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from shapely.geometry import mapping
from shapely.ops import polygonize
import fiona

def polyline_to_polygon(input_file, output_file):
    polylines = fiona.open(input_file)
    geom = [x['geometry'] for x in polylines]
    coords = [x['coordinates']for x in geom[:-1]]
    schema = {'geometry': 'Polygon','properties': {'id': 'int'}}
    with fiona.open(output_file, 'w', 'ESRI Shapefile', schema) as c:

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import pandas as pd
import datetime
import os

def make_raw_files(path_to_raw_df, output_folder):
    raw_df = pd.read_pickle(path_to_raw_df)
    os.chdir(output_folder)
    timestamp = datetime.datetime(2013,2,1,0,17,59)
    half_hour_delta = datetime.timedelta(0,1800)
    final_timestamp = datetime.datetime(2013,2,28,23,48)

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import pandas as pd
from datetime import datetime

def month_his_to_df(his_file_path, resample=True):
    his_columns = ['date_time', 'Tp', 'dirp', 'sprp', 'Tz', 'Hm0', 'TI', 'T1', 
                   'Tc', 'Tdw2', 'Tdw1', 'Tpc', 'nu','eps','QP','Ss','TRef',
                   'TSea','Bat']
    month_dataframe = pd.io.parsers.read_csv(his_file_path, names = his_columns)
    date_time_array = []
    for date_time_string in month_dataframe['date_time'].values:

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# -*- coding: utf-8 -*-
"""
Created on Tue Oct 21 15:49:56 2014

@author: le12jm
"""

import os
import numpy as np
import matplotlib.cm as cm

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// Use Gists to store code you would like to remember later on
console.log(window); // log the "window" object to the console

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function output_spectra = datawell_raw_to_diwasp(file_path, output_dir, visible)
% read the raw file data into a matrix stripping signal quality info
try
    raw_matrix = csvread(file_path);
catch err
    disp('Problem with RAW file')
    output_spectra = 0;
    return
end
raw_matrix = raw_matrix/100;

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% An example file for importing datawell raw displacements into wafo
% ( http://www.maths.lth.se/matstat/wafo/ ) 

function [S,mean_wave_dir_deg_peak_freq, Hm0, Tp] = datawell_raw_to_wafo(file_path)
%displacements=csvread(file_path);
displacements=dlmread(file_path);
heave=displacements(:,2)/100;
north=-1*displacements(:,3)/100;
west=displacements(:,4)/100;
%length of the time series

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import os
import matplotlib.pyplot as plt
import pandas as pd
fig = plt.figure(figsize=(20,10), dpi=100)
from datetime import datetime
os.chdir('/path/to/buoy_name/year/')

date_index = []
battery_status = []
months = os.listdir('.')

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