Doc fixes

docs/source/users/demography/canopy.md

@@ -139,7 +139,7 @@ should equal the whole canopy $f_{abs}$ calculated using the simple Beer-Lambert
 equation and the PFT trait values.
 
 ```{code-cell} ipython3
-print(simple_canopy.extinction_profile[-1])
+print(simple_canopy.community_data.extinction_profile[-1])
 ```
 
 ```{code-cell} ipython3
@@ -182,15 +182,15 @@ ax1.set_xlabel("Profile radius (m)")
 ax1.set_ylabel("Vertical height (m)")
 
 # Plot the leaf area between heights for stems
-ax2.plot(simple_canopy.stem_leaf_area, hghts, color="red")
+ax2.plot(simple_canopy.cohort_data.stem_leaf_area, hghts, color="red")
 ax2.set_xlabel("Leaf area (m2)")
 
 # Plot the fraction of light absorbed at different heights
-ax3.plot(simple_canopy.f_abs, hghts, color="red")
+ax3.plot(simple_canopy.cohort_data.f_abs, hghts, color="red")
 ax3.set_xlabel("Light absorption fraction (-)")
 
 # Plot the light extinction profile through the canopy.
-ax4.plot(simple_canopy.extinction_profile, hghts, color="red")
+ax4.plot(simple_canopy.community_data.extinction_profile, hghts, color="red")
 ax4.set_xlabel("Cumulative light\nabsorption fraction (-)")
 ```
 
@@ -312,7 +312,7 @@ print(1 - np.exp(np.sum(-community.stem_traits.par_ext * cohort_lai)))
 ```
 
 ```{code-cell} ipython3
-print(canopy.extinction_profile[-1])
+print(canopy.community_data.extinction_profile[-1])
 ```
 
 ```{code-cell} ipython3
@@ -349,16 +349,16 @@ ax1.set_xlabel("Profile radius (m)")
 ax1.set_ylabel("Vertical height (m)")
 
 # Plot the leaf area between heights for stems
-ax2.plot(canopy.stem_leaf_area, hghts)
+ax2.plot(canopy.cohort_data.stem_leaf_area, hghts)
 ax2.set_xlabel("Leaf area per stem (m2)")
 
 # Plot the fraction of light absorbed at different heights
-ax3.plot(canopy.f_abs, hghts, color="grey")
-ax3.plot(1 - canopy.cohort_f_trans, hghts)
+ax3.plot(canopy.cohort_data.f_abs, hghts, color="grey")
+ax3.plot(1 - canopy.cohort_data.f_trans, hghts)
 ax3.set_xlabel("Light absorption fraction (-)")
 
 # Plot the light extinction profile through the canopy.
-ax4.plot(canopy.extinction_profile, hghts, color="grey")
+ax4.plot(canopy.community_data.extinction_profile, hghts, color="grey")
 _ = ax4.set_xlabel("Cumulative light\nabsorption fraction (-)")
 ```
 
@@ -416,7 +416,7 @@ l_m = \left\lceil \frac{\sum_1^{N_s}{A_c}}{ A(1 - f_G)}\right\rceil
 $$
 
 ```{code-cell} ipython3
-canopy_ppa = Canopy(community=community, canopy_gap_fraction=2 / 32, fit_ppa=True)
+canopy_ppa = Canopy(community=community, canopy_gap_fraction=0 / 32, fit_ppa=True)
 ```
 
 The `canopy_ppa.heights` attribute now contains the heights at which the PPA
@@ -430,7 +430,7 @@ And the final value in the canopy extinction profile still matches the expectati
 above:
 
 ```{code-cell} ipython3
-print(canopy_ppa.extinction_profile[-1])
+print(canopy_ppa.community_data.extinction_profile[-1])
 ```
 
 ### Visualizing layer closure heights and areas
@@ -503,18 +503,18 @@ ax1.legend(frameon=False)
 for val in canopy_ppa.heights:
     ax2.axhline(val, color="red", linewidth=0.5, zorder=0)
 
-for val in canopy_ppa.extinction_profile:
+for val in canopy_ppa.community_data.extinction_profile:
     ax2.axvline(val, color="red", linewidth=0.5, zorder=0)
 
-ax2.plot(canopy.extinction_profile, hghts)
+ax2.plot(canopy.community_data.extinction_profile, hghts)
 
 ax2_top = ax2.twiny()
 ax2_top.set_xlim(ax2.get_xlim())
 extinction_labels = [
     f"$f_{{abs{l + 1}}}$ = {z:.3f}"
-    for l, z in enumerate(np.nditer(canopy_ppa.extinction_profile))
+    for l, z in enumerate(np.nditer(canopy_ppa.community_data.extinction_profile))
 ]
-ax2_top.set_xticks(canopy_ppa.extinction_profile)
+ax2_top.set_xticks(canopy_ppa.community_data.extinction_profile)
 ax2_top.set_xticklabels(extinction_labels, rotation=90)
 
 ax2.set_xlabel("Light extinction (-)")
@@ -548,11 +548,11 @@ The steps below show this partitioning process for the PPA layers calculated abo
 
 ```{code-cell} ipython3
 print("k = \n", community.stem_traits.par_ext, "\n")
-print("L_H = \n", canopy_ppa.cohort_lai)
+print("L_H = \n", canopy_ppa.cohort_data.lai)
 ```
 
 ```{code-cell} ipython3
-layer_cohort_f_tr = np.exp(-community.stem_traits.par_ext * canopy_ppa.cohort_lai)
+layer_cohort_f_tr = np.exp(-community.stem_traits.par_ext * canopy_ppa.cohort_data.lai)
 print(layer_cohort_f_tr)
 ```
 

docs/source/users/demography/crown.md

@@ -532,7 +532,3 @@ plt.legend(
     bbox_to_anchor=(0.5, 1.15),
 )
 ```
-
-```{code-cell} ipython3
-
-```