tommylees112

tommylees112

import calplot

cfg_date_ranges = {    "test_date_ranges": [
      [
        "2011-01-01",
        "2011-12-31"
      ],
      [
        "2020-01-01",
        "2020-12-31"

tommylees112

conda create -n stan2 python=3.7 --yes
conda activate stan2
conda install -c anaconda gcc_linux-64 gxx_linux-64 --yes
## FOR MAC:
# conda install -c anaconda clang_osx-64 clangxx_osx-64 --yes
conda install -c conda-forge numpy pandas scipy cython ipython jupyterlab matplotlib freetype --yes
python -m pip install --upgrade pip
pip install pystan==2.19.0.0
conda install -c conda-forge arviz --yes

tommylees112

conda create -n stan --yes
conda activate stan
conda install pip --yes

# Install httpstan from source (this will take a while).
pip install -v git+https://github.com/tillahoffmann/httpstan@pip
# Install pystan.
pip install 'pystan>=3'
# Try a dummy program (this should report build and sampling progress).
python -c 'import stan; stan.build("parameters { real x; } model { x ~ normal(0, 1); }").sample()'

tommylees112

# For Macbook Air 2020 (M1 Chip)

First you need to install xcode from the app store

Then you can run:

xcode-select --install

See Here for why

tommylees112

conda create -n h2ox --yes 
conda activate h2ox
conda install pytorch torchvision cudatoolkit -c pytorch --yes
conda install -c conda-forge jupyterlab seaborn loguru --yes
conda install -c conda-forge netcdf4 numba tqdm tensorboard ipython pip ruamel.yaml xarray descartes scikit-learn black mypy xskillscore cdsapi cftime --yes
# conda install -c alex-marty sacred
pip install sacred
pip install geopandas

tommylees112

from matplotlib import cm
from matplotlib.colors import ListedColormap, LinearSegmentedColormap
import seaborn as sns

n_unique_vals = 5
colors = cm.get_cmap('viridis', n_unique_vals)(np.linspace(0, 1, n_unique_vals))
sns.palplot(colors)

# create colormap and mappable for colorbar construction
cmap = LinearSegmentedColormap.from_list("RANDOM", colors, N=n_pcs)

tommylees112

conda create -n gdal --yes
conda activate gdal
conda install -c conda-forge gdal --yes
conda install -c conda-forge rioxarray geopandas --yes
conda install -c conda-forge netcdf4 xarray ipython six scipy scikit-learn seaborn matplotlib jupyterlab --yes

tommylees112

import pandas as pd
from pathlib import Path
import numpy as np
from datetime import datetime


# CHANGE THIS >>>>>>>>>
DATA_DIR = "/Users/tommylees/Downloads"
USER = "kouji"
FIRST_ROW_TO_READ = 13  # remember it is 0-based indexing

tommylees112

from pathlib import Path
from cmdstanpy import cmdstan_path, CmdStanModel, CmdStanMCMC
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from typing import Dict
import arviz as az


model_dir = Path("stan_code")