Confusing issue of 'ndarray' object cannot be converted to 'PyArray<T, D>'

[IanQS]

I have some code across a few files, but my structure boils down to:

src/
    - lib.rs
    - bindings/
        - np_bindings.rs
        - mod.rs  // just a `pub mod np_bindings;`
    - implementation/
        - circuit_common.rs
        - mod.rs  // just a `pub mod X`
        - ...

lib.rs

use bindings::np_bindings::{
    map_neuron_ids_to_cmat_idxs_np,
};
use pyo3::prelude::*;
pub mod implementation;
pub mod bindings;


#[pymodule]
fn circuit_rs(m: &Bound<'_, PyModule>) -> PyResult<()> {
    // ... a few others
    m.add_function(wrap_pyfunction!(map_neuron_ids_to_cmat_idxs_np, m)?)?;

    Ok(())
}

in np_bindings.rs

use numpy::PyReadonlyArray2;
use std::collections::{HashMap, HashSet};

use crate::implementation::{
    circuit_common::{
        map_neuron_id_to_cmat_idx,
        readonly_arr_to_vec64,
    },
    isolate::find_subcircuit_from_edge_list,
};
use pyo3::prelude::*;

/// Generate a default mapping from neuron IDs to some index in a adjacency matrix
#[pyfunction]
#[pyo3(signature = (edge_array))]
pub(crate) fn map_neuron_ids_to_cmat_idxs_np(
    edge_array: PyReadonlyArray2<NeuronID>,
) -> HashMap<NeuronID, CMatIdx> {
    let edge_list = readonly_arr_to_vec64(edge_array);

    map_neuron_id_to_cmat_idx(&edge_list)
}

in circuit_common.rs

use std::collections::{HashMap, HashSet};

use numpy::PyReadonlyArray2;


pub(crate) type NeuronID = u64;
pub(crate) type CMatIdx = u64;

pub(crate) fn readonly_arr_to_vec64(
    edge_array: PyReadonlyArray2<NeuronID>,
) -> Vec<(NeuronID, NeuronID)> {
    println!("Showing up?");
    let edge_view = edge_array.as_array();
    let mut edge_list: Vec<(u64, u64)> = Vec::new();

    for row in edge_view.outer_iter() {
        if row.len() >= 2 {
            let source = row[0] as NeuronID;
            let target = row[1] as NeuronID;
            edge_list.push((source, target));
        }
    }
    edge_list
}

I have some simple python code that loads in a pandas dataframe, filters it, then converts it to a numpy array and passes it in:

fc_as_np = full_conn_edge_list[["pre_root_id", "post_root_id"]].to_numpy()
test_full_nid_cidx_map: dict[int, int] = circuit_rs.map_neuron_ids_to_cmat_idxs_np(fc_as_np)

but I get an error on that very last line, with TypeError: argument 'edge_array': 'ndarray' object cannot be converted to 'PyArray<T, D>'

if you're interested in recreating this you can see oahmedlab/circuit-rs but it's a little messy now

[IanQS]

Closing and moving to pyo3 rust numpy specifically