code: def calc_init_params(x, y):
      """This generates the min, max, x value at the mid-y value, and Hill
      coefficient. These values are starting points for the sigmoid fitting.
  
      x & y are the points to be fit
      returns minimum, maximum, ec50 and hill coefficient starting points
      """
      min_0 = min(y)
      max_0 = max(y)
  
      # Parameter 3
      # OLD:  parms(3)=(min(x)+max(x))/2;
      # This is an estimate of the EC50, i.e., the half maximal effective
      # concentration (here denoted as x-value)
      #
      # Note that this was originally simply mean([max(x); min(x)]).  This does not
      # take into account the y-values though, so it was changed to be the
      # x-value that corresponded to the y-value closest to the mean([max(y); min(y)]).
      # Unfortunately, for x-values with only two categories e.g., [0 1], this results in
      # an initial EC50 of either 0 or 1 (min(x) or max(x)), which seems a bad estimate.
      # 5 We will take a two-pronged approach: Use the estimate from this latter approach,
      # unless the parameter will equal either the max(x) or min(x).  In this case, we will use the
      # former approach, namely (mean([max(x); min(x)]).  DL 2007.09.24
      YvalueAt50thPercentile = (min(y) + max(y)) / 2
      DistanceToCentralYValue = numpy.abs(y - YvalueAt50thPercentile)
      LocationOfNearest = numpy.argmin(DistanceToCentralYValue)
      XvalueAt50thPercentile = x[LocationOfNearest]
      if XvalueAt50thPercentile == min(
          x
      ) or XvalueAt50thPercentile == max(x):
          ec50 = (min(x) + max(x)) / 2
      else:
          ec50 = XvalueAt50thPercentile
  
      # Parameter 4
      # The OLD way used 'size' oddly - perhaps meant 'length'?  It would cause
      # divide-by-zero warnings since 'x(2)-x(sizex)' would necessarily have
      # zeros.
      # The NEW way just checks to see whether the depenmdent var is increasing (note
      # negative hillc) or decreasing (positive hillc) and sets them initially
      # to +/-1.  This could be smarter about how to initialize hillc, but +/-1 seems ok for now
      # DL 2007.09.25
  
      # OLD
      # sizey=size(y);
      # sizex=size(x);
      # if (y(1)-y(sizey))./(x(2)-x(sizex))>0
      #     init_params(4)=(y(1)-y(sizey))./(x(2)-x(sizex));
      # else
      #     init_params(4)=1;
      # end
  
      # I've made this look at the Y response at the minimum and maximum dosage
      # whereas before, it was looking at the Y response at the first and last
      # point which could just happen to be the same.
      min_idx = numpy.argmin(x)
      max_idx = numpy.argmax(x)
      x0 = x[min_idx]
      x1 = x[max_idx]
      y0 = y[min_idx]
      y1 = y[max_idx]
  
      if x0 == x1:
          # If all of the doses are the same, why are we doing this?
          # There's not much point in fitting.
          raise ValueError(
              "All doses or labels for all image sets are %s. Can't calculate dose-response curves."
              % x0
          )
      elif y1 > y0:
          hillc = -1
      else:
          hillc = 1
      return min_0, max_0, ec50, hillc
  
imports: import functools
  import os
  import numpy
  import scipy.optimize
  from cellprofiler_core.constants.measurement import EXPERIMENT
  from cellprofiler_core.constants.measurement import IMAGE
  from cellprofiler_core.constants.measurement import NEIGHBORS
  from cellprofiler_core.constants.module import IO_FOLDER_CHOICE_HELP_TEXT, IO_WITH_METADATA_HELP_TEXT
  from cellprofiler_core.measurement import Measurements
  from cellprofiler_core.module import Module
  from cellprofiler_core.preferences import ABSOLUTE_FOLDER_NAME
  from cellprofiler_core.preferences import DEFAULT_INPUT_FOLDER_NAME
  from cellprofiler_core.preferences import DEFAULT_INPUT_SUBFOLDER_NAME
  from cellprofiler_core.preferences import DEFAULT_OUTPUT_FOLDER_NAME
  from cellprofiler_core.preferences import DEFAULT_OUTPUT_SUBFOLDER_NAME
  from cellprofiler_core.setting import Binary
  from cellprofiler_core.setting import Divider
  from cellprofiler_core.setting import Measurement
  from cellprofiler_core.setting import SettingsGroup
  from cellprofiler_core.setting import ValidationError
  from cellprofiler_core.setting.do_something import DoSomething
  from cellprofiler_core.setting.do_something import RemoveSettingButton
  from cellprofiler_core.setting.text import Directory
  from cellprofiler_core.setting.text import Text
label_desc: Use image node_id 7 for calling a global function with example usage: calc_init_params(x, y) and returns: min_0,  max_0,  ec50,  hillc