Fix up docs

docs/further-background/representations.py

@@ -39,9 +39,7 @@
 import pint
 from IPython.lib.pretty import pretty
 
-from continuous_timeseries.time_axis import TimeAxis
-from continuous_timeseries.timeseries_discrete import TimeseriesDiscrete
-from continuous_timeseries.values_at_bounds import ValuesAtBounds
+import continuous_timeseries as ct
 
 # %% [markdown]
 # ## Set up pint
@@ -54,26 +52,26 @@
 # ## Set up some example objects
 
 # %%
-basic_ts = TimeseriesDiscrete(
+basic_ts = ct.TimeseriesDiscrete(
     name="basic",
-    time_axis=TimeAxis(Q([1750.0, 1850.0, 1950.0], "yr")),
-    values_at_bounds=ValuesAtBounds(Q([1.0, 2.0, 3.0], "m")),
+    time_axis=ct.TimeAxis(Q([1750.0, 1850.0, 1950.0], "yr")),
+    values_at_bounds=ct.ValuesAtBounds(Q([1.0, 2.0, 3.0], "m")),
 )
 basic_ts
 
 # %%
-long_ts = TimeseriesDiscrete(
+long_ts = ct.TimeseriesDiscrete(
     name="basic",
-    time_axis=TimeAxis(Q(np.arange(1850.0, 2300.0, 1), "yr")),
-    values_at_bounds=ValuesAtBounds(Q(np.arange(450.0), "m")),
+    time_axis=ct.TimeAxis(Q(np.arange(1850.0, 2300.0, 1), "yr")),
+    values_at_bounds=ct.ValuesAtBounds(Q(np.arange(450.0), "m")),
 )
 long_ts
 
 # %%
-really_long_ts = TimeseriesDiscrete(
+really_long_ts = ct.TimeseriesDiscrete(
     name="basic",
-    time_axis=TimeAxis(Q(np.arange(1850.0, 2300.0, 1 / 12), "yr")),
-    values_at_bounds=ValuesAtBounds(Q(np.arange(450.0 * 12), "m")),
+    time_axis=ct.TimeAxis(Q(np.arange(1850.0, 2300.0, 1 / 12), "yr")),
+    values_at_bounds=ct.ValuesAtBounds(Q(np.arange(450.0 * 12), "m")),
 )
 really_long_ts
 

docs/further-background/why-this-api.py

@@ -365,14 +365,14 @@
 for label, updated_time_axis, updated_interpolation in (
     ("starting_point", None, None),
     (
-        "same time - piecewise constant previous",
+        "same time - piecewise constant next left-closed",
         ts_varying_step_size.time_axis,
-        ct.InterpolationOption.PiecewiseConstantPreviousLeftClosed,
+        ct.InterpolationOption.PiecewiseConstantNextLeftClosed,
     ),
     (
-        "decadal steps - piecewise constant previous",
+        "decadal steps - piecewise constant next left-closed",
         decadal_steps,
-        ct.InterpolationOption.PiecewiseConstantPreviousLeftClosed,
+        ct.InterpolationOption.PiecewiseConstantNextLeftClosed,
     ),
 ):
     if updated_time_axis is not None:

docs/tutorials/continuous_timeseries_tutorial.py

@@ -32,11 +32,9 @@
 import pint
 import scipy.interpolate
 
+import continuous_timeseries as ct
 from continuous_timeseries.exceptions import ExtrapolationNotAllowedError
-from continuous_timeseries.timeseries_continuous import (
-    ContinuousFunctionScipyPPoly,
-    TimeseriesContinuous,
-)
+from continuous_timeseries.timeseries_continuous import ContinuousFunctionScipyPPoly
 
 # %% [markdown]
 # ## Handy pint aliases
@@ -110,7 +108,7 @@
 # We then create our `TimeseriesContinuous` instance.
 
 # %%
-ts = TimeseriesContinuous(
+ts = ct.TimeseriesContinuous(
     name="piecewise_constant",
     time_units=time_axis.u,
     values_units=values.u,
@@ -143,7 +141,7 @@
 )
 continuous_linear = ContinuousFunctionScipyPPoly(piecewise_polynomial_linear)
 
-ts_linear = TimeseriesContinuous(
+ts_linear = ct.TimeseriesContinuous(
     name="piecewise_linear",
     time_units=time_axis.u,
     values_units=values.u,
@@ -178,7 +176,7 @@
 )
 continuous_quadratic = ContinuousFunctionScipyPPoly(piecewise_polynomial_quadratic)
 
-ts_quadratic = TimeseriesContinuous(
+ts_quadratic = ct.TimeseriesContinuous(
     name="piecewise_quadratic",
     time_units=time_axis.u,
     values_units=values.u,
@@ -215,7 +213,7 @@
 )
 continuous_quadratic = ContinuousFunctionScipyPPoly(piecewise_polynomial_quadratic)
 
-ts_cubic = TimeseriesContinuous(
+ts_cubic = ct.TimeseriesContinuous(
     name="piecewise_cubic",
     time_units=time_axis.u,
     values_units=values.u,

docs/tutorials/discrete_timeseries_tutorial.py

@@ -30,9 +30,7 @@
 import matplotlib.units
 import pint
 
-from continuous_timeseries.time_axis import TimeAxis
-from continuous_timeseries.timeseries_discrete import TimeseriesDiscrete
-from continuous_timeseries.values_at_bounds import ValuesAtBounds
+import continuous_timeseries as ct
 
 # %% [markdown]
 # ## Handy pint aliases
@@ -55,7 +53,7 @@
 # the third from `bounds[2]`, to `bounds[3]` etc.
 
 # %%
-time_axis = TimeAxis(
+time_axis = ct.TimeAxis(
     Q([1900.0, 1950.0, 1975.0, 2000.0, 2010.0, 2020.0, 2030.0, 2050.0], "yr")
 )
 time_axis
@@ -67,7 +65,7 @@
 # These must represent the values at each bound (i.e. value) in `time_axis`.
 
 # %%
-values_at_bounds = ValuesAtBounds(
+values_at_bounds = ct.ValuesAtBounds(
     Q([2.3, 4.5, 6.4, 10.0, 11.0, 12.3, 10.2, 3.5], "Gt / yr")
 )
 values_at_bounds
@@ -79,7 +77,7 @@
 # and initialise our instance.
 
 # %%
-ts = TimeseriesDiscrete(
+ts = ct.TimeseriesDiscrete(
     name="example",
     time_axis=time_axis,
     values_at_bounds=values_at_bounds,
@@ -134,15 +132,15 @@
 # will automatically be plotted with the same units.
 
 # %%
-ts_compatible_unit = TimeseriesDiscrete(
+ts_compatible_unit = ct.TimeseriesDiscrete(
     name="example_compatible_unit",
-    time_axis=TimeAxis(
+    time_axis=ct.TimeAxis(
         Q(
             [(1932 + 6) * 12.0, 2000 * 12.0, (2010 + 5) * 12.0, (2025 + 3) * 12.0],
             "month",
         )
     ),
-    values_at_bounds=ValuesAtBounds(Q([140.0, 160.0, 120.0, -10.0], "Mt / month")),
+    values_at_bounds=ct.ValuesAtBounds(Q([140.0, 160.0, 120.0, -10.0], "Mt / month")),
 )
 
 ax = ts.plot()
@@ -177,15 +175,15 @@
 # Instead, you will get an error.
 
 # %%
-ts_incompatible_unit = TimeseriesDiscrete(
+ts_incompatible_unit = ct.TimeseriesDiscrete(
     name="example_incompatible_unit",
-    time_axis=TimeAxis(
+    time_axis=ct.TimeAxis(
         Q(
             [(1932 + 6) * 12.0, 2000 * 12.0, (2010 + 5) * 12.0, (2025 + 3) * 12.0],
             "month",
         )
     ),
-    values_at_bounds=ValuesAtBounds(Q([10.0, 20.0, 30.0, 40.0], "Mt")),
+    values_at_bounds=ct.ValuesAtBounds(Q([10.0, 20.0, 30.0, 40.0], "Mt")),
 )
 
 ax = ts.plot()

docs/tutorials/timeseries_tutorial.py

@@ -378,7 +378,7 @@
     integral_preserving_demo_annual_time_axis
 )
 annual_average = ts_linear_annual_to_show.update_interpolation_integral_preserving(
-    interpolation=ct.InterpolationOption.PiecewiseConstantPreviousLeftClosed,
+    interpolation=ct.InterpolationOption.PiecewiseConstantNextLeftClosed,
     name_res="annual_average",
 )
 
@@ -404,7 +404,7 @@
 decadal_average = ts_integral_preserving_demo_start.interpolate(
     Q(np.hstack([[2025, 2040], np.arange(2060, 2100 + 1, 20)]), "yr"),
 ).update_interpolation_integral_preserving(
-    interpolation=ct.InterpolationOption.PiecewiseConstantPreviousLeftClosed,
+    interpolation=ct.InterpolationOption.PiecewiseConstantNextLeftClosed,
     name_res="custom_average",
 )
 
@@ -523,12 +523,12 @@
     ),
     show_discrete=True,
     discrete_plot_kwargs=dict(
-        alpha=0.3,
+        alpha=0.7,
+        zorder=3,
         marker="x",
         s=150,
         color="tab:blue",
         label="demo_continuous_and_discrete",
-        zorder=3,
     ),
 )