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from builtins import str 

from builtins import object 

import os, warnings 

from sqlalchemy import create_engine 

from sqlalchemy.orm import sessionmaker 

from sqlalchemy.engine import url 

from sqlalchemy.ext.declarative import declarative_base 

from sqlalchemy import Column, Integer, String, Float 

from sqlalchemy import ForeignKey 

from sqlalchemy.orm import relationship, backref 

from sqlalchemy.exc import DatabaseError 

from lsst.daf.persistence import DbAuth 

 

import numpy as np 

 

Base = declarative_base() 

 

__all__ = ['MetricRow', 'DisplayRow', 'PlotRow', 'SummaryStatRow', 'ResultsDb'] 

 

class MetricRow(Base): 

""" 

Define contents and format of metric list table. 

 

(Table to list all metrics, their metadata, and their output data files). 

""" 

__tablename__ = "metrics" 

# Define columns in metric list table. 

metricId = Column(Integer, primary_key=True) 

metricName = Column(String) 

slicerName = Column(String) 

simDataName = Column(String) 

sqlConstraint = Column(String) 

metricMetadata = Column(String) 

metricDataFile = Column(String) 

def __repr__(self): 

return "<Metric(metricId='%d', metricName='%s', slicerName='%s', simDataName='%s', sqlConstraint='%s', metadata='%s', metricDataFile='%s')>" \ 

%(self.metricId, self.metricName, self.slicerName, self.simDataName, 

self.sqlConstraint, self.metricMetadata, self.metricDataFile) 

 

class DisplayRow(Base): 

""" 

Define contents and format of the displays table. 

 

(Table to list the display properties for each metric.) 

""" 

__tablename__ = "displays" 

displayId = Column(Integer, primary_key=True) 

metricId = Column(Integer, ForeignKey('metrics.metricId')) 

# Group for displaying metric (in webpages). 

displayGroup = Column(String) 

# Subgroup for displaying metric. 

displaySubgroup = Column(String) 

# Order to display metric (within subgroup). 

displayOrder = Column(Float) 

# The figure caption. 

displayCaption = Column(String) 

metric = relationship("MetricRow", backref=backref('displays', order_by=displayId)) 

def __rep__(self): 

return "<Display(displayGroup='%s', displaySubgroup='%s', displayOrder='%.1f', displayCaption='%s')>" \ 

%(self.displayGroup, self.displaySubgroup, self.displayOrder, self.displayCaption) 

 

class PlotRow(Base): 

""" 

Define contents and format of plot list table. 

 

(Table to list all plots, link them to relevant metrics in MetricList, and provide info on filename). 

""" 

__tablename__ = "plots" 

# Define columns in plot list table. 

plotId = Column(Integer, primary_key=True) 

# Matches metricID in MetricList table. 

metricId = Column(Integer, ForeignKey('metrics.metricId')) 

plotType = Column(String) 

plotFile = Column(String) 

metric = relationship("MetricRow", backref=backref('plots', order_by=plotId)) 

def __repr__(self): 

return "<Plot(metricId='%d', plotType='%s', plotFile='%s')>" \ 

%(self.metricId, self.plotType, self.plotFile) 

 

class SummaryStatRow(Base): 

""" 

Define contents and format of the summary statistics table. 

 

(Table to list and link summary stats to relevant metrics in MetricList, and provide summary stat name, 

value and potentially a comment). 

""" 

__tablename__ = "summarystats" 

# Define columns in plot list table. 

statId = Column(Integer, primary_key=True) 

# Matches metricID in MetricList table. 

metricId = Column(Integer, ForeignKey('metrics.metricId')) 

summaryName = Column(String) 

summaryValue = Column(Float) 

metric = relationship("MetricRow", backref=backref('summarystats', order_by=statId)) 

def __repr__(self): 

return "<SummaryStat(metricId='%d', summaryName='%s', summaryValue='%f')>" \ 

%(self.metricId, self.summaryName, self.summaryValue) 

 

class ResultsDb(object): 

def __init__(self, outDir= None, database=None, driver='sqlite', 

host=None, port=None, verbose=False): 

""" 

Instantiate the results database, creating metrics, plots and summarystats tables. 

""" 

# Connect to database 

# for sqlite, connecting to non-existent database creates it automatically 

if database is None: 

# Using default value for database name, should specify directory. 

if outDir is None: 

outDir = '.' 

# Check for output directory, make if needed. 

if not os.path.isdir(outDir): 

try: 

os.makedirs(outDir) 

except OSError as msg: 

raise OSError(msg, '\n (If this was the database file (not outDir), ' 

'remember to use kwarg "database")') 

self.database = os.path.join(outDir, 'resultsDb_sqlite.db') 

self.driver = 'sqlite' 

else: 

if driver == 'sqlite': 

# Using non-default database, but may also specify directory root. 

if outDir is not None: 

database = os.path.join(outDir, database) 

self.database = database 

self.driver = driver 

else: 

# If not sqlite, then 'outDir' doesn't make much sense. 

self.database = database 

self.driver = driver 

self.host = host 

self.port = port 

 

if self.driver == 'sqlite': 

dbAddress = url.URL(self.driver, database=self.database) 

else: 

dbAddress = url.URL(self.driver, 

username=DbAuth.username(self.host, str(self.port)), 

password=DbAuth.password(self.host, str(self.port)), 

host=self.host, 

port=self.port, 

database=self.database) 

 

engine = create_engine(dbAddress, echo=verbose) 

self.Session = sessionmaker(bind=engine) 

self.session = self.Session() 

# Create the tables, if they don't already exist. 

try: 

Base.metadata.create_all(engine) 

except DatabaseError: 

raise ValueError("Cannot create a %s database at %s. Check directory exists." %(self.driver, self.database)) 

self.slen = 1024 

 

def close(self): 

""" 

Close connection to database. 

""" 

self.session.close() 

 

def updateMetric(self, metricName, slicerName, simDataName, sqlConstraint, 

metricMetadata, metricDataFile): 

""" 

Add a row to or update a row in the metrics table. 

 

- metricName: the name of the metric 

- sliceName: the name of the slicer 

- simDataName: the name used to identify the simData 

- sqlConstraint: the sql constraint used to select data from the simData 

- metricMetadata: the metadata associated with the metric 

- metricDatafile: the data file the metric data is stored in 

 

If same metric (same metricName, slicerName, simDataName, sqlConstraint, metadata) 

already exists, it does nothing. 

 

Returns metricId: the Id number of this metric in the metrics table. 

""" 

if simDataName is None: 

simDataName = 'NULL' 

if sqlConstraint is None: 

sqlConstraint = 'NULL' 

if metricMetadata is None: 

metricMetadata = 'NULL' 

if metricDataFile is None: 

metricDataFile = 'NULL' 

# Check if metric has already been added to database. 

prev = self.session.query(MetricRow).filter_by(metricName=metricName, 

slicerName=slicerName, 

simDataName=simDataName, 

metricMetadata=metricMetadata, 

sqlConstraint=sqlConstraint).all() 

if len(prev) == 0: 

metricinfo = MetricRow(metricName=metricName, slicerName=slicerName, simDataName=simDataName, 

sqlConstraint=sqlConstraint, metricMetadata=metricMetadata, 

metricDataFile=metricDataFile) 

self.session.add(metricinfo) 

self.session.commit() 

else: 

metricinfo = prev[0] 

return metricinfo.metricId 

 

def updateDisplay(self, metricId, displayDict, overwrite=True): 

""" 

Add a row to or update a row in the displays table. 

 

- metricID: the metric Id of this metric in the metrics table 

- displayDict: dictionary containing the display info 

 

Replaces existing row with same metricId. 

""" 

# Because we want to maintain 1-1 relationship between metricId's and displayDict's: 

# First check if a display line is present with this metricID. 

displayinfo = self.session.query(DisplayRow).filter_by(metricId=metricId).all() 

if len(displayinfo) > 0: 

if overwrite: 

for d in displayinfo: 

self.session.delete(d) 

else: 

return 

# Then go ahead and add new displayDict. 

for k in displayDict: 

if displayDict[k] is None: 

displayDict[k] = 'NULL' 

keys = ['group', 'subgroup', 'order', 'caption'] 

for k in keys: 

if k not in displayDict: 

displayDict[k] = 'NULL' 

if displayDict['order'] == 'NULL': 

displayDict['order'] = 0 

displayGroup = displayDict['group'] 

displaySubgroup = displayDict['subgroup'] 

displayOrder = displayDict['order'] 

displayCaption = displayDict['caption'] 

if displayCaption.endswith('(auto)'): 

displayCaption = displayCaption.replace('(auto)', '', 1) 

displayinfo = DisplayRow(metricId=metricId, 

displayGroup=displayGroup, displaySubgroup=displaySubgroup, 

displayOrder=displayOrder, displayCaption=displayCaption) 

self.session.add(displayinfo) 

self.session.commit() 

 

def updatePlot(self, metricId, plotType, plotFile): 

""" 

Add a row to or update a row in the plot table. 

 

- metricId: the metric Id of this metric in the metrics table 

- plotType: the 'type' of this plot 

- plotFile: the filename of this plot 

 

Remove older rows with the same metricId, plotType and plotFile. 

""" 

plotinfo = self.session.query(PlotRow).filter_by(metricId=metricId, plotType=plotType, 

plotFile=plotFile).all() 

if len(plotinfo) > 0: 

for p in plotinfo: 

self.session.delete(p) 

plotinfo = PlotRow(metricId=metricId, plotType=plotType, plotFile=plotFile) 

self.session.add(plotinfo) 

self.session.commit() 

 

def updateSummaryStat(self, metricId, summaryName, summaryValue): 

""" 

Add a row to or update a row in the summary statistic table. 

 

- metricId: the metric ID of this metric in the metrics table 

- summaryName: the name of this summary statistic 

- summaryValue: the value for this summary statistic 

 

Most summary statistics will be a simple name (string) + value (float) pair. 

For special summary statistics which must return multiple values, the base name 

can be provided as 'name', together with a np recarray as 'value', where the 

recarray also has 'name' and 'value' columns (and each name/value pair is then saved 

as a summary statistic associated with this same metricId). 

""" 

# Allow for special summary statistics which return data in a np structured array with 

# 'name' and 'value' columns. (specificially needed for TableFraction summary statistic). 

if isinstance(summaryValue, np.ndarray): 

if (('name' in summaryValue.dtype.names) and ('value' in summaryValue.dtype.names)): 

for value in summaryValue: 

sSuffix = value['name'] 

if isinstance(sSuffix, bytes): 

sSuffix = sSuffix.decode('utf-8') 

else: 

sSuffix = str(sSuffix) 

summarystat = SummaryStatRow(metricId=metricId, 

summaryName=summaryName + ' ' + sSuffix, 

summaryValue=value['value']) 

self.session.add(summarystat) 

self.session.commit() 

else: 

warnings.warn('Warning! Cannot save non-conforming summary statistic.') 

# Most summary statistics will be simple floats. 

else: 

if isinstance(summaryValue, float) or isinstance(summaryValue, int): 

summarystat = SummaryStatRow(metricId=metricId, summaryName=summaryName, 

summaryValue=summaryValue) 

self.session.add(summarystat) 

self.session.commit() 

else: 

warnings.warn('Warning! Cannot save summary statistic that is not a simple float or int') 

 

def getMetricId(self, metricName, slicerName=None, metricMetadata=None, simDataName=None): 

""" 

Given a metric name and optional slicerName/metricMetadata/simData information, 

Return a list of the matching metricIds. 

""" 

metricId = [] 

query = self.session.query(MetricRow.metricId, MetricRow.metricName, MetricRow.slicerName, 

MetricRow.metricMetadata, 

MetricRow.simDataName).filter(MetricRow.metricName == metricName) 

if slicerName is not None: 

query = query.filter(MetricRow.slicerName == slicerName) 

if metricMetadata is not None: 

query = query.filter(MetricRow.metricMetadata == metricMetadata) 

if simDataName is not None: 

query = query.filter(MetricRow.simDataName == simDataName) 

query = query.order_by(MetricRow.slicerName, MetricRow.metricMetadata) 

for m in query: 

metricId.append(m.metricId) 

return metricId 

 

def getMetricIdLike(self, metricNameLike=None, slicerNameLike=None, 

metricMetadataLike=None, simDataName=None): 

metricId = [] 

query = self.session.query(MetricRow.metricId, MetricRow.metricName, MetricRow.slicerName, 

MetricRow.metricMetadata, 

MetricRow.simDataName) 

if metricNameLike is not None: 

query = query.filter(MetricRow.metricName.like('%' + str(metricNameLike) + '%')) 

if slicerNameLike is not None: 

query = query.filter(MetricRow.slicerName.like('%' + str(slicerNameLike) + '%')) 

if metricMetadataLike is not None: 

query = query.filter(MetricRow.metricMetadata.like('%' + str(metricMetadataLike) + '%')) 

if simDataName is not None: 

query = query.filter(MetricRow.simDataName == simDataName) 

for m in query: 

metricId.append(m.metricId) 

return metricId 

 

def getAllMetricIds(self): 

""" 

Return a list of all metricIds. 

""" 

metricIds = [] 

for m in self.session.query(MetricRow.metricId).all(): 

metricIds.append(m.metricId) 

return metricIds 

 

def getSummaryStats(self, metricId=None, summaryName=None): 

""" 

Get the summary stats (optionally for metricId list). 

Optionally, also specify the summary metric name. 

Returns a numpy array of the metric information + summary statistic information. 

""" 

if metricId is None: 

metricId = self.getAllMetricIds() 

if not hasattr(metricId, '__iter__'): 

metricId = [metricId,] 

summarystats = [] 

for mid in metricId: 

# Join the metric table and the summarystat table, based on the metricID (the second filter) 

query = (self.session.query(MetricRow, SummaryStatRow).filter(MetricRow.metricId == mid) 

.filter(MetricRow.metricId == SummaryStatRow.metricId)) 

if summaryName is not None: 

query = query.filter(SummaryStatRow.summaryName == summaryName) 

for m, s in query: 

summarystats.append((m.metricId, m.metricName, m.slicerName, m.metricMetadata, 

s.summaryName, s.summaryValue)) 

# Convert to numpy array. 

dtype = np.dtype([('metricId', int), ('metricName', np.str_, self.slen), 

('slicerName', np.str_, self.slen), ('metricMetadata', np.str_, self.slen), 

('summaryName', np.str_, self.slen), ('summaryValue', float)]) 

summarystats = np.array(summarystats, dtype) 

return summarystats 

 

def getPlotFiles(self, metricId=None): 

""" 

Return the metricId, name, metadata, and all plot info (optionally for metricId list). 

Returns a numpy array of the metric information + plot file names. 

""" 

if metricId is None: 

metricId = self.getAllMetricIds() 

if not hasattr(metricId, '__iter__'): 

metricId = [metricId,] 

plotFiles = [] 

for mid in metricId: 

# Join the metric table and the plot table based on the metricID (the second filter does the join) 

query = (self.session.query(MetricRow, PlotRow).filter(MetricRow.metricId == mid) 

.filter(MetricRow.metricId == PlotRow.metricId)) 

for m, p in query: 

# The plotFile typically ends with .pdf (but the rest of name can have '.' or '_') 

thumbfile = 'thumb.' + '.'.join(p.plotFile.split('.')[:-1]) + '.png' 

plotFiles.append((m.metricId, m.metricName, m.metricMetadata, 

p.plotType, p.plotFile, thumbfile)) 

# Convert to numpy array. 

dtype = np.dtype([('metricId', int), ('metricName', np.str_, self.slen), 

('metricMetadata', np.str_, self.slen), 

('plotType', np.str_, self.slen), ('plotFile', np.str_, self.slen), 

('thumbFile', np.str_, self.slen)]) 

plotFiles = np.array(plotFiles, dtype) 

return plotFiles 

 

def getMetricDataFiles(self, metricId=None): 

""" 

Get the metric data filenames for all or a single metric. 

Returns a list. 

""" 

if metricId is None: 

metricId = self.getAllMetricIds() 

if not hasattr(metricId, '__iter__'): 

metricId = [metricId,] 

dataFiles = [] 

for mid in metricId: 

for m in self.session.query(MetricRow).filter(MetricRow.metricId == mid).all(): 

dataFiles.append(m.metricDataFile) 

return dataFiles 

 

 

def getMetricDisplayInfo(self, metricId=None): 

""" 

Get the contents of the metrics and displays table, together with the 'basemetricname' 

(optionally, for metricId list). 

Returns a numpy array of the metric information + display information. 

""" 

if metricId is None: 

metricId = self.getAllMetricIds() 

if not hasattr(metricId, '__iter__'): 

metricId = [metricId,] 

metricInfo = [] 

for mId in metricId: 

# Query for all rows in metrics and displays that match any of the metricIds. 

query = (self.session.query(MetricRow, DisplayRow).filter(MetricRow.metricId==mId) 

.filter(MetricRow.metricId==DisplayRow.metricId)) 

for m, d in query: 

baseMetricName = m.metricName.split('_')[0] 

mInfo = (m.metricId, m.metricName, baseMetricName, m.slicerName, 

m.sqlConstraint, m.metricMetadata, m.metricDataFile, 

d.displayGroup, d.displaySubgroup, d.displayOrder, d.displayCaption) 

metricInfo.append(mInfo) 

# Convert to numpy array. 

dtype = np.dtype([('metricId', int), ('metricName', np.str_, self.slen), 

('baseMetricNames', np.str_, self.slen), 

('slicerName', np.str_, self.slen), 

('sqlConstraint', np.str_, self.slen), 

('metricMetadata', np.str_, self.slen), 

('metricDataFile', np.str_, self.slen), 

('displayGroup', np.str_, self.slen), 

('displaySubgroup', np.str_, self.slen), 

('displayOrder', float), 

('displayCaption', np.str_, self.slen * 10)]) 

metricInfo = np.array(metricInfo, dtype) 

return metricInfo