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move code to core
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1 +1 @@ | ||
| __version__ = "0.0.1" | ||
| __version__ = "0.0.5" |
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,247 @@ | ||
| # AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/01_aicorebridge.ipynb. | ||
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| # %% auto 0 | ||
| __all__ = ['syslog', 'AICoreModule'] | ||
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| # %% ../nbs/01_aicorebridge.ipynb 2 | ||
| import typing | ||
| import logging | ||
| import inspect | ||
| import datetime | ||
| import json | ||
| import pandas as pd | ||
| import numpy as np | ||
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| from fastcore.basics import patch_to, patch | ||
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| # %% ../nbs/01_aicorebridge.ipynb 4 | ||
| syslog = logging.getLogger(__name__) | ||
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| # %% ../nbs/01_aicorebridge.ipynb 6 | ||
| class AICoreModule(): pass | ||
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| # %% ../nbs/01_aicorebridge.ipynb 7 | ||
| @patch | ||
| def __init__(self:AICoreModule, | ||
| save_dir:str, # path where the module can keep files | ||
| processor:typing.Callable, # data processing function | ||
| *args, **kwargs): | ||
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| self.save_dir = save_dir | ||
| self._init_processor(processor) | ||
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| self.init_args = args | ||
| self.init_kwargs = kwargs | ||
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| # %% ../nbs/01_aicorebridge.ipynb 8 | ||
| @patch | ||
| def _init_processor( | ||
| self:AICoreModule, | ||
| processor:typing.Callable): | ||
| """Initializes processor related variables on self""" | ||
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| self.processor = processor | ||
| self.processor_signature = inspect.signature(self.processor) | ||
| self.processor_params = dict(self.processor_signature.parameters) | ||
| self.return_param = self.processor_params.pop('return', None) | ||
| self.data_param, *self.call_params = list(self.processor_params.keys()) | ||
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| # %% ../nbs/01_aicorebridge.ipynb 9 | ||
| @patch | ||
| def infer(self:AICoreModule, data:dict, *_, **kwargs): | ||
| try: | ||
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| msg=[ | ||
| f"{self.processor.__name__}({self.processor_signature})", | ||
| f"init_args: {self.init_args}, init_kwargs: {self.init_kwargs}", | ||
| ] | ||
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| lastSeen = kwargs.pop('lastSeen', False) | ||
| recordformat = kwargs.pop('format', "records").lower() | ||
| reversed = kwargs.pop('reversed', False) | ||
| timezone = kwargs.get('timezone', 'UTC') | ||
| msg.append(f"lastSeen: {lastSeen}, recordformat: {recordformat}, timezone: {timezone}") | ||
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| calldata = self.get_call_data( | ||
| data, | ||
| recordformat=recordformat, | ||
| timezone=timezone, | ||
| reversed=reversed) | ||
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| msg.append(f"calldata shape: {calldata.shape}") | ||
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| callargs = self.get_callargs(**kwargs) | ||
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| for arg, val in callargs.items(): | ||
| msg.append(f"{arg}: {val}") | ||
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| result = self.processor(calldata, **callargs) | ||
| msg.append(f"result shape: {result.shape}") | ||
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| return { | ||
| 'msg':msg, | ||
| 'data': self.rewrite_data( | ||
| result if not lastSeen else result[-1:], | ||
| recordformat=recordformat, | ||
| timezone=timezone, | ||
| reversed=reversed) | ||
| } | ||
| except Exception as err: | ||
| return { | ||
| 'msg': f"Unexpected {err=}, {type(err)=}", | ||
| 'data': [] | ||
| } | ||
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| # %% ../nbs/01_aicorebridge.ipynb 10 | ||
| @patch | ||
| def get_callargs(self:AICoreModule, **kwargs): | ||
| "Get arguments for the processor call" | ||
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| metadata = kwargs.pop('metadata', {}) # TODO: historic metadata | ||
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| return { | ||
| K:self.processor_signature.parameters[K].annotation(kwargs.get(K,metadata.get(K, self.init_kwargs.get(K, self.processor_signature.parameters[K].default)))) | ||
| for K in self.call_params | ||
| } | ||
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| # %% ../nbs/01_aicorebridge.ipynb 11 | ||
| @patch | ||
| def get_call_data( | ||
| self:AICoreModule, | ||
| data:dict, | ||
| recordformat='records', | ||
| timezone='UTC', | ||
| reversed=False): | ||
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| "Convert data to the processor signature" | ||
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| orient = recordformat.lower() | ||
| assert orient in ['records', 'table'] | ||
| #assert False, "started work on format" | ||
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| if orient == 'records': | ||
| df = pd.DataFrame.from_records(data) | ||
| time_column = [C for C in df.columns if C.lower() in ['datetimemeasure', 'time']][0] | ||
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| elif orient == 'table': | ||
| time_column = data['schema']['primaryKey'][0] | ||
| df = pd.DataFrame.from_dict(data['data']).set_index(data['schema']['primaryKey']) | ||
| df.index.name = 'time' | ||
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| df.columns = [C.lower() for C in df.columns] | ||
| time_column = [C for C in df.columns if C in ['datetimemeasure', 'time']][0] | ||
| df[time_column] = pd.to_datetime(df[time_column],utc=True,format='ISO8601') | ||
| df.set_index(time_column, inplace=True) | ||
| #df.index = pd.DatetimeIndex(df.index).round('ms') | ||
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| df.index.name = 'time' | ||
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| if reversed: | ||
| df = df[::-1] | ||
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| if not df.index.tz: | ||
| df.index = df.index.tz_localize('UTC').tz_convert(timezone) | ||
| elif str(df.index.tz) != timezone: | ||
| df.index = df.index.tz_convert(timezone) | ||
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| if self.processor_params[self.data_param].annotation == pd.DataFrame: | ||
| return df | ||
| elif len(df.columns) > 1: | ||
| df.index = (df.index - datetime.datetime(1970,1,1, tzinfo=datetime.timezone.utc)) / datetime.timedelta(seconds=1) | ||
| return df.to_records(index=True) | ||
| else: | ||
| df.index = (df.index - datetime.datetime(1970,1,1, tzinfo=datetime.timezone.utc)) / datetime.timedelta(seconds=1) | ||
| return df.reset_index().to_numpy() | ||
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| # %% ../nbs/01_aicorebridge.ipynb 12 | ||
| @patch | ||
| def rewrite_data( | ||
| self:AICoreModule, | ||
| data:typing.Union[pd.DataFrame, pd.Series, dict], | ||
| recordformat:str='split', | ||
| timezone:str='UTC', | ||
| reversed:bool=False): | ||
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| "Rewrite data to dictionary matching the requested recordformat" | ||
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| orient = recordformat.lower() | ||
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| if orient == 'split-index': | ||
| orient = 'split' | ||
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| normalized_data = self.convert_to_dataframe(data, timezone=timezone) | ||
| normalized_data.index = normalized_data.index.map(lambda x: x.isoformat()) | ||
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| if reversed: | ||
| normalized_data = normalized_data[::-1] | ||
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| if orient == 'records': | ||
| records = normalized_data.reset_index().to_dict(orient='records') | ||
| else: | ||
| records = normalized_data.to_dict(orient=orient) | ||
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| if normalized_data.isna().any(axis=None): | ||
| return [ {k:v for k,v in m.items() if pd.notnull(v)} for m in records] | ||
| else: | ||
| return records | ||
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| # %% ../nbs/01_aicorebridge.ipynb 13 | ||
| @patch | ||
| def convert_to_dataframe( | ||
| self:AICoreModule, | ||
| adata:typing.Union[pd.DataFrame, pd.Series, dict, np.ndarray, np.recarray], | ||
| timezone='UTC', | ||
| columnnames=None): | ||
| """Convert various data formats to standardized timeseries DataFrame""" | ||
|
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| if isinstance(adata, pd.DataFrame): | ||
| df = adata | ||
| elif isinstance(adata, pd.Series): | ||
| df = pd.DataFrame(adata) | ||
|
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| elif isinstance(adata, dict): | ||
| # dict/mapping of individual timeseries | ||
| df = pd.DataFrame({ | ||
| C:pd.Series(data=A[:,1], index=pd.DatetimeIndex(A[:,0]*1e9)) if isinstance(A, np.ndarray) else A | ||
| for C,A in adata.items() | ||
| }) | ||
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| elif adata.dtype.names is not None: | ||
| # structured or recarray | ||
| df = pd.DataFrame( | ||
| data=adata.view(dtype=np.float64).reshape(adata.shape[0],len(adata.dtype))[:,range(1,len(adata.dtype))], | ||
| index=pd.DatetimeIndex(adata.view(dtype=np.float64).reshape(adata.shape[0],len(adata.dtype))[:,0] * 1e9), | ||
| columns=adata.dtype.names[1:] | ||
| ) | ||
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| else: | ||
| if adata.shape[0] > 0: | ||
| if adata.shape[1]>2: | ||
| columns=[f"value_{str(i+1)}" for i in range(adata.shape[1]-1)] if not columnnames else [f"{str(i)}" for i in columnnames[1:]] | ||
| else: | ||
| columns=['value'] | ||
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| df = pd.DataFrame( | ||
| data=adata[:, 1:], | ||
| index=pd.DatetimeIndex(adata[:,0]*1e9), | ||
| columns=columns | ||
| ) | ||
| else: | ||
| return pd.DataFrame() | ||
|
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| df.index.name = 'time' | ||
| if not df.index.tz: | ||
| df.index = df.index.tz_localize('UTC').tz_convert(timezone) | ||
| elif str(df.index.tz) != timezone: | ||
| df.index = df.index.tz_convert(timezone) | ||
|
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| return df |
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