pablomm

import torch
from diffusers import StableDiffusionImg2ImgPipeline
from ovam import StableDiffusionHooker
from ovam.utils import set_seed
import requests
from io import BytesIO
import matplotlib.pyplot as plt
from PIL import Image

device = "cuda"

pablomm

from typing import Union

import pandas as pd

# Load dataset with codes order by probability
URL = ('https://gist.githubusercontent.com/pablomm/'
       '99cb95ddf65a1001a3c98312418254a0/raw/'
       '259deec38e3e1e3da72d2f6b8de8c0690b4d28f7/'
       'gistfile1.txt')

pablomm

pablomm

"""
Outlier detection with Local Outlier Factor
===========================================

Shows the use of the Local Outlier Factor to detect outliers in the octane
dataset.
"""

# Author: Pablo Marcos Manchón
# License: MIT

pablomm

library(fda)
library(fda.usc)

# Random data and labels
data("growth")

girls_data <- t(matrix(growth$hgtf, 31, 54))
boys_data <- t(matrix(growth$hgtm, 31, 39))
ages <- growth$age
girls <- fdata(girls_data, ages)

pablomm

pablomm

Examples of fda.registration

Shift Registration

• shift_registration1.py: Periodic registration
• shift_registration2.py: Non-periodic registration
• landmark_shift.py: Align using landmarks

Interpolation

• curve_interpolation.py: Interpolation of curves R -> R^n
• surface_interpolation.py: Surfaces R^2 -> R^n

pablomm

Golden Ratio

D3 interactive plot based in the Numberphile video 'The Golden Ratio(why it is so irrational)'

The result is on bl.ocks. Enjoy it!

3 Aug 2018, Pablo Marcos

pablomm

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pablomm

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