Move sphinx_design to docdeps (#992)

* move sphinx_design to docdeps

Signed-off-by: Chris Trevino <chtrevin@microsoft.com>

* changed np.float to float as recommended by numpy 1.24 (throws an error otherwise)

Signed-off-by: Amit Sharma <amit_sharma@live.com>

---------

Signed-off-by: Chris Trevino <chtrevin@microsoft.com>
Signed-off-by: Amit Sharma <amit_sharma@live.com>
Co-authored-by: Amit Sharma <amit_sharma@live.com>

dowhy/gcm/shapley.py

@@ -522,7 +522,7 @@ def _create_subsets_and_weights_exact(num_players: int, high_weight: float) -> T
                 scipy.special.binom(num_players, subset_size) * subset_size * (num_players - subset_size)
             )
 
-    return np.array(all_subsets, dtype=np.int32), weights.astype(np.float)
+    return np.array(all_subsets, dtype=np.int32), weights.astype(float)
 
 
 def _create_subsets_and_weights_approximation(
@@ -562,7 +562,7 @@ def _create_subsets_and_weights_approximation(
 
     weights = np.array([weights[tuple(x)] for x in all_subsets])
 
-    return np.array(all_subsets, dtype=np.int32), weights.astype(np.float)
+    return np.array(all_subsets, dtype=np.int32), weights.astype(float)
 
 
 def _convert_list_of_indices_to_binary_vector_as_tuple(list_of_indices: List[int], num_players: int) -> Tuple[int]:

pyproject.toml

@@ -69,7 +69,6 @@ causal-learn = ">=0.1.3.0"
 
 #Plotting Extra
 matplotlib = { version = ">=3.5.3", optional = true }
-sphinx_design = "^0.3.0"
 cvxpy = "^1.2.2"
 
 [tool.poetry.extras]
@@ -109,6 +108,8 @@ optional = true
 #
 # Dependencies for Documentation Generation
 #
+
+sphinx_design = "^0.3.0"
 sphinx = "^5.3.0"
 sphinxcontrib-googleanalytics = { git = "https://github.com/sphinx-contrib/googleanalytics.git", branch = "master" }
 nbsphinx = "^0.8.9"