Configuration files

The configuration files copied to the project directory from smartmove/_templates are used for configuration of ___

Project configuration

# Datalogger calibration directories
cal:
  # Contains acceleration calibration YAMLs for associated tag ID
  # Sensors should be calibrated per month--closest calibration used for analysis
  w190pd3gt:
    34839:
      2015:
        03: 20150306_W190PD3GT_34839_Notag_Control

    34840:
      2016:
        04: 20160418_W190PD3GT_34840_Skinny_2Neutral

# Parameters for field experiment
experiment:
  # 69° 41′ 57.9″ North, 18° 39′ 4.5″ East
  coords:
    lon: 18.65125
    lat: 69.69942
  net_depth: 18 #meters
  fname_ctd: 'kaldfjorden2016_inner.mat'

Glide analysis

# Number of samples per frequency segment in PSD calculation
nperseg: 256

# Threshold above which to find peaks in PSD
peak_thresh: 0.10

# High/low pass cutoff frequency, determined from PSD plot
cutoff_frq: None

# Frequency of stroking, determinded from PSD plot
stroke_frq: 0.4 # Hz

# fraction of `stroke_frq` to calculate cutoff frequency (Wn)
stroke_ratio: 0.4

# Maximum length of stroke signal
# 1/stroke_freq
t_max: 2.5 # seconds

# Minimumn frequency for identifying strokes
# 2 / (180*numpy.pi) (Hz)
J: 0.0349

# For magnetic pry routine
alpha: 25

# Minimum depth at which to recognize a dive
min_depth: 0.4

Sub-glide filtering

# Pitch angle (degrees) to consider sgls
pitch_thresh: 30

# Minimum depth at which to recognize a dive (2. Define dives)
min_depth: 0.4

# Maximum cummulative change in depth over a glide
max_depth_delta: 8.0

# Minimum mean speed of sublide
min_speed: 0.3

# Maximum mean speed of sublide
max_speed: 10

# Maximum cummulative change in speed over a glide
max_speed_delta: 1.0

Artificial Neural network

# Parameters for compiling data
data:
    sgl_cols:
        - 'exp_id'
    glides:
      cutoff_frq: 0.3
      J: 0.05
    sgls:
      dur: 2
    filter:
      pitch_thresh: 30
      max_depth_delta: 8.0
      min_speed: 0.3
      max_speed: 10
      max_speed_delta: 1.0

# Data and network config common to all structures
net_all:
    features:
        - 'abs_depth_change'
        - 'dive_phase_int'
        - 'mean_a'
        - 'mean_depth'
        - 'mean_pitch'
        - 'mean_speed'
        - 'mean_swdensity'
        - 'total_depth_change'
        - 'total_speed_change'
    target: 'rho_mod'
    valid_frac: 0.6
    n_targets:  10

# Network tuning parameters, all permutations of these will be trained/validated
net_tuning:
    # Number of nodes in each hidden layer
    hidden_nodes:
        - 10
        - 20
        - 40
        - 60
        - 100
        - 500
    # Number of hidden layers
    hidden_layers:
        - 1
        - 2
        - 3
    # Trainers (optimizers)
    # https://theanets.readthedocs.io/en/stable/api/trainers.html
    # http://sebastianruder.com/optimizing-gradient-descent/
    algorithm:
        - adadelta
        - rmsprop
    hidden_l1:
        - 0.1
        - 0.001
        - 0.0001
    weight_l2:
        - 0.1
        - 0.001
        - 0.0001
    momentum:
        - 0.9
    patience:
        - 10
    min_improvement:
        - 0.999
    validate_every:
        - 10
    learning_rate:
        - 0.0001