Generate test data using a function in one dimension.
make_fit_data --help # Best source of information Usage: make_fit_data poly4 c.1 50 1.0 10.0 0.0 2.0 Y arg1 - type of curve arg2 - name of coefficients file arg3 - number of points arg4 - xmin arg5 - xmax arg6 - st.dev. of iX-axis noise added arg7 - st.dev. of iY-axis noise added arg8 - Run in debug mode (Y/N) Note, you can get a quick listing of available finctions with: make_fit_data LThe data are written to a file named make_fit_data.out. The analytical functions available are provide by gen_curve.sh. Use the "--help" option with gendata.sh to get a detailed listing of these funtions.
It should be noted that it is not necessary to prepare a coeficients file before the make_fit_data script is run. If the file is not present then the user will be interactivel queried for the coefiicients. A file with the name specified on the command line (arg2) will then be created. Bleow I show some examples of data sets generated with make_fit_data and then plotted with the suggested pxy_SM_plot.py.
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Data generated with make_fit_data using a 4 term polynomial with noise
added to each axis. The commands used were:
% make_fit_data poly4 c.1 50 1.0 10.0 0.0 2.0 Y % cat c.1 1 0.5 0.05 0.01 To make the plot: pxy_SM_plot.py STYLE 1.0 10.0 -0.02498 23.02544 SHOWBy using the show() option of matplotlib we can adjust the scaling of the plot before generating a hardcopy file. |