heartonbit

def predict_score(model_pickle_path, target_filepath, n_meta_columns, n_feature_columns):
    """
    model_pickle_path : 
    target_filepath : target gene expression examples with meta
    n_meta_columns : number of meta columns
    n_feature_columns : number of feature(gene)s
    return score DataFrame
    """
    df0 = pd.read_csv(target_filepath, header=-1)
    x_header = df0.iloc[:, 0:n_meta_columns]

heartonbit

def cosine_distances(X, Y):
    """
    X : Target example score vector DataFrame with inst_id as the first column
    Y : All example score vector DataFrame with inst_id as the first column
    return pair-wise cosine distance DataFrame
    """
    from sklearn.metrics import pairwise
    x_header = X.iloc[:, 0].values
    X = X.iloc[:, 1:]
    y_header = Y.iloc[:, 0].values

heartonbit

for idx in range(3,351):
    tablename = "table_{0}".format(idx)
    print(tablename)
    !bq rm -f -t $tablename

heartonbit

CREATE TEMPORARY FUNCTION do(x float64, y float64)
RETURNS float64
LANGUAGE js AS """
  function add(a, b) {
    return a + b;
  }
  return add(x, y)
""";
with data as (
  select *

heartonbit

https://gist.github.com/application2000/73fd6f4bf1be6600a2cf9f56315a2d91

sudo apt-get update -y && \
sudo apt-get upgrade -y && \
sudo apt-get dist-upgrade -y && \
sudo apt-get install build-essential software-properties-common -y && \
sudo add-apt-repository ppa:ubuntu-toolchain-r/test -y && \
sudo apt-get update -y && \
sudo apt-get install gcc-7 g++-7 -y && \
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-7 60 --slave /usr/bin/g++ g++ /usr/bin/g++-7 && \