kuchaale

kuchaale

import xarray as xr
import numpy as np

# create an example dataset
da = xr.DataArray(np.random.rand(10,30,40), dims=['time', 'lat', 'lon'])

# define a function to compute a linear trend of a timeseries
def linear_trend(x):
    pf = np.polyfit(x.time, x, 1)
    # we need to return a dataarray or else xarray's groupby won't be happy

kuchaale

kuchaale

kuchaale

# implement my own aggregation downsampling function

from itertools import product
import numpy as np
import xarray as xr

def aggregate(data, factor=2, mean=True):
    ndim = data.ndim
    shape = data.shape
    # promote single value to list

kuchaale

kuchaale

kuchaale

Project Name

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Installation

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Usage

kuchaale

"""
pysom.py is a python script for self-organizing map (SOM).
"""

import numpy as np
import matplotlib.pyplot as plt

# learning paras.
loop = 1000       # def: 1000
alpha_base = 1.0  # def: 1.0

kuchaale

import pandas as pd
import matplotlib.pyplot as plt
import seaborn
from sklearn.cluster import KMeans
import numpy as np
from scipy.spatial.distance import cdist, pdist

def eblow(df, n):
    kMeansVar = [KMeans(n_clusters=k).fit(df.values) for k in range(1, n)]
    centroids = [X.cluster_centers_ for X in kMeansVar]