Here is a workaround:
Extract the values of the original function:
list = Table[{\[Delta]δ, solution[\[Delta]solution[δ, 1]}, {\[Delta]δ, -1, 1,0.01}];
Interpolate, derivate, plot:
f = Interpolation[list];
df = D[f[x], x];
Plot[df, {x, -1, 1}]
Where df closely approximates D[solution[δ, 1], δ].
As expected, the derivative is negative for $\delta <0$, and follows the form one might expect from the original plot.
Here is a workaround:
Extract the values of the original function:
list = Table[{\[Delta], solution[\[Delta], 1]}, {\[Delta], -1, 1,0.01}];
Interpolate, derivate, plot:
f = Interpolation[list];
df = D[f[x], x];
Plot[df, {x, -1, 1}]
Where df closely approximates D[solution[δ, 1], δ].
As expected, the derivative is negative for $\delta <0$, and follows the form one might expect from the original plot.
Here is a workaround:
Extract the values of the original function:
list = Table[{δ, solution[δ, 1]}, {δ, -1, 1,0.01}];
Interpolate, derivate, plot:
f = Interpolation[list];
df = D[f[x], x];
Plot[df, {x, -1, 1}]
Where df closely approximates D[solution[δ, 1], δ].
As expected, the derivative is negative for $\delta <0$, and follows the form one might expect from the original plot.
Here is a workaround:
Extract the values of the original function:
list = Transpose[Table[{Range[-1, 1\[Delta], 0.01],Table[solution[δsolution[\[Delta], 1]}, {δ\[Delta], -1, 1, 0.01}]}];
Interpolate, derivate, plot:
f = Interpolation[list];
df = D[f[x], x];
Plot[df, {x, -1, 1}]
Where df closely approximates D[solution[δ, 1], δ].
As expected, the derivative is negative for $\delta <0$, and follows the form one might expect from the original plot.
Here is a workaround:
Extract the values of the original function:
list = Transpose[{Range[-1, 1, 0.01],Table[solution[δ, 1], {δ, -1, 1, 0.01}]}];
Interpolate, derivate, plot:
f = Interpolation[list];
df = D[f[x], x];
Plot[df, {x, -1, 1}]
Where df closely approximates D[solution[δ, 1], δ].
As expected, the derivative is negative for $\delta <0$, and follows the form one might expect from the original plot.
Here is a workaround:
Extract the values of the original function:
list = Table[{\[Delta], solution[\[Delta], 1]}, {\[Delta], -1, 1,0.01}];
Interpolate, derivate, plot:
f = Interpolation[list];
df = D[f[x], x];
Plot[df, {x, -1, 1}]
Where df closely approximates D[solution[δ, 1], δ].
As expected, the derivative is negative for $\delta <0$, and follows the form one might expect from the original plot.
Here is a workaround:
Extract the values of the original function:
list = Transpose[{Range[-1, 1, 0.01],Table[solution[δ, 1], {δ, -1, 1, 0.01}]}];
Interpolate, derivate, plot:
f = Interpolation[list];
df = D[f[x], x];
Plot[df, {x, -1, 1}]
Where df closely approximates D[solution[δ, 1], δ].
As expected, the derivative is negative for $\delta <0$, and follows the form one might expect from the original plot.
Here is a workaround:
Extract the values of the original function:
list = Transpose[{Range[-1, 1, 0.01],Table[solution[δ, 1], {δ, -1, 1, 0.01}]}];
Interpolate, derivate, plot:
f = Interpolation[list];
df = D[f[x], x];
Plot[df, {x, -1, 1}]
Where df closely approximates D[solution[δ, 1], δ]
Here is a workaround:
Extract the values of the original function:
list = Transpose[{Range[-1, 1, 0.01],Table[solution[δ, 1], {δ, -1, 1, 0.01}]}];
Interpolate, derivate, plot:
f = Interpolation[list];
df = D[f[x], x];
Plot[df, {x, -1, 1}]
Where df closely approximates D[solution[δ, 1], δ].
As expected, the derivative is negative for $\delta <0$, and follows the form one might expect from the original plot.