asammdf based signal.append functionality doesn't handle conversion type

[parthipan-ganeshaperumal]

asammdf based signal.append functionality doesn't handle conversion type:

Example :not possible to add this conversion as part of signal if conversion attribute of signal : {0:xx,1:yy,2:xxx} output : it seeting defualt None or conversion_type=0 if pass above dict values Kindly make fix on this?

[parthipan-ganeshaperumal]

output always like this : conversion:<ChannelConversion (name: , unit: , comment: , formula: , referenced blocks: None, address: 0, fields: ['address:0', 'block_len:80', 'comment:', 'comment_addr:0', 'conversion_type:0', 'flags:0', 'formula:', "id:b'##CC'", 'inv_conv_addr:0', 'links_nr:4', 'max_phy_value:0', 'min_phy_value:0', 'name:', 'name_addr:0', 'precision:1', 'ref_param_nr:0', 'referenced_blocks:None', 'reserved0:0', 'unit:', 'unit_addr:0', 'val_param_nr:0'])>

but I expect convesion_type like that : {0:xx,1:yy,2:xxx} under conversion type attribute

[danielhrisca]

You probably need to setup the correct dict keys like the example shows https://github.com/danielhrisca/asammdf/blob/1585aa9e8c2519fd9a57ddef5fd5fc68ea6af63b/examples/mf4_demo.py#L90

[parthipan-ganeshaperumal]

For my case : input look like 'conversion_type': 'lookup_dict', 'lookup_dict': [[0, 'FALSE'], [1, 'TRUE']]}

     but received out like conversion=<ChannelConversion (name: , unit: , comment: , formula: , referenced blocks: None, address: 0, fields: ['address:0', 'block_len:80', 'comment:', 'comment_addr:0', 'conversion_type:0', 'flags:0', 'formula:', "id:b'##CC'", 'inv_conv_addr:0', 'links_nr:4', 'max_phy_value:0', 'min_phy_value:0', 'name:', 'name_addr:0', 'precision:1', 'ref_param_nr:0', 'referenced_blocks:None', 'reserved0:0', 'unit:', 'unit_addr:0', 'val_param_nr:0'])>

[danielhrisca]

Like I said, you need to follow the dict key naming. This will not work with any doct that you throw at it

[parthipan-ganeshaperumal]

Do you wanna align like this {'val_0': 0, 'val_1': 1, 'text_0': 'FALSE', 'text_1': 'TRUE'}

[danielhrisca]

I would also add the default key for unmapped values

[parthipan-ganeshaperumal]

Basically those approach worked but while extracting mdf4 files converstion automatically applied on values in array (np.array) values of concerned signal.. for example : {'val_0': 0, 'val_1': 1, 'text_0': 'FALSE', 'text_1': 'TRUE', 'default': b'default key'} after applied on mdf4 file ...then try to extract information conversion type automatically applied on 0 to False and 1 to True (in np.array).. how to make conversion type visible in attribute level instead of applied on data ???

[danielhrisca]

Call get or select with raw=True

[danielhrisca]

Call get or select with raw=True

[parthipan-ganeshaperumal]

Yes, it worked with proper data but converstion type based information missed and giving as attribute info like this : conversion:{"dict":{}m "type":7} instead of {'val_0': 0, 'val_1': 1, 'text_0': 'FALSE', 'text_1': 'TRUE'} or {0:True, 1:False} ... how to fix

[danielhrisca]

print(ch.conversion)

[parthipan-ganeshaperumal]

before building below mdf file with converstion value :

enter conversion:{'val_0': 0, 'val_1': 1, 'val_2': 2, 'val_3': 3, 'val_4': 4, 'val_5': 5, 'val_6': 6, 'val_7': 7, 'val_8': 8, 'text_0': 'EmiCtrl', 'text_1': 'PartialFC', 'text_2': 'EmiOSC', 'text_3': 'EmiHeat', 'text_4': 'EmiGpf', 'text_5': 'Diagnostics (SwiftLamOffs)', 'text_6': 'ProtExh', 'text_7': 'ProtIgn', 'text_8': 'Debug', 'default': b'default key'}

after try to view the file via below:

1.mdf = asammdf.MDF('particular.mf4') 2.signals = mdf.select(["rVcLamTar_D_LamSrc"])

signal(as below):

[<Signal rVcLamTar_D_LamSrc: samples=[b'EmiCtrl' b'EmiCtrl' b'EmiCtrl' ... b'EmiGpf' b'EmiGpf' b'EmiGpf'] timestamps=[ -5.05789961 -5.0478505 -5.03780139 ... 1384.68072007 1384.69071935 1384.70076962] invalidation_bits=None unit="-" conversion=None source=SignalSource(name='Python', path='Python', comment='', source_type=4, bus_type=0) comment="Lambda source" mastermeta="('time', 1)" raw=False display_name= attachment=()> ]

conclusion : converstion type applied on samples but conversion comes as None so here my query : I don't wanna apply conversion_type on samples but i just wanna see the converstion information in conversion ... how to do this?

[danielhrisca]

Call get or select with raw=True

https://asammdf.readthedocs.io/en/latest/