In [58]:
from matplotlib import pyplot as plt
from astropy.io import fits
import numpy as np
from scipy import ndimage
import re
import glob
import datetime
import os
import seaborn
from astropy.utils.data import get_file_contents
import astropy.units as u
from astropy.time import Time
from astropy.utils.console import ProgressBar
import pandas as pd
%matplotlib inline
plt.style.use('ggplot')
from IPython.utils import io
In [2]:
# Load the PANOPTES module dir
import sys
sys.path.append('../')
# For development
%load_ext autoreload
%autoreload 2
from panoptes.utils.images import *
INFO:PanoptesLogger:
INFO:PanoptesLogger:********************************************************************************
INFO:PanoptesLogger:
DEBUG:PanoptesLogger:Adding warning logging to: PanError
DEBUG:PanoptesLogger:Adding warning logging to: SerialData
DEBUG:PanoptesLogger:Adding warning logging to: PanStateMachine
DEBUG:PanoptesLogger:Adding warning logging to: AbstractCamera
DEBUG:PanoptesLogger:Adding warning logging to: Observation
DEBUG:PanoptesLogger:Adding warning logging to: Target
DEBUG:PanoptesLogger:Adding warning logging to: Scheduler
DEBUG:PanoptesLogger:Adding warning logging to: Observatory
DEBUG:PanoptesLogger:Adding warning logging to: Panoptes
DEBUG:PanoptesLogger:Adding warning logging to: Messaging
DEBUG:PanoptesLogger:Adding warning logging to: EnvironmentalMonitor
DEBUG:PanoptesLogger:Adding warning logging to: Webcams
DEBUG:PanoptesLogger:Adding warning logging to: PanSensors
In [80]:
dir1 = '/var/panoptes/images/20150920/raw/01_2[0-4][0-9].cr2'
In [69]:
cr2_files = glob.glob(dir1)
cr2_files.sort()
cr2_files
Out[69]:
['/var/panoptes/images/20150920/raw/01_200.cr2',
'/var/panoptes/images/20150920/raw/01_201.cr2',
'/var/panoptes/images/20150920/raw/01_202.cr2',
'/var/panoptes/images/20150920/raw/01_203.cr2',
'/var/panoptes/images/20150920/raw/01_204.cr2',
'/var/panoptes/images/20150920/raw/01_205.cr2',
'/var/panoptes/images/20150920/raw/01_206.cr2',
'/var/panoptes/images/20150920/raw/01_207.cr2',
'/var/panoptes/images/20150920/raw/01_208.cr2',
'/var/panoptes/images/20150920/raw/01_209.cr2',
'/var/panoptes/images/20150920/raw/01_210.cr2',
'/var/panoptes/images/20150920/raw/01_211.cr2',
'/var/panoptes/images/20150920/raw/01_212.cr2',
'/var/panoptes/images/20150920/raw/01_213.cr2',
'/var/panoptes/images/20150920/raw/01_214.cr2',
'/var/panoptes/images/20150920/raw/01_215.cr2',
'/var/panoptes/images/20150920/raw/01_216.cr2',
'/var/panoptes/images/20150920/raw/01_217.cr2',
'/var/panoptes/images/20150920/raw/01_218.cr2',
'/var/panoptes/images/20150920/raw/01_219.cr2',
'/var/panoptes/images/20150920/raw/01_220.cr2',
'/var/panoptes/images/20150920/raw/01_221.cr2',
'/var/panoptes/images/20150920/raw/01_222.cr2',
'/var/panoptes/images/20150920/raw/01_223.cr2',
'/var/panoptes/images/20150920/raw/01_224.cr2',
'/var/panoptes/images/20150920/raw/01_225.cr2',
'/var/panoptes/images/20150920/raw/01_226.cr2',
'/var/panoptes/images/20150920/raw/01_227.cr2',
'/var/panoptes/images/20150920/raw/01_228.cr2',
'/var/panoptes/images/20150920/raw/01_229.cr2',
'/var/panoptes/images/20150920/raw/01_230.cr2',
'/var/panoptes/images/20150920/raw/01_231.cr2',
'/var/panoptes/images/20150920/raw/01_232.cr2',
'/var/panoptes/images/20150920/raw/01_233.cr2',
'/var/panoptes/images/20150920/raw/01_234.cr2',
'/var/panoptes/images/20150920/raw/01_235.cr2',
'/var/panoptes/images/20150920/raw/01_236.cr2',
'/var/panoptes/images/20150920/raw/01_237.cr2',
'/var/panoptes/images/20150920/raw/01_238.cr2',
'/var/panoptes/images/20150920/raw/01_239.cr2',
'/var/panoptes/images/20150920/raw/01_240.cr2',
'/var/panoptes/images/20150920/raw/01_241.cr2',
'/var/panoptes/images/20150920/raw/01_242.cr2',
'/var/panoptes/images/20150920/raw/01_243.cr2',
'/var/panoptes/images/20150920/raw/01_244.cr2',
'/var/panoptes/images/20150920/raw/01_245.cr2',
'/var/panoptes/images/20150920/raw/01_246.cr2',
'/var/panoptes/images/20150920/raw/01_247.cr2',
'/var/panoptes/images/20150920/raw/01_248.cr2',
'/var/panoptes/images/20150920/raw/01_249.cr2']
In [14]:
pixel_scale = ((206.265) * (18.5 * u.micron) / (85 * u.mm)).cgs * u.arcsecond
In [70]:
def compare(f0, f1):
pgm_00 = f0.replace('.cr2','.pgm')
pgm_01 = f1.replace('.cr2','.pgm')
#if not os.path.exists(pgm_00):
pgm_00 = cr2_to_pgm(f0)
#else:
# print("Path exists, using {}".format(pgm_00))
#if not os.path.exists(pgm_01):
pgm_01 = cr2_to_pgm(f1)
#else:
# print("Path exists, using {}".format(pgm_01))
# exif_00 = read_exif(pgm_00)
exif_01 = read_exif(f1)
raw_data_00 = read_pgm(pgm_00)
print(raw_data_00)
raw_data_01 = read_pgm(pgm_01)
print(raw_data_01)
x0, y0 = measure_offset(raw_data_00,raw_data_01, box_width=200)
with io.capture_output() as captured:
!/var/panoptes/bin/measure_offset $f0 $f1
x1 = float(get_file_contents('xcent.txt'))
y1 = float(get_file_contents('ycent.txt'))
# return ( x0, y0, x1, y1 )
fmt = '%a %b %d %H:%M:%S %Y'
t = datetime.datetime.strptime(exif_01.get('Timestamp'), fmt)
return (x0, y0, x1, y1, t)
In [71]:
comparison = []
for i in np.arange(len(cr2_files)):
if i < len(cr2_files) - 1:
comparison.append(compare(cr2_files[i], cr2_files[i+1]))
[[2073 2082 2074 ..., 2091 2066 2112]
[2097 2059 2108 ..., 2070 2099 2067]
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...,
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...,
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[2111 2073 2092 ..., 2084 2118 2100]
[2068 2097 2082 ..., 2089 2078 2122]
...,
[2102 2088 2096 ..., 2091 2088 2085]
[2059 2109 2060 ..., 2094 2072 2114]
[2096 2076 2113 ..., 2095 2102 2097]]
[[2062 2100 2075 ..., 2108 2089 2131]
[2102 2078 2111 ..., 2071 2103 2105]
[2077 2123 2082 ..., 2094 2085 2126]
...,
[2117 2080 2079 ..., 2056 2106 2092]
[2061 2083 2080 ..., 2111 2079 2142]
[2109 2074 2105 ..., 2092 2149 2107]]
[[2062 2100 2075 ..., 2108 2089 2131]
[2102 2078 2111 ..., 2071 2103 2105]
[2077 2123 2082 ..., 2094 2085 2126]
...,
[2117 2080 2079 ..., 2056 2106 2092]
[2061 2083 2080 ..., 2111 2079 2142]
[2109 2074 2105 ..., 2092 2149 2107]]
[[2059 2102 2068 ..., 2107 2096 2132]
[2101 2090 2114 ..., 2056 2097 2084]
[2073 2126 2086 ..., 2113 2081 2135]
...,
[2107 2078 2102 ..., 2080 2109 2077]
[2070 2109 2072 ..., 2111 2089 2125]
[2080 2068 2109 ..., 2089 2141 2095]]
[[2059 2102 2068 ..., 2107 2096 2132]
[2101 2090 2114 ..., 2056 2097 2084]
[2073 2126 2086 ..., 2113 2081 2135]
...,
[2107 2078 2102 ..., 2080 2109 2077]
[2070 2109 2072 ..., 2111 2089 2125]
[2080 2068 2109 ..., 2089 2141 2095]]
[[2073 2095 2062 ..., 2092 2078 2119]
[2095 2078 2099 ..., 2080 2102 2085]
[2085 2123 2090 ..., 2112 2080 2139]
...,
[2109 2109 2129 ..., 2078 2101 2086]
[2067 2101 2089 ..., 2088 2078 2106]
[2092 2073 2114 ..., 2082 2108 2088]]
[[2073 2095 2062 ..., 2092 2078 2119]
[2095 2078 2099 ..., 2080 2102 2085]
[2085 2123 2090 ..., 2112 2080 2139]
...,
[2109 2109 2129 ..., 2078 2101 2086]
[2067 2101 2089 ..., 2088 2078 2106]
[2092 2073 2114 ..., 2082 2108 2088]]
[[2086 2115 2074 ..., 2089 2072 2117]
[2107 2076 2105 ..., 2076 2099 2092]
[2062 2114 2066 ..., 2082 2078 2125]
...,
[2106 2092 2141 ..., 2082 2106 2103]
[2068 2097 2091 ..., 2094 2075 2111]
[2102 2080 2097 ..., 2071 2094 2096]]
[[2086 2115 2074 ..., 2089 2072 2117]
[2107 2076 2105 ..., 2076 2099 2092]
[2062 2114 2066 ..., 2082 2078 2125]
...,
[2106 2092 2141 ..., 2082 2106 2103]
[2068 2097 2091 ..., 2094 2075 2111]
[2102 2080 2097 ..., 2071 2094 2096]]
[[2078 2102 2072 ..., 2102 2074 2119]
[2112 2085 2085 ..., 2088 2103 2107]
[2068 2090 2083 ..., 2094 2074 2125]
...,
[2095 2088 2106 ..., 2084 2106 2088]
[2074 2105 2079 ..., 2112 2077 2120]
[2102 2080 2109 ..., 2090 2100 2110]]
[[2078 2102 2072 ..., 2102 2074 2119]
[2112 2085 2085 ..., 2088 2103 2107]
[2068 2090 2083 ..., 2094 2074 2125]
...,
[2095 2088 2106 ..., 2084 2106 2088]
[2074 2105 2079 ..., 2112 2077 2120]
[2102 2080 2109 ..., 2090 2100 2110]]
[[2074 2090 2080 ..., 2094 2063 2123]
[2096 2066 2106 ..., 2068 2076 2084]
[2070 2100 2103 ..., 2115 2065 2141]
...,
[2106 2077 2139 ..., 2074 2090 2094]
[2078 2114 2108 ..., 2091 2073 2092]
[2097 2078 2108 ..., 2073 2091 2088]]
[[2074 2090 2080 ..., 2094 2063 2123]
[2096 2066 2106 ..., 2068 2076 2084]
[2070 2100 2103 ..., 2115 2065 2141]
...,
[2106 2077 2139 ..., 2074 2090 2094]
[2078 2114 2108 ..., 2091 2073 2092]
[2097 2078 2108 ..., 2073 2091 2088]]
[[2071 2085 2075 ..., 2107 2083 2107]
[2091 2067 2119 ..., 2083 2083 2074]
[2078 2078 2080 ..., 2108 2071 2107]
...,
[2105 2092 2172 ..., 2074 2118 2096]
[2079 2114 2090 ..., 2100 2077 2102]
[2099 2088 2126 ..., 2089 2101 2078]]
[[2071 2085 2075 ..., 2107 2083 2107]
[2091 2067 2119 ..., 2083 2083 2074]
[2078 2078 2080 ..., 2108 2071 2107]
...,
[2105 2092 2172 ..., 2074 2118 2096]
[2079 2114 2090 ..., 2100 2077 2102]
[2099 2088 2126 ..., 2089 2101 2078]]
[[2078 2117 2074 ..., 2103 2078 2099]
[2092 2067 2101 ..., 2082 2097 2086]
[2061 2109 2078 ..., 2115 2085 2136]
...,
[2112 2082 2120 ..., 2082 2092 2083]
[2072 2086 2119 ..., 2089 2096 2112]
[2091 2078 2135 ..., 2096 2100 2106]]
[[2078 2117 2074 ..., 2103 2078 2099]
[2092 2067 2101 ..., 2082 2097 2086]
[2061 2109 2078 ..., 2115 2085 2136]
...,
[2112 2082 2120 ..., 2082 2092 2083]
[2072 2086 2119 ..., 2089 2096 2112]
[2091 2078 2135 ..., 2096 2100 2106]]
[[2079 2103 2084 ..., 2078 2084 2086]
[2089 2080 2096 ..., 2072 2101 2101]
[2084 2095 2067 ..., 2088 2080 2130]
...,
[2114 2073 2129 ..., 2072 2099 2079]
[2066 2102 2113 ..., 2111 2056 2113]
[2101 2076 2117 ..., 2062 2092 2101]]
[[2079 2103 2084 ..., 2078 2084 2086]
[2089 2080 2096 ..., 2072 2101 2101]
[2084 2095 2067 ..., 2088 2080 2130]
...,
[2114 2073 2129 ..., 2072 2099 2079]
[2066 2102 2113 ..., 2111 2056 2113]
[2101 2076 2117 ..., 2062 2092 2101]]
[[2074 2077 2062 ..., 2094 2086 2103]
[2073 2066 2101 ..., 2086 2092 2077]
[2076 2096 2072 ..., 2084 2071 2106]
...,
[2101 2078 2115 ..., 2079 2102 2073]
[2076 2115 2066 ..., 2124 2077 2102]
[2106 2074 2147 ..., 2082 2097 2082]]
[[2074 2077 2062 ..., 2094 2086 2103]
[2073 2066 2101 ..., 2086 2092 2077]
[2076 2096 2072 ..., 2084 2071 2106]
...,
[2101 2078 2115 ..., 2079 2102 2073]
[2076 2115 2066 ..., 2124 2077 2102]
[2106 2074 2147 ..., 2082 2097 2082]]
[[2073 2101 2088 ..., 2085 2079 2106]
[2086 2076 2092 ..., 2073 2091 2095]
[2076 2082 2077 ..., 2096 2095 2092]
...,
[2103 2085 2129 ..., 2074 2100 2065]
[2058 2112 2100 ..., 2099 2086 2107]
[2089 2071 2123 ..., 2079 2084 2086]]
[[2073 2101 2088 ..., 2085 2079 2106]
[2086 2076 2092 ..., 2073 2091 2095]
[2076 2082 2077 ..., 2096 2095 2092]
...,
[2103 2085 2129 ..., 2074 2100 2065]
[2058 2112 2100 ..., 2099 2086 2107]
[2089 2071 2123 ..., 2079 2084 2086]]
[[2079 2086 2080 ..., 2092 2074 2095]
[2095 2079 2101 ..., 2070 2084 2080]
[2073 2092 2062 ..., 2117 2071 2112]
...,
[2106 2085 2111 ..., 2077 2103 2097]
[2086 2103 2084 ..., 2105 2084 2106]
[2100 2067 2129 ..., 2079 2109 2073]]
[[2079 2086 2080 ..., 2092 2074 2095]
[2095 2079 2101 ..., 2070 2084 2080]
[2073 2092 2062 ..., 2117 2071 2112]
...,
[2106 2085 2111 ..., 2077 2103 2097]
[2086 2103 2084 ..., 2105 2084 2106]
[2100 2067 2129 ..., 2079 2109 2073]]
[[2073 2079 2071 ..., 2107 2090 2107]
[2077 2060 2096 ..., 2065 2097 2072]
[2078 2092 2074 ..., 2094 2085 2105]
...,
[2176 2102 2120 ..., 2078 2111 2091]
[2070 2109 2100 ..., 2097 2091 2108]
[2092 2094 2130 ..., 2080 2095 2074]]
[[2073 2079 2071 ..., 2107 2090 2107]
[2077 2060 2096 ..., 2065 2097 2072]
[2078 2092 2074 ..., 2094 2085 2105]
...,
[2176 2102 2120 ..., 2078 2111 2091]
[2070 2109 2100 ..., 2097 2091 2108]
[2092 2094 2130 ..., 2080 2095 2074]]
[[2080 2096 2063 ..., 2078 2092 2090]
[2106 2090 2088 ..., 2077 2115 2080]
[2077 2106 2089 ..., 2094 2070 2092]
...,
[2434 2112 2122 ..., 2068 2105 2089]
[2086 2131 2088 ..., 2099 2084 2111]
[2107 2107 2117 ..., 2076 2100 2084]]
[[2080 2096 2063 ..., 2078 2092 2090]
[2106 2090 2088 ..., 2077 2115 2080]
[2077 2106 2089 ..., 2094 2070 2092]
...,
[2434 2112 2122 ..., 2068 2105 2089]
[2086 2131 2088 ..., 2099 2084 2111]
[2107 2107 2117 ..., 2076 2100 2084]]
[[2079 2083 2079 ..., 2090 2072 2113]
[2080 2074 2106 ..., 2074 2086 2070]
[2065 2100 2080 ..., 2094 2093 2088]
...,
[2253 2107 2126 ..., 2085 2102 2077]
[2073 2113 2090 ..., 2094 2074 2122]
[2095 2068 2131 ..., 2082 2083 2084]]
[[2079 2083 2079 ..., 2090 2072 2113]
[2080 2074 2106 ..., 2074 2086 2070]
[2065 2100 2080 ..., 2094 2093 2088]
...,
[2253 2107 2126 ..., 2085 2102 2077]
[2073 2113 2090 ..., 2094 2074 2122]
[2095 2068 2131 ..., 2082 2083 2084]]
[[2073 2090 2082 ..., 2103 2072 2106]
[2084 2086 2105 ..., 2071 2086 2082]
[2074 2092 2068 ..., 2086 2079 2113]
...,
[2429 2147 2123 ..., 2072 2112 2088]
[2088 2127 2088 ..., 2113 2080 2103]
[2089 2083 2120 ..., 2062 2105 2083]]
[[2073 2090 2082 ..., 2103 2072 2106]
[2084 2086 2105 ..., 2071 2086 2082]
[2074 2092 2068 ..., 2086 2079 2113]
...,
[2429 2147 2123 ..., 2072 2112 2088]
[2088 2127 2088 ..., 2113 2080 2103]
[2089 2083 2120 ..., 2062 2105 2083]]
[[2063 2090 2070 ..., 2091 2072 2102]
[2090 2085 2100 ..., 2068 2070 2092]
[2078 2108 2070 ..., 2112 2065 2108]
...,
[2522 2162 2103 ..., 2090 2107 2090]
[2233 2222 2097 ..., 2105 2084 2095]
[2451 2145 2138 ..., 2082 2108 2080]]
[[2063 2090 2070 ..., 2091 2072 2102]
[2090 2085 2100 ..., 2068 2070 2092]
[2078 2108 2070 ..., 2112 2065 2108]
...,
[2522 2162 2103 ..., 2090 2107 2090]
[2233 2222 2097 ..., 2105 2084 2095]
[2451 2145 2138 ..., 2082 2108 2080]]
[[2067 2062 2077 ..., 2096 2075 2111]
[2092 2066 2089 ..., 2076 2099 2079]
[2071 2102 2073 ..., 2102 2077 2109]
...,
[2586 2184 2109 ..., 2065 2092 2101]
[2255 2292 2083 ..., 2113 2083 2103]
[2445 2132 2130 ..., 2074 2099 2086]]
[[2067 2062 2077 ..., 2096 2075 2111]
[2092 2066 2089 ..., 2076 2099 2079]
[2071 2102 2073 ..., 2102 2077 2109]
...,
[2586 2184 2109 ..., 2065 2092 2101]
[2255 2292 2083 ..., 2113 2083 2103]
[2445 2132 2130 ..., 2074 2099 2086]]
[[2068 2109 2077 ..., 2094 2091 2117]
[2071 2082 2095 ..., 2074 2082 2083]
[2070 2090 2059 ..., 2111 2072 2106]
...,
[2661 2242 2147 ..., 2085 2101 2101]
[2189 2349 2089 ..., 2109 2085 2115]
[2343 2115 2146 ..., 2089 2094 2095]]
[[2068 2109 2077 ..., 2094 2091 2117]
[2071 2082 2095 ..., 2074 2082 2083]
[2070 2090 2059 ..., 2111 2072 2106]
...,
[2661 2242 2147 ..., 2085 2101 2101]
[2189 2349 2089 ..., 2109 2085 2115]
[2343 2115 2146 ..., 2089 2094 2095]]
[[2083 2091 2080 ..., 2095 2079 2097]
[2100 2072 2103 ..., 2076 2105 2092]
[2082 2097 2066 ..., 2117 2085 2085]
...,
[2287 2166 2109 ..., 2092 2103 2073]
[2248 2316 2107 ..., 2108 2089 2112]
[2603 2195 2131 ..., 2063 2097 2098]]
[[2083 2091 2080 ..., 2095 2079 2097]
[2100 2072 2103 ..., 2076 2105 2092]
[2082 2097 2066 ..., 2117 2085 2085]
...,
[2287 2166 2109 ..., 2092 2103 2073]
[2248 2316 2107 ..., 2108 2089 2112]
[2603 2195 2131 ..., 2063 2097 2098]]
[[2076 2096 2095 ..., 2095 2078 2111]
[2099 2096 2102 ..., 2082 2097 2084]
[2070 2084 2075 ..., 2108 2078 2105]
...,
[2126 2097 2120 ..., 2062 2109 2091]
[2132 2142 2148 ..., 2108 2086 2101]
[2348 2241 2127 ..., 2078 2094 2098]]
In [72]:
comparison
Out[72]:
[(0.29473684210526313,
-0.23684210526315788,
0.2181,
0.477107,
datetime.datetime(2015, 9, 20, 10, 10, 58)),
(0.18947368421052632,
-0.13157894736842105,
0.185534,
0.315553,
datetime.datetime(2015, 9, 20, 10, 13, 16)),
(-1.0566037735849056,
0.062893081761006289,
0.250061,
-2.04142,
datetime.datetime(2015, 9, 20, 10, 15, 34)),
(-0.76165803108808294,
-0.015544041450777202,
0.171347,
-1.27753,
datetime.datetime(2015, 9, 20, 10, 17, 51)),
(0.62962962962962965,
-0.18518518518518517,
0.123623,
1.00728,
datetime.datetime(2015, 9, 20, 10, 20, 10)),
(-0.72413793103448276,
-0.10344827586206896,
0.119082,
-1.12748,
datetime.datetime(2015, 9, 20, 10, 22, 27)),
(-1.4375,
-0.23214285714285715,
0.135838,
-2.40791,
datetime.datetime(2015, 9, 20, 10, 24, 45)),
(0.48618784530386738,
0.055248618784530384,
0.0550171,
0.683814,
datetime.datetime(2015, 9, 20, 10, 27, 3)),
(0.35028248587570621,
-0.062146892655367235,
0.0448144,
0.479751,
datetime.datetime(2015, 9, 20, 10, 29, 20)),
(-1.3083333333333333,
0.050000000000000003,
0.043822,
-2.16141,
datetime.datetime(2015, 9, 20, 10, 31, 39)),
(-0.84375,
-0.18124999999999999,
0.0548904,
-1.04912,
datetime.datetime(2015, 9, 20, 10, 33, 56)),
(0.94630872483221473,
0.17449664429530201,
-0.126447,
1.25523,
datetime.datetime(2015, 9, 20, 10, 36, 14)),
(-0.73793103448275865,
-0.13793103448275862,
0.0739727,
-1.05442,
datetime.datetime(2015, 9, 20, 10, 38, 32)),
(-1.2601626016260163,
0.0,
0.14494,
-2.27508,
datetime.datetime(2015, 9, 20, 10, 40, 50)),
(0.44910179640718562,
0.065868263473053898,
-0.062189,
0.759974,
datetime.datetime(2015, 9, 20, 10, 43, 9)),
(0.13872832369942195,
-0.15028901734104047,
0.114578,
0.0740052,
datetime.datetime(2015, 9, 20, 10, 45, 27)),
(-1.264,
-0.080000000000000002,
0.10024,
-2.24014,
datetime.datetime(2015, 9, 20, 10, 47, 45)),
(-0.32407407407407407,
0.15740740740740741,
0.0165496,
-0.92843,
datetime.datetime(2015, 9, 20, 10, 50, 3)),
(0.94011976047904189,
-0.029940119760479042,
-0.0414926,
1.47823,
datetime.datetime(2015, 9, 20, 10, 52, 21)),
(-0.94674556213017746,
0.029585798816568046,
-0.0475558,
-1.45357,
datetime.datetime(2015, 9, 20, 10, 54, 39)),
(-1.3816793893129771,
0.068702290076335881,
0.10252,
-2.34788,
datetime.datetime(2015, 9, 20, 10, 56, 57)),
(0.6171428571428571,
-0.10857142857142857,
-0.00872601,
0.955511,
datetime.datetime(2015, 9, 20, 10, 59, 15)),
(0.20454545454545456,
-0.14772727272727273,
0.0966372,
0.153209,
datetime.datetime(2015, 9, 20, 11, 1, 33)),
(-1.3303571428571428,
-0.035714285714285712,
0.15261,
-2.47171,
datetime.datetime(2015, 9, 20, 11, 3, 51)),
(-0.24550898203592814,
-0.18562874251497005,
0.128461,
-0.473596,
datetime.datetime(2015, 9, 20, 11, 6, 9)),
(0.75151515151515147,
-0.10303030303030303,
0.0847779,
1.22915,
datetime.datetime(2015, 9, 20, 11, 8, 26)),
(-0.8571428571428571,
-0.099378881987577633,
0.20831,
-1.34559,
datetime.datetime(2015, 9, 20, 11, 10, 44)),
(-1.4705882352941178,
0.0,
0.19086,
-2.00752,
datetime.datetime(2015, 9, 20, 11, 13, 2)),
(0.75652173913043474,
-0.026086956521739129,
0.0534065,
1.25077,
datetime.datetime(2015, 9, 20, 11, 15, 20)),
(0.12820512820512819,
-0.083333333333333329,
0.0638729,
0.0515392,
datetime.datetime(2015, 9, 20, 11, 17, 37)),
(-1.5714285714285714,
-0.21428571428571427,
0.184381,
-2.7477,
datetime.datetime(2015, 9, 20, 11, 19, 55)),
(-0.11627906976744186,
-0.19767441860465115,
0.154912,
-0.287177,
datetime.datetime(2015, 9, 20, 11, 22, 14)),
(0.625,
-0.012500000000000001,
0.151616,
1.02943,
datetime.datetime(2015, 9, 20, 11, 24, 33)),
(-1.0126582278481013,
-0.13924050632911392,
0.116496,
-1.56635,
datetime.datetime(2015, 9, 20, 11, 26, 51)),
(-1.3580246913580247,
-0.086419753086419748,
0.246054,
-2.03581,
datetime.datetime(2015, 9, 20, 11, 29, 9)),
(1.072289156626506,
-0.21686746987951808,
0.0631482,
1.3921,
datetime.datetime(2015, 9, 20, 11, 31, 26)),
(-0.46835443037974683,
-0.050632911392405063,
0.136176,
-0.485271,
datetime.datetime(2015, 9, 20, 11, 33, 44)),
(-1.421875,
0.03125,
0.171058,
-2.4233,
datetime.datetime(2015, 9, 20, 11, 36, 2)),
(-0.030303030303030304,
-0.31313131313131315,
0.224961,
0.0796581,
datetime.datetime(2015, 9, 20, 11, 38, 20)),
(0.55555555555555558,
-0.080808080808080815,
0.0659351,
0.786677,
datetime.datetime(2015, 9, 20, 11, 40, 38)),
(-1.05,
-0.029999999999999999,
0.150606,
-1.57503,
datetime.datetime(2015, 9, 20, 11, 42, 55)),
(-1.0392156862745099,
-0.088235294117647065,
0.0527641,
-1.7295,
datetime.datetime(2015, 9, 20, 11, 45, 13)),
(0.93999999999999995,
0.040000000000000001,
0.157805,
1.33909,
datetime.datetime(2015, 9, 20, 11, 47, 31)),
(-0.28205128205128205,
-0.17948717948717949,
0.18585,
-0.482677,
datetime.datetime(2015, 9, 20, 11, 49, 49)),
(-1.45,
-0.28333333333333333,
0.217464,
-2.42193,
datetime.datetime(2015, 9, 20, 11, 52, 9)),
(0.14999999999999999,
-0.16250000000000001,
0.058778,
0.250657,
datetime.datetime(2015, 9, 20, 11, 54, 27)),
(0.47435897435897434,
0.0,
0.113712,
0.70778,
datetime.datetime(2015, 9, 20, 11, 56, 44)),
(-1.2318840579710144,
0.014492753623188406,
0.130394,
-1.89597,
datetime.datetime(2015, 9, 20, 11, 59, 3)),
(-1.0,
-0.14285714285714285,
0.148088,
-1.5077,
datetime.datetime(2015, 9, 20, 12, 1, 21))]
In [73]:
x0 = [x[0] for x in comparison]
y0 = [x[1]*-1 for x in comparison]
x1 = [x[2] for x in comparison]
y1 = [x[3] for x in comparison]
dates = [x[4] for x in comparison]
dt_index = pd.DatetimeIndex(dates)
dt_index
In [75]:
x0_offset = pd.DataFrame(x0, dt_index)
y0_offset = pd.DataFrame(y0, dt_index)
x1_offset = pd.DataFrame(y1, dt_index)
y1_offset = pd.DataFrame(x1, dt_index)
In [76]:
series = pd.concat([x0_offset, x1_offset, y0_offset, y1_offset], axis=1)
series.index = dt_index
series.columns=["Gee $\Delta{x}$","Guyon $\Delta{x}$","Gee $\Delta{y}$","Guyon $\Delta{y}$"]
In [77]:
series
Out[77]:
Gee $\Delta{x}$
Guyon $\Delta{x}$
Gee $\Delta{y}$
Guyon $\Delta{y}$
2015-09-20 10:10:58
0.294737
0.477107
0.236842
0.218100
2015-09-20 10:13:16
0.189474
0.315553
0.131579
0.185534
2015-09-20 10:15:34
-1.056604
-2.041420
-0.062893
0.250061
2015-09-20 10:17:51
-0.761658
-1.277530
0.015544
0.171347
2015-09-20 10:20:10
0.629630
1.007280
0.185185
0.123623
2015-09-20 10:22:27
-0.724138
-1.127480
0.103448
0.119082
2015-09-20 10:24:45
-1.437500
-2.407910
0.232143
0.135838
2015-09-20 10:27:03
0.486188
0.683814
-0.055249
0.055017
2015-09-20 10:29:20
0.350282
0.479751
0.062147
0.044814
2015-09-20 10:31:39
-1.308333
-2.161410
-0.050000
0.043822
2015-09-20 10:33:56
-0.843750
-1.049120
0.181250
0.054890
2015-09-20 10:36:14
0.946309
1.255230
-0.174497
-0.126447
2015-09-20 10:38:32
-0.737931
-1.054420
0.137931
0.073973
2015-09-20 10:40:50
-1.260163
-2.275080
-0.000000
0.144940
2015-09-20 10:43:09
0.449102
0.759974
-0.065868
-0.062189
2015-09-20 10:45:27
0.138728
0.074005
0.150289
0.114578
2015-09-20 10:47:45
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2015-09-20 10:50:03
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2015-09-20 10:52:21
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2015-09-20 10:54:39
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2015-09-20 10:59:15
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2015-09-20 11:01:33
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2015-09-20 11:03:51
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2015-09-20 11:06:09
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2015-09-20 11:08:26
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2015-09-20 11:10:44
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2015-09-20 11:13:02
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2015-09-20 11:15:20
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2015-09-20 11:17:37
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2015-09-20 11:19:55
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2015-09-20 11:22:14
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2015-09-20 11:24:33
0.625000
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2015-09-20 11:26:51
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2015-09-20 11:29:09
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2015-09-20 11:31:26
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2015-09-20 11:33:44
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2015-09-20 11:36:02
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2015-09-20 11:38:20
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2015-09-20 11:40:38
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2015-09-20 11:42:55
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2015-09-20 11:45:13
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2015-09-20 11:47:31
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2015-09-20 11:49:49
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2015-09-20 11:52:09
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2015-09-20 11:54:27
0.150000
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2015-09-20 11:56:44
0.474359
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2015-09-20 11:59:03
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2015-09-20 12:01:21
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In [78]:
series.plot()
plt.legend(loc=1)
Out[78]:
<matplotlib.legend.Legend at 0x7f60cd32e390>
In [ ]:
Content source: fmin2958/POCS
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