Source code for k1lib.imports

# AUTOGENERATED FILE! PLEASE DON'T EDIT
"""These are pretty standard imports that I always
do. I put it here so that I can do::

    from k1lib.imports import *

and everything will be in place"""
import torch; from torch import nn, optim
import torch.nn.functional as F, torch.utils.data as data
import matplotlib.pyplot as plt, matplotlib as mpl
import numpy as np, dill as pickle, multiprocessing as mp, concurrent.futures as futures
import math, os, time, sys, random, logging, traceback, re, typing, glob, warnings
import dill, json, inspect, xml
import functools; from functools import partial, lru_cache
import contextlib; from contextlib import contextmanager
from collections import deque
from typing import List, Tuple, Callable, Union, Iterator, Set, Dict, Any
import k1lib; from k1lib import schedule, graphEqn, mo, kdata, knn, fmt, selector,\
viz, Cbs, settings, cli
from k1lib.cli import *; k1 = k1lib
for e in cli._scatteredClis: globals()[e.__name__] = e
if "py_k1lib_in_applyMp" not in os.environ: k1lib.dontWrap()
plt.rcParams['figure.dpi'] = 100
plt.rcParams["animation.html"] = "jshtml"
from math import e, pi; inf = float("inf"); # this section is for constants
h = 6.62607015e-34; hbar = h/(2*pi); Na = 6.0221408e23; kb = 1.380649e-23
c = 299_792_458; qe = 1.60217663e-19; me = 9.1093837e-31; mn = 1.67262192e-27
e0 = 8.85418782e-12; Dal = u = 1.6605390666e-27; R = 8.3145; sb = 5.670374e-8
if settings.startup.or_patch:
    try:
        import forbiddenfruit; #forbiddenfruit.reverse(np.ndarray, "__or__") # old version
        oldOr = np.ndarray.__or__
        def _newNpOr(self, v):
            if isinstance(v, BaseCli): return NotImplemented
            return oldOr(self, v)
        forbiddenfruit.curse(np.ndarray, "__or__", _newNpOr)
        # patching all numpy's numeric types
        for _type in list(np.__dict__.keys()) | apply(lambda s: getattr(np, s)) | filt(inspect.isclass) | filt(lambda x: issubclass(x, np.number)) | ~filt(lambda x: issubclass(x, np.integer)):
            _oldOr = _type.__or__
            def _typeNewOr(self, v):
                if isinstance(v, BaseCli): return NotImplemented
                return _oldOr(self, v)
            forbiddenfruit.curse(_type, "__or__", _typeNewOr)
            #forbiddenfruit.reverse(_type, "__or__") # old version
    except Exception as e:
        warnings.warn(f"Tried to patch __or__ operator of built-in type `np.ndarray` but can't because: {e}")
try:
    import pandas as pd
    if settings.startup.or_patch:
        try:
            import forbiddenfruit
            oldPdOr = pd.core.series.Series.__or__
            def _newPdOr(self, v):
                if isinstance(v, BaseCli): return NotImplemented
                return oldPdOr(self, v)
            #forbiddenfruit.curse(pd.core.series.Series, "__or__", _newPdOr)
            forbiddenfruit.reverse(pd.core.series.Series, "__or__")
        except Exception as e:
            warnings.warn(f"Tried to patch __or__ operator of built-in type `pd.core.series.Series` but can't because: {e}")
except ImportError as e: pass
def dummy():
    """Does nothing. Only here so that you can read source code of this file
and see what's up."""
    pass
try:
    import torchvision as vision
    import torchvision.datasets as tvDs
    import torchvision.transforms as tf
except: pass
try:
    import IPython
except: pass