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Move flagging app to app folder with initialized callbacks/ and components/ modules

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florez_j
2025-02-13 18:13:45 +01:00
parent 479c11d0d4
commit 11ecdebf1b
5 changed files with 40 additions and 32 deletions
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0
app/__init__.py Normal file
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0
app/callbacks/__inti__.py Normal file
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0
app/components/__inti__.py Normal file
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15
app/data_flagging_app.py
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@ -9,9 +9,14 @@ except NameError:
#print("Otherwise, path to submodule DIMA may not be resolved properly.")
thisFilePath = os.getcwd() # Use current directory or specify a default
dimaPath = os.path.normpath(os.path.join(thisFilePath, "..",'..')) # Move up to project root
projectPath = os.path.normpath(os.path.join(thisFilePath, "..",".."))
print(dimaPath)
print(projectPath)
if not projectPath in sys.path:
sys.path.insert(0,projectPath)
#print(dimaPath)
import pandas as pd
import numpy as np
@ -20,9 +25,9 @@ import dash
import io
# Set up project root directory
root_dir = os.path.abspath(os.curdir)
sys.path.append(root_dir)
sys.path.append(os.path.join(root_dir,'dima'))
#root_dir = os.path.abspath(os.curdir)
#sys.path.append(root_dir)
#sys.path.append(os.path.join(root_dir,'dima'))
import data_flagging_utils as data_flagging_utils

57
app/data_flagging_utils.py
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@ -57,54 +57,56 @@ def filter_flags_by_label(flags_dict, label):
for code, value in flags_dict.items() if value['flag_label'] == label]
def create_loaded_file_figure(file_path, instfolder):
def create_loaded_file_figure(file_path, instFolder, dataset_name, datetime_var, datetime_var_format, variables):
DataOpsAPI = h5de.HDF5DataOpsManager(file_path)
if not DataOpsAPI.file_obj:
DataOpsAPI.load_file_obj()
target_channels = DataOpsAPI.file_obj[instfolder].attrs['target_channels']['names'][0].decode().split(',')
target_loc = DataOpsAPI.file_obj[instfolder].attrs['target_channels']['location'][0].decode()
diagnostic_channels = DataOpsAPI.file_obj[instfolder].attrs['diagnostic_channels']['names'][0].decode().split(',')
diagnostic_loc = DataOpsAPI.file_obj[instfolder].attrs['diagnostic_channels']['location'][0].decode()
#target_channels = DataOpsAPI.file_obj[instfolder].attrs['target_channels']['names'][0].decode().split(',')
#target_loc = DataOpsAPI.file_obj[instfolder].attrs['target_channels']['location'][0].decode()
#diagnostic_channels = DataOpsAPI.file_obj[instfolder].attrs['diagnostic_channels']['names'][0].decode().split(',')
#diagnostic_loc = DataOpsAPI.file_obj[instfolder].attrs['diagnostic_channels']['location'][0].decode()
#fig = make_subplots(rows=(len(target_channels+diagnostic_channels)-2), cols=1, shared_xaxes=True,
# row_heights = [1 for i in range(len(target_channels+diagnostic_channels)-2)])
fig = make_subplots(rows=(len(target_channels+diagnostic_channels)-2), cols=1,
row_heights = [1 for i in range(len(target_channels+diagnostic_channels)-2)])
fig = make_subplots(rows=(len(variables)), cols=1,
row_heights = [1 for i in range(len(variables))])
traces = []
trace_idx = 1
dataset = DataOpsAPI.file_obj[target_loc]
time_column = DataOpsAPI.reformat_datetime_column(target_loc,target_channels[0],'%d.%m.%Y %H:%M:%S.%f')
dataset = DataOpsAPI.file_obj[dataset_name]
time_column = DataOpsAPI.reformat_datetime_column(dataset_name,
datetime_var,
datetime_var_format)
for i in range(1,len(target_channels)):
#time_column = dataset[datetime_var][:]
for i in range(1,len(variables)):
fig.add_trace(go.Scatter(x = time_column,
y = dataset[target_channels[i]][:],
y = dataset[variables[i]][:],
mode = 'lines',
name = target_channels[i]), row=trace_idx, col=1)
fig.update_yaxes(title_text= target_channels[i], row=trace_idx, col=1)
name = variables[i]), row=trace_idx, col=1)
fig.update_yaxes(title_text= variables[i], row=trace_idx, col=1)
trace_idx = trace_idx + 1
dataset = DataOpsAPI.file_obj[diagnostic_loc]
time_column = DataOpsAPI.reformat_datetime_column(diagnostic_loc,diagnostic_channels[0],'%d.%m.%Y %H:%M:%S')
for i in range(1,len(diagnostic_channels)):
#dataset = DataOpsAPI.file_obj[diagnostic_loc]
#time_column = DataOpsAPI.reformat_datetime_column(diagnostic_loc,diagnostic_channels[0],'%d.%m.%Y %H:%M:%S')
#for i in range(1,len(diagnostic_channels)):
fig.add_trace(go.Scatter(x = time_column,
y = dataset[diagnostic_channels[i]][:],
mode = 'lines',
name = diagnostic_channels[i]), row=trace_idx, col=1)
fig.update_yaxes(title_text= diagnostic_channels[i], row=trace_idx, col=1, type="log")
trace_idx = trace_idx + 1
# fig.add_trace(go.Scatter(x = time_column,
# y = dataset[diagnostic_channels[i]][:],
# mode = 'lines',
# name = diagnostic_channels[i]), row=trace_idx, col=1)
# fig.update_yaxes(title_text= diagnostic_channels[i], row=trace_idx, col=1, type="log")
# trace_idx = trace_idx + 1
fig.update_layout(height=1200, title_text=f"{instfolder} : Target and Diagnostic Channels", showlegend=False)
fig.update_layout(height=1200, title_text=f"{instFolder} : Target and Diagnostic Channels", showlegend=False)
DataOpsAPI.unload_file_obj()
target_channels.remove(target_channels[0])
diagnostic_channels.remove(diagnostic_channels[0])
return fig, [','.join([item,target_loc]) for item in target_channels] + [','.join([item,diagnostic_loc]) for item in diagnostic_channels]
#target_channels.remove(target_channels[0])
#diagnostic_channels.remove(diagnostic_channels[0])
return fig , [','.join([item,dataset_name]) for item in variables] #+ [','.join([item,diagnostic_loc]) for item in diagnostic_channels]
#import os
import json
@ -142,6 +144,7 @@ def load_flags(filePath, instFolder, dry_run : bool = False):
# Construct the flags folder path
flagFolderPath = os.path.join(os.path.splitext(filePath)[0], f'{instFolder}_flags')
# Return None if the flags folder does not exist
if not os.path.exists(flagFolderPath):