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Commit ce909f1b authored by matthmey's avatar matthmey
Browse files

fixed configuration with forward()

parent 8b642f83
......@@ -3,4 +3,3 @@ from __future__ import absolute_import
from . import data
from . import global_config
from .convenience import *
......@@ -190,15 +190,13 @@ def configuration(delayed, request, keys=None, default_merge=None):
# print(f"configuring {k}",requests[k])
# set configuration for this node k
# If we create a delayed object from a class, `self` will be dsk[k][1]
print(dsk[k])
print(type(dsk[k][1]))
argument_is_node = None
if isinstance(dsk[k],tuple):
# check the first two arguments # TODO: possibly change this to only the first argument
for ain in range(2):
if hasattr(dsk[k][ain], '__self__'):
if isinstance(dsk[k], tuple):
# check the first argument
# # TODO: make tests for all use cases and then remove for-loop
for ain in range(1):
if hasattr(dsk[k][ain], "__self__"):
if isinstance(dsk[k][ain].__self__, Node):
argument_is_node = ain
# Check if we get a node of type Node class
......@@ -226,27 +224,24 @@ def configuration(delayed, request, keys=None, default_merge=None):
else:
new_request = requests[k]
if (
if (new_request[0] is not None and
"requires_request" in new_request[0]
and new_request[0]["requires_request"] == True
):
del new_request[0]["requires_request"]
# TODO: check if we need a deepcopy here!
input_requests[k] = copy.deepcopy(
new_request[0]
)
input_requests[k] = copy.deepcopy(new_request[0])
# update dependencies
current_deps = get_dependencies(dsk, k, as_list=True)
for i, d in enumerate(current_deps):
if d in requests:
requests[d] += new_request
remove[d] = remove[d] and (not new_request[0])
remove[d] = remove[d] and (new_request[0] is None)
else:
requests[d] = new_request
remove[d] = not new_request[
0
] # if we received an empty dictionary flag deps for removal
# if we received None
remove[d] = new_request[0] is None
# only configure each node once in a round!
if d not in new_work and d not in work: # TODO: verify this
......@@ -261,17 +256,20 @@ def configuration(delayed, request, keys=None, default_merge=None):
# After we have aquired all requests we can input the required_requests as a input node to the requiring node
# we assume that the last argument is the request
for k in input_requests:
if isinstance(out[k][-1],dict):
out[k][-1].update(input_requests[k])
# Here we assume that we always receive the same tuple of (bound method, data, request)
# If the interface changes this will break #TODO: check for all cases
if isinstance(out[k][2], dict):
out[k][2].update(input_requests[k])
else:
# replace the last entry
out[k] = out[k][:-1] + (input_requests[k],)
out[k] = out[k][:2] + (input_requests[k],)
# convert to delayed object
from dask.delayed import Delayed
in_keys = list(flatten(keys))
# print(in_keys)
if len(in_keys) > 1:
collection = [Delayed(key=key, dsk=out) for key in in_keys]
else:
......@@ -282,7 +280,6 @@ def configuration(delayed, request, keys=None, default_merge=None):
return collection
def optimize_freeze(dsk, keys, request_key="request"):
""" Return new dask with tasks removed which are unnecessary because a later stage
reads from cache
......
......@@ -8,6 +8,7 @@ import datetime as dt
from .management import DataSource
from ..core import configuration
class DataCollector(DataSource):
def __init__(self, data_paths=[], granularities=[]):
"""Add and choose data path according to its granularity.
......@@ -25,30 +26,33 @@ class DataCollector(DataSource):
self.data_paths = data_paths
self.granularities = granularities
if(len(self.data_paths) != len(self.granularities)):
raise ValueError("Each granularity is supposed to have its corresponding data manager")
if len(self.data_paths) != len(self.granularities):
raise ValueError(
"Each granularity is supposed to have its corresponding data manager"
)
if len(self.granularities) > 1 and not self.is_sorted(self.granularities):
raise ValueError('Granularities should be sorted')
raise ValueError("Granularities should be sorted")
def forward(self, data=None, request=None):
if(len(self.data_paths) != len(self.granularities)):
raise ValueError("Each granularity is supposed to have its corresponding data manager")
if len(self.data_paths) != len(self.granularities):
raise ValueError(
"Each granularity is supposed to have its corresponding data manager"
)
if len(self.granularities) > 1 and not self.is_sorted(self.granularities):
raise ValueError('Granularities should be sorted')
raise ValueError("Granularities should be sorted")
# TODO: change to generic indices or slices
granularity = request['end_time'] - request['start_time']
granularity = request["end_time"] - request["start_time"]
data_path = None
for i in range(len(self.granularities)):
print(i,granularity,'<',self.granularities[i],self.data_paths[i])
print(i, granularity, "<", self.granularities[i], self.data_paths[i])
if granularity < self.granularities[i]:
data_path = self.data_paths[i]
break
if data_path is None:
raise AttributeError('No data manager can be used for this timeframe')
raise AttributeError("No data manager can be used for this timeframe")
return data_path
......
......@@ -27,12 +27,15 @@ import datetime as dt
from pathlib import Path
def forward(x, data=None, request=None):
print("inforward", x, data, request)
class DataSource(StuettNode):
def __init__(self, **kwargs):
super().__init__(kwargs=kwargs)
def __call__(self, data=None, request=None, delayed=False):
print(data,request)
if data is not None:
if request is None:
request = data
......@@ -48,19 +51,23 @@ class DataSource(StuettNode):
config.update(request)
# TODO: change when rewriting for general indices
if 'start_time' in config and config['start_time'] is not None:
config['start_time'] = pd.to_datetime(config['start_time'], utc=True).tz_localize(
if "start_time" in config and config["start_time"] is not None:
config["start_time"] = pd.to_datetime(
config["start_time"], utc=True
).tz_localize(
None
) # TODO: change when xarray #3291 is fixed
if 'end_time' in config and config['end_time'] is not None:
config['end_time'] = pd.to_datetime(config['end_time'], utc=True).tz_localize(
if "end_time" in config and config["end_time"] is not None:
config["end_time"] = pd.to_datetime(
config["end_time"], utc=True
).tz_localize(
None
) # TODO: change when xarray #3291 is fixed
if delayed:
return dask.delayed(self.forward)(None,config)
return dask.delayed(self.forward)(None, config)
else:
return self.forward(None,config)
return self.forward(None, config)
def configure(self, requests=None):
""" Default configure for DataSource nodes
......@@ -72,22 +79,38 @@ class DataSource(StuettNode):
Returns:
dict -- Original request or merged requests
"""
requests = super().configure(requests)
requests = super().configure(requests) # merging request here
requests["requires_request"] = True
return requests
class GSNDataSource(DataSource):
def __init__(
self, deployment=None, vsensor=None, position=None, start_time=None, end_time=None, **kwargs
self,
deployment=None,
vsensor=None,
position=None,
start_time=None,
end_time=None,
**kwargs,
):
super().__init__(deployment=deployment, position=position, vsensor=vsensor, start_time=start_time, end_time=end_time, kwargs=kwargs)
super().__init__(
deployment=deployment,
position=position,
vsensor=vsensor,
start_time=start_time,
end_time=end_time,
kwargs=kwargs,
)
def forward(self, data=None, request=None):
#### 1 - DEFINE VSENSOR-DEPENDENT COLUMNS ####
colnames = pd.read_csv(
Path(get_setting("metadata_directory")).joinpath("vsensor_metadata/{:s}_{:s}.csv".format(
request["deployment"], request["vsensor"])
Path(get_setting("metadata_directory")).joinpath(
"vsensor_metadata/{:s}_{:s}.csv".format(
request["deployment"], request["vsensor"]
)
),
skiprows=0,
)
......@@ -131,8 +154,10 @@ class GSNDataSource(DataSource):
"&c_max[1]={:02d}"
).format(
virtual_sensor,
pd.to_datetime(request['start_time'],utc=True).strftime("%d/%m/%Y+%H:%M:%S"),
pd.to_datetime(request['end_time'],utc=True).strftime("%d/%m/%Y+%H:%M:%S"),
pd.to_datetime(request["start_time"], utc=True).strftime(
"%d/%m/%Y+%H:%M:%S"
),
pd.to_datetime(request["end_time"], utc=True).strftime("%d/%m/%Y+%H:%M:%S"),
virtual_sensor,
int(request["position"]) - 1,
request["position"],
......@@ -158,13 +183,12 @@ class GSNDataSource(DataSource):
url, skiprows=2
) # skip header lines (first 2) for import: skiprows=2
df = pd.DataFrame(columns=columns_new)
df.time = pd.to_datetime(d.generation_time,utc=True)
df.time = pd.to_datetime(d.generation_time, utc=True)
# if depo in ['mh25', 'mh27old', 'mh27new', 'mh30', 'jj22', 'jj25', 'mh-nodehealth']:
# d = d.convert_objects(convert_numeric=True) # TODO: rewrite to remove warning
for k in list(df):
df[k]=pd.to_numeric(df[k], errors='ignore')
df[k] = pd.to_numeric(df[k], errors="ignore")
# df = pd.DataFrame(columns=columns_new)
# df.time = timestamp2datetime(d['generation_time']/1000)
......
......@@ -14,43 +14,41 @@ def test_collector():
node = stuett.data.CsvSource(filename)
minmax_rate2 = stuett.data.MinMaxDownsampling(rate=2, dim="time")
print('creating delayed node')
print("creating delayed node")
x = node(delayed=True)
print('downsampled delayed node')
downsampled = minmax_rate2(x,delayed=True)
print("downsampled delayed node")
downsampled = minmax_rate2(x, delayed=True)
print('DataCollector node')
data_paths = [x,downsampled]
granularities = [stuett.to_timedelta(180,'s'), stuett.to_timedelta(2,'d')]
print("DataCollector node")
data_paths = [x, downsampled]
granularities = [stuett.to_timedelta(180, "s"), stuett.to_timedelta(2, "d")]
collector_node = stuett.data.DataCollector(data_paths, granularities)
print('Instatiating DataCollector node')
request = {'start_time':'2017-08-01', 'end_time':'2017-08-02'}
print("Instatiating DataCollector node")
request = {"start_time": "2017-08-01", "end_time": "2017-08-02"}
path = collector_node(request=request)
# print(type(path))
print('Configuration node')
print("Configuration node")
import dask
dsk, dsk_keys = dask.base._extract_graph_and_keys([path])
dsk, dsk_keys = dask.base._extract_graph_and_keys([path])
path = stuett.core.configuration(path,request)
path = stuett.core.configuration(path, request)
dsk, dsk_keys = dask.base._extract_graph_and_keys([path])
print(dsk)
print(type(path))
print('executing delayed node')
print("executing delayed node")
print(path.compute())
# request = {'start_time':'2017-08-01 10:01:00', 'end_time':'2017-08-01 10:02:00'}
# path = collector_node(request=request)
# path = stuett.core.configuration(path,request)
# print(path.compute())
test_collector()
......@@ -15,6 +15,7 @@ class MyNode(stuett.core.StuettNode):
super().__init__()
def forward(self, data=None, request=None):
print(data, request)
return data + 4
def configure(self, requests=None):
......@@ -24,16 +25,16 @@ class MyNode(stuett.core.StuettNode):
return requests
# class MyMerge(stuett.core.StuettNode):
# def forward(self, x, y):
# return x + y
class MyMerge(stuett.core.StuettNode):
def forward(self, data, request):
return data[0] + data[1]
class MySource(stuett.data.DataSource):
def __init__(self,start_time=None):
def __init__(self, start_time=None):
super().__init__(start_time=start_time)
def forward(self, request=None):
def forward(self, data=None, request=None):
return request["start_time"]
......@@ -41,18 +42,40 @@ def test_configuration():
node = MyNode()
# create a stuett graph
x = node({"start_time": 0, "end_time": -1})
x = bypass(x)
x = node(x)
x_in = node(data=5, delayed=True) # data input
x = bypass(x_in)
x = node(x, delayed=True)
print(x.compute())
# x.visualize()
import dask
dsk, dsk_keys = dask.base._extract_graph_and_keys([x])
print(dict(dsk))
# create a configuration file
config = {}
# configure the graph
x_configured = stuett.core.configuration(x, config)
x_configured = stuett.core.configuration(
x, config
) # BUG: somehow config cuts the graph off
import dask
dsk, dsk_keys = dask.base._extract_graph_and_keys([x_configured])
print(dsk)
x = x_configured.compute()
print(x)
# TODO: finalize test
test_configuration()
def test_datasource():
source = MySource()
node = MyNode()
......@@ -60,51 +83,84 @@ def test_datasource():
# create a stuett graph
x = source(delayed=True)
x = bypass(x)
x = node(x,delayed=True)
x = node(x, delayed=True)
# create a configuration file
config = {"start_time": 0, "end_time": 1}
# configure the graph
configured = stuett.core.configuration(x, config)
x_configured = configured.compute(
scheduler="single-threaded", rerun_exceptions_locally=True
)
assert x_configured == 5
test_datasource()
def test_merging():
source = MySource()
node = MyNode()
merge = MyMerge()
# create a stuett graph
import dask
x = source(delayed=True)
x = bypass(x)
x = node(x, delayed=True)
x_b = node(x, delayed=True)
x = merge([x_b, x],delayed=True)
# create a configuration file
config = {"start_time": 0, "end_time": 1}
# configure the graph
configured = stuett.core.configuration(x, config)
import dask
dsk, dsk_keys = dask.base._extract_graph_and_keys([configured])
x_configured = configured.compute()
print(dsk)
x_configured = configured.compute(scheduler='single-threaded',rerun_exceptions_locally=True)
assert x_configured == 14
assert x_configured == 5
# TODO: Test default_merge
test_datasource()
# TODO:
try:
'''
This still fails. Configuration cannot handle "apply" nodes in the dask graph.
The problem arises if we have a branch that needs to merge request and the
apply node is the one which receives the two requests. Then it requires a
default merge handler, which is not supplied (and does not need to) because the
underlying function in this case supplies the merger.
'''
x = source(delayed=True)(dask_key_name="source")
x = bypass(x)(dask_key_name="bypass")
x = node(x, delayed=True)(dask_key_name="node")
x_b = node(x, delayed=True)(dask_key_name="branch") # branch
x = merge([x_b, x],delayed=True)(dask_key_name="merge")
# def test_merging():
# source = MySource()
# node = MyNode()
# merge = MyMerge()
# create a configuration file
config = {"start_time": 0, "end_time": 1}
# # create a stuett graph
# import dask
# x = source(dask_key_name="source")
# x = bypass(x, dask_key_name="bypass")
# x = node(x, dask_key_name="node")
# x_b = node(x, dask_key_name="branch") # branch
# x = merge(x_b, x, dask_key_name="merge")
import dask
# # create a configuration file
# config = {"start_time": 0, "end_time": 1}
dsk, dsk_keys = dask.base._extract_graph_and_keys([x])
# # configure the graph
# configured = stuett.core.configuration(x, config)
print(dict(dsk))
# x_configured = configured.compute()
# configure the graph
configured = stuett.core.configuration(x, config)
# assert x_configured == 14
x_configured = configured.compute()
# # TODO: Test default_merge
assert x_configured == 14
except Exception as e:
print(e)
pass
# # TODO:
test_merging()
\ No newline at end of file
......@@ -46,14 +46,17 @@ class TestSeismicSource(object):
# TODO: make test to compare start_times
@pytest.mark.slow
def test_gsn():
# test_data = pd.read_csv(test_data_dir + 'matterhorn_27_temperature_rock.csv',index_col='time')
gsn_node = stuett.data.GSNDataSource(deployment="matterhorn", position=30, vsensor="temperature_rock")
x = gsn_node({"start_time":"2017-07-01","end_time":"2017-07-02"})
gsn_node = stuett.data.GSNDataSource(
deployment="matterhorn", position=30, vsensor="temperature_rock"
)
x = gsn_node({"start_time": "2017-07-01", "end_time": "2017-07-02"})
assert x.sum() == 1600959.34
#TODO: proper testing
# TODO: proper testing
# test_gsn()
......
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