From f94ffa73ce14ca949d029d1fe8105d8887441b42 Mon Sep 17 00:00:00 2001
From: Zhichao Zhang <zhichao.zhang@stud.tu-darmstadt.de>
Date: Mon, 5 Sep 2022 21:07:02 +0200
Subject: [PATCH] move keyvalue class into archive
---
{pykkn => .archive}/dataset_keyvalue.py | 96 ++++++++++++++-----------
1 file changed, 55 insertions(+), 41 deletions(-)
rename {pykkn => .archive}/dataset_keyvalue.py (75%)
diff --git a/pykkn/dataset_keyvalue.py b/.archive/dataset_keyvalue.py
similarity index 75%
rename from pykkn/dataset_keyvalue.py
rename to .archive/dataset_keyvalue.py
index 138191a..c5f3b6b 100644
--- a/pykkn/dataset_keyvalue.py
+++ b/.archive/dataset_keyvalue.py
@@ -1,17 +1,17 @@
import numpy as np
-
-from dataset import Dataset
-from instrument import Instrument
-from model import Model
-from parameter import Parameter
-from pipeline import Pipeline
-from run import Run
-from storage import Storage
+from pykkn.dataset import Dataset
+from pykkn.instrument import Instrument
+from pykkn.model import Model
+from pykkn.parameter import Parameter
+from pykkn.pipeline import Pipeline
+from pykkn.run import Run
+from pykkn.storage import Storage
class Dataset_KeyValue(Storage):
- """Dataset_KeyValue class is used as a converter between a dictionary formated in an HDF5 storable way to a hdf file
+ """Dataset_KeyValue class is used as a converter between a
+ dictionary formated in an HDF5 storable way to a HDF file
Parameters
@@ -58,46 +58,48 @@ class Dataset_KeyValue(Storage):
Parameter:
1. see if dictname = parameter;
- 2. if last group = parameter, go into dict and create parameter for each (e. g.: gain, offset )
+ 2. if last group = parameter, go into dict and create parameter
+ for each (e. g.: gain, offset )
3. Go into the parameters and add the attributes
Data is similar to parameter, just that we add data instead
- XXXXXXXXXX data kann also have attributes ----> How would attributes look in a JSON-> Dict?
+ XXXXXXXXXX data kann also have attributes ---->
+ How would attributes look in a JSON-> Dict?
_Group : str
- parameter to be used by the recursive function; describes the last "wrapper class" (pipeline,instruments,model)
+ parameter to be used by the recursive function; describes
+ the last "wrapper class" (pipeline,instruments,model)
_last_group : str
parameter to be used by the recursive function
Dict : list, tuple, dict
nested key value pairs -->
- Dicti[key]: whole dictionary is called by the name Dicti, to get a single value Dicti[key] is called
+ Dicti[key]: whole dictionary is called by the name Dicti,
+ to get a single value Dicti[key] is called
Dict structure => Dicti = {key : value, .. ,}
"""
- # (self, Dict, _last_group = None, _key = None, _nested_group):: Key is the key as string/object
+ # (self, Dict, _last_group = None, _key = None, _nested_group)::
+ # Key is the key as string/object
for key in Dict:
"""key : value
key = our key as a string
Dict[key] = value of key
"""
- #### run
-
if (
isinstance(Dict[key], (list, tuple, dict))
- and _last_group == None
- and _key == None
+ and _last_group is None
+ and _key is None
): # first dict name is the name of the run (e.g. run_01)
key = Run(key)
key.add([self.nested_dict(Dict[key], "run_start")])
key.store()
- #### param
# TODO
if (
isinstance(Dict[key], (list, tuple, dict))
@@ -117,7 +119,6 @@ class Dataset_KeyValue(Storage):
elif _last_group == "parameters": # add parameter attributes
_key.attrs[key] = Dict[key] # gain.attrs["value"] = 10 ..
- #### dataset
# TODO
if (
isinstance(Dict[key], (list, tuple, dict))
@@ -127,16 +128,19 @@ class Dataset_KeyValue(Storage):
return self.nested_dict(Dict[key], "data")
elif (
- isinstance(Dict[key], (list, tuple, dict)) and _last_group == "data"
+ isinstance(Dict[key], (list, tuple, dict))
+ and _last_group == "data"
): # create data class
key = Dataset(key) # 1000 = dataset("1000")
self.nested_dict(Dict, "data", _key=key)
self.nested_dict(Dict[key], _last_group, key)
- # key.data = self.nested_dict(Dict[key], _last_group, key) --- and return Dict[key]
+ # key.data = self.nested_dict(Dict[key], _last_group, key)
+ # --- and return Dict[key]
return key
elif (
- not isinstance(Dict[key], (list, tuple, dict)) and _last_group == "data"
+ not isinstance(Dict[key], (list, tuple, dict))
+ and _last_group == "data"
): # add the meta data
_key.attrs[key] = Dict[key]
# TODO
@@ -145,9 +149,8 @@ class Dataset_KeyValue(Storage):
): # and not isinstance? # add data to dataset
_key.data = Dict[key] # Can we pass a array like this?
# Is array list or tuple
- # is it possible to get lists or tuples as data (add them for safety?)
-
- #### model
+ # is it possible to get lists or tuples as data
+ # (add them for safety?)
if (
isinstance(Dict[key], (list, tuple, dict))
@@ -158,20 +161,22 @@ class Dataset_KeyValue(Storage):
# inside the model dict
- elif isinstance(Dict[key], (list, tuple, dict)) and _last_group == "model":
+ elif (isinstance(Dict[key], (list, tuple, dict))
+ and _last_group == "model"):
key = Model(key) # create model class
self.nested_dict(Dict, "data", _key=key) # check for meta data
- key.add([self.nested_dict(Dict[key], _last_group="")]) # add models
+ key.add([self.nested_dict(Dict[key], _last_group="")])
+ # add models
return key
# meta data
elif (
- not isinstance(Dict[key], (list, tuple, dict)) and _last_group == "data"
+ not isinstance(Dict[key], (list, tuple, dict))
+ and _last_group == "data"
): # add the meta data
_key.attrs[key] = Dict[key]
- #### instrument
# TODO
if (
isinstance(Dict[key], (list, tuple, dict))
@@ -196,16 +201,19 @@ class Dataset_KeyValue(Storage):
# meta data
elif (
- not isinstance(Dict[key], (list, tuple, dict)) and _last_group == "data"
+ not isinstance(Dict[key], (list, tuple, dict))
+ and _last_group == "data"
): # add the meta data
_key.attrs[key] = Dict[key]
- #### pipeline
+ # pipeline
# TODO
if (
- isinstance(Dict[key], (list, tuple, dict)) and key == "pipeline"
+ isinstance(Dict[key], (list, tuple, dict))
+ and key == "pipeline"
): # check if pipeline
- return self.nested_dict(Dict[key], "pipeline", _nested_group=None)
+ return self.nested_dict(Dict[key],
+ "pipeline", _nested_group=None)
# inside the pipeline dict
@@ -218,19 +226,24 @@ class Dataset_KeyValue(Storage):
and key != "model"
and key != "parameters"
):
- if _nested_group == None:
- return self.nested_dict(Dict[key], "pipeline", _nested_group=key)
- elif _nested_group != None:
+ if _nested_group is None:
+ return self.nested_dict(Dict[key],
+ "pipeline",
+ _nested_group=key)
+ elif _nested_group is not None:
return self.nested_dict(
- Dict[key], "pipeline", _nested_group=_nested_group + "/" + key
+ Dict[key], "pipeline",
+ _nested_group=_nested_group + "/" + key
) # measured/capa1/raw
# create the pipeline with nested name
elif (
- isinstance(Dict[key], (list, tuple, dict)) and _last_group == "pipeline"
+ isinstance(Dict[key], (list, tuple, dict))
+ and _last_group == "pipeline"
):
- _nested_group = Pipeline(_nested_group) # create instrument class
+ _nested_group = Pipeline(_nested_group)
+ # create instrument class
self.nested_dict(
Dict, "data", _key=_nested_group
) # check for meta data
@@ -242,7 +255,8 @@ class Dataset_KeyValue(Storage):
# meta data
elif (
- not isinstance(Dict[key], (list, tuple, dict)) and _last_group == "data"
+ not isinstance(Dict[key], (list, tuple, dict))
+ and _last_group == "data"
): # add the meta data
_key.attrs[key] = Dict[key]
--
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