least-squares

问题 I have two functions and a set of data. Both functions have the same x data and the same parameters. I want to obtain the parameters by least squares method that makes the best fit of my data. The parameters are: ex,ey,ez. The X data are: RA,DE (like 3000 points). The Y data are: dRA,dDE. I tried this but I obtained a wrong solution: def residuals(p, dRA, dDE, RA, DEC): ex,ey,ez = p f1 = dRA-(ex*sin(DEC)*cos(RA)+ey*sin(DEC)*sin(RA)-ez*cos(DEC)) f2 = dDE-(-ex*sin(RA)+ey*cos(RA)) err = np

问题 I have two functions and a set of data. Both functions have the same x data and the same parameters. I want to obtain the parameters by least squares method that makes the best fit of my data. The parameters are: ex,ey,ez. The X data are: RA,DE (like 3000 points). The Y data are: dRA,dDE. I tried this but I obtained a wrong solution: def residuals(p, dRA, dDE, RA, DEC): ex,ey,ez = p f1 = dRA-(ex*sin(DEC)*cos(RA)+ey*sin(DEC)*sin(RA)-ez*cos(DEC)) f2 = dDE-(-ex*sin(RA)+ey*cos(RA)) err = np

问题 I have these values: T_values = (222, 284, 308.5, 333, 358, 411, 477, 518, 880, 1080, 1259) (x values) C/(3Nk)_values = (0.1282, 0.2308, 0.2650, 0.3120 , 0.3547, 0.4530, 0.5556, 0.6154, 0.8932, 0.9103, 0.9316) (y values) I know they follow the model: C/(3Nk)=(h*w/(k*T))**2*(exp(h*w/(k*T)))/(exp(h*w/(k*T)-1))**2 I also know that k=1.38*10**(-23) and h=6.626*10**(-34) . I have to find the w that best describes the measurement data. I'd like to solve this using the least square method in python,

问题 Explanation of the problem: I have points with (x,y,z) coordinates at two+ distinct times. For convenience, they can be imagined as irregularly spaced points along the surface of an inverted paraboloid. There is some minimal thickness to the paraboloid. The paraboloid changes shape slightly as time proceeds (like a balloon inflating) and when it does so, all of the points move. By substracting the coordinates at time2 - time1, I can get the displacement vectors at each point. It is important

问题 Explanation of the problem: I have points with (x,y,z) coordinates at two+ distinct times. For convenience, they can be imagined as irregularly spaced points along the surface of an inverted paraboloid. There is some minimal thickness to the paraboloid. The paraboloid changes shape slightly as time proceeds (like a balloon inflating) and when it does so, all of the points move. By substracting the coordinates at time2 - time1, I can get the displacement vectors at each point. It is important

问题 I'm using ceres solver for a project, and when I call the ceres::Solve function, the library starts to output lines such as this one: iterative_schur_complement_solver.cc:88 No parameter blocks left in the schur complement. wall_time.cc:74 IterativeSchurComplementSolver::Solve Delta Cumulative Total : 0.00001 0.00001 I tried to disable the logging of these intermediate steps but I had no success so far. I'm calling this line on the constructor of my class: google::InitGoogleLogging("my

问题 I'm using ceres solver for a project, and when I call the ceres::Solve function, the library starts to output lines such as this one: iterative_schur_complement_solver.cc:88 No parameter blocks left in the schur complement. wall_time.cc:74 IterativeSchurComplementSolver::Solve Delta Cumulative Total : 0.00001 0.00001 I tried to disable the logging of these intermediate steps but I had no success so far. I'm calling this line on the constructor of my class: google::InitGoogleLogging("my

来源： https://stackoverflow.com/questions/49931455/python-lmfit-constraints-a-b-c

来源： https://stackoverflow.com/questions/49931455/python-lmfit-constraints-a-b-c

来源： https://stackoverflow.com/questions/42388139/how-to-compute-standard-deviation-errors-with-scipy-optimize-least-squares