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creating function main #4

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creating function main #4

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36fce4d
Initial commit creating main
aajayi-21 Jun 21, 2023
2ffed0c
Merge branch 'main' of github.com:diffpy/diffpy.snmf into create_main
aajayi-21 Jul 17, 2023
42dac41
reformatted
aajayi-21 Jul 17, 2023
dfa4910
setup library behavior
aajayi-21 Jul 18, 2023
b982382
updated main, fixed io
aajayi-21 Jul 18, 2023
6d8be90
added create_parser function to handle application input
aajayi-21 Jul 19, 2023
6fb2879
added the maximum iterations variable and the condition for when the …
aajayi-21 Jul 19, 2023
07cd3ec
renamed parameters and added output directory parameter. Added functi…
aajayi-21 Jul 20, 2023
1be46c2
Merge branch 'main' into create_main
aajayi-21 Jul 20, 2023
32bf269
added import statement, synced main with branch
aajayi-21 Jul 20, 2023
e527a19
added functionality to test cli app
aajayi-21 Jul 21, 2023
865251e
added explicit default value for --input-directory and modified help …
aajayi-21 Jul 21, 2023
8f6b94e
changed import statement to explicitly import functions
aajayi-21 Jul 21, 2023
a174475
reformatted io.py, moved version argument to bottom of create_parser,…
aajayi-21 Jul 22, 2023
8b26f4f
changed "component_amount" to "number_of_components" in io.py. change…
aajayi-21 Jul 22, 2023
a024bb5
fixed typo out-directory help string
aajayi-21 Jul 22, 2023
1331805
changed 'xrd' to 'power_diffraction' choices for data_type, renamed v…
aajayi-21 Jul 24, 2023
7d4c97f
added a lifting factor optional argument
aajayi-21 Jul 26, 2023
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14 changes: 8 additions & 6 deletions diffpy/snmf/stretchednmfapp.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,6 +18,8 @@ def create_parser():
help="The directory where the results will be written. Defaults to '<input_directory>/snmf_results'.")
parser.add_argument('-t', '--data-type', type=str, choices=['powder_diffraction', 'pdf'],
help="The type of the experimental data.")
parser.add_argument('-l', '--lift', type=float, default=1,
help="The factor that determines how much the data is lifted. By default, the data will be vertically translated to make the minimum value 0.")
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how about "The lifting factor. Data will be lifted by lifted data = data - min(data)*lift. Default is 1"

btw, it occurs to me that if the min(data) is positive, the "lift" will "lower" the data to zero if lift = 1 and will lower it to below zero if lift > 1. This is probably undesirable behavior. Make sure you have tests for this eventuality that give the behavior you want.

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I will make this changes.

The same thought occurred to me. If the min(data) is positive, it's not apparent to me that the data would need to be lifted. My idea is that if the minimum is positive, then do nothing to the data.

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That is reasonable, though why not allow the user to lift the data if she wants to?

Maybe make sure the lift is a lift, so it adds the absolute value of min(data)*lift to the data, something like that.

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Ok.

parser.add_argument('components', type=int,
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help="The number of component signals for the NMF decomposition. Must be an integer greater than 0.")
parser.add_argument('-v', '--version', action='version', help='Print the software version number')
Expand All @@ -36,17 +38,17 @@ def main():
variables = initialize_variables(data_input, args.components, data_type)

if variables["data_type"] == 'pdf':
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lifted_data = data_input - np.ndarray.min(data_input[:]) # Will later use to function in subroutines
lifted_data = data_input - np.ndarray.min(data_input[:]) # Will later use the lift_data function in subroutines

maxiter = 300

for out_iter in range(maxiter):
variables["weights_matrix"] = update_weights_matrix(variables["number_of_components"],
variables["signal_length"],
variables["stretching_factor_matrix"],
variables["component_matrix"], lifted_data,
variables["number_of_moments"], variables["weights_matrix"],
None)
variables["signal_length"],
variables["stretching_factor_matrix"],
variables["component_matrix"], lifted_data,
variables["number_of_moments"], variables["weights_matrix"],
None)

residual_matrix = get_residual_matrix(variables["component_matrix"], variables["weights_matrix"],
variables["stretching_factor_matrix"], lifted_data,
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