add conda environemnt yml file; change camera fov to reflect accurate…

… stats (60 degree FOV)

environment.yml

@@ -0,0 +1,58 @@
+name: cern_camera_placement
+channels:
+  - defaults
+dependencies:
+  - blas=1.0=mkl
+  - bottleneck=1.3.5=py38h080aedc_0
+  - brotli=1.0.9=ha925a31_2
+  - ca-certificates=2022.4.26=haa95532_0
+  - certifi=2022.6.15=py38haa95532_0
+  - cycler=0.11.0=pyhd3eb1b0_0
+  - fonttools=4.25.0=pyhd3eb1b0_0
+  - freetype=2.10.4=hd328e21_0
+  - icc_rt=2019.0.0=h0cc432a_1
+  - icu=58.2=ha925a31_3
+  - intel-openmp=2021.4.0=haa95532_3556
+  - jpeg=9e=h2bbff1b_0
+  - kiwisolver=1.4.2=py38hd77b12b_0
+  - libpng=1.6.37=h2a8f88b_0
+  - libtiff=4.2.0=he0120a3_1
+  - libwebp=1.2.2=h2bbff1b_0
+  - lz4-c=1.9.3=h2bbff1b_1
+  - matplotlib=3.5.1=py38haa95532_1
+  - matplotlib-base=3.5.1=py38hd77b12b_1
+  - mkl=2021.4.0=haa95532_640
+  - mkl-service=2.4.0=py38h2bbff1b_0
+  - mkl_fft=1.3.1=py38h277e83a_0
+  - mkl_random=1.2.2=py38hf11a4ad_0
+  - munkres=1.1.4=py_0
+  - numexpr=2.8.3=py38hb80d3ca_0
+  - numpy=1.22.3=py38h7a0a035_0
+  - numpy-base=1.22.3=py38hca35cd5_0
+  - openssl=1.1.1q=h2bbff1b_0
+  - packaging=21.3=pyhd3eb1b0_0
+  - pandas=1.4.3=py38hd77b12b_0
+  - pillow=9.0.1=py38hdc2b20a_0
+  - pip=21.2.2=py38haa95532_0
+  - pyparsing=3.0.4=pyhd3eb1b0_0
+  - pyqt=5.9.2=py38hd77b12b_6
+  - python=3.8.13=h6244533_0
+  - python-dateutil=2.8.2=pyhd3eb1b0_0
+  - pytz=2022.1=py38haa95532_0
+  - qt=5.9.7=vc14h73c81de_0
+  - scipy=1.7.3=py38h0a974cb_0
+  - seaborn=0.11.2=pyhd3eb1b0_0
+  - setuptools=61.2.0=py38haa95532_0
+  - sip=4.19.13=py38hd77b12b_0
+  - six=1.16.0=pyhd3eb1b0_1
+  - sqlite=3.38.3=h2bbff1b_0
+  - tk=8.6.12=h2bbff1b_0
+  - tornado=6.1=py38h2bbff1b_0
+  - vc=14.2=h21ff451_1
+  - vs2015_runtime=14.27.29016=h5e58377_2
+  - wheel=0.37.1=pyhd3eb1b0_0
+  - wincertstore=0.2=py38haa95532_2
+  - xz=5.2.5=h8cc25b3_1
+  - zlib=1.2.12=h8cc25b3_2
+  - zstd=1.5.2=h19a0ad4_0
+prefix: C:\Users\vraut\Anaconda3\envs\cern_camera_placement

optimizer.py

@@ -4,16 +4,16 @@
 from scipy.optimize import Bounds, minimize, NonlinearConstraint
 from typing import List
 
-from guesses import gen_guess_box
-from obstacles import CylinderObstacle, Obstacle
+from optimization.guesses import gen_guess_box
+from optimization.obstacles import CylinderObstacle, Obstacle
 
 # TODO: change these to reflect the most accurate specs
 # FOV lower bound (objects must be at least this far to be seen)
 fov_lower_bound = 1
 # FOV upper bound a.k.a height of the cone (objects further than this are out of range)
 fov_upper_bound = 5
 # FOV degree (a.k.a angle between cone axis and slant)
-fov_degree = 50
+fov_degree = 60
 # FOV base radius (a.k.a radius of the base of the cone)
 fov_base_radius = fov_upper_bound * np.tan(np.deg2rad(fov_degree))
 
@@ -350,7 +350,7 @@ def main():
     x0 = gen_guess_box(V_x, V_y, V_z)
 
     # specify the obstacles present in the space
-    obstacles = [CylinderObstacle(np.array([1.5,6,1.5]), np.array([2.5,6,1.5]), 0.25)]
+    obstacles = [CylinderObstacle(np.array([1.5,6,1.5]), np.array([2.5,6,1.5]), 1)]
 
     res = minimize(average_reciprocal_gdop, x0, args=(obstacles,), bounds=bounds, options={"eps":0.1, "disp":True})
     print(res)