gen sqd 0.9.0

Author: arnaucasau

docs/api/qiskit-addon-sqd/_package.json

@@ -1,4 +1,4 @@
 {
   "name": "qiskit-addon-sqd",
-  "version": "0.8.1"
+  "version": "0.9.0"
 }

docs/api/qiskit-addon-sqd/configuration-recovery.mdx

@@ -18,12 +18,12 @@ Functions for performing self-consistent configuration recovery.
 
 ### post\_select\_by\_hamming\_weight
 
-<Function id="qiskit_addon_sqd.configuration_recovery.post_select_by_hamming_weight" github="https://github.com/Qiskit/qiskit-addon-sqd/tree/stable/0.8/qiskit_addon_sqd/configuration_recovery.py#L24-L48" signature="post_select_by_hamming_weight(bitstring_matrix, *, hamming_right, hamming_left)">
+<Function id="qiskit_addon_sqd.configuration_recovery.post_select_by_hamming_weight" github="https://github.com/Qiskit/qiskit-addon-sqd/tree/stable/0.9/qiskit_addon_sqd/configuration_recovery.py#L24-L48" signature="post_select_by_hamming_weight(bitstring_matrix, *, hamming_right, hamming_left)">
   Post-select bitstrings based on the hamming weight of each half.
 
   **Parameters**
 
-  *   **bitstring\_matrix** ([*ndarray*](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray "(in NumPy v2.1)")) – A 2D array of `bool` representations of bit values such that each row represents a single bitstring
+  *   **bitstring\_matrix** ([*ndarray*](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray "(in NumPy v2.2)")) – A 2D array of `bool` representations of bit values such that each row represents a single bitstring
   *   **hamming\_right** ([*int*](https://docs.python.org/3/library/functions.html#int "(in Python v3.13)")) – The target hamming weight of the right half of bitstrings
   *   **hamming\_left** ([*int*](https://docs.python.org/3/library/functions.html#int "(in Python v3.13)")) – The target hamming weight of the left half of bitstrings
 
@@ -33,12 +33,12 @@ Functions for performing self-consistent configuration recovery.
 
   **Return type**
 
-  [*ndarray*](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray "(in NumPy v2.1)")
+  [*ndarray*](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray "(in NumPy v2.2)")
 </Function>
 
 ### recover\_configurations
 
-<Function id="qiskit_addon_sqd.configuration_recovery.recover_configurations" github="https://github.com/Qiskit/qiskit-addon-sqd/tree/stable/0.8/qiskit_addon_sqd/configuration_recovery.py#L51-L117" signature="recover_configurations(bitstring_matrix, probabilities, avg_occupancies, num_elec_a, num_elec_b, rand_seed=None)">
+<Function id="qiskit_addon_sqd.configuration_recovery.recover_configurations" github="https://github.com/Qiskit/qiskit-addon-sqd/tree/stable/0.9/qiskit_addon_sqd/configuration_recovery.py#L51-L112" signature="recover_configurations(bitstring_matrix, probabilities, avg_occupancies, num_elec_a, num_elec_b, rand_seed=None)">
   Refine bitstrings based on average orbital occupancy and a target hamming weight.
 
   This function refines each bit in isolation in an attempt to transform the Hilbert space represented by the input `bitstring_matrix` into a space closer to that which supports the ground state.
@@ -47,26 +47,22 @@ Functions for performing self-consistent configuration recovery.
     This function makes the assumption that bit `i` represents the spin-down orbital corresponding to the spin-up orbital in bit `i + N` where `N` is the number of spatial orbitals and `i < N`.
   </Admonition>
 
-  <Admonition title="Note" type="note">
-    The output configurations may not necessarily have correct hamming weight, as each bit is flipped in isolation from the other bits in the bitstring.
-  </Admonition>
-
   **Parameters**
 
-  *   **bitstring\_matrix** ([*ndarray*](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray "(in NumPy v2.1)")) – A 2D array of `bool` representations of bit values such that each row represents a single bitstring
+  *   **bitstring\_matrix** ([*ndarray*](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray "(in NumPy v2.2)")) – A 2D array of `bool` representations of bit values such that each row represents a single bitstring
   *   **probabilities** ([*Sequence*](https://docs.python.org/3/library/collections.abc.html#collections.abc.Sequence "(in Python v3.13)")*\[*[*float*](https://docs.python.org/3/library/functions.html#float "(in Python v3.13)")*]*) – A 1D array specifying a probability distribution over the bitstrings
-  *   **avg\_occupancies** ([*ndarray*](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray "(in NumPy v2.1)")) – A 1D array containing the mean occupancy of each orbital. It is assumed that `avg_occupancies[i]` corresponds to the orbital represented by column `i` in `bitstring_matrix`.
+  *   **avg\_occupancies** ([*ndarray*](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray "(in NumPy v2.2)")) – A 1D array containing the mean occupancy of each orbital. It is assumed that `avg_occupancies[i]` corresponds to the orbital represented by column `i` in `bitstring_matrix`.
   *   **num\_elec\_a** ([*int*](https://docs.python.org/3/library/functions.html#int "(in Python v3.13)")) – The number of spin-up electrons in the system.
   *   **num\_elec\_b** ([*int*](https://docs.python.org/3/library/functions.html#int "(in Python v3.13)")) – The number of spin-down electrons in the system.
-  *   **rand\_seed** ([*Generator*](https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator "(in NumPy v2.1)")  *|*[*int*](https://docs.python.org/3/library/functions.html#int "(in Python v3.13)") *| None*) – A seed for controlling randomness
+  *   **rand\_seed** ([*Generator*](https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator "(in NumPy v2.2)")  *|*[*int*](https://docs.python.org/3/library/functions.html#int "(in Python v3.13)") *| None*) – A seed for controlling randomness
 
   **Returns**
 
   A refined bitstring matrix and an updated probability array.
 
   **Return type**
 
-  [tuple](https://docs.python.org/3/library/stdtypes.html#tuple "(in Python v3.13)")\[[*ndarray*](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray "(in NumPy v2.1)"), [*ndarray*](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray "(in NumPy v2.1)")]
+  [tuple](https://docs.python.org/3/library/stdtypes.html#tuple "(in Python v3.13)")\[[*ndarray*](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray "(in NumPy v2.2)"), [*ndarray*](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray "(in NumPy v2.2)")]
 
   **References**
 

docs/api/qiskit-addon-sqd/counts.mdx

@@ -18,7 +18,7 @@ Functions for transforming counts dictionaries.
 
 ### counts\_to\_arrays
 
-<Function id="qiskit_addon_sqd.counts.counts_to_arrays" github="https://github.com/Qiskit/qiskit-addon-sqd/tree/stable/0.8/qiskit_addon_sqd/counts.py#L21-L40" signature="counts_to_arrays(counts)">
+<Function id="qiskit_addon_sqd.counts.counts_to_arrays" github="https://github.com/Qiskit/qiskit-addon-sqd/tree/stable/0.9/qiskit_addon_sqd/counts.py#L21-L40" signature="counts_to_arrays(counts)">
   Convert a counts dictionary into a bitstring matrix and a probability array.
 
   **Parameters**
@@ -32,19 +32,19 @@ Functions for transforming counts dictionaries.
 
   **Return type**
 
-  [tuple](https://docs.python.org/3/library/stdtypes.html#tuple "(in Python v3.13)")\[[*ndarray*](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray "(in NumPy v2.1)"), [*ndarray*](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray "(in NumPy v2.1)")]
+  [tuple](https://docs.python.org/3/library/stdtypes.html#tuple "(in Python v3.13)")\[[*ndarray*](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray "(in NumPy v2.2)"), [*ndarray*](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray "(in NumPy v2.2)")]
 </Function>
 
 ### generate\_counts\_uniform
 
-<Function id="qiskit_addon_sqd.counts.generate_counts_uniform" github="https://github.com/Qiskit/qiskit-addon-sqd/tree/stable/0.8/qiskit_addon_sqd/counts.py#L43-L77" signature="generate_counts_uniform(num_samples, num_bits, rand_seed=None)">
+<Function id="qiskit_addon_sqd.counts.generate_counts_uniform" github="https://github.com/Qiskit/qiskit-addon-sqd/tree/stable/0.9/qiskit_addon_sqd/counts.py#L43-L77" signature="generate_counts_uniform(num_samples, num_bits, rand_seed=None)">
   Generate a bitstring counts dictionary of samples drawn from the uniform distribution.
 
   **Parameters**
 
   *   **num\_samples** ([*int*](https://docs.python.org/3/library/functions.html#int "(in Python v3.13)")) – The number of samples to draw
   *   **num\_bits** ([*int*](https://docs.python.org/3/library/functions.html#int "(in Python v3.13)")) – The number of bits in the bitstrings
-  *   **rand\_seed** ([*Generator*](https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator "(in NumPy v2.1)")  *|*[*int*](https://docs.python.org/3/library/functions.html#int "(in Python v3.13)") *| None*) – A seed for controlling randomness
+  *   **rand\_seed** ([*Generator*](https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator "(in NumPy v2.2)")  *|*[*int*](https://docs.python.org/3/library/functions.html#int "(in Python v3.13)") *| None*) – A seed for controlling randomness
 
   **Returns**
 
@@ -61,7 +61,7 @@ Functions for transforming counts dictionaries.
 
 ### generate\_counts\_bipartite\_hamming
 
-<Function id="qiskit_addon_sqd.counts.generate_counts_bipartite_hamming" github="https://github.com/Qiskit/qiskit-addon-sqd/tree/stable/0.8/qiskit_addon_sqd/counts.py#L80-L135" signature="generate_counts_bipartite_hamming(num_samples, num_bits, *, hamming_right, hamming_left, rand_seed=None)">
+<Function id="qiskit_addon_sqd.counts.generate_counts_bipartite_hamming" github="https://github.com/Qiskit/qiskit-addon-sqd/tree/stable/0.9/qiskit_addon_sqd/counts.py#L80-L134" signature="generate_counts_bipartite_hamming(num_samples, num_bits, *, hamming_right, hamming_left, rand_seed=None)">
   Generate a bitstring counts dictionary with specified bipartite hamming weight.
 
   **Parameters**
@@ -70,7 +70,7 @@ Functions for transforming counts dictionaries.
   *   **num\_bits** ([*int*](https://docs.python.org/3/library/functions.html#int "(in Python v3.13)")) – The number of bits in the bitstrings
   *   **hamming\_right** ([*int*](https://docs.python.org/3/library/functions.html#int "(in Python v3.13)")) – The hamming weight on the right half of each bitstring
   *   **hamming\_left** ([*int*](https://docs.python.org/3/library/functions.html#int "(in Python v3.13)")) – The hamming weight on the left half of each bitstring
-  *   **rand\_seed** ([*Generator*](https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator "(in NumPy v2.1)")  *|*[*int*](https://docs.python.org/3/library/functions.html#int "(in Python v3.13)") *| None*) – A seed for controlling randomness
+  *   **rand\_seed** ([*Generator*](https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator "(in NumPy v2.2)")  *|*[*int*](https://docs.python.org/3/library/functions.html#int "(in Python v3.13)") *| None*) – A seed for controlling randomness
 
   **Returns**
 
@@ -89,7 +89,7 @@ Functions for transforming counts dictionaries.
 
 ### normalize\_counts\_dict
 
-<Function id="qiskit_addon_sqd.counts.normalize_counts_dict" github="https://github.com/Qiskit/qiskit-addon-sqd/tree/stable/0.8/qiskit_addon_sqd/counts.py#L138-L145" signature="normalize_counts_dict(counts)">
+<Function id="qiskit_addon_sqd.counts.normalize_counts_dict" github="https://github.com/Qiskit/qiskit-addon-sqd/tree/stable/0.9/qiskit_addon_sqd/counts.py#L137-L144" signature="normalize_counts_dict(counts)">
   Convert a counts dictionary into a probability dictionary.
 
   **Parameters**