adding remaining figures and notebooks

%% Cell type:code id:7c8b21a9 tags:

``` python

import math

import numpy as np

import os

import pickle

```

%% Cell type:code id:2487f03f tags:

``` python

def apply_rotation(xy, angle):

    theta = np.radians(angle)

    # Calculate cosine and sine of the angle

    cos_theta = np.cos(theta)

    sin_theta = np.sin(theta)

    x,y = xy

    # Apply the rotation matrix formula

    rx = np.round(x * cos_theta - y * sin_theta)

    ry = np.round(x * sin_theta + y * cos_theta)

    return np.array([rx,ry], dtype=int)

```

%% Cell type:code id:503b4eef tags:

``` python

results_filename = "minimal_bilinear_deficit_red_200_2026_02_10_19_12_08.pkl"

results_path = os.path.join("./test_results", results_filename)

with open(results_path, "rb") as f:

    results = pickle.load(f)

```

%% Cell type:code id:79e51e5c tags:

``` python

analyze_res = {}

for ilayout, res in results.items():

    if not res['rref']['match_obs']:

        analyze_res[ilayout] = res

print(len(analyze_res), len(results))

```

%% Output

    7 4096

%% Cell type:code id:c908c30a tags:

``` python

from PIL import Image

import copy

def plot_layout(result, img_name):

    nsens = 6

    mass_meas = result['soar']['layout'][0:nsens]

    conc_meas = result['soar']['layout'][nsens:]

    mass_soar_obs = result['soar']['obs'][0:nsens]

    conc_soar_obs = result['soar']['obs'][nsens:]

    mass_mrror_obs = result['rref']['obs'][0:nsens]

    conc_mrror_obs = result['rref']['obs'][nsens:]

    # set sensor rotation

    rot = [

        0,0,0,90,0,0,

    ]

    xy_mass = [

        (490,25),

        (1000,25),

        (2250,25),

        (1580,400),

        (2250,765),

        (1000,765),

    ]

    xy_offset = (130,0)

    # Open the main (background) image

    # layout_img_meas = Image.open("./diagrams/minimal_layout_nosensors.png").convert("RGBA")

    layout_img_sensors = Image.open("./diagrams/minimal_layout_nosensors.png").convert("RGBA")

    layout_img_soar = Image.open("./diagrams/minimal_layout_nosensors.png").convert("RGBA")

    layout_img_mrror = Image.open("./diagrams/minimal_layout_nosensors.png").convert("RGBA")

    # Open the images to overlay

    mass_hs = Image.open("./diagrams/massflow_sensor.png").convert("RGBA")

    conc_hs = Image.open("./diagrams/concentration_sensor.png").convert("RGBA")

    mass_ss = Image.open("./diagrams/massflow_sensor_soft.png").convert("RGBA")

    conc_ss = Image.open("./diagrams/concentration_sensor_soft.png").convert("RGBA")

    # Define the coordinates where each overlay will be pasted (top-left corner)

    # Coordinates are a tuple: (x, y)

    for sid, (xym, ro) in enumerate(zip(xy_mass, rot)):

        rot_offset = apply_rotation(xy_offset, ro)

        xyc = (xym[0] + rot_offset[0], xym[1] + rot_offset[1])

        if mass_meas[sid]:

            layout_img_sensors.paste(mass_hs.rotate(ro,expand=True), xym, mass_hs.rotate(ro,expand=True))

            layout_img_soar.paste(mass_hs.rotate(ro,expand=True), xym, mass_hs.rotate(ro,expand=True))

            layout_img_mrror.paste(mass_hs.rotate(ro,expand=True), xym, mass_hs.rotate(ro,expand=True))

        if conc_meas[sid]:

            layout_img_sensors.paste(conc_hs.rotate(ro,expand=True), xyc, conc_hs.rotate(ro,expand=True))

            layout_img_soar.paste(conc_hs.rotate(ro,expand=True), xyc, conc_hs.rotate(ro,expand=True))

            layout_img_mrror.paste(conc_hs.rotate(ro,expand=True), xyc, conc_hs.rotate(ro,expand=True))

        if mass_soar_obs[sid] and not mass_meas[sid]:

            layout_img_soar.paste(mass_ss.rotate(ro,expand=True), xym, mass_ss.rotate(ro,expand=True))

        if conc_soar_obs[sid] and not conc_meas[sid]:

            layout_img_soar.paste(conc_ss.rotate(ro,expand=True), xyc, conc_ss.rotate(ro,expand=True))

        if mass_mrror_obs[sid] and not mass_meas[sid]:

            layout_img_mrror.paste(mass_ss.rotate(ro,expand=True), xym, mass_ss.rotate(ro,expand=True))

        if conc_mrror_obs[sid] and not conc_meas[sid]:

            layout_img_mrror.paste(conc_ss.rotate(ro,expand=True), xyc, conc_ss.rotate(ro,expand=True))

    # Save the final image

    layout_img_sensors.save(f"./plots/layout_{img_name}.png", "PNG")

    layout_img_soar.save(f"./plots/SOAR_obs_{img_name}.png", "PNG")

    layout_img_mrror.save(f"./plots/MRROR_obs_{img_name}.png", "PNG")

for ires, res in analyze_res.items():

    plot_layout(result=res, img_name = f"{str(ires)}_paper")

```