5] , which doesn’t exist in JavaScript. But the spread operator approach is still a cool trick to know and being comfortable with basic data structures in Python is important! You can refer to the single asterisk * as “iterable unpacking” or “splat” .

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