Mårten Wasteson's blog: juli 2022

fredag 22 juli 2022

From a list, count how many numbers are within the standard deviation from the mean. (Python)

heights = [180, 172, 178, 185, 190, 195, 192, 200, 210, 190]

height_sum = sum(heights)
mean = height_sum / len(heights)

# **2 makes negatives (heights less than the mean) become positive.
diff_list = [(x - mean) ** 2 for x in heights]
variance = sum(diff_list) / len(heights)

# We get the square root in order to get back the original units.
standard_deviation = variance **0.5

# Now we just need to find out how many heights are within the 
# standard deviation from the mean.
count = 0
upper_lim = mean + standard_deviation
lower_lim = mean - standard_deviation

# Count how many heights are within the 
# standard deviation from the mean.
for height in heights:
    if lower_lim < height < upper_lim:
        count += 1
        
print(count)






''' Or as a class, initiated with the heights list: '''

class Std():
    
    def __init__(self, data: list):
        self.data = data
        self.mean = self._get_mean()
        self.var = self._get_variance()
        self.std = self._get_std_from_var()
        
        self.upper_lim = self.mean + self.std
        self.lower_lim = self.mean - self.std
    
        self.in_range = lambda x: self.lower_lim < x < self.upper_lim
        self.count_within = len(list(filter(self.in_range, self.data)))

    def _get_mean(self):
        return sum(self.data) / len(self.data)

    def _get_variance(self):
        diff_list = [(x - self.mean) ** 2 for x in self.data]
        return sum(diff_list) / len(diff_list)

    def _get_std_from_var(self):
        return self.var **0.5

std = Std(heights)
print(std.count_within)

måndag 11 juli 2022

OpenArtViewer

I've made an art viewer program in Unity. I'm now working on database update automatization in Python. That is because the files with art information provided are updated frequently.

OpenArtViewer uses the National Gallery of Art Open Data API and data from Metropolitan Museum of Art. The included SQLite database has stored info about the artworks in public domain (100K+) including image links to the artworks on the NGA and MM servers.

From the GUI you can search type of art and by title, year, artist. To the left there's a scroll bar with the results as thumbnails. These can be clicked to get more information and a higher resolution version of the artwork in the big panel to the right. A high resolution image can then be downloaded.

Download this program (Windows) https://wartem.se/files/OpenArtViewer.zip

National Gallery of Art

https://www.nga.gov/open-access-images.html

Metropolitan Museum of Art

https://www.metmuseum.org/about-the-met/policies-and-documents/image-resources

lördag 9 juli 2022

Flask - Absolute basic client input and render

The following example shows how you can handle input with Flask and update pages, in this case with the user input sent back to the client.

I'm making this as short as possible.

Requirements: pip install Flask

Implementation:

1. In your project root dir create: A file named app.py

2. In your project root dir create: A folder named "templates" and inside a file named "index.html"

index.html

<html lang="en"> 
  <head> 
  <title>Flask Basic Example</title>
  </head>  
  <body>    
  <h1>Flask Post: {{ text_to_show }}</h1>    
  <form action="/" method="POST">      
  <input type="text" name="content" />     
  <input type="submit" />    
  </form>  
  </body></html>

app.py

from flask import Flask, render_template, request
app = Flask(__name__)

@app.route("/", methods=['GET', 'POST'])
def index():
    if request.method == 'POST':
        user_input = request.form['content']
        return render_template("index.html", text_to_show=user_input)
    return render_template("index.html")

if __name__ == "__main__":
    app.run(debug=True, port=5000)

How it's used: Run app.py and go to http://127.0.0.1:5000 in your browser. Type some input, press send and the server will update the HTML with your input in a HTML paragraph. The Internet is full of extensive guides and tutorials. Sometimes you just want a quick example.

Python Virtual Environment Setup

Working in a virtual environment is easy to setup and makes life easier thanks to the project isolation and dependency management.

Run once:

py -m pip install --user virtualenv

Run in project folder:

py -m venv env

Run in project folder:

.\env\Scripts\activate

Done! Happy coding.