In [1]:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import datetime as dt
from salishsea_tools import evaltools as et

%matplotlib inline

In [2]:

ls '/ocean/ksuchy/MOAD/observe/Data and Code files for KS 2020dec11/2020_05_21 1995-2011 SoG VNH.csv'

/ocean/ksuchy/MOAD/observe/Data and Code files for KS 2020dec11/2020_05_21 1995-2011 SoG VNH.csv

In [3]:

df=pd.read_csv('/ocean/ksuchy/MOAD/observe/Data and Code files for KS 2020dec11/2020_05_21 2012-2015 SoG VNH.csv',
               encoding = "ISO-8859-1")

In [4]:

df

Out[4]:

	Key	region_name	Station	PROJECT	lon	lat	Date	STN_TIME	Twilight	Net_Type	...	Phylum:	Class:	Order:	Family:	Name	Abundance(#/m3)	Biomass(mg/m3)	NumberOfSpecies	Station Diversity	Station Equitability
0	IOS2012005000901	Northern Strait of Georgia	22	Str. Geo.	-124.272	49.670	6/14/2012	7:32	Daylight	SCOR VNH	...	Arthropoda	Branchiopoda	Diplostraca	Podonidae	Podon *sp. s1	12.22541	0.06113	51	2.63	0.67
1	IOS2012005000901	Northern Strait of Georgia	22	Str. Geo.	-124.272	49.670	6/14/2012	7:32	Daylight	SCOR VNH	...	Arthropoda	Cirripedia	Thecostraca	NaN	Cirripedia *sp. nauplii s1	30.56351	1.22254	51	2.63	0.67
2	IOS2012005000901	Northern Strait of Georgia	22	Str. Geo.	-124.272	49.670	6/14/2012	7:32	Daylight	SCOR VNH	...	Arthropoda	Malacostraca	Amphipoda	Hyperiidae	Themisto pacifica juvenile s1	6.11270	1.44871	51	2.63	0.67
3	IOS2012005000901	Northern Strait of Georgia	22	Str. Geo.	-124.272	49.670	6/14/2012	7:32	Daylight	SCOR VNH	...	Arthropoda	Malacostraca	Decapoda	NaN	Caridea *sp. zoea s1	3.05635	0.07030	51	2.63	0.67
4	IOS2012005000901	Northern Strait of Georgia	22	Str. Geo.	-124.272	49.670	6/14/2012	7:32	Daylight	SCOR VNH	...	Arthropoda	Malacostraca	Decapoda	Hippolytidae	Hippolytidae *sp. mysis s2	0.09551	0.06017	51	2.63	0.67
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
60225	SOO2015095000801	Tidal Mixed	MAC41	Citizen Science	-123.409	48.402	7/27/2015	13:00	Daylight	SCOR VNH	...	Ctenophora	Tentaculata	Cydippida	Pleurobrachiidae	Pleurobrachia bachei s2	0.25316	0.31797	44	2.56	0.67
60226	SOO2015095000801	Tidal Mixed	MAC41	Citizen Science	-123.409	48.402	7/27/2015	13:00	Daylight	SCOR VNH	...	Ectoprocta	Gymnolaemata	NaN	NaN	Bryozoa *sp. cyphonautes s1	48.60759	0.06319	44	2.56	0.67
60227	SOO2015095000801	Tidal Mixed	MAC41	Citizen Science	-123.409	48.402	7/27/2015	13:00	Daylight	SCOR VNH	...	Mollusca	Bivalvia	Pholadomyoida	NaN	Bivalvia *sp. veligers s1	21.60338	0.01296	44	2.56	0.67
60228	SOO2015095000801	Tidal Mixed	MAC41	Citizen Science	-123.409	48.402	7/27/2015	13:00	Daylight	SCOR VNH	...	Mollusca	Cephalopoda	Teuthida	Gonatidae	Berryteuthis magister s2	0.08439	0.46414	44	2.56	0.67
60229	SOO2015095000801	Tidal Mixed	MAC41	Citizen Science	-123.409	48.402	7/27/2015	13:00	Daylight	SCOR VNH	...	Mollusca	Gastropoda	NaN	NaN	Gastropoda *sp. veligers s1	10.80169	0.02808	44	2.56	0.67

60230 rows × 29 columns

In [5]:

df.keys()

Out[5]:

Index(['Key', 'region_name', 'Station', 'PROJECT', 'lon', 'lat', 'Date',
       'STN_TIME', 'Twilight', 'Net_Type', 'Mesh_Size(um)', 'Net_Mouth_Dia(m)',
       'DEPTH_STRT1', 'DEPTH_END1', 'Bottom Depth(m)', 'Volume Filtered(m3)',
       'CTD', 'NOTES', 'PI', 'Phylum:', 'Class:', 'Order:', 'Family:', 'Name',
       'Abundance(#/m3)', 'Biomass(mg/m3)', 'NumberOfSpecies',
       'Station Diversity', 'Station Equitability'],
      dtype='object')

In [6]:

df['Biomass(mg/m3)']

Out[6]:

0        0.06113
1        1.22254
2        1.44871
3        0.07030
4        0.06017
          ...   
60225    0.31797
60226    0.06319
60227    0.01296
60228    0.46414
60229    0.02808
Name: Biomass(mg/m3), Length: 60230, dtype: float64

In [7]:

df['Date'][0],df['STN_TIME'][0]

Out[7]:

('6/14/2012', '7:32')

In [8]:

df['Date'][1000:1020]

Out[8]:

1000    6/15/2012
1001    6/15/2012
1002    6/15/2012
1003    6/15/2012
1004    6/15/2012
1005    6/15/2012
1006    6/15/2012
1007    6/15/2012
1008    6/15/2012
1009    6/15/2012
1010    6/15/2012
1011    6/15/2012
1012    6/15/2012
1013    6/15/2012
1014    6/15/2012
1015    6/15/2012
1016    6/15/2012
1017    6/15/2012
1018    6/15/2012
1019    6/15/2012
Name: Date, dtype: object

In [9]:

df['Date'][0].split('/')

Out[9]:

['6', '14', '2012']

In [10]:

dateslist=list()

In [11]:

for el in df['Date']:
    dateslist.append(el.split('/'))

In [12]:

timeslist=list()
for el in df['STN_TIME']:
    timeslist.append(el.split(':'))

In [13]:

dts=list()
for ii,jj in zip(dateslist,timeslist):
    dts.append(dt.datetime(int(ii[2]),int(ii[0]),int(ii[1]),int(jj[0]),int(jj[1])))

In [14]:

df.loc[df.Twilight=='Daylight']['STN_TIME'].unique()

Out[14]:

array(['7:32', '7:52', '3:30', '7:42', '7:49', '15:09', '16:30', '22:09',
       '22:27', '19:36', '19:53', '9:21', '9:35', '13:29', '13:45',
       '19:25', '19:43', '5:26', '5:43', '5:45', '5:47', '5:56', '5:59',
       '8:38', '8:39', '8:40', '8:41', '8:57', '11:10', '11:44', '11:45',
       '11:47', '11:48', '11:49', '12:40', '12:42', '15:14', '15:15',
       '15:16', '15:17', '15:18', '17:54', '17:55', '17:57', '17:58',
       '17:59', '5:39', '6:05', '14:47', '15:02', '19:13', '19:30',
       '14:32', '14:49', '20:04', '20:24', '20:27', '20:47', '9:37',
       '9:48', '13:57', '14:17', '19:41', '19:59', '7:18', '7:53', '9:25',
       '12:57', '13:09', '7:30', '7:45', '13:33', '13:36', '13:38',
       '10:00', '10:30', '11:00', '11:30', '12:30', '13:00', '13:30',
       '16:00', '17:00', '9:29', '10:26', '11:19', '13:39', '9:16',
       '10:04', '10:42', '11:03', '9:00', '9:41', '10:17', '10:40',
       '12:00', '9:33', '10:13', '11:11', '12:02', '12:32', '13:22',
       '9:57', '10:35', '10:02', '12:08', '13:18', '14:50', '17:45',
       '18:45', '8:30', '9:30', '11:41', '12:37', '13:03', '14:05',
       '9:20', '11:56', '13:43', '9:32', '11:22', '11:52', '7:27',
       '19:08', '9:45', '16:38', '16:57', '16:04', '16:26', '13:31',
       '13:35', '7:12', '16:12', '16:14', '16:18', '16:20', '16:22',
       '3:48', '4:04', '15:20', '15:35', '21:28', '21:42', '4:33', '4:45',
       '11:38', '11:55', '18:18', '18:29', '10:12', '12:55', '10:16',
       '11:20', '13:08', '11:07', '12:19', '12:58', '14:42', '15:37',
       '12:10', '12:23', '13:24', '14:33', '10:32', '12:39', '9:49',
       '10:53', '12:49', '11:36', '14:11', '9:51', '11:24', '13:04',
       '13:19', '9:24', '10:15', '11:53', '12:51', '12:50', '16:11',
       '6:15', '17:15', '11:16', '12:17', '13:10', '13:59', '11:21',
       '12:01', '12:35', '9:58', '10:41', '11:29', '9:05', '9:50', '8:49',
       '9:55', '11:14', '12:14', '9:10', '10:20', '10:50', '11:25',
       '11:50', '19:52', '20:32', '6:20', '5:58', '20:29', '5:20',
       '20:10', '15:52', '6:43', '20:12', '7:22', '21:03', '21:55',
       '14:56', '10:08', '20:01', '11:33', '15:22', '16:40', '23:15',
       '8:51', '12:12', '15:12', '10:57', '7:03', '8:03', '14:22',
       '23:06', '4:05', '6:25', '9:26', '11:28', '13:27', '15:11',
       '15:53', '15:54', '15:56', '15:59', '18:06', '19:45', '9:40',
       '20:11', '7:10', '14:34', '11:42', '13:28', '17:12', '9:04',
       '14:10', '16:17', '8:02', '10:31', '15:27', '17:01', '16:43',
       '10:46', '13:15', '14:43', '9:44', '13:55', '15:44', '16:59',
       '18:41', '8:18', '11:13', '8:28', '15:43', '18:08', '7:40',
       '10:56', '10:33', '12:52', '14:55', '7:43', '12:13', '13:44',
       '7:41', '16:56', '8:17', '9:13', '11:12', '15:40', '18:27',
       '10:07', '12:06', '16:07', '16:41', '10:52', '16:33', '17:48',
       '7:48', '11:09', '15:08', '8:31', '12:22', '14:39', '12:03',
       '14:30', '17:31', '14:15', '18:16', '7:55', '17:38', '6:36',
       '18:22', '7:15', '9:17', '12:44', '18:54', '12:43', '18:44',
       '7:08', '13:02', '7:19', '16:36', '8:25', '8:33', '13:25', '17:20',
       '17:26', '13:42', '18:37', '18:43', '13:21', '14:53', '17:24',
       '9:38', '7:06', '9:31', '12:20', '15:28', '11:01', '11:57',
       '14:12', '15:10', '7:35', '14:38', '16:06', '8:08', '16:05',
       '16:52', '17:47', '8:21', '9:19', '16:35', '8:10', '8:59', '10:21',
       '14:41', '16:09', '18:26', '11:23', '8:14', '10:10', '11:27',
       '13:26', '11:15', '13:11', '9:18', '12:04', '10:45', '12:25',
       '13:56', '10:22', '13:53', '9:28', '11:06', '11:32', '10:34',
       '14:08', '11:18', '12:48', '14:01', '12:07', '14:07', '11:08',
       '14:04', '10:06', '11:43', '13:40', '10:18', '13:34', '16:27',
       '10:28', '15:26', '9:14', '12:15', '15:23', '8:23', '14:58',
       '9:08', '10:43', '14:29', '8:44', '9:52', '8:13', '14:27', '14:46',
       '14:16', '10:11', '14:51', '8:32', '10:37'], dtype=object)

In [15]:

df['dtUTC']=et.pac_to_utc(dts) #convert from Pac time to UTC

In [16]:

df['Order:'].unique()

Out[16]:

array(['Diplostraca', 'Thecostraca', 'Amphipoda', 'Decapoda',
       'Euphausiacea', 'Calanoida', 'Cyclopoida', 'Poecilostomatoida',
       'Halocyprida', 'Aphragmophora', 'Copelata', 'Leptothecate',
       'Siphonophorae', 'Trachylina', 'Cydippida', nan, 'Pholadomyoida',
       'Neotaenioglossa', 'Thecosomata', 'Aciculata', 'Canalipalpata',
       'Osmeriformes', 'Perciformes', 'Beroida', 'Teuthida',
       'Gymnosomata', 'Isopoda', 'Siphonostomatoida', 'Anthoathecatae',
       'Scorpaeniformes', 'Phragmophora', 'Clupeiformes', 'Ophiurida',
       'Gadiformes', 'Semaeostomeae', 'Cumacea', 'Echinoida',
       'Harpacticoida', 'Pleuronectiformes', 'Tricladida', 'Myodocopida',
       'Phaeogromia', 'Noctilucales', 'Octopoda', 'Actiniaria',
       'Foraminiferida', 'Monstrilloida', 'Oligotrichida', 'Mysida',
       'Acariformes', 'Lophogastrida', 'Ophidiiformes',
       'Thalassocalycida', 'Doliolida', 'Lepadomorpha', 'Cephalaspidea',
       'Sygnathiformes'], dtype=object)

In [17]:

colList=('Amphipoda', 'Decapoda','Euphausiacea', 'Calanoida', 'Cyclopoida', 
    'Poecilostomatoida','Copelata','Harpacticoida',)

In [18]:

df.keys()

Out[18]:

Index(['Key', 'region_name', 'Station', 'PROJECT', 'lon', 'lat', 'Date',
       'STN_TIME', 'Twilight', 'Net_Type', 'Mesh_Size(um)', 'Net_Mouth_Dia(m)',
       'DEPTH_STRT1', 'DEPTH_END1', 'Bottom Depth(m)', 'Volume Filtered(m3)',
       'CTD', 'NOTES', 'PI', 'Phylum:', 'Class:', 'Order:', 'Family:', 'Name',
       'Abundance(#/m3)', 'Biomass(mg/m3)', 'NumberOfSpecies',
       'Station Diversity', 'Station Equitability', 'dtUTC'],
      dtype='object')

In [19]:

dtsutc=et.pac_to_utc(dts)

In [20]:

df.loc[0]

Out[20]:

Key                                                      IOS2012005000901
region_name                                    Northern Strait of Georgia
Station                                                                22
PROJECT                                                         Str. Geo.
lon                                                              -124.272
lat                                                                 49.67
Date                                                            6/14/2012
STN_TIME                                                             7:32
Twilight                                                         Daylight
Net_Type                                                         SCOR VNH
Mesh_Size(um)                                                         236
Net_Mouth_Dia(m)                                                     0.56
DEPTH_STRT1                                                            50
DEPTH_END1                                                              0
Bottom Depth(m)                                                       352
Volume Filtered(m3)                                                 10.47
CTD                                                                     8
NOTES                   Flowmeter reading may be incorrect. Value ente...
PI                                                            Dave Mackas
Phylum:                                                        Arthropoda
Class:                                                       Branchiopoda
Order:                                                        Diplostraca
Family:                                                         Podonidae
Name                                                       Podon *sp.  s1
Abundance(#/m3)                                                   12.2254
Biomass(mg/m3)                                                    0.06113
NumberOfSpecies                                                        51
Station Diversity                                                    2.63
Station Equitability                                                 0.67
dtUTC                                                 2012-06-14 14:32:00
Name: 0, dtype: object

In [21]:

towIDlist=['Key', 'region_name', 'Station',  'lon', 'lat', 'dtUTC', 'Twilight', 'Net_Type', 'Mesh_Size(um)', 'DEPTH_STRT1', 'DEPTH_END1', 'Bottom Depth(m)']

In [22]:

towIDlist2=['Key', 'region_name', 'Station',  'lon', 'lat', 'dtUTC', 'Twilight', 'Net_Type', 'Mesh_Size(um)', 'DEPTH_STRT1', 'DEPTH_END1', 'Bottom Depth(m)','CTD']

In [23]:

len(df.groupby(towIDlist)),len(df.groupby(towIDlist2)),len(df.groupby(['Key']))

Out[23]:

(654, 12694, 654)

In [24]:

# Key is a unique identifier for each tow
# do not group by CTD due to NaN values

In [25]:

biomassDF=df.groupby(towIDlist,as_index=False).first()\
     .loc[:,towIDlist].copy(deep=True)

In [26]:

biomassDF

Out[26]:

	Key	region_name	Station	lon	lat	dtUTC	Twilight	Net_Type	Mesh_Size(um)	DEPTH_STRT1	DEPTH_END1	Bottom Depth(m)
0	IOS2012005000901	Northern Strait of Georgia	22	-124.272	49.670	2012-06-14 14:32:00	Daylight	SCOR VNH	236	50	0	352
1	IOS2012005001001	Northern Strait of Georgia	22	-124.272	49.670	2012-06-14 14:52:00	Daylight	SCOR VNH	236	345	0	352
2	IOS2012005002101	Northern Strait of Georgia	11	-124.722	49.710	2012-06-14 07:00:00	Night	SCOR VNH	236	50	0	307
3	IOS2012005002201	Northern Strait of Georgia	11	-124.722	49.710	2012-06-14 07:05:00	Night	SCOR VNH	236	300	0	307
4	IOS2012005002901	Northern Strait of Georgia	CPF2	-124.499	49.466	2012-06-15 10:00:00	Night	SCOR VNH	236	50	0	325
...	...	...	...	...	...	...	...	...	...	...	...	...
649	SOO2015095000101	Tidal Mixed	CLO-42	-123.345	48.394	2015-04-27 17:37:00	Daylight	SCOR VNH	236	58	0	72
650	SOO2015095000401	Tidal Mixed	CB01	-123.318	48.344	2015-04-30 19:00:00	Daylight	SCOR VNH	236	54	0	64
651	SOO2015095000501	Tidal Mixed	CLO-41	-123.345	48.395	2015-07-09 19:25:00	Daylight	SCOR VNH	236	42	0	64
652	SOO2015095000701	Tidal Mixed	CB01	-123.318	48.344	2015-07-27 19:06:00	Daylight	SCOR VNH	236	28	0	60
653	SOO2015095000801	Tidal Mixed	MAC41	-123.409	48.402	2015-07-27 20:00:00	Daylight	SCOR VNH	236	49	0	62

654 rows × 12 columns

In [27]:

def getbiomass(colname,key,origdf):
    biomassArray=df.loc[(origdf.Key==key)&(origdf['Order:']==colname),
                    ['Biomass(mg/m3)']]
    biomass=np.nansum(biomassArray)
    return biomass

In [28]:

for icol in colList:
    biomassDF[icol]=[getbiomass(icol,ikey,df) for ikey in biomassDF['Key']]

In [29]:

biomassDF

Out[29]:

	Key	region_name	Station	lon	lat	dtUTC	Twilight	Net_Type	Mesh_Size(um)	DEPTH_STRT1	DEPTH_END1	Bottom Depth(m)	Amphipoda	Decapoda	Euphausiacea	Calanoida	Cyclopoida	Poecilostomatoida	Copelata	Harpacticoida
0	IOS2012005000901	Northern Strait of Georgia	22	-124.272	49.670	2012-06-14 14:32:00	Daylight	SCOR VNH	236	50	0	352	1.44871	0.13047	0.65310	14.21881	0.35546	0.59598	0.91691	0.0
1	IOS2012005001001	Northern Strait of Georgia	22	-124.272	49.670	2012-06-14 14:52:00	Daylight	SCOR VNH	236	345	0	352	2.57318	0.23591	0.16876	17.75443	0.37904	0.23747	1.15807	0.0
2	IOS2012005002101	Northern Strait of Georgia	11	-124.722	49.710	2012-06-14 07:00:00	Night	SCOR VNH	236	50	0	307	8.45483	5.76780	0.07720	57.97920	1.18232	0.31802	0.01917	0.0
3	IOS2012005002201	Northern Strait of Georgia	11	-124.722	49.710	2012-06-14 07:05:00	Night	SCOR VNH	236	300	0	307	23.57762	3.69101	4.27121	68.21370	1.32736	0.58393	0.14046	0.0
4	IOS2012005002901	Northern Strait of Georgia	CPF2	-124.499	49.466	2012-06-15 10:00:00	Night	SCOR VNH	236	50	0	325	124.31430	24.79259	14.47768	34.16656	0.77657	0.14856	0.36571	0.0
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
649	SOO2015095000101	Tidal Mixed	CLO-42	-123.345	48.394	2015-04-27 17:37:00	Daylight	SCOR VNH	236	58	0	72	1.81260	0.93396	0.01031	6.19344	0.00191	0.01527	0.69466	0.0
650	SOO2015095000401	Tidal Mixed	CB01	-123.318	48.344	2015-04-30 19:00:00	Daylight	SCOR VNH	236	54	0	64	5.31255	2.51960	0.02307	10.53489	0.00427	0.04784	0.47838	0.0
651	SOO2015095000501	Tidal Mixed	CLO-41	-123.345	48.395	2015-07-09 19:25:00	Daylight	SCOR VNH	236	42	0	64	0.00000	0.56055	0.02636	5.75176	0.00000	0.03222	3.30984	0.0
652	SOO2015095000701	Tidal Mixed	CB01	-123.318	48.344	2015-07-27 19:06:00	Daylight	SCOR VNH	236	28	0	60	1.29901	1.55372	0.06543	2.18596	0.00539	0.02079	3.39476	0.0
653	SOO2015095000801	Tidal Mixed	MAC41	-123.409	48.402	2015-07-27 20:00:00	Daylight	SCOR VNH	236	49	0	62	1.28000	2.11012	0.19443	21.37141	0.01080	0.11882	27.27426	0.0

654 rows × 20 columns

In [30]:

import netCDF4 as nc

In [31]:

ftemp=nc.Dataset('/data/eolson/results/MEOPAR/NEMO-forcing-new/grid/mesh_mask201702.nc')

In [32]:

ftemp.variables.keys()

Out[32]:

dict_keys(['nav_lon', 'nav_lat', 'time_counter', 'tmask', 'umask', 'vmask', 'fmask', 'tmaskutil', 'umaskutil', 'vmaskutil', 'fmaskutil', 'glamt', 'glamu', 'glamv', 'glamf', 'gphit', 'gphiu', 'gphiv', 'gphif', 'e1t', 'e1u', 'e1v', 'e1f', 'e2t', 'e2u', 'e2v', 'e2f', 'ff', 'mbathy', 'misf', 'isfdraft', 'e3t_0', 'e3u_0', 'e3v_0', 'e3w_0', 'gdept_0', 'gdepu', 'gdepv', 'gdepw_0', 'gdept_1d', 'gdepw_1d', 'e3t_1d', 'e3w_1d'])

In [33]:

ftemp.variables['e3t_0']

Out[33]:

<class 'netCDF4._netCDF4.Variable'>
float64 e3t_0(t, z, y, x)
    _FillValue: nan
    standard_name: e3t_0
    long_name: grid spacing on T-grid in w direction
    units: m
unlimited dimensions: t
current shape = (1, 40, 898, 398)
filling on

In [34]:

ftemp.variables['e3t_1d'][:]

Out[34]:

masked_array(data=[[ 1.00000115,  1.00000501,  1.00001253,  1.00002718,
                     1.0000557 ,  1.00011125,  1.00021946,  1.0004302 ,
                     1.00084067,  1.00164012,  1.0031971 ,  1.00622914,
                     1.01213271,  1.02362358,  1.04597551,  1.08940061,
                     1.17356428,  1.33592899,  1.64636781,  2.22990285,
                     3.29248567,  5.11998508,  7.97451506, 11.8252972 ,
                    16.10792044, 19.95870258, 22.81323256, 24.64073198,
                    25.70331479, 26.28684983, 26.59728865, 26.75965336,
                    26.84381704, 26.88724213, 26.90959407, 26.92108493,
                    26.9269885 , 26.93002054, 26.93157752, 26.93237697]],
             mask=False,
       fill_value=1e+20)

In [35]:

fdict={'ptrc_T':1,'grid_T':1}
start_date = dt.datetime(2015,6,1)
end_date = dt.datetime(2015,6,30)
flen=1 # number of days per model output file. always 1 for 201905 and 201812 model runs
namfmt='nowcast' # for 201905 and 201812 model runs, this should always be 'nowcast'
# filemap is dictionary of the form variableName: fileType, where variableName is the name
# of the variable you want to extract and fileType designates the type of 
# model output file it can be found in (usually ptrc_T for biology, grid_T for temperature and 
# salinity)
filemap={'microzooplankton':'ptrc_T','mesozooplankton':'ptrc_T'}
# fdict is a dictionary mappy file type to its time resolution. Here, 1 means hourly output
# (1h file) and 24 means daily output (1d file). In certain runs, multiple time resolutions 
# are available
fdict={'ptrc_T':1,'grid_T':1}

In [36]:

PATH= '/results2/SalishSea/nowcast-green.201905/'

In [37]:

biomassDF.rename(columns={'lon':'Lon','lat':'Lat'},inplace=True)

In [38]:

biomassDF.keys()

Out[38]:

Index(['Key', 'region_name', 'Station', 'Lon', 'Lat', 'dtUTC', 'Twilight',
       'Net_Type', 'Mesh_Size(um)', 'DEPTH_STRT1', 'DEPTH_END1',
       'Bottom Depth(m)', 'Amphipoda', 'Decapoda', 'Euphausiacea', 'Calanoida',
       'Cyclopoida', 'Poecilostomatoida', 'Copelata', 'Harpacticoida'],
      dtype='object')

In [39]:

biomassDF.rename(columns={'DEPTH_STRT1':'Z_lower','DEPTH_END1':'Z_upper','Bottom Depth (m)': 'Z'},inplace=True)

In [40]:

data=et.matchData(biomassDF,filemap,fdict,start_date,end_date,'nowcast',PATH,1,quiet=False,method='vertNet');

Warning: lower limit is not an ocean value:  i=159, j=646, k_upper=0, k_lower=34, k_seafloor=34 Lon=-124.72399999999999, Lat=49.707, dtUTC=2015-06-28 06:15:00
Warning: lower limit is not an ocean value:  i=159, j=646, k_upper=0, k_lower=34, k_seafloor=34 Lon=-124.72399999999999, Lat=49.707, dtUTC=2015-06-28 06:15:00

In [41]:

data

Out[41]:

	Key	region_name	Station	Lon	Lat	dtUTC	Twilight	Net_Type	Mesh_Size(um)	Z_lower	...	Cyclopoida	Poecilostomatoida	Copelata	Harpacticoida	j	i	mod_microzooplankton	mod_mesozooplankton	k_upper	k_lower
0	IOS2015020019801	Northern Strait of Georgia	14	-124.997	49.884	2015-06-06 06:06:00	Daylight	Bongo VNH	236	302	...	0.72407	0.94464	0.49944	0.00000	700	141	0.074582	0.290741	0	34
1	IOS2015020020001A	Northern Strait of Georgia	11	-124.723	49.707	2015-06-06 08:37:00	Night	Bongo VNH	236	289	...	0.50000	0.43750	0.05000	0.00000	645	159	0.072160	0.309218	0	33
2	IOS2015020020201	Northern Strait of Georgia	CPF2	-124.500	49.466	2015-06-06 11:05:00	Daylight	Bongo VNH	236	315	...	0.91324	0.41343	0.09291	0.00000	583	162	0.048654	0.186083	0	34
3	IOS2015020020401	Central Strait of Georgia	CPF1	-124.084	49.367	2015-06-06 13:25:00	Daylight	Bongo VNH	236	233	...	0.87370	0.44702	0.23760	0.00000	534	211	0.094083	0.301332	0	31
4	IOS2015020020601	Northern Strait of Georgia	22	-124.272	49.670	2015-06-06 16:26:00	Daylight	Bongo VNH	236	342	...	0.73786	0.43804	1.47271	0.00000	606	221	0.042945	0.192460	0	35
5	IOS2015020020801	Northern Strait of Georgia	24	-124.098	49.504	2015-06-06 18:28:00	Daylight	Bongo VNH	236	411	...	0.77318	0.35132	0.90786	0.00018	562	226	0.047029	0.173742	0	38
6	IOS2015020021001	Central Strait of Georgia	28	-123.755	49.402	2015-06-06 20:27:00	Daylight	Bongo VNH	236	122	...	1.87486	0.49741	1.77711	0.00000	517	263	0.148792	0.430705	0	27
7	IOS2015020021201	Central Strait of Georgia	GEO1	-123.750	49.249	2015-06-06 22:11:00	Daylight	Bongo VNH	236	390	...	0.76200	0.38549	0.32561	0.00000	487	245	0.058598	0.176175	0	37
8	IOS2015020021301	Central Strait of Georgia	GEO1	-123.748	49.249	2015-06-06 22:53:00	Daylight	MPS VNH	250	390	...	0.03467	0.04440	0.17067	0.00000	487	245	0.003679	0.025794	34	37
9	IOS2015020021302	Central Strait of Georgia	GEO1	-123.748	49.249	2015-06-06 22:54:00	Daylight	MPS VNH	250	300	...	0.02844	0.02329	0.07585	0.00000	487	245	0.014898	0.055481	30	34
10	IOS2015020021303	Central Strait of Georgia	GEO1	-123.748	49.249	2015-06-06 22:56:00	Daylight	MPS VNH	250	200	...	0.41095	0.08984	0.14523	0.00000	487	245	0.049306	0.136318	26	30
11	IOS2015020021304	Central Strait of Georgia	GEO1	-123.748	49.249	2015-06-06 22:59:00	Daylight	MPS VNH	250	100	...	0.36214	0.07894	0.32747	0.00000	487	245	0.092179	0.276844	23	26
12	IOS2015020021305	Central Strait of Georgia	GEO1	-123.748	49.249	2015-06-06 23:00:00	Daylight	MPS VNH	250	50	...	1.12051	0.81724	1.01784	0.00000	487	245	0.242380	0.688722	0	23
13	IOS2015020021501	Central Strait of Georgia	38	-123.440	49.202	2015-06-07 01:06:00	Daylight	Bongo VNH	236	293	...	1.18817	0.44428	0.48725	0.00000	456	285	0.129881	0.326925	0	33
14	IOS2015020021701	Central Strait of Georgia	41	-123.372	49.056	2015-06-07 02:45:00	Daylight	Bongo VNH	236	219	...	1.04013	0.54064	0.18782	0.00000	423	276	0.148957	0.415778	0	31
15	PSF2015098003201	Baynes Sound	BS-7	-124.767	49.484	2015-06-08 16:08:00	Daylight	Ring VNH	250	47	...	0.47805	2.34147	45.46341	0.00000	605	125	0.315842	1.034672	0	23
16	PSF2015098003301	Baynes Sound	BS-1	-124.866	49.609	2015-06-08 17:43:00	Daylight	Ring VNH	250	24	...	0.06772	3.79260	135.90124	0.00000	636	126	0.465556	1.880479	0	20
17	PSF2015097002501	Northern Strait of Georgia	IS-4	-124.155	49.575	2015-06-09 18:32:00	Daylight	Ring VNH	250	141	...	0.32217	0.40143	1.29828	0.00000	579	226	0.105121	0.394998	0	28
18	PSF2015097002601	Northern Strait of Georgia	IS-3	-124.287	49.655	2015-06-09 20:44:00	Daylight	Ring VNH	250	148	...	0.32345	0.35797	0.28382	0.00000	604	217	0.101539	0.444235	0	28
19	PSF2015097002701	Nearshore-North East	IS-2	-124.083	49.637	2015-06-09 22:40:00	Daylight	Ring VNH	250	25	...	0.71367	0.85947	9.95299	0.00000	587	245	0.336851	0.906971	0	20
20	PSF2015097002801	Northern Strait of Georgia	IS-4	-124.157	49.575	2015-06-15 17:34:00	Daylight	Ring VNH	250	150	...	1.33018	0.22629	6.52331	0.00000	580	226	0.189448	0.438321	0	28
21	PSF2015097002901	Northern Strait of Georgia	IS-3	-124.287	49.655	2015-06-15 19:08:00	Daylight	Ring VNH	250	148	...	0.29802	0.22109	8.11830	0.00000	604	217	0.205938	0.534066	0	28
22	PSF2015097003001	Nearshore-North East	IS-2	-124.083	49.637	2015-06-15 21:08:00	Daylight	Ring VNH	250	36	...	1.90443	0.86977	94.24747	0.00000	587	245	0.804913	1.618268	0	22
23	PSF2015098006001	Baynes Sound	BS-7	-124.767	49.483	2015-06-18 15:32:00	Daylight	Ring VNH	250	57	...	0.74627	0.89228	20.63169	0.00000	605	125	0.563907	0.800657	0	24
24	PSF2015098003401	Baynes Sound	BS-1	-124.867	49.608	2015-06-18 16:48:00	Daylight	Ring VNH	250	33	...	0.23051	1.43729	26.57627	0.00000	636	126	0.702900	1.055745	0	22
25	PSF2015098003501	Northern Strait of Georgia	BS-3	-124.666	49.692	2015-06-18 18:49:00	Daylight	Ring VNH	250	150	...	1.03680	0.25693	3.19715	0.00000	639	166	0.260603	0.456427	0	28
26	PSF2015098003601	Nearshore North West	BS-6	-124.605	49.491	2015-06-18 21:29:00	Daylight	Ring VNH	250	36	...	0.56746	0.72541	2.45704	0.00000	595	149	0.780453	0.950406	0	22
27	PSF2015098003701	Baynes Sound	BS-7	-124.767	49.483	2015-06-23 15:44:00	Daylight	Ring VNH	250	47	...	0.05405	0.61622	73.62163	0.10811	605	125	0.416449	0.689419	0	23
28	PSF2015098003801	Baynes Sound	BS-1	-124.867	49.609	2015-06-23 16:52:00	Daylight	Ring VNH	250	31	...	0.17524	1.60000	26.66667	0.00000	637	126	1.018696	1.327305	0	21
29	PSF2015098003901	Northern Strait of Georgia	BS-3	-124.667	49.692	2015-06-23 19:04:00	Daylight	Ring VNH	250	130	...	0.91690	0.85479	3.88494	0.29224	639	166	0.257833	0.493006	0	27
30	PSF2015097003101	Northern Strait of Georgia	IS-4	-124.155	49.575	2015-06-24 18:18:00	Daylight	Ring VNH	250	150	...	1.52572	0.12528	0.89013	0.00000	579	226	0.161277	0.365172	0	28
31	PSF2015097003201	Northern Strait of Georgia	IS-3	-124.287	49.655	2015-06-24 19:48:00	Daylight	Ring VNH	250	150	...	1.03530	0.22246	1.39992	0.00000	604	217	0.146848	0.341614	0	28
32	PSF2015097003301	Nearshore-North East	IS-2	-124.083	49.637	2015-06-24 21:41:00	Daylight	Ring VNH	250	32	...	0.57785	0.67135	5.76987	0.00000	587	245	0.449345	0.688347	0	22
33	IOS2015018000301	Tidal Mixed	59	-123.244	48.630	2015-06-25 04:55:00	Daylight	SCOR VNH	236	151	...	0.15325	1.04130	0.73676	0.00000	331	242	0.302414	0.548781	0	28
34	IOS2015018001501	Juan de Fuca	72	-124.067	48.311	2015-06-25 21:56:00	Daylight	SCOR VNH	236	171	...	0.17342	0.02021	0.28119	0.00000	329	82	0.144993	0.381645	0	29
35	IOS2015018002801	Tidal Mixed	63	-122.976	48.244	2015-06-26 08:46:00	Night	SCOR VNH	236	144	...	0.06949	0.50700	11.33600	0.00000	238	234	0.270909	0.616372	0	28
36	IOS2015018003501	Gulf Islands	52	-123.025	48.773	2015-06-26 17:08:00	Daylight	SCOR VNH	236	203	...	0.27303	0.63049	2.91797	0.00000	344	292	0.260919	0.516593	0	30
37	IOS2015018004801	Central Strait of Georgia	42	-123.437	49.030	2015-06-27 03:01:00	Daylight	SCOR VNH	236	312	...	0.21688	0.14958	1.43429	0.00000	422	263	0.156038	0.311815	0	34
38	IOS2015018005801	Central Strait of Georgia	GEO1	-123.748	49.250	2015-06-27 09:54:00	Night	SCOR VNH	236	395	...	1.38083	0.40716	0.41838	0.00000	487	245	0.079141	0.164747	0	37
39	IOS2015018006901	Central Strait of Georgia	CPF1	-124.086	49.366	2015-06-27 18:33:00	Daylight	SCOR VNH	236	231	...	1.15273	0.20288	0.38883	0.00000	534	210	0.104848	0.246499	0	31
40	IOS2015018007401	Northern Strait of Georgia	CPF2	-124.500	49.467	2015-06-27 22:22:00	Daylight	SCOR VNH	236	325	...	1.27439	0.30115	2.72906	0.00000	583	162	0.088338	0.207112	0	35
41	IOS2015018007501	Baynes Sound	BS1	-124.763	49.480	2015-06-27 23:40:00	Daylight	SCOR VNH	236	61	...	0.69324	0.58465	13.15498	0.10440	604	125	0.401219	0.796621	0	24
42	IOS2015018008401	Northern Strait of Georgia	11	-124.724	49.707	2015-06-28 06:15:00	Daylight	SCOR VNH	236	298	...	1.06781	0.23454	0.10399	0.00000	646	159	0.118683	0.252703	0	34
43	IOS2015018008701	Northern Strait of Georgia	14	-124.994	49.884	2015-06-28 09:57:00	Night	SCOR VNH	236	313	...	0.64792	0.41158	0.15437	0.00000	699	141	0.100846	0.233627	0	34
44	IOS2015018010001	Northern Strait of Georgia	22	-124.271	49.670	2015-06-29 02:59:00	Daylight	SCOR VNH	236	347	...	1.20016	0.33240	0.40017	0.00000	606	221	0.053246	0.155823	0	35

45 rows × 26 columns

In [ ]: