<commit_before># -*- coding: utf-8 -*-
"""
.. module:: TS
   :synopsis: Deal with MT time series 

.. moduleauthor:: <NAME> <<EMAIL>>
"""

#==============================================================================
# Imports
#==============================================================================
import os
import datetime
import calendar

import numpy as np
import pandas as pd
import scipy.signal as signal

import mtpy.utils.gis_tools as gis_tools
import mtpy.processing.filter as mtfilter

import matplotlib.pyplot as plt

#==============================================================================

#==============================================================================
class MT_TS(object):
    """
    MT time series object that will read/write data in different formats
    including hdf5, txt, miniseed.
    
    The foundations are based on Pandas Python package.
    
    The data are store in the variable ts, which is a pandas dataframe with
    the data in the column 'data'.  This way the data can be indexed as a
    numpy array:
        
        >>> MT_TS.ts['data'][0:256]
        
        or
        
        >>> MT_TS.ts.data[0:256]
        <commit_msg>added a filter module with simple filters and a gis tool for position<commit_after># -*- coding: utf-8 -*-
"""
.. module:: TS
   :synopsis: Deal with MT time series 

.. moduleauthor:: <NAME> <<EMAIL>>
"""

#==============================================================================
# Imports
#==============================================================================
import os
import datetime
import calendar

import numpy as np
import pandas as pd
import scipy.signal as signal

import gis_tools as gis_tools
import ts_filter as mtfilter

import matplotlib.pyplot as plt

#==============================================================================

#==============================================================================
class MT_TS(object):
    """
    MT time series object that will read/write data in different formats
    including hdf5, txt, miniseed.
    
    The foundations are based on Pandas Python package.
    
    The data are store in the variable ts, which is a pandas dataframe with
    the data in the column 'data'.  This way the data can be indexed as a
    numpy array:
        
        >>> MT_TS.ts['data'][0:256]
        
        or
        
        >>> MT_TS.ts.data[0:256]
        
{'fraction_non_alphanumeric': 0.3215169002473207, 'fraction_numerical': 0.008244023083264633, 'mean_word_length': 3.78698224852071, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 21, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '6369639', 'n_tokens_mistral': 616, 'n_tokens_neox': 569, 'n_words': 220}