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#! /usr/bin/env python | |
import tarfile | |
import re | |
import os | |
import subprocess | |
def find_tar_files(top_dir, exclude): | |
tar_files = [] | |
for root, dirs, files in os.walk(top_dir): |
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from math import pi, cos, sin, sinh, sqrt, asinh, atan2, fabs | |
class LorentzVector(object): | |
def __init__(self, x, y, z, T, r2=None): | |
self.x = x | |
self.y = y | |
self.z = z | |
self.T = T | |
if r2: |
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import numpy as np | |
class MaskedUprootTree(): | |
def __init__(self, tree, mask=None): | |
if isinstance(tree, MaskedUprootTree): | |
self.tree = tree.tree | |
self._mask = tree._mask | |
else: | |
self.tree = tree |
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import pandas as pd | |
_interval_regex = r"^(?P<open>[[(])" | |
_interval_regex += r"(?P<low>-inf|[0-9][.0-9]*)" | |
_interval_regex += r"\s*,\s*" | |
_interval_regex += r"(?P<high>\+?inf|[0-9][.0-9]*)" | |
_interval_regex += r"(?P<close>[)\]])$" | |
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def flatten_to_wideform(df, mask_column=None, max_objects=None): | |
# get the list columns | |
lst_cols = [col for col, dtype in df.dtypes.items() | |
if pd.api.types.is_object_dtype(dtype) | |
and df[col].head(10).apply(lambda x: isinstance(x, (list, np.ndarray, tuple))).all() | |
] | |
if not lst_cols: | |
return df | |
# all columns except `lst_cols` |
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edit_path () | |
{ | |
local tmpfile=$(mktemp); | |
local variable="${1:-PATH}"; | |
tr ':' '\n' <<< "${!variable}" > "$tmpfile"; | |
"$EDITOR" "$tmpfile"; | |
export ${variable}="$(tr '\n' : < "$tmpfile"| sed -e 's/:$//' )" | |
} |