"""
Example 8

- evaluate the effects of the trajectory errors on the FEL gain
- errors caused by the BPM misalignment and injection error
"""

import sys
isjupyter = "ipykernel" in sys.modules

import simplex 

if isjupyter:
    simplex.Start(mode="c") 
    import plotly.io as pio
    pio.renderers.default = "notebook" # to enable exporting as an HTML file
    from IPython.display import display, HTML
else:
    simplex.Start() 

# open "sample.json" in the current directory
simplex.Open("sample_sase.json") 

# ideal trajectory
simplex.StartSimulation(folder="./output", prefix="sample8", serial=0)

# trajectory error due to BPM misalignment
Ncases = 4
simplex.Set("alignment", "BPMalign", "Specify Tolerance")
# BPM alignment tolerance scanned from 5um to 20um
simplex.ScanXY("alignment", "xytol", 5e-3, 0.02, Ncases, link=True, serial=1, iniSN=1)

# data names 
datanames = []
for n in range(Ncases):
    datanames.append("sample8-1"+"_"+str(n+1))

# plot and compare the results
if isjupyter:
    display(HTML("<h2>Gain reduction by the BPM misalignment"))
    simplex.PostProcessCLI.Plot(data=["sample8-0", *datanames], 
        item="Pulse Energy", config={"yscale":"Logarithmic"})
else:
    simplex.PostProcess.Plot("Pulse Energy")
    simplex.PostProcess.PlotScale(y="log")
    simplex.PostProcess.SelectData("sample8-0")
    simplex.PostProcess.ComparativePlot(*datanames)
    simplex.PostProcess.DuplicatePlot("Gain reduction by the BPM misalignment")

# betatron oscillation due to injection error
simplex.Set("alignment", "BPMalign", "Ideal")
simplex.Set("dispersion", "einjec", True)
# injection error scanned from 1urad to 4urad
simplex.ScanXY("dispersion", "exyp", 1e-3, 4e-3, Ncases, link=True, serial=2, iniSN=1)

# data names 
datanames = []
for n in range(Ncases):
    datanames.append("sample8-2"+"_"+str(n+1))

# plot and compare the results
if isjupyter:
    display(HTML("<h2>Gain reduction by the injection error"))
    simplex.PostProcessCLI.Plot(data=["sample8-0", *datanames], 
        item="Pulse Energy", config={"yscale":"Logarithmic"})
else:
    simplex.PostProcess.Plot("Pulse Energy")
    simplex.PostProcess.PlotScale(y="log")
    simplex.PostProcess.SelectData("sample8-0")
    simplex.PostProcess.ComparativePlot(*datanames)
    simplex.PostProcess.DuplicatePlot("Gain reduction by the injection error")

if not isjupyter:
    input("Completed. Press enter to exit. ")
    simplex.Exit()