class TestMemoryDB:
def setup(self):
self.connection_string = "sqlite:///:memory:"
self.series_service = SeriesService(
connection_string=self.connection_string, debug=False)
self.session = self.series_service._session_factory.get_session()
engine = self.series_service._session_factory.engine
test_util.build_db(engine)
self.memory_db = MemoryDatabase()
self.memory_db.set_series_service(self.series_service)
self.series = test_util.add_series(self.session)
self.memory_db.initEditValues(self.series.id)
def test_get_data_values(self):
dvs = self.memory_db.getDataValuesDF()
assert len(dvs) == 10
def test_update_points(self):
self.memory_db.update([{"value": 15, "id": 1}])
dvs = self.memory_db.getDataValuesDF()
print dvs["DataValue"]
assert dvs["DataValue"][1 - 1] == 9
def test_update_value(self):
self.memory_db.updateValue([1], '+', 5)
dvs = self.memory_db.getDataValuesDF()
assert dvs["DataValue"][1 - 1] == 9
def test_add_points(self):
#with pytest.raises(NotImplementedError):
point = [('-9999', None, datetime.datetime(2011, 3, 25, 0, 0), '-7',
datetime.datetime(2015, 3, 25, 7, 0), None, None, u'nc',
None, None, self.series.site_id, self.series.variable_id,
self.series.method_id, self.series.source_id,
self.series.quality_control_level_id)]
self.memory_db.addPoints(point)
dvs = self.memory_db.getDataValuesDF()
assert len(dvs) == 11
assert dvs["DataValue"][-1] == -9999
def test_update_flag(self):
self.memory_db.updateFlag([5], '50')
dvs = self.memory_db.getDataValuesDF()
assert dvs["QualifierID"][5 - 1] == '50'
def test_delete_points(self):
stlen = len(self.memory_db.getDataValuesDF())
self.memory_db.delete([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
dvs = self.memory_db.getDataValuesDF()
assert len(dvs) == stlen - 10
class EditService():
# Mutual exclusion: cursor, or connection_string
def __init__(self, series_id, connection=None, connection_string="", debug=False):
'''
:param series_id:
:param connection: memory database, contains connection to remote database
:param connection_string: connection to remote database
:param debug:
:return:
'''
self._series_id = series_id
self._filter_from_selection = False
self._debug = debug
if connection_string is "" and connection is not None:
self.memDB= connection
elif connection_string is not "" and connection is None:
from odmtools.odmdata import MemoryDatabase
self.memDB= MemoryDatabase()
self.memDB.set_series_service(SeriesService(connection_string, False))
else:
logger.error("must send in either a remote db connection string or a memory database object")
logger.debug("Initializing Memory Database")
self.memDB.initEditValues(series_id)
logger.debug("Finished Initializing Memory Database")
self._populate_series()
self.reset_filter()
def get_series_service(self):
return self.memDB.series_service
def _populate_series(self):
# [(ID, value, datetime), ...]
#self._cursor.execute("SELECT ValueID, DataValue, LocalDateTime FROM DataValues ORDER BY LocalDateTime")
self._series_points_df = self.memDB.getDataValuesDF()
def _test_filter_previous(self):
'''
if not self._filter_from_selection:
self.reset_filter()
'''
df = None
if not self._filter_from_selection:
df = self._series_points_df
else:
df = self.filtered_dataframe
# Ensure that we're not working with an empty dataframe
if isinstance(df, pd.DataFrame):
if df.empty:
return self._series_points_df
else:
if not df:
return self._series_points_df
return df
def datetime2dataframe(self, datetime_list):
""" Converts datetime_list to a pandas Dataframe
:param datetime_list:
:return Pandas.DataFrame:
"""
result = None
if isinstance(datetime_list, list):
result = pd.DataFrame(datetime_list, columns=["LocalDateTime"])
result.set_index("LocalDateTime", inplace=True)
return result
###################
# Stubs
###################
def selectPointsStub(self):
"""
:param filtered_dataframe:
:return:
"""
## Convert dataframe into list of datetimes
filtered_dataframe = self.get_filtered_points()
if isinstance(filtered_dataframe, pd.DataFrame):
if not filtered_dataframe.empty:
datetime_list = filtered_dataframe.index.to_pydatetime()
return datetime_list.tolist()
return []
###################
# Filters
###################
# operator is a character, either '<' or '>'
def filter_value(self, value, ops):
df = self._test_filter_previous()
if ops == '>':
self.filtered_dataframe = df[df['DataValue'] > value]
if ops == '<':
self.filtered_dataframe = df[df['DataValue'] < value]
def filter_date(self, before, after):
df = self._test_filter_previous()
if before and after:
self.filtered_dataframe = df[(df.index < before) & (df.index > after)]
def fill_gap(self, gap, fill):
df = self.memDB.getDataValuesDF()
gaps= self.find_gaps(df, gap[0], gap[1])
points = []
series= self.memDB.series
timegap = np.timedelta64(fill[0], self.time_units[fill[1]])
#if gaps is not of type dataframe- put it in a dataframe
#if not isinstance(gaps, pd.DataFrame
for g in gaps.iterrows():
row = g[1]
e = row.datetime
s = row.dateprev
#prime the loop
s = s + timegap
# for each gap time period in the larger gap ( until datetime = prev value)
while s < e:
utc_offset = (series.begin_date_time-series.begin_date_time_utc).total_seconds()/3600
points.append((-9999, None, s, utc_offset, s, None, None, u'nc', None, None, series.site_id, series.variable_id, series.method_id, series.source_id, series.quality_control_level_id))
#('-9999', None, DATE, series.begin_date_time_utc, UTCDATE, None, None, u'nc', None, None,
# series.site_id, series.variable_id, series.method_id, series.source_id,
# series.quality_control_level_id
s = s + timegap
#print points
self.add_points(points)
time_units = {
'second': 's',
'minute': 'm',
'hour': 'h',
'day': 'D',
'week': 'W',
'month': 'M',
'year': 'Y'
}
# Data Gaps
def find_gaps(self, df, value, time_period):
# make a copy of the dataframe in order to modify it to be in the form we need to determine data gaps
copy_df = df
copy_df['datetime'] = df.index
copy_df['dateprev'] = copy_df['datetime'].shift()
# ensure that 'value' is an integer
if not isinstance(value, int):
value = int(value)
# create a bool column indicating which rows meet condition
filtered_results = copy_df['datetime'].diff() > np.timedelta64(value, self.time_units[time_period])
# filter on rows that passed previous condition
return copy_df[filtered_results]
def data_gaps(self, value, time_period):
df = self._test_filter_previous()
copy_df = self.find_gaps(df, value, time_period)
print (copy_df)
# merge values and remove duplicates. this hack allows for both values to be marked when selecting data gaps
newdf = pd.concat([copy_df['datetime'], copy_df['dateprev']], join='inner')
# clean up
del copy_df
self.filtered_dataframe= df[df.index.isin(newdf.drop_duplicates().dropna())]
def change_value_threshold(self, value, operator):
df = self._test_filter_previous()
# make a copy of the dataframe in order to modify it to be in the form we need to determine data gaps
copy_df = df
copy_df['values'] = df['DataValue']
copy_df['diff'] = copy_df['values'].shift()
copy_df["diff_date"] = copy_df['LocalDateTime'].shift()
copy_df['change_threshold'] = abs(df['values'] - df['diff'])
if not isinstance(value, float):
logger.error("Need to have a float")
return
copy_df['threshold'] = value
if operator == ">":
copy_df['matches'] = df['change_threshold'] >= copy_df['threshold']
if operator == "<":
copy_df['matches'] = df['change_threshold'] <= copy_df['threshold']
filtered_df = copy_df[copy_df['matches']]
tmplist = filtered_df['diff_date'].tolist() + filtered_df.index.tolist()
del copy_df
self.filtered_dataframe = df[df.index.isin(tmplist)]
#Duplicate values filter
def duplicate_value_filter(self):
df = self._test_filter_previous()
#self.filtered_dataframe= df[df.index.get_duplicates()]
self.filtered_dataframe= df[df.index.isin(df.index.get_duplicates())]
#self.filtered_dataframe = df[df['DataValue'] < value]
def select_points_tf(self, tf_list):
self._filter_list = tf_list
#def select_points(self, id_list=[], datetime_list=[]):
def select_points(self, id_list=[], dataframe=[]):
#self.reset_filter()
# This should be either one or the other. If it's both, id is used first.
# If neither are set this function does nothing.
if len(id_list) > 0:
for i in range(len(self._series_points)):
if self._series_points[i][0] in id_list:
self._filter_list[i] = True
if isinstance(dataframe, pd.DataFrame):
result = dataframe.index.astype(datetime.datetime)
self.filtered_dataframe = self._series_points_df[self._series_points_df.index.isin(dataframe.index)]
def reset_filter(self):
self.filtered_dataframe = None
def filter_from_previous(self, value):
self._filter_from_selection = value
def get_toggle(self):
return self._filter_from_selection
###################
# Gets
###################
def get_series(self):
return self.memDB.series_service.get_series_by_id(self._series_id)
def get_series_points(self):
# all point in the series
return self._series_points
def get_series_points_df(self):
"""
:return Pandas DataFrame:
"""
return self._series_points_df
def get_filtered_points(self):
"""
:return Pandas DataFrame:
"""
if isinstance(self.filtered_dataframe, pd.DataFrame):
if self.filtered_dataframe.empty:
return None
else:
if not self.filtered_dataframe:
return None
if len(self.filtered_dataframe) > 0:
return self.filtered_dataframe
return None
def get_filtered_dates(self):
return self.filtered_dataframe
def get_filter_list(self):
# true or false list the length of the entire series. true indicate the point is selected
return self._filter_list
def get_qcl(self, qcl_id):
return self.memDB.series_service.get_qcl_by_id(qcl_id)
def get_method(self, method_id):
return self.memDB.series_service.get_method_by_id(method_id)
def get_variable(self, variable_id):
logger.debug(variable_id)
return self.memDB.series_service.get_variable_by_id(variable_id)
#################
# Edits
#################
def change_value(self, value, operator):
filtered_points = self.get_filtered_points()
ids = filtered_points.index.tolist()
self.memDB.updateValue(ids, operator, float(value))
self._populate_series()
## update filtered_dataframe
self.filtered_dataframe = self._series_points_df[self._series_points_df.index.isin(ids)]
def add_points(self, points):
# todo: add the ability to send in multiple datetimes to a single 'point'
self.memDB.addPoints(points)
self._populate_series()
self.reset_filter()
def delete_points(self):
filtered_points = self.get_filtered_points()
if not filtered_points.empty:
values = filtered_points.index.tolist()
self.memDB.delete(values)
self._populate_series()
self.filtered_dataframe = None
def interpolate(self):
'''
In [75]: ser = Series(np.sort(np.random.uniform(size=100)))
# interpolate at new_index
In [76]: new_index = ser.index | Index([49.25, 49.5, 49.75, 50.25, 50.5, 50.75])
In [77]: interp_s = ser.reindex(new_index).interpolate(method='pchip')
'''
tmp_filter_list =self.get_filtered_points()
df = self._series_points_df
issel = df.index.isin(tmp_filter_list.index)
mdf = df["DataValue"].mask(issel)
mdf.interpolate(method = "time", inplace=True)
tmp_filter_list["DataValue"]=mdf[issel]
ids = tmp_filter_list.index.tolist()
#update_list = [(row["DataValue"], row["ValueID"]) for index, row in tmp_filter_list.iterrows()]
update_list = [{"value": row["DataValue"], "id": index} for index, row in tmp_filter_list.iterrows()]
self.memDB.update(update_list)
self._populate_series()
self.filtered_dataframe = self._series_points_df[self._series_points_df.index.isin(ids)]
def drift_correction(self, gap_width):
if self.isOneGroup():
tmp_filter_list =self.get_filtered_points()
startdate =tmp_filter_list.index[0]
x_l = (tmp_filter_list.index[-1]-startdate).total_seconds()
#nodv= self.memDB.series_service.get_variable_by_id(self.memDB.df["VariableID"][0])
nodv = self.memDB.series.variable.no_data_value
# y_n = y_0 + G(x_i / x_l)
f = lambda row : row["DataValue"]+(gap_width * ((row.name-startdate).total_seconds() / x_l)) if row["DataValue"] != nodv else row["DataValue"]
tmp_filter_list["DataValue"]=tmp_filter_list.apply(f, axis = 1)
update_list = [{"value": row["DataValue"], "id":index} for index, row in tmp_filter_list.iterrows()]
ids = tmp_filter_list.index.tolist()
self.memDB.update(update_list)
self._populate_series()
self.filtered_dataframe = self._series_points_df[self._series_points_df.index.isin(ids)]
return True
return False
def isOneGroup(self):
issel = self._series_points_df.index.isin(self.get_filtered_points().index)
found_group = False
count = 0
for x in issel:
if x:
if not found_group:
found_group=True
count =count+1
else:
found_group = False
if count >1:
return False
if count == 1:
return True
def flag(self, qualifier_id):
filtered_points = self.get_filtered_points()
'''
query = "UPDATE DataValues SET QualifierID = %s WHERE ValueID = ?" % (qualifier_id)
#self._cursor.executemany(query, [(str(x[0]),) for x in filtered_points])
self._cursor.executemany(query, [(str(x),) for x in filtered_points["ValueID"].astype(int).tolist()])
'''
self.memDB.updateFlag(filtered_points.index.tolist(), qualifier_id)
def updateValues(self, values):
"""
:param values: pandas Dataframe - must contain a "datavalues" column and a date time as the index
:return:
"""
if values is None:
print("please send in a valid DataFrame object")
return
update_list = [{"value": row["DataValue"], "id": index} for index, row in values.iterrows()]
ids = values.index.tolist()
self.memDB.update(update_list)
self._populate_series()
self.filtered_dataframe = self._series_points_df[self._series_points_df.index.isin(ids)]
###################
# Save/Restore
###################
def restore(self):
self.memDB.rollback()
self._populate_series()
self.reset_filter()
def updateSeries(self, var=None, method=None, qcl=None, is_new_series=False, overwrite = True, append = False):
"""
:param var:
:param method:
:param qcl:
:param is_new_series:
:return:
"""
var_id = var.id if var is not None else None
method_id = method.id if method is not None else None
qcl_id = qcl.id if qcl is not None else None
#self.memDB.changeSeriesIDs(var_id, method_id, qcl_id)
dvs = self.memDB.getDataValuesDF()
if var_id is not None:
dvs["VariableID"] = var_id
if method_id is not None:
dvs["MethodID"] = method_id
if qcl_id is not None:
dvs["QualityControlLevelID"] = qcl_id
#if is new series remove valueids
#if is_new_series:
dvs["ValueID"] = None
'''
for dv in dvs:
dv.id = None
'''
series = self.memDB.series_service.get_series_by_id(self._series_id)
logger.debug("original editing series id: %s" % str(series.id))
if (var or method or qcl ):
tseries = self.memDB.series_service.get_series_by_id_quint(site_id=int(series.site_id),
var_id=var_id if var else int(series.variable_id),
method_id=method_id if method else int(
series.method_id),
source_id=series.source_id,
qcl_id=qcl_id if qcl else int(
series.quality_control_level_id))
if tseries:
logger.debug("Save existing series ID: %s" % str(tseries.id))
series = tseries
else:
print "Series doesn't exist (if you are not, you should be running SaveAs)"
if is_new_series:
series = series_module.copy_series(series)
if var:
series.variable_id = var_id
series.variable_code = var.code
series.variable_name = var.name
series.speciation = var.speciation
series.variable_units_id = var.variable_unit_id
series.variable_units_name = var.variable_unit.name
series.sample_medium = var.sample_medium
series.value_type = var.value_type
series.time_support = var.time_support
series.time_units_id = var.time_unit_id
series.time_units_name = var.time_unit.name
series.data_type = var.data_type
series.general_category = var.general_category
if method:
series.method_id = method_id
series.method_description = method.description
if qcl:
series.quality_control_level_id = qcl_id
series.quality_control_level_code = qcl.code
'''
dvs["LocalDateTime"] = pd.to_datetime(dvs["LocalDateTime"])
dvs["DateTimeUTC"] = pd.to_datetime(dvs["DateTimeUTC"])
'''
form = "%Y-%m-%d %H:%M:%S"
if not append:
series.begin_date_time = datetime.datetime.strptime(str(np.min(dvs["LocalDateTime"])), form)#np.min(dvs["LocalDateTime"])#dvs[c0].local_date_time
series.end_date_time = datetime.datetime.strptime(str(np.max(dvs["LocalDateTime"])), form)#np.max(dvs["LocalDateTime"])#dvs[-1].local_date_time
series.begin_date_time_utc = datetime.datetime.strptime(str(np.min(dvs["DateTimeUTC"])), form) #dvs[0].date_time_utc
series.end_date_time_utc = datetime.datetime.strptime(str(np.max(dvs["DateTimeUTC"])), form) #dvs[-1].date_time_utc
series.value_count = len(dvs)
## Override previous save
if not is_new_series:
# delete old dvs
#pass
self.memDB.series_service.delete_values_by_series(series)
elif append:
#if series end date is after dvs startdate
dbend = series.end_date_time
dfstart = datetime.datetime.strptime(str(np.min(dvs["LocalDateTime"])), form)
overlap = dbend>= dfstart
#leave series start dates to those previously set
series.end_date_time = datetime.datetime.strptime(str(np.max(dvs["LocalDateTime"])), form)
series.end_date_time_utc = datetime.datetime.strptime(str(np.max(dvs["DateTimeUTC"])), form)
#TODO figure out how to calculate the new value count
series.value_count = len(dvs)
if overlap:
if overwrite:
#remove values from the database
self.memDB.series_service.delete_values_by_series(series, startdate=dfstart)
else:
#remove values from df
dvs = dvs[dvs["LocalDateTime"] > dbend]
#logger.debug("series.data_values: %s" % ([x for x in series.data_values]))
dvs.drop('ValueID', axis=1, inplace=True)
return series, dvs
def save(self):
""" Save to an existing catalog
:param var:
:param method:
:param qcl:
:return:
"""
series, dvs = self.updateSeries(is_new_series=False)
if self.memDB.series_service.save_series(series, dvs):
logger.debug("series saved!")
return True
else:
logger.debug("The Save was unsuccessful")
return False
def save_as(self, var=None, method=None, qcl=None):
"""
:param var:
:param method:
:param qcl:
:return:
"""
series, dvs = self.updateSeries(var, method, qcl, is_new_series=True)
if self.memDB.series_service.save_new_series(series, dvs):
logger.debug("series saved!")
return True
else:
logger.debug("The Save As Function was Unsuccessful")
return False
def save_appending(self, var= None, method = None, qcl=None, overwrite=False):
series, dvs = self.updateSeries(var, method, qcl, is_new_series=False, append= True, overwrite=overwrite)
if self.memDB.series_service.save_series(series, dvs):
logger.debug("series saved!")
return True
else:
logger.debug("The Append Existing Function was Unsuccessful")
return False
def save_existing(self, var=None, method=None, qcl=None):
"""
:param var:
:param method:
:param qcl:
:return:
"""
series, dvs = self.updateSeries(var, method, qcl, is_new_series=False)
if self.memDB.series_service.save_series(series, dvs):
logger.debug("series saved!")
return True
else:
logger.debug("The Save As Existing Function was Unsuccessful")
return False
def create_qcl(self, code, definition, explanation):
return self.memDB.series_service.create_qcl(code, definition, explanation)
def create_method(self, description, link):
return self.memDB.series_service.create_method(description, link)
def create_qualifier(self, code, definition):
return self.memDB.series_service.create_qualifier(code, definition)
def create_variable(self, code, name, speciation, variable_unit_id, sample_medium,
value_type, is_regular, time_support, time_unit_id, data_type, general_category, no_data_value):
return self.memDB.series_service.create_variable(code, name, speciation, variable_unit_id, sample_medium,
value_type, is_regular, time_support, time_unit_id, data_type,
general_category, no_data_value)
def reconcile_dates(self, parent_series_id):
# FUTURE FEATURE: pull in new field data from another series and add to this series
# (i.e one series contains new field data of an edited series at a higher qcl)
pass
class TestMemoryDB:
def setup(self):
self.connection_string = "sqlite:///:memory:"
self.series_service = SeriesService(connection_string=self.connection_string, debug=False)
self.session = self.series_service._session_factory.get_session()
engine = self.series_service._session_factory.engine
test_util.build_db(engine)
self.memory_db = MemoryDatabase()
self.memory_db.set_series_service(self.series_service)
self.series = test_util.add_series(self.session)
self.memory_db.initEditValues(self.series.id)
sorted_df = sorted(self.memory_db.df['LocalDateTime'])
self.sdate = sorted_df[0]
def test_get_data_values(self):
dvs = self.memory_db.getDataValuesDF()
assert len(dvs) == 10
def test_build_series(self):
dvs = 100
self.series = test_util.add_series_bulk_data(self.session, dvs_size=dvs)
assert self.series
assert len(self.series.data_values) == dvs
def test_update_points(self):
self.memory_db.update([{"value":15,"id":self.sdate}])
dvs = self.memory_db.getDataValuesDF()
print dvs["DataValue"]
assert dvs["DataValue"][0] == 15
def test_update_value(self):
self.memory_db.updateValue([self.sdate],'+', 5 )
dvs = self.memory_db.getDataValuesDF()
assert dvs["DataValue"][0] == 14
def test_add_points(self):
#with pytest.raises(NotImplementedError):
assert len(self.memory_db.getDataValuesDF().index)==10
point = [('-9999', None, datetime.datetime(2011, 3, 25, 0, 0), '-7', datetime.datetime(2015, 3, 25, 7, 0), None,
None, u'nc', None, None, self.series.site_id, self.series.variable_id, self.series.method_id,
self.series.source_id, self.series.quality_control_level_id)]
self.memory_db.addPoints(point)
dvs = self.memory_db.getDataValuesDF()
assert len(dvs.index) == 11
assert dvs["DataValue"][0] == -9999
def test_update_flag(self):
self.memory_db.updateFlag([self.sdate], '50')
dvs=self.memory_db.getDataValuesDF()
assert dvs["QualifierID"][0] == '50'
def test_delete_points(self):
stlen= len(self.memory_db.df.index)
self.memory_db.delete(self.memory_db.df["LocalDateTime"].tolist()[0:10])
dvs = self.memory_db.getDataValuesDF()
assert len(dvs.index) == stlen-10
class EditService():
# Mutual exclusion: cursor, or connection_string
def __init__(self,
series_id,
connection=None,
connection_string="",
debug=False):
'''
:param series_id:
:param connection: memory database, contains connection to remote database
:param connection_string: connection to remote database
:param debug:
:return:
'''
self._series_id = series_id
self._filter_from_selection = False
self._debug = debug
if connection_string is "" and connection is not None:
self.memDB = connection
#self._series_service = self.memDB.series_service#SeriesService(connection_string, debug)
elif connection_string is not "" and connection is None:
from odmtools.odmdata import MemoryDatabase
self.memDB = MemoryDatabase() #(series_service)
self.memDB.set_series_service(
SeriesService(connection_string, False))
else:
logger.error(
"must send in either a remote db connection string or a memory database object"
)
logger.debug("Initializing Memory Database")
self.memDB.initEditValues(series_id)
logger.debug("Finished Initializing Memory Database")
self._populate_series()
self.reset_filter()
def get_series_service(self):
return self.memDB.series_service
def _populate_series(self):
# [(ID, value, datetime), ...]
#self._cursor.execute("SELECT ValueID, DataValue, LocalDateTime FROM DataValues ORDER BY LocalDateTime")
self._series_points_df = self.memDB.getDataValuesDF()
def _test_filter_previous(self):
'''
if not self._filter_from_selection:
self.reset_filter()
'''
df = None
if not self._filter_from_selection:
df = self._series_points_df
else:
df = self.filtered_dataframe
# Ensure that we're not working with an empty dataframe
if isinstance(df, pd.DataFrame):
if df.empty:
return self._series_points_df
else:
if not df:
return self._series_points_df
return df
def datetime2dataframe(self, datetime_list):
""" Converts datetime_list to a pandas Dataframe
:param datetime_list:
:return Pandas.DataFrame:
"""
result = None
if isinstance(datetime_list, list):
result = pd.DataFrame(datetime_list, columns=["LocalDateTime"])
result.set_index("LocalDateTime", inplace=True)
return result
###################
# Stubs
###################
def selectPointsStub(self):
"""
:param filtered_dataframe:
:return:
"""
## Convert dataframe into list of datetimes
filtered_dataframe = self.get_filtered_points()
if isinstance(filtered_dataframe, pd.DataFrame):
if not filtered_dataframe.empty:
datetime_list = filtered_dataframe.index.to_pydatetime()
return datetime_list.tolist()
return []
###################
# Filters
###################
# operator is a character, either '<' or '>'
def filter_value(self, value, ops):
df = self._test_filter_previous()
if ops == '>':
self.filtered_dataframe = df[df['DataValue'] > value]
if ops == '<':
self.filtered_dataframe = df[df['DataValue'] < value]
def filter_date(self, before, after):
df = self._test_filter_previous()
if before and after:
self.filtered_dataframe = df[(df.index < before)
& (df.index > after)]
# Data Gaps
def data_gaps(self, value, time_period):
df = self._test_filter_previous()
time_units = {
'second': 's',
'minute': 'm',
'hour': 'h',
'day': 'D',
'week': 'W',
'month': 'M',
'year': 'Y'
}
# make a copy of the dataframe in order to modify it to be in the form we need to determine data gaps
copy_df = df
copy_df['datetime'] = df.index
copy_df['dateprev'] = copy_df['datetime'].shift()
# ensure that 'value' is an integer
if not isinstance(value, int):
value = int(value)
# create a bool column indicating which rows meet condition
filtered_results = copy_df['datetime'].diff() >= np.timedelta64(
value, time_units[time_period])
# filter on rows that passed previous condition
copy_df = copy_df[filtered_results]
# merge values and remove duplicates. this hack allows for both values to be marked when selecting data gaps
newdf = pd.concat([copy_df['datetime'], copy_df['dateprev']],
join='inner')
self.filtered_dataframe = df[df.index.isin(
newdf.drop_duplicates().dropna())]
# clean up
del copy_df
del filtered_results
del newdf
def change_value_threshold(self, value, operator):
df = self._test_filter_previous()
# make a copy of the dataframe in order to modify it to be in the form we need to determine data gaps
copy_df = df
copy_df['values'] = df['DataValue']
copy_df['diff'] = copy_df['values'].shift()
copy_df["diff_date"] = copy_df['LocalDateTime'].shift()
copy_df['change_threshold'] = abs(df['values'] - df['diff'])
if not isinstance(value, float):
logger.error("Need to have a float")
return
copy_df['threshold'] = value
if operator == ">":
copy_df['matches'] = df['change_threshold'] >= copy_df['threshold']
if operator == "<":
copy_df['matches'] = df['change_threshold'] <= copy_df['threshold']
filtered_df = copy_df[copy_df['matches']]
tmplist = filtered_df['diff_date'].tolist() + filtered_df.index.tolist(
)
del copy_df
self.filtered_dataframe = df[df.index.isin(tmplist)]
def select_points_tf(self, tf_list):
self._filter_list = tf_list
#def select_points(self, id_list=[], datetime_list=[]):
def select_points(self, id_list=[], dataframe=[]):
#self.reset_filter()
# This should be either one or the other. If it's both, id is used first.
# If neither are set this function does nothing.
if len(id_list) > 0:
for i in range(len(self._series_points)):
if self._series_points[i][0] in id_list:
self._filter_list[i] = True
if isinstance(dataframe, pd.DataFrame):
result = dataframe.index.astype(datetime.datetime)
self.filtered_dataframe = self._series_points_df[
self._series_points_df.index.isin(dataframe.index)]
def reset_filter(self):
self.filtered_dataframe = None
def filter_from_previous(self, value):
self._filter_from_selection = value
def get_toggle(self):
return self._filter_from_selection
###################
# Gets
###################
def get_series(self):
return self.memDB.series_service.get_series_by_id(self._series_id)
def get_series_points(self):
# all point in the series
return self._series_points
def get_series_points_df(self):
"""
:return Pandas DataFrame:
"""
return self._series_points_df
def get_filtered_points(self):
"""
:return Pandas DataFrame:
"""
if isinstance(self.filtered_dataframe, pd.DataFrame):
if self.filtered_dataframe.empty:
return None
else:
if not self.filtered_dataframe:
return None
if len(self.filtered_dataframe) > 0:
return self.filtered_dataframe
return None
def get_filtered_dates(self):
return self.filtered_dataframe
def get_filter_list(self):
# true or false list the length of the entire series. true indicate the point is selected
return self._filter_list
def get_qcl(self, qcl_id):
return self.memDB.series_service.get_qcl_by_id(qcl_id)
def get_method(self, method_id):
return self.memDB.series_service.get_method_by_id(method_id)
def get_variable(self, variable_id):
logger.debug(variable_id)
return self.memDB.series_service.get_variable_by_id(variable_id)
#################
# Edits
#################
def change_value(self, value, operator):
filtered_points = self.get_filtered_points()
ids = filtered_points.index.tolist()
self.memDB.updateValue(ids, operator, float(value))
self._populate_series()
## update filtered_dataframe
self.filtered_dataframe = self._series_points_df[
self._series_points_df.index.isin(ids)]
def add_points(self, points):
# todo: add the ability to send in multiple datetimes to a single 'point'
self.memDB.addPoints(points)
self._populate_series()
self.reset_filter()
def delete_points(self):
filtered_points = self.get_filtered_points()
if not filtered_points.empty:
values = filtered_points.index.tolist()
self.memDB.delete(values)
self._populate_series()
self.filtered_dataframe = None
def interpolate(self):
'''
In [75]: ser = Series(np.sort(np.random.uniform(size=100)))
# interpolate at new_index
In [76]: new_index = ser.index | Index([49.25, 49.5, 49.75, 50.25, 50.5, 50.75])
In [77]: interp_s = ser.reindex(new_index).interpolate(method='pchip')
'''
tmp_filter_list = self.get_filtered_points()
df = self._series_points_df
issel = df.index.isin(tmp_filter_list.index)
mdf = df["DataValue"].mask(issel)
mdf.interpolate(method="time", inplace=True)
tmp_filter_list["DataValue"] = mdf[issel]
ids = tmp_filter_list.index.tolist()
#update_list = [(row["DataValue"], row["ValueID"]) for index, row in tmp_filter_list.iterrows()]
update_list = [{
"value": row["DataValue"],
"id": index
} for index, row in tmp_filter_list.iterrows()]
self.memDB.update(update_list)
self._populate_series()
self.filtered_dataframe = self._series_points_df[
self._series_points_df.index.isin(ids)]
def drift_correction(self, gap_width):
if self.isOneGroup():
tmp_filter_list = self.get_filtered_points()
startdate = tmp_filter_list.index[0]
x_l = (tmp_filter_list.index[-1] - startdate).total_seconds()
# y_n = y_0 + G(x_i / x_l)
f = lambda row: row["DataValue"] + (gap_width * (
(row.name - startdate).total_seconds() / x_l))
tmp_filter_list["DataValue"] = tmp_filter_list.apply(f, axis=1)
update_list = [{
"value": row["DataValue"],
"id": index
} for index, row in tmp_filter_list.iterrows()]
ids = tmp_filter_list.index.tolist()
self.memDB.update(update_list)
self._populate_series()
self.filtered_dataframe = self._series_points_df[
self._series_points_df.index.isin(ids)]
return True
return False
def isOneGroup(self):
issel = self._series_points_df.index.isin(
self.get_filtered_points().index)
found_group = False
count = 0
for x in issel:
if x:
if not found_group:
found_group = True
count = count + 1
else:
found_group = False
if count > 1:
return False
if count == 1:
return True
def flag(self, qualifier_id):
filtered_points = self.get_filtered_points()
'''
query = "UPDATE DataValues SET QualifierID = %s WHERE ValueID = ?" % (qualifier_id)
#self._cursor.executemany(query, [(str(x[0]),) for x in filtered_points])
self._cursor.executemany(query, [(str(x),) for x in filtered_points["ValueID"].astype(int).tolist()])
'''
self.memDB.updateFlag(filtered_points.index.tolist(), qualifier_id)
###################
# Save/Restore
###################
def restore(self):
self.memDB.rollback()
self._populate_series()
self.reset_filter()
def updateSeries(self,
var=None,
method=None,
qcl=None,
is_new_series=False):
"""
:param var:
:param method:
:param qcl:
:param is_new_series:
:return:
"""
var_id = var.id if var is not None else None
method_id = method.id if method is not None else None
qcl_id = qcl.id if qcl is not None else None
#self.memDB.changeSeriesIDs(var_id, method_id, qcl_id)
dvs = self.memDB.getDataValuesDF()
if var_id is not None:
dvs["VariableID"] = var_id
if method_id is not None:
dvs["MethodID"] = method_id
if qcl_id is not None:
dvs["QualityControlLevelID"] = qcl_id
#if is new series remove valueids
#if is_new_series:
dvs["ValueID"] = None
'''
for dv in dvs:
dv.id = None
'''
series = self.memDB.series_service.get_series_by_id(self._series_id)
logger.debug("original editing series id: %s" % str(series.id))
if (var or method or qcl):
tseries = self.memDB.series_service.get_series_by_id_quint(
site_id=int(series.site_id),
var_id=var_id if var else int(series.variable_id),
method_id=method_id if method else int(series.method_id),
source_id=series.source_id,
qcl_id=qcl_id if qcl else int(series.quality_control_level_id))
if tseries:
logger.debug("Save existing series ID: %s" % str(series.id))
series = tseries
else:
print "Series doesn't exist (if you are not, you should be running SaveAs)"
if is_new_series:
series = series_module.copy_series(series)
if var:
series.variable_id = var_id
series.variable_code = var.code
series.variable_name = var.name
series.speciation = var.speciation
series.variable_units_id = var.variable_unit_id
series.variable_units_name = var.variable_unit.name
series.sample_medium = var.sample_medium
series.value_type = var.value_type
series.time_support = var.time_support
series.time_units_id = var.time_unit_id
series.time_units_name = var.time_unit.name
series.data_type = var.data_type
series.general_category = var.general_category
if method:
series.method_id = method_id
series.method_description = method.description
if qcl:
series.quality_control_level_id = qcl_id
series.quality_control_level_code = qcl.code
'''
dvs["LocalDateTime"] = pd.to_datetime(dvs["LocalDateTime"])
dvs["DateTimeUTC"] = pd.to_datetime(dvs["DateTimeUTC"])
'''
form = "%Y-%m-%d %H:%M:%S"
series.begin_date_time = datetime.datetime.strptime(
str(np.min(dvs["LocalDateTime"])),
form) #np.min(dvs["LocalDateTime"])#dvs[0].local_date_time
series.end_date_time = datetime.datetime.strptime(
str(np.max(dvs["LocalDateTime"])),
form) #np.max(dvs["LocalDateTime"])#dvs[-1].local_date_time
series.begin_date_time_utc = datetime.datetime.strptime(
str(np.min(dvs["DateTimeUTC"])), form) #dvs[0].date_time_utc
series.end_date_time_utc = datetime.datetime.strptime(
str(np.max(dvs["DateTimeUTC"])), form) #dvs[-1].date_time_utc
series.value_count = len(dvs)
## Override previous save
if not is_new_series:
# delete old dvs
#pass
self.memDB.series_service.delete_values_by_series(series)
#logger.debug("series.data_values: %s" % ([x for x in series.data_values]))
dvs.drop('ValueID', axis=1, inplace=True)
return series, dvs
def save(self):
""" Save to an existing catalog
:param var:
:param method:
:param qcl:
:return:
"""
series, dvs = self.updateSeries(is_new_series=False)
if self.memDB.series_service.save_series(series, dvs):
logger.debug("series saved!")
return True
else:
logger.debug("The Save was unsuccessful")
return False
def save_as(self, var=None, method=None, qcl=None):
"""
:param var:
:param method:
:param qcl:
:return:
"""
series, dvs = self.updateSeries(var, method, qcl, is_new_series=True)
if self.memDB.series_service.save_new_series(series, dvs):
logger.debug("series saved!")
return True
else:
logger.debug("The Save As Function was Unsuccessful")
return False
def save_existing(self, var=None, method=None, qcl=None):
"""
:param var:
:param method:
:param qcl:
:return:
"""
series, dvs = self.updateSeries(var, method, qcl, is_new_series=False)
if self.memDB.series_service.save_series(series, dvs):
logger.debug("series saved!")
return True
else:
logger.debug("The Save As Existing Function was Unsuccessful")
return False
def create_qcl(self, code, definition, explanation):
return self.memDB.series_service.create_qcl(code, definition,
explanation)
def create_method(self, description, link):
return self.memDB.series_service.create_method(description, link)
def create_qualifier(self, code, definition):
return self.memDB.series_service.create_qualifier(code, definition)
def create_variable(self, code, name, speciation, variable_unit_id,
sample_medium, value_type, is_regular, time_support,
time_unit_id, data_type, general_category,
no_data_value):
return self.memDB.series_service.create_variable(
code, name, speciation, variable_unit_id, sample_medium,
value_type, is_regular, time_support, time_unit_id, data_type,
general_category, no_data_value)
def reconcile_dates(self, parent_series_id):
# FUTURE FEATURE: pull in new field data from another series and add to this series
# (i.e one series contains new field data of an edited series at a higher qcl)
pass
class TestMemoryDB:
def setup(self):
self.connection_string = "sqlite:///:memory:"
self.series_service = SeriesService(
connection_string=self.connection_string, debug=False)
self.session = self.series_service._session_factory.get_session()
engine = self.series_service._session_factory.engine
test_util.build_db(engine)
self.memory_db = MemoryDatabase()
self.memory_db.set_series_service(self.series_service)
self.series = test_util.add_series(self.session)
self.memory_db.initEditValues(self.series.id)
sorted_df = sorted(self.memory_db.df['LocalDateTime'])
self.sdate = sorted_df[0]
def test_get_data_values(self):
dvs = self.memory_db.getDataValuesDF()
assert len(dvs) == 10
def test_build_series(self):
dvs = 100
self.series = test_util.add_series_bulk_data(self.session,
dvs_size=dvs)
assert self.series
assert len(self.series.data_values) == dvs
def test_update_points(self):
self.memory_db.update([{"value": 15, "id": self.sdate}])
dvs = self.memory_db.getDataValuesDF()
print dvs["DataValue"]
assert dvs["DataValue"][0] == 15
def test_update_value(self):
self.memory_db.updateValue([self.sdate], '+', 5)
dvs = self.memory_db.getDataValuesDF()
assert dvs["DataValue"][0] == 14
def test_add_points(self):
#with pytest.raises(NotImplementedError):
assert len(self.memory_db.getDataValuesDF().index) == 10
point = [('-9999', None, datetime.datetime(2011, 3, 25, 0, 0), '-7',
datetime.datetime(2015, 3, 25, 7, 0), None, None, u'nc',
None, None, self.series.site_id, self.series.variable_id,
self.series.method_id, self.series.source_id,
self.series.quality_control_level_id)]
self.memory_db.addPoints(point)
dvs = self.memory_db.getDataValuesDF()
assert len(dvs.index) == 11
assert dvs["DataValue"][0] == -9999
def test_update_flag(self):
self.memory_db.updateFlag([self.sdate], '50')
dvs = self.memory_db.getDataValuesDF()
assert dvs["QualifierID"][0] == '50'
def test_delete_points(self):
stlen = len(self.memory_db.df.index)
self.memory_db.delete(
self.memory_db.df["LocalDateTime"].tolist()[0:10])
dvs = self.memory_db.getDataValuesDF()
assert len(dvs.index) == stlen - 10
class TestMemoryDB:
def setup(self):
self.connection_string = "sqlite:///:memory:"
self.series_service = SeriesService(connection_string=self.connection_string, debug=False)
self.session = self.series_service._session_factory.get_session()
engine = self.series_service._session_factory.engine
test_util.build_db(engine)
self.memory_db = MemoryDatabase()
self.memory_db.set_series_service(self.series_service)
self.series = test_util.add_series(self.session)
self.memory_db.initEditValues(self.series.id)
def test_get_data_values(self):
dvs = self.memory_db.getDataValuesDF()
assert len(dvs) == 10
def test_update_points(self):
self.memory_db.update([{"value": 15, "id": 1}])
dvs = self.memory_db.getDataValuesDF()
print dvs["DataValue"]
assert dvs["DataValue"][1 - 1] == 9
def test_update_value(self):
self.memory_db.updateValue([1], "+", 5)
dvs = self.memory_db.getDataValuesDF()
assert dvs["DataValue"][1 - 1] == 9
def test_add_points(self):
# with pytest.raises(NotImplementedError):
point = [
(
"-9999",
None,
datetime.datetime(2011, 3, 25, 0, 0),
"-7",
datetime.datetime(2015, 3, 25, 7, 0),
None,
None,
u"nc",
None,
None,
self.series.site_id,
self.series.variable_id,
self.series.method_id,
self.series.source_id,
self.series.quality_control_level_id,
)
]
self.memory_db.addPoints(point)
dvs = self.memory_db.getDataValuesDF()
assert len(dvs) == 11
assert dvs["DataValue"][-1] == -9999
def test_update_flag(self):
self.memory_db.updateFlag([5], "50")
dvs = self.memory_db.getDataValuesDF()
assert dvs["QualifierID"][5 - 1] == "50"
def test_delete_points(self):
stlen = len(self.memory_db.getDataValuesDF())
self.memory_db.delete([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
dvs = self.memory_db.getDataValuesDF()
assert len(dvs) == stlen - 10
