Module: Prophet::Plot

Included in:
Forecaster
Defined in:
lib/prophet/plot.rb

Class Method Summary collapse

Instance Method Summary collapse

Class Method Details

.plot_cross_validation_metric(df_cv, metric:, rolling_window: 0.1, ax: nil, figsize: [10, 6], color: "b", point_color: "gray") ⇒ Object 



114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
 
# File 'lib/prophet/plot.rb', line 114

def self.plot_cross_validation_metric(df_cv, metric:, rolling_window: 0.1, ax: nil, figsize: [10, 6], color: "b", point_color: "gray")
  if ax.nil?
    fig = plt.figure(facecolor: "w", figsize: figsize)
    ax = fig.add_subplot(111)
  else
    fig = ax.get_figure
  end
  # Get the metric at the level of individual predictions, and with the rolling window.
  df_none = Diagnostics.performance_metrics(df_cv, metrics: [metric], rolling_window: -1)
  df_h = Diagnostics.performance_metrics(df_cv, metrics: [metric], rolling_window: rolling_window)

  # Some work because matplotlib does not handle timedelta
  # Target ~10 ticks.
  tick_w = df_none["horizon"].max * 1e9 / 10.0
  # Find the largest time resolution that has <1 unit per bin.
  dts = ["D", "h", "m", "s", "ms", "us", "ns"]
  dt_names = ["days", "hours", "minutes", "seconds", "milliseconds", "microseconds", "nanoseconds"]
  dt_conversions = [
    24 * 60 * 60 * 10 ** 9,
    60 * 60 * 10 ** 9,
    60 * 10 ** 9,
    10 ** 9,
    10 ** 6,
    10 ** 3,
    1.0
  ]
  # TODO update
  i = 0
  # dts.each_with_index do |dt, i|
  #   if np.timedelta64(1, dt) < np.timedelta64(tick_w, "ns")
  #     break
  #   end
  # end

  x_plt = df_none["horizon"] * 1e9 / dt_conversions[i].to_f
  x_plt_h = df_h["horizon"] * 1e9 / dt_conversions[i].to_f

  ax.plot(x_plt.to_a, df_none[metric].to_a, ".", alpha: 0.1, c: point_color)
  ax.plot(x_plt_h.to_a, df_h[metric].to_a, "-", c: color)
  ax.grid(true)

  ax.set_xlabel("Horizon (#{dt_names[i]})")
  ax.set_ylabel(metric)
  fig
end

.plt ⇒ Object 



160
161
162
163
164
165
166
167
 
# File 'lib/prophet/plot.rb', line 160

def self.plt
  begin
    require "matplotlib/pyplot"
  rescue LoadError
    raise Error, "Install the matplotlib gem for plots"
  end
  Matplotlib::Pyplot
end

Instance Method Details

#add_changepoints_to_plot(ax, fcst, threshold: 0.01, cp_color: "r", cp_linestyle: "--", trend: true) ⇒ Object

in Python, this is a separate method



97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
 
# File 'lib/prophet/plot.rb', line 97

def add_changepoints_to_plot(ax, fcst, threshold: 0.01, cp_color: "r", cp_linestyle: "--", trend: true)
  artists = []
  if trend
    artists << ax.plot(to_pydatetime(fcst["ds"]), fcst["trend"].to_a, c: cp_color)
  end
  signif_changepoints =
    if @changepoints.size > 0
      (@params["delta"].mean(axis: 0, nan: true).abs >= threshold).mask(@changepoints.to_numo)
    else
      []
    end
  to_pydatetime(signif_changepoints).each do |cp|
    artists << ax.axvline(x: cp, c: cp_color, ls: cp_linestyle)
  end
  artists
end

#plot(fcst, ax: nil, uncertainty: true, plot_cap: true, xlabel: "ds", ylabel: "y", figsize: [10, 6]) ⇒ Object 



3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
 
# File 'lib/prophet/plot.rb', line 3

def plot(fcst, ax: nil, uncertainty: true, plot_cap: true, xlabel: "ds", ylabel: "y", figsize: [10, 6])
  if ax.nil?
    fig = plt.figure(facecolor: "w", figsize: figsize)
    ax = fig.add_subplot(111)
  else
    fig = ax.get_figure
  end
  fcst_t = to_pydatetime(fcst["ds"])
  ax.plot(to_pydatetime(@history["ds"]), @history["y"].to_a, "k.")
  ax.plot(fcst_t, fcst["yhat"].to_a, ls: "-", c: "#0072B2")
  if fcst.include?("cap") && plot_cap
    ax.plot(fcst_t, fcst["cap"].to_a, ls: "--", c: "k")
  end
  if @logistic_floor && fcst.include?("floor") && plot_cap
    ax.plot(fcst_t, fcst["floor"].to_a, ls: "--", c: "k")
  end
  if uncertainty && @uncertainty_samples
    ax.fill_between(fcst_t, fcst["yhat_lower"].to_a, fcst["yhat_upper"].to_a, color: "#0072B2", alpha: 0.2)
  end
  # Specify formatting to workaround matplotlib issue #12925
  locator = dates.AutoDateLocator.new(interval_multiples: false)
  formatter = dates.AutoDateFormatter.new(locator)
  ax.xaxis.set_major_locator(locator)
  ax.xaxis.set_major_formatter(formatter)
  ax.grid(true, which: "major", c: "gray", ls: "-", lw: 1, alpha: 0.2)
  ax.set_xlabel(xlabel)
  ax.set_ylabel(ylabel)
  fig.tight_layout
  fig
end

#plot_components(fcst, uncertainty: true, plot_cap: true, weekly_start: 0, yearly_start: 0, figsize: nil) ⇒ Object 



34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
 
# File 'lib/prophet/plot.rb', line 34

def plot_components(fcst, uncertainty: true, plot_cap: true, weekly_start: 0, yearly_start: 0, figsize: nil)
  components = ["trend"]
  if @train_holiday_names && fcst.include?("holidays")
    components << "holidays"
  end
  # Plot weekly seasonality, if present
  if @seasonalities["weekly"] && fcst.include?("weekly")
    components << "weekly"
  end
  # Yearly if present
  if @seasonalities["yearly"] && fcst.include?("yearly")
    components << "yearly"
  end
  # Other seasonalities
  components.concat(@seasonalities.keys.select { |name| fcst.include?(name) && !["weekly", "yearly"].include?(name) }.sort)
  regressors = {"additive" => false, "multiplicative" => false}
  @extra_regressors.each do |name, props|
    regressors[props[:mode]] = true
  end
  ["additive", "multiplicative"].each do |mode|
    if regressors[mode] && fcst.include?("extra_regressors_#{mode}")
      components << "extra_regressors_#{mode}"
    end
  end
  npanel = components.size

  figsize = figsize || [9, 3 * npanel]
  fig, axes = plt.subplots(npanel, 1, facecolor: "w", figsize: figsize)

  if npanel == 1
    axes = [axes]
  end

  multiplicative_axes = []

  axes.tolist.zip(components) do |ax, plot_name|
    if plot_name == "trend"
      plot_forecast_component(fcst, "trend", ax: ax, uncertainty: uncertainty, plot_cap: plot_cap)
    elsif @seasonalities[plot_name]
      if plot_name == "weekly" || @seasonalities[plot_name][:period] == 7
        plot_weekly(name: plot_name, ax: ax, uncertainty: uncertainty, weekly_start: weekly_start)
      elsif plot_name == "yearly" || @seasonalities[plot_name][:period] == 365.25
        plot_yearly(name: plot_name, ax: ax, uncertainty: uncertainty, yearly_start: yearly_start)
      else
        plot_seasonality(name: plot_name, ax: ax, uncertainty: uncertainty)
      end
    elsif ["holidays", "extra_regressors_additive", "extra_regressors_multiplicative"].include?(plot_name)
      plot_forecast_component(fcst, plot_name, ax: ax, uncertainty: uncertainty, plot_cap: false)
    end
    if @component_modes["multiplicative"].include?(plot_name)
      multiplicative_axes << ax
    end
  end

  fig.tight_layout
  # Reset multiplicative axes labels after tight_layout adjustment
  multiplicative_axes.each do |ax|
    ax = set_y_as_percent(ax)
  end
  fig
end