Using curve_fit to fit a parameter that varies with x
So I am trying to use Scipy curve_fit to fit the Fuchs-Sondheimer formula to some resistivity (y) against sample thickness (x) data. The formula looks like this:
y = (rho_0)*(1 + 3l/8x)
Where rho_0 is constant for all x values but l varies for each value of x.
My problem is curve_fit returns a single value for both rho_0 l and I can't fathom how to get it to return different optimum values of l for each x value. I'm twisting my mind trying to write functions within functions but I'm sure theres an easy way of going about this that I'm missing.
Thank you for your help and I hope I've not worded that too confusingly.
python scipy curve-fitting
asked Nov 24 '18 at 21:02
Daniel MarchantDaniel Marchant
42
add a comment |
So I am trying to use Scipy curve_fit to fit the Fuchs-Sondheimer formula to some resistivity (y) against sample thickness (x) data. The formula looks like this:
y = (rho_0)*(1 + 3l/8x)
Where rho_0 is constant for all x values but l varies for each value of x.
My problem is curve_fit returns a single value for both rho_0 l and I can't fathom how to get it to return different optimum values of l for each x value. I'm twisting my mind trying to write functions within functions but I'm sure theres an easy way of going about this that I'm missing.
Thank you for your help and I hope I've not worded that too confusingly.
python scipy curve-fitting
asked Nov 24 '18 at 21:02
Daniel MarchantDaniel Marchant
42
Please provide some code and data, then it will be much easier to help. Right now it is not entirely clear to me what the actual problem is.
– Cleb
Nov 24 '18 at 21:13
1
"Where rho_0 is constant for all x values but l varies for each value of x." So you meany = f(x) = rho_0*(1 + 3*I(x)/(8*x))?curve_fitrequires a model with a finite number of parameters. It can't find an arbitrary functionI(x).
– Warren Weckesser
Nov 24 '18 at 21:34
1
So you have to decide on a parametrized family of functions that defines the possible forms of the function I(x), and then express the function passed tocurve_fitin terms of those parameters.
– Warren Weckesser
Nov 24 '18 at 21:40
I see another potential problem. If you have three data points, you will have four parameters to be fitted - and curve_fit will give an error that there are more parameters than data points..
– James Phillips
Nov 24 '18 at 21:45
add a comment |
So I am trying to use Scipy curve_fit to fit the Fuchs-Sondheimer formula to some resistivity (y) against sample thickness (x) data. The formula looks like this:
y = (rho_0)*(1 + 3l/8x)
Where rho_0 is constant for all x values but l varies for each value of x.
My problem is curve_fit returns a single value for both rho_0 l and I can't fathom how to get it to return different optimum values of l for each x value. I'm twisting my mind trying to write functions within functions but I'm sure theres an easy way of going about this that I'm missing.
Thank you for your help and I hope I've not worded that too confusingly.
python scipy curve-fitting
asked Nov 24 '18 at 21:02
Daniel MarchantDaniel Marchant
42
So I am trying to use Scipy curve_fit to fit the Fuchs-Sondheimer formula to some resistivity (y) against sample thickness (x) data. The formula looks like this:
y = (rho_0)*(1 + 3l/8x)
Where rho_0 is constant for all x values but l varies for each value of x.
My problem is curve_fit returns a single value for both rho_0 l and I can't fathom how to get it to return different optimum values of l for each x value. I'm twisting my mind trying to write functions within functions but I'm sure theres an easy way of going about this that I'm missing.
Thank you for your help and I hope I've not worded that too confusingly.
python scipy curve-fitting
python scipy curve-fitting
asked Nov 24 '18 at 21:02
Daniel MarchantDaniel Marchant
42
asked Nov 24 '18 at 21:02
Daniel MarchantDaniel Marchant
42
asked Nov 24 '18 at 21:02
Daniel MarchantDaniel Marchant
42
asked Nov 24 '18 at 21:02
Daniel MarchantDaniel Marchant
42
asked Nov 24 '18 at 21:02
Daniel MarchantDaniel Marchant
42
42
Please provide some code and data, then it will be much easier to help. Right now it is not entirely clear to me what the actual problem is.
– Cleb
Nov 24 '18 at 21:13
1
"Where rho_0 is constant for all x values but l varies for each value of x." So you meany = f(x) = rho_0*(1 + 3*I(x)/(8*x))?curve_fitrequires a model with a finite number of parameters. It can't find an arbitrary functionI(x).
– Warren Weckesser
Nov 24 '18 at 21:34
1
So you have to decide on a parametrized family of functions that defines the possible forms of the function I(x), and then express the function passed tocurve_fitin terms of those parameters.
– Warren Weckesser
Nov 24 '18 at 21:40
I see another potential problem. If you have three data points, you will have four parameters to be fitted - and curve_fit will give an error that there are more parameters than data points..
– James Phillips
Nov 24 '18 at 21:45
add a comment |
Please provide some code and data, then it will be much easier to help. Right now it is not entirely clear to me what the actual problem is.
– Cleb
Nov 24 '18 at 21:13
1
"Where rho_0 is constant for all x values but l varies for each value of x." So you meany = f(x) = rho_0*(1 + 3*I(x)/(8*x))?curve_fitrequires a model with a finite number of parameters. It can't find an arbitrary functionI(x).
– Warren Weckesser
Nov 24 '18 at 21:34
1
So you have to decide on a parametrized family of functions that defines the possible forms of the function I(x), and then express the function passed tocurve_fitin terms of those parameters.
– Warren Weckesser
Nov 24 '18 at 21:40
I see another potential problem. If you have three data points, you will have four parameters to be fitted - and curve_fit will give an error that there are more parameters than data points..
– James Phillips
Nov 24 '18 at 21:45
Please provide some code and data, then it will be much easier to help. Right now it is not entirely clear to me what the actual problem is.
– Cleb
Nov 24 '18 at 21:13
Please provide some code and data, then it will be much easier to help. Right now it is not entirely clear to me what the actual problem is.
– Cleb
Nov 24 '18 at 21:13
1
1
"Where rho_0 is constant for all x values but l varies for each value of x." So you mean
y = f(x) = rho_0*(1 + 3*I(x)/(8*x))? curve_fit requires a model with a finite number of parameters. It can't find an arbitrary function I(x).– Warren Weckesser
Nov 24 '18 at 21:34
"Where rho_0 is constant for all x values but l varies for each value of x." So you mean
y = f(x) = rho_0*(1 + 3*I(x)/(8*x))? curve_fit requires a model with a finite number of parameters. It can't find an arbitrary function I(x).– Warren Weckesser
Nov 24 '18 at 21:34
1
1
So you have to decide on a parametrized family of functions that defines the possible forms of the function I(x), and then express the function passed to
curve_fit in terms of those parameters.– Warren Weckesser
Nov 24 '18 at 21:40
So you have to decide on a parametrized family of functions that defines the possible forms of the function I(x), and then express the function passed to
curve_fit in terms of those parameters.– Warren Weckesser
Nov 24 '18 at 21:40
I see another potential problem. If you have three data points, you will have four parameters to be fitted - and curve_fit will give an error that there are more parameters than data points..
– James Phillips
Nov 24 '18 at 21:45
I see another potential problem. If you have three data points, you will have four parameters to be fitted - and curve_fit will give an error that there are more parameters than data points..
– James Phillips
Nov 24 '18 at 21:45
add a comment |
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Please provide some code and data, then it will be much easier to help. Right now it is not entirely clear to me what the actual problem is.
– Cleb
Nov 24 '18 at 21:13
1
"Where rho_0 is constant for all x values but l varies for each value of x." So you mean
y = f(x) = rho_0*(1 + 3*I(x)/(8*x))?curve_fitrequires a model with a finite number of parameters. It can't find an arbitrary functionI(x).– Warren Weckesser
Nov 24 '18 at 21:34
1
So you have to decide on a parametrized family of functions that defines the possible forms of the function I(x), and then express the function passed to
curve_fitin terms of those parameters.– Warren Weckesser
Nov 24 '18 at 21:40
I see another potential problem. If you have three data points, you will have four parameters to be fitted - and curve_fit will give an error that there are more parameters than data points..
– James Phillips
Nov 24 '18 at 21:45