miller/test/input/window2.mlr

# ================================================================
# Sliding average with window over m previous rows, current row, and
# n subsequent rows.
# ================================================================

begin {
  # Input parameters
  # They can do 'mlr put -s input_field_names=x,y ...'
  @window_size_backward ??= 3;
  @window_size_forward ??= 3;
  @input_field_names ??= "x,y";
  @input_field_names = splitnv(@input_field_names, ",");

  # Initialization
  @window_size = @window_size_backward + 1 + @window_size_forward;
  @center_record_index = @window_size_backward; # index 0-up
  @output_field_names = apply(@input_field_names, func(k,v) { return {v: v . "_avg"}});
  @window_records = {};
  # dump;
}

# Slide the windows, then update them with new data
for (i = 1; i < @window_size; i+=1) {
  @window_records[i-1] = @window_records[i]
}
@window_records[@window_size-1] = $*;

# Compute the averages

denominator = @window_size;
if (NR < @window_size) {
    denominator = NR
}

sums = {};
for (_, name in @input_field_names) {
  sums[name] = 0.0;
  for (i = 0; i < denominator; i+=1) {
    # Windows are filled in from the end, not the beginning, so index backward
    int j = @window_size - 1 - i;
    sums[name] += float(@window_records[j][name]);
  }
}

# Emit the record from the window center, with averages attached to it
if (NR > @center_record_index) {
  output_record = @window_records[@center_record_index];
  for (_, name in @input_field_names) {
    output_record[@output_field_names[name]] = sums[name] / denominator;
  }
  emit output_record
}