seumasmorrison

seumasmorrison

import pandas as pd
from datetime import datetime
from scipy.stats.stats import pearsonr

his_columns = ['date_time', 'tp', 'dirp', 'sprp', 'tz', 'hm0', 'ti', 't1', 
               'tc', 'tdw2', 'tdw1', 'tpc', 'nu','eps','qp','ss','tref','tsea',
               'bat']

hiw_columns = ['date_time','% no reception errors','hmax','tmax','h1_10',
               't1_10','h1_3','t1_3','Hav','Tav','Eps','#Waves']

seumasmorrison

ctrl_interface=DIR=/var/run/wpa_supplicant GROUP=netdev
update_config=1
network={
ssid="BTHub3-****"
key_mgmt=WPA-PSK
proto=RSN
group=CCMP TKIP
pairwise=CCMP TKIP
proto=RSN
psk="********"

seumasmorrison

def dedupe_df(df):
    df['index'] = df.index
    df = df.drop_duplicates(subset='index')
    df = df.drop("index",1)
    return df

seumasmorrison

import os
import pandas as pd
os.chdir('D://J_Morrison//Data//Datawell//Siadar_HebMarine1')
wave_height_dfs = []
for year in os.listdir('.'):
    os.chdir(year)
    for month in os.listdir('.'):
        os.chdir(month)
        wave_height_dfs.append(pd.read_hdf('buoy_data.h5','wave_height'))
        os.chdir('..')

seumasmorrison

import pandas as pd

data_frame = pd.io.parsers.read_csv('time-series.csv',index_col = 0, names=['index','heave'])
_max = [[5, 259.0]]
indexes = [x[0] for x in _max ]
index = data_frame.index
timestamps = [index[z] for z in indexes]
#['2011-12-30 00:00:04']
print data_frame.ix[timestamps]
#                     heave

seumasmorrison

/usr/local/lib/python3.2/subprocess.py:389: RuntimeWarning: The _posixsubprocess module is not being used. Child process reliability may suffer if your program uses threads.
  "program uses threads.", RuntimeWarning)
basedirlist is: ['/usr/local', '/usr']
============================================================================
BUILDING MATPLOTLIB
            matplotlib: 1.2.x
                python: 3.2.3 (default, Sep  6 2012, 14:51:03)  [GCC 4.1.2
                        20080704 (Red Hat 4.1.2-46)]
              platform: linux2

seumasmorrison

# Python modules for taking Cumulus ( sandaysoft.com ) logs into a Pandas
# ( pandas.pydata.org ) DataFrame, and using the date and time columns to
# create a DateTimeIndex for the DataFrame and sort upon it.

import pandas as pd
import os
import glob
from datetime import datetime

log_path = 'D:\\log_files_folder'

seumasmorrison

import os
import glob
import pandas as pd
from datetime import datetime

# Example below assumes following folder hierarchy D:\Buoy_Data\Buoy_Name\Year\Month\
buoy_names = ['Buoy_Name']
buoy_path = 'D:\\Buoy_Data\\'

his_columns = ['date_time', 'Tp', 'dirp', 'sprp', 'Tz', 'Hm0', 'TI', 'T1', 'Tc', 

seumasmorrison

{
 "metadata": {
  "name": "Basemap HebMarine"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {