gridspec_kw={'height_ratios': height_ratio},
figsize=(12, 5))
plt.subplots_adjust(hspace=.2, left=None, bottom=None, right=None, top=None)
indices = [3, 2]
rescaled = temperatures_spatial_demeaned.copy()
rescaled[:, indices] = rescaled[:, indices] + np.linspace(
-1,
len(indices) - 1, len(indices)) * 2.5
fig_1 = EvT.plot_raw_TS(
rescaled,
indices=indices,
start_plot=1880,
stop_plot=2010,
xlab=None,
ylab="°C",
ylab_fontsize=17,
yticks_fontsize=15,
ylabel_coords=ylabel_coords,
custom_colors_series=["black"] *
6, #["black","lightgray", "darkgray", "dimgray", "black"]*len(indices))
ax=ax_array[0])
period_time_list = [[1880, 1914], [1950, 1973], [1987, 2010]]
label_list = ["1", "2", "3"]
fig_2 = EvT.plot_model_posterior(
indices=mods, #mods, #mods, #relevant_models,
plot_type="MAP",
y_axis_labels=[ #"AR(1)",
"M(5+)", "M(6)", "M(6+)", "M(7)", "M(7+)"
fig, ax_array = plt.subplots(2,
figsize=(8, 5),
sharex=True,
gridspec_kw={'height_ratios': height_ratio})
plt.subplots_adjust(hspace=.35, left=None, bottom=None, right=None, top=None)
ylabel_coords = [-0.065, 0.5]
#Plot of raw Time Series
EvT.plot_raw_TS(
data.reshape(T, S1, S2),
indices=[0, 1],
xlab=None,
show_MAP_CPs=True,
time_range=np.linspace(1, T, T, dtype=int),
print_plt=False,
ylab="value",
ax=ax_array[0],
#all_dates = np.linspace(622 + 1, 1284, 1284 - (622 + 1), dtype = int),
custom_colors_series=["black"] * 4,
custom_colors_CPs=["blue", "blue"] * 100,
custom_linestyles=["solid"] * 100,
ylab_fontsize=14,
ylabel_coords=ylabel_coords)
#Run length distribution plot
EvT.plot_run_length_distr(
buffer=0,
show_MAP_CPs=False,
mark_median=False,
mark_max=True,
upper_limit=1000,
ax_arrays = np.array([np.array([ax1, ax2]), np.array([ax3, ax4])])
plt.subplots_adjust(hspace = .05, wspace = .05, left = None, bottom = None,
right = None, top = None)
ylabel_coords = [-0.15, 0.5]
#for (ax_array, EvT) in zip(ax_arrays, (EvTKL, EvTDPD)):
#Plot of raw Time Series
EvTKL.plot_raw_TS(data.reshape(T,1), indices = [0],
xlab = None,
show_MAP_CPs = True,
time_range = np.linspace(1,T, T, dtype=int),
print_plt = False,
ylab = "Nuclear Response",
ax = ax_arrays[0][0],
#all_dates = np.linspace(622 + 1, 1284, 1284 - (622 + 1), dtype = int),
custom_colors_series = ["black"],
custom_colors_CPs = ["blue", "blue"]* 100,
custom_linestyles = [":"]*100,
custom_linewidth = 1.5,
ylab_fontsize = 12,
ylabel_coords = ylabel_coords)
EvTDPD.plot_raw_TS(data.reshape(T,1), indices = [0],
xlab = "Time",
show_MAP_CPs = True,
time_range = np.linspace(1,T, T, dtype=int),
print_plt = False,
ylab = "",
ax = ax_arrays[0][1],
#all_dates = np.linspace(622 + 1, 1284, 1284 - (622 + 1), dtype = int),
#INSERT THE ADDITIONAL CPs KL DECLARES AS VERTICAL LINES
#Plot of raw Time Series
if singlePlot:
EvTKL.plot_raw_TS(
data.reshape(T, S1, S2),
indices=[0, 1, 2, 3, 4],
show_MAP_CPs=True,
time_range=np.linspace(1, T, T, dtype=int),
print_plt=False,
ylab="",
xlab="Time",
ax=ax, #ax_array[0],
#all_dates = np.linspace(622 + 1, 1284, 1284 - (622 + 1), dtype = int),
custom_colors_series=["black"] * 5,
custom_colors_CPs=["red"] * 100,
custom_linestyles=[":"] * 100,
custom_linewidth=2,
ylab_fontsize=14,
xlab_fontsize=14,
ylabel_coords=ylabel_coords,
additional_CPs=EvTDPD.results[EvTDPD.names.index("MAP CPs")][-2],
custom_colors_additional_CPs=["blue"] * 100,
custom_linewidth_additional_CPs=5.0,
custom_linestyles_additional_CPs=["-"] * 10)
fig.savefig(result_path + "5SeriesRes_solidline.pdf",
format="pdf",
dpi=800)
elif doublePlot:
num_subplots = 6
"""set ylabel position"""
#paper: ylabel_coords = [-0.09, 0.5] poster: ylabel_coords = [-0.045, 0.5]
ylabel_coords = [-0.09, 0.5]
yticks_fontsize = 10
#paper: figsize argument left out poster: figsize = (12,5)
fig, ax_array = plt.subplots(num_subplots, sharex = True,
gridspec_kw = {'height_ratios':height_ratio})#,
#figsize = (12,5))
plt.subplots_adjust(hspace = .185, left = None, bottom = None, right = None, top = None)
"""plot raw data"""
fig_1 = EvT.plot_raw_TS(data, indices=[0,2,4],
custom_colors_series = custom_colors_series,
ax = ax_array[0],xlab=None,
ylabel_coords = ylabel_coords) #ax_array[0])
"""Plot + save pics (4) prediction + error"""
fig_2 = EvT.plot_prediction_error(show_var= True, data = data_original,
indices = [0],
custom_colors = ['black', 'darkgray'],
ax=ax_array[1],
time_range = np.linspace(1,T-2,T-2,dtype=int),
aspect_ratio = 'auto', xlab = None, ylab = "PE",
ylabel_coords = ylabel_coords)
"""Plot + save pictures: (3) model posteriors"""
"""Plot + save pictures: (2) Raw TS with MAP CPs"""
#backconverter = tick/C2-C1 (backconv+C1)*C2 = tick
C1, C2 = 100, 1
figsize=(8, 5),
sharex=True,
gridspec_kw={'height_ratios': height_ratio})
plt.subplots_adjust(hspace=.35, left=None, bottom=None, right=None, top=None)
ylabel_coords = [-0.065, 0.5]
#Plot of raw Time Series
EvT.plot_raw_TS(river_height[2:].reshape(T - 2, 1),
indices=[0],
xlab=None,
show_MAP_CPs=True,
time_range=np.linspace(1, T - 2, T - 2, dtype=int),
print_plt=False,
ylab="River Height",
ax=ax_array[0],
all_dates=np.linspace(622 + 1,
1284,
1284 - (622 + 1),
dtype=int),
custom_colors_series=["black"],
custom_colors_CPs=["blue", "blue"] * 10,
custom_linestyles=["solid"] * 10,
ylab_fontsize=14,
ylabel_coords=ylabel_coords)
#Run length distribution plot
EvT.plot_run_length_distr(buffer=0,
show_MAP_CPs=True,
mark_median=False,
mark_max=True,
upper_limit=660,
fig, ax_array = plt.subplots(num_subplots,
sharex=True,
gridspec_kw={'height_ratios': height_ratio},
figsize=(8, 5))
plt.subplots_adjust(hspace=.2, left=None, bottom=None, right=None, top=None)
off = 5
time_range = np.linspace(10, T - 2, T - 2 - off, dtype=int)
all_dates = all_dates[-len(time_range):]
fig_1 = EvT.plot_raw_TS(data[-len(time_range):, :].reshape(
len(time_range), 29),
all_dates=all_dates,
ax=ax_array[0],
time_range=time_range,
custom_colors_series=["black"] * 10,
ylab_fontsize=14,
yticks_fontsize=14,
ylab="NOX",
xlab=None,
ylabel_coords=ylabel_coords,
true_CPs=true_CPs)
mod = [17, 21]
EvT.plot_model_posterior(
indices=mod, #mods, #mods, #relevant_models,
plot_type="trace", #"MAPVariance1_trace",
#y_axis_labels = [str(e) for e in all_models],#[#"AR(1)",
#"M(5+)", "M(6)",
# "M(6+)",
# "M(7)", "M(7+)"],#relevant_models],
time_range=time_range,
# Prepare the axes
fig, ax_array = plt.subplots(2, figsize=(8, 5), sharex=True,
gridspec_kw={'height_ratios': [10, 14]})
plt.subplots_adjust(hspace=.35, left=None, bottom=None, right=None, top=None)
# Placement of y-labels
ylabel_coords = [-0.065, 0.5]
# Upper panel: plot the time-series
EvT.plot_raw_TS(river_height[2:].reshape(T-2, 1),
indices=[0],
xlab=None,
show_MAP_CPs=True,
time_range=np.linspace(1, T-2, T-2, dtype=int),
print_plt=False,
ylab="River Height", ax=ax_array[0],
all_dates=np.linspace(int(dates[1]), int(dates[-2]), T-2, dtype=int),
custom_colors_series=["black"],
custom_colors_CPs=["blue", "blue"],
custom_linestyles=["solid"] * 2,
ylab_fontsize=14,
ylabel_coords=ylabel_coords,
set_ylims=(-2.75, 3.95))
# Lower panel: plot the run length distribution
EvT.plot_run_length_distr(buffer=0,
show_MAP_CPs=True,
mark_median=False,
mark_max=True,
upper_limit=660,
print_colorbar=True,
colorbar_location='bottom',
S1=S1,
S2=S2,
T=T,
store_rl=True,
store_mrl=True,
trim_type="keep_K",
threshold=200,
training_period=25, #i.e., we let 2 years pass before MSE computed
notifications=1500,
save_performance_indicators=True)
detector.run()
"""Store results + real CPs into EvaluationTool obj"""
EvT = EvaluationTool()
EvT.build_EvaluationTool_via_run_detector(detector)
"""plot transformed data"""
fig = EvT.plot_raw_TS(data.reshape(T, 1))
"""plot prediction error"""
fig = EvT.plot_prediction_error(data,
indices=[0],
print_plt=True,
time_range=np.linspace(2 * 365,
T - upper_AR - 1,
T - upper_AR - 1 -
2 * 365,
dtype=int))
"""plot predictions themselves"""
fig = EvT.plot_predictions(indices=[0],
print_plt=True,
legend=False,
legend_labels=None,
legend_position=None,
fig.subplots_adjust(hspace = .05,
left = None, bottom = None,
right = None, top = None)
ylabel_coords = [0.0, 0.25]
EvTDPD.plot_raw_TS(data.reshape(T,S1*S2), indices = [0], xlab = None,
show_MAP_CPs = True,
time_range = np.linspace(1,T, T, dtype=int),
print_plt = False,
ylab = "Response",
ax = ax_array[0],
custom_colors_series = ["black"]*5,
custom_colors_CPs = [DPD_CP_color]* 100,
custom_linestyles = [CP_style_DPD]*100,
custom_linewidth = CP_linewidth_DPD,
custom_transparency = CP_transparence_DPD,
ylab_fontsize = ylabsize,
yticks_fontsize = ticksize,
ylabel_coords = [-0.06,0.5],
additional_CPs = additional_CPs,
custom_colors_additional_CPs = [KL_CP_color] * 100,
custom_linewidth_additional_CPs = CP_linewidth_KL,
custom_linestyles_additional_CPs = [CP_style_KL] * 10,
custom_transparency_additional_CPs = CP_transparence_KL)
EvTDPD.plot_run_length_distr(buffer=0, show_MAP_CPs = show_CPs_in_rld,
mark_median = False,
mark_max = True,
upper_limit = 1300,