Python outputRfileの例

コード例 #1

ファイル: get_data.py プロジェクト: otsegun/lightcurves

connection.commit()

####
#### get the flux / time measurements for some objects
####

sql_cmd = '''SELECT source_id FROM sources WHERE survey='debosscher' AND original_source_id=source_id'''
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
db_info
source_id = []
for i in db_info:
    source_id.append(i[0])

db_output.tfeOutput(source_id, cursor, 'tfe.txt')
db_output.outputRfile(source_id, cursor, 'features.txt')

####
#### get class of object we are looking at
####

sql_cmd = '''SELECT source_id,classification FROM sources WHERE survey='debosscher' AND number_points > 200 AND original_source_id=source_id'''
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
db_info

to_output = []
for i in range(len(db_info)):
    to_output.append(str(db_info[i][0]) + '; ' + str(db_info[i][1]) + '\n')

g = open('class_output.txt', 'w')

コード例 #2

derive_features.derive_features_par(source_ids,
                                    noise_dict,
                                    cursor,
                                    connection,
                                    number_processors=2,
                                    delete_existing=True)
connection.commit()

### check that we have filenames

##########
########## OUTPUT RESULTS
##########
## output all sources to R file for analysis
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids, cursor,
                      '../data_processed/hip_ogle_plot.dat')

## output tfes
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.tfeOutput(source_ids, cursor,
                    '../data_processed/hip_ogle_plot_tfe.dat')

connection.commit()

コード例 #3

# make a nice view of the features table
sql_cmd = """CREATE VIEW IF NOT EXISTS features_short AS SELECT source_id,freq1_harmonics_freq_0,std,max,weighted_average FROM features"""
cursor.execute(sql_cmd)

# take a look at the features
sql_cmd = """SELECT * FROM features_short"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
for i in db_info:
    print i

#######
####### OUTPUT FOR ANALYSIS IN R
#######

# output all sources to R file for analysis
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids, cursor,
                      '../data_processed/hipparcos/sources00001.dat')

# output tfes
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.tfeOutput(source_ids, cursor,
                    '../data_processed/hipparcos/tfe00001.dat')

コード例 #4

ファイル: interp_sharmo_sim.py プロジェクト: jpl2116/lightcurves

## retreive everything
sql_cmd = """SELECT source_id FROM sources"""        
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
noise_dict = noisification.get_noisification_dict()
derive_features.derive_features_par(source_ids,noise_dict,cursor,connection,number_processors=2,delete_existing=True)


#######
####### OUTPUT FOR ANALYSIS IN R
#######

## output all sources to R file for analysis
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids,cursor,'../data_processed/sharmo_outliers.dat')

## output tfes
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.tfeOutput(source_ids,cursor,'../data_processed/sharmo_outliers_tfe.dat')


connection.commit()

コード例 #5

ファイル: interp_job_talk.py プロジェクト: jpl2116/lightcurves

db_info = cursor.fetchall()
source_ids = tolist(db_info)
noise_dict = noisification.get_noisification_dict()
derive_features.derive_features_par(source_ids,noise_dict,cursor,connection,number_processors=2,delete_existing=True)
connection.commit()


##########
########## OUTPUT RESULTS
##########
## output all sources to R file for analysis
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids,cursor,'../data_processed/job_talk.dat')

## output tfes
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.tfeOutput(source_ids,cursor,'../data_processed/job_talk_tfe.dat')

connection.commit()

# sql_cmd = """SELECT number_points FROM sources"""
# cursor.execute(sql_cmd)
# db_info = cursor.fetchall()
# print db_info

コード例 #6

ファイル: interp_visualize_feat_error.py プロジェクト: jpl2116/lightcurves

# take a look at the features
sql_cmd = """SELECT * FROM features_short"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
for i in db_info:
	print i




# output all sources to R file for analysis
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids,cursor,'../data_processed/visualize_feat_error.dat')

# output tfes
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.tfeOutput(source_ids,cursor,'../data_processed/visualize_feat_error_tfe.dat')

コード例 #7

source_ids = tolist(db_info)
noise_dict = noisification.get_noisification_dict()
derive_features.derive_features_par(source_ids,
                                    noise_dict,
                                    cursor,
                                    connection,
                                    number_processors=2,
                                    delete_existing=True)

#######
####### OUTPUT FOR ANALYSIS IN R
#######

## output all sources to R file for analysis
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids, cursor,
                      '../data_processed/sharmo_outliers.dat')

## output tfes
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.tfeOutput(source_ids, cursor,
                    '../data_processed/sharmo_outliers_tfe.dat')

connection.commit()

コード例 #8

hip = synthetic_data.CadenceFromSurvey(database_location='../db/hip_three_class.db')
## test hip and ogle
cadence_dict = {'hip':hip,'ogle':ogle}
derive_features.derive_features_par(source_ids,noise_dict,cursor,connection,cadence_dict,number_processors=2,delete_existing=True)
connection.commit()


##########
########## OUTPUT RESULTS
##########
## output all sources to R file for analysis
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids,cursor,'../data_processed/hip_train_three_class.dat')

## output tfes
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.tfeOutput(source_ids,cursor,'../data_processed/hip_train_three_class_tfe.dat')

connection.commit()


#### write function (or modify tfeOutput) so that we can write smoothed tfe's out for
#### examination

コード例 #9

ファイル: interp_lc_plots.py プロジェクト: jpl2116/lightcurves

db_info = cursor.fetchall()
source_ids = tolist(db_info)
noise_dict = noisification.get_noisification_dict()
derive_features.derive_features_par(source_ids,noise_dict,cursor,connection,number_processors=2,delete_existing=True)
connection.commit()




### check that we have filenames


##########
########## OUTPUT RESULTS
##########
## output all sources to R file for analysis
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids,cursor,'../data_processed/hip_ogle_plot.dat')

## output tfes
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.tfeOutput(source_ids,cursor,'../data_processed/hip_ogle_plot_tfe.dat')

connection.commit()

コード例 #10

ファイル: interp_job_talk.py プロジェクト: otsegun/lightcurves

                                    noise_dict,
                                    cursor,
                                    connection,
                                    number_processors=2,
                                    delete_existing=True)
connection.commit()

##########
########## OUTPUT RESULTS
##########
## output all sources to R file for analysis
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids, cursor, '../data_processed/job_talk.dat')

## output tfes
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.tfeOutput(source_ids, cursor, '../data_processed/job_talk_tfe.dat')

connection.commit()

# sql_cmd = """SELECT number_points FROM sources"""
# cursor.execute(sql_cmd)
# db_info = cursor.fetchall()
# print db_info

コード例 #11

ファイル: interp_eclipse_RR.py プロジェクト: otsegun/lightcurves

db_info = cursor.fetchall()
source_ids = tolist(db_info)
noise_dict = noisification.get_noisification_dict()
derive_features.derive_features_par(source_ids,noise_dict,cursor,connection,number_processors=2,delete_existing=True)
connection.commit()





##########
########## OUTPUT RESULTS
##########
## output all sources to R file for analysis
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids,cursor,'../data_processed/eclipse-rr.dat')

## output tfes
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.tfeOutput(source_ids,cursor,'../data_processed/eclipse-rr-tfe.dat')


connection.commit()

コード例 #12

ファイル: interp_simulated.py プロジェクト: jpl2116/lightcurves

cursor.execute(sql_cmd)
db_info = cursor.fetchall()
for i in db_info:
	print i







#############
############# OUTPUT R FILES FOR ANALYSIS
#############

# output all sources to R file for analysis
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids,cursor,'../data_processed/simulated_data.dat')

# output tfes
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.tfeOutput(source_ids,cursor,'../data_processed/simulated_data_tfe.dat')

コード例 #13

derive_features.derive_features_par(source_ids,
                                    noise_dict,
                                    cursor,
                                    connection,
                                    cadence_dict,
                                    number_processors=2,
                                    delete_existing=True)

##########
########## OUTPUT RESULTS
##########
## output all sources to R file for analysis
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(
    source_ids, cursor,
    '../data_processed/cadence_comparison/ogle_versus_hipparcos.dat')

## output tfes
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.tfeOutput(
    source_ids, cursor,
    '../data_processed/cadence_comparison/tfe_ogle_versus_hipparcos.dat')

connection.commit()

コード例 #14

source_ids = tolist(db_info)
noise_dict = noisification.get_noisification_dict()
derive_features.derive_features_par(source_ids,
                                    noise_dict,
                                    cursor,
                                    connection,
                                    number_processors=2,
                                    delete_existing=True)

#######
####### OUTPUT FOR ANALYSIS IN R
#######

## output all sources to R file for analysis
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids, cursor,
                      '../data_processed/cadence_comparison/sources00001.dat')

## output tfes
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.tfeOutput(source_ids, cursor,
                    '../data_processed/cadence_comparison/DELETE_THIS.dat')

connection.commit()

コード例 #15

ファイル: interp_hip_dubath.py プロジェクト: jpl2116/lightcurves

derive_features.derive_features_par(source_ids,noise_dict,cursor,connection,number_processors=2,delete_existing=True)








#######
####### OUTPUT FOR ANALYSIS IN R
#######

## output all sources to R file for analysis
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids,cursor,'../data_processed/hipparcos_dubath_sources.dat')

## output tfes
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.tfeOutput(source_ids,cursor,'../data_processed/hipparcos_dubath_tfe.dat')


connection.commit()

コード例 #16

ファイル: interp_hip_dubath.py プロジェクト: otsegun/lightcurves

source_ids = tolist(db_info)
noise_dict = noisification.get_noisification_dict()
derive_features.derive_features_par(source_ids,
                                    noise_dict,
                                    cursor,
                                    connection,
                                    number_processors=2,
                                    delete_existing=True)

#######
####### OUTPUT FOR ANALYSIS IN R
#######

## output all sources to R file for analysis
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids, cursor,
                      '../data_processed/hipparcos_dubath_sources.dat')

## output tfes
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.tfeOutput(source_ids, cursor,
                    '../data_processed/hipparcos_dubath_tfe.dat')

connection.commit()

コード例 #17

ファイル: interp_read_debosscher.py プロジェクト: jpl2116/lightcurves

# make a nice view of the features table
sql_cmd = """CREATE VIEW IF NOT EXISTS features_short AS SELECT source_id,freq1_harmonics_freq_0,std,max,weighted_average FROM features"""
cursor.execute(sql_cmd)

# take a look at the features
sql_cmd = """SELECT * FROM features_short"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
for i in db_info:
	print i



#######
####### OUTPUT FOR ANALYSIS IN R
#######

# output all sources to R file for analysis
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids,cursor,'../data_processed/hipparcos/sources00001.dat')

# output tfes
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.tfeOutput(source_ids,cursor,'../data_processed/hipparcos/tfe00001.dat')

コード例 #18

ファイル: interp_convex_project.py プロジェクト: jpl2116/lightcurves

## get rid of missing data by imputing median / mode


##########
########## OUTPUT RESULTS
##########
features_to_remove = ['n_points','min','max','median','weighted_average','small_kurtosis', \
                          'fold2P_slope_90percentile','fold2P_slope_10percentile','medperc90_2p_p',\
                          'freq_signif','p2p_scatter_over_mad',]
## output all sources to R file for analysis
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids,cursor,'../data_processed/RR2convexMeta.dat')


## output original sources information
## column for class, column for source id, column for features, so 
## (#columns) = 2 + (#features)
sql_cmd = """SELECT source_id FROM sources WHERE source_id = original_source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputOriginalOnly(source_ids,cursor,'../data_processed/RR2convexPoint.dat',features_to_remove)

## output intervals for sources
## NOTE: removing the WHERE will ensure that range of interval covers
##       the entire feature, this may not be such a bad idea
sql_cmd = """SELECT source_id FROM sources WHERE source_id != original_source_id"""

コード例 #19

## DERIVE FEATURES
sql_cmd = """SELECT source_id FROM sources"""        
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
noise_dict = noisification.get_noisification_dict()
derive_features.derive_features_par(source_ids,noise_dict,cursor,connection,number_processors=2,delete_existing=True)


##########
########## OUTPUT RESULTS
##########
## output all sources to R file for analysis
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids,cursor,'../data_processed/ogleIIIall-fund.dat')

## output tfes
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.tfeOutput(source_ids,cursor,'../data_processed/ogleIIIall-fund-tfe.dat')


connection.commit()

コード例 #20

ファイル: interp_convex_project.py プロジェクト: otsegun/lightcurves

                                    delete_existing=True)

## get rid of missing data by imputing median / mode

##########
########## OUTPUT RESULTS
##########
features_to_remove = ['n_points','min','max','median','weighted_average','small_kurtosis', \
                          'fold2P_slope_90percentile','fold2P_slope_10percentile','medperc90_2p_p',\
                          'freq_signif','p2p_scatter_over_mad',]
## output all sources to R file for analysis
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids, cursor,
                      '../data_processed/RR2convexMeta.dat')

## output original sources information
## column for class, column for source id, column for features, so
## (#columns) = 2 + (#features)
sql_cmd = """SELECT source_id FROM sources WHERE source_id = original_source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputOriginalOnly(source_ids, cursor,
                             '../data_processed/RR2convexPoint.dat',
                             features_to_remove)

## output intervals for sources
## NOTE: removing the WHERE will ensure that range of interval covers
##       the entire feature, this may not be such a bad idea

コード例 #21

ファイル: interp_asas.py プロジェクト: otsegun/lightcurves

source_ids = tolist(db_info)
noise_dict = noisification.get_noisification_dict()
derive_features.derive_features_par(source_ids,noise_dict,cursor,connection,number_processors=2,delete_existing=True)
connection.commit()







##########
########## OUTPUT RESULTS
##########
## output features file
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids,cursor,'../data_processed/asas.dat')
connection.commit()

## output tfes (i.e. time, fluxes (magnitudes actually), and errors) in 
## a file, nice for doing visualization
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.tfeOutput(source_ids,cursor,'../data_processed/asas_tfe.dat')
connection.commit()

コード例 #22

ファイル: interp_ogle_hip_cadence_comp.py プロジェクト: jpl2116/lightcurves

cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
noise_dict = noisification.get_noisification_dict()
hip = synthetic_data.CadenceFromSurvey(database_location='../db/hipparcos_cadences.db')
ogle = synthetic_data.CadenceFromSurvey(database_location='../db/ogle_cadences.db')
cadence_dict = {'hip':hip,'ogle':ogle}
derive_features.derive_features_par(source_ids,noise_dict,cursor,connection,cadence_dict,number_processors=2,delete_existing=True)



##########
########## OUTPUT RESULTS
##########
## output all sources to R file for analysis
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids,cursor,'../data_processed/cadence_comparison/ogle_versus_hipparcos.dat')

## output tfes
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.tfeOutput(source_ids,cursor,'../data_processed/cadence_comparison/tfe_ogle_versus_hipparcos.dat')


connection.commit()

コード例 #23

ファイル: interp_test.py プロジェクト: jpl2116/lightcurves

cadence_dict = {'ogle':ogle}

## derive the features and save
derive_features.derive_features_par(source_ids,noise_dict,cursor,connection,cadence_dict,number_processors=2,delete_existing=True)
connection.commit()


##########
########## OUTPUT RESULTS
##########
## output features file
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids,cursor,'../data_processed/test.dat')
connection.commit()

## output tfes (i.e. time, fluxes (magnitudes actually), and errors) in 
## a file, nice for doing visualization
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.tfeOutput(source_ids,cursor,'../data_processed/test_tfe.dat')
connection.commit()

## output smoothed tfes, same thing as previous lines but uses measurements_smoothed table
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()

コード例 #24

ファイル: get_data.py プロジェクト: jpl2116/lightcurves

####
#### get the flux / time measurements for some objects
####

sql_cmd = '''SELECT source_id FROM sources WHERE survey='debosscher' AND original_source_id=source_id'''
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
db_info
source_id = []
for i in db_info:
    source_id.append(i[0])


db_output.tfeOutput(source_id,cursor,'tfe.txt')
db_output.outputRfile(source_id,cursor,'features.txt')





####
#### get class of object we are looking at
####


sql_cmd = '''SELECT source_id,classification FROM sources WHERE survey='debosscher' AND number_points > 200 AND original_source_id=source_id'''
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
db_info

コード例 #25

noise_dict = noisification.get_noisification_dict()
derive_features.derive_features_par(source_ids,
                                    noise_dict,
                                    cursor,
                                    connection,
                                    number_processors=2,
                                    delete_existing=True)

# take a look at the features
sql_cmd = """SELECT * FROM features_short"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
for i in db_info:
    print i

# output all sources to R file for analysis
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids, cursor,
                      '../data_processed/visualize_feat_error.dat')

# output tfes
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.tfeOutput(source_ids, cursor,
                    '../data_processed/visualize_feat_error_tfe.dat')

コード例 #26

ファイル: interp_cadence_compar.py プロジェクト: jpl2116/lightcurves

cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
noise_dict = noisification.get_noisification_dict()
derive_features.derive_features_par(source_ids,noise_dict,cursor,connection,number_processors=2,delete_existing=True)




#######
####### OUTPUT FOR ANALYSIS IN R
#######

## output all sources to R file for analysis
sql_cmd = """SELECT source_id FROM sources"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.outputRfile(source_ids,cursor,'../data_processed/cadence_comparison/sources00001.dat')

## output tfes
sql_cmd = """SELECT source_id FROM sources WHERE original_source_id = source_id"""
cursor.execute(sql_cmd)
db_info = cursor.fetchall()
source_ids = tolist(db_info)
db_output.tfeOutput(source_ids,cursor,'../data_processed/cadence_comparison/DELETE_THIS.dat')


connection.commit()