def __init__(self):
super().__init__("SquareGen")
# ports
self.frequency = free_int_input(self, "freq", 1, 3, 5)
self.amplitude = free_int_input(self, "amp", 0, 20, 100)
self.square = ArrayOutput(self, "square", self.read_square)
def __init__(self):
super().__init__("SinGen")
# ports
self.frequency = free_int_input(self, "frequency", 100, 200, 500)
self.amplitude = free_int_input(self, "frequency", 0, 1, 100)
self.line1 = free_int_input(self, "line1", 0, 1, 100)
self.line2 = free_int_input(self, "line2", 0, 1, 100)
self.sin = ArrayOutput(self, "sin", self.read_sin)
def __init__(self):
super().__init__("background_subtraction")
# streamed inputs
# self.e = StreamInput(self, "e")
self.input_data = StreamInput(self, "input_data")
# input.changed += self.on_data
# parameter inputs
self.fit = choice_input(
fn=self,
name="fit",
default="No fit",
choices=[
"No fit",
"Polynomial fit inside limits",
"Polynomial fit outside limits",
"exp decay (fits for all e < 'Background_start' and e > ' Background_end')",
"2 point linear (straight line between 2 points)",
],
)
self.apply_offset = choice_input(
fn=self,
name="apply_offset",
default="off",
choices=[
"off",
"on (shifts post 'Background_end' by amount equal to e = 'Background_end' to e = 'Background_start' )",
],
)
# self.apply_offset = int_input(self, "apply_offset", 1, 1, 3)
self.p_start = int_input(self, "Background_start", self.input_data,
None)
self.p_end = int_input(self, "Background_end", self.input_data, None)
self.power = free_int_input(self, "power", 1, 1, 3)
# output ports
self.background = ArrayOutput(self, "background", self.read_background)
self.subtracted_background = ArrayOutput(
self, "subtracted_background", self.read_subtracted_background)
def __init__(self):
super().__init__("Identify Peaks")
# Input Ports
self.input_array = StreamInput(self, "input_array")
self.number_of_peaks = free_int_input(self, "number_of_peaks", 1, 2, 10)
self.center_of_peaks = int_input(
self, "center_of_peaks", self.input_array, 5990
)
self.sigma_of_peaks = int_input(self, "sigma_of_peaks", self.input_array, 30)
self.height_of_peaks = int_input(
self, "height_of_peaks", self.input_array, 0.12
)
self.type_of_peaks = choice_input(
self, "GaussianModel", "GaussianModel", ["GaussianModel", "LorentzianModel"]
)
# output ports
self.fitted_peaks = ArrayOutput(self, "fitted_peaks", self.read_fitted_peaks)
def __init__(self):
super().__init__("background_subtraction")
# streamed inputs
# self.e = StreamInput(self, "e")
self.t_p_all = StreamInput(self, "t_p_all")
self.t_a_all = StreamInput(self, "t_a_all")
# parameter inputs
self.fit = choice_input(
self,
"fit",
"No fit",
[
"No fit",
"Polynomial fit inside limits",
"Polynomial fit outside limits",
"exp decay (fits for all e < 'Background_start' and e > ' Background_end')",
"2 point linear (straight line between 2 points)",
],
)
self.apply_offset = choice_input(
self,
"apply_offset",
"off",
[
"off",
"on (shifts post 'Background_end' by amount equal to e = 'Background_end' to e = 'Background_start' )",
],
)
# self.apply_offset = int_input(self, "apply_offset", 1, 1, 3)
self.p_start = int_input(self, "Background_start", self.t_p_all, None)
self.p_end = int_input(self, "Background_end", self.t_p_all, None)
self.power = free_int_input(self, "power", 1, 1, 4)
# output ports
self.a_p_background_subtraction = ArrayOutput(
self, "a_p_background_subtraction",
self.read_a_p_background_subtraction)
self.a_a_background_subtraction = ArrayOutput(
self, "a_a_background_subtraction",
self.read_a_a_background_subtraction)
self.a_p_background_subtracted = ArrayOutput(
self, "a_p_background_subtracted",
self.read_ia_p_background_subtracted)
self.a_a_background_subtracted = ArrayOutput(
self, "a_a_background_subtracted",
self.read_ia_a_background_subtracted)
# self.e_out= ArrayOutput(self, "e_out", self.read_e_out)
# publish ports
self.inputs = [
# self.e,
self.t_p_all,
self.t_a_all,
self.fit,
self.apply_offset,
self.p_start,
self.p_end,
self.power,
]
self.outputs = [
self.a_p_background_subtraction,
self.a_a_background_subtraction,
self.a_p_background_subtracted,
self.a_a_background_subtracted,
# self.e_out,
]