solsticepy

https://solsticepy.readthedocs.io/en/latest/
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solsticepy provides a set of Python functions to set up, run, and post-process Solstice ray-tracing...
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### Locate Solstice Installation and Programs

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/find_solstice.html

Contains the core logic for finding the Solstice root directory via the Windows Registry and resolving executable paths.

```python
# This script finds the location of Solstice from the Windows Registry, assuming
# it was installed with ANU's NSIS-based installer. It works with Python 2.7 and
# Python 3.8, with both 32 and 64-bit versions, on both Windows 7 and Windows 10
# -- John Pye, April 2020

import sys, platform, os


[docs]def find_solstice_root(version_required=None,verbose=0):
	"""Locate the place where Solstice files are installed on Windows

	``Arguments``

	  * version_required (None or str): if not None, then enforce this specified version of Solstice (eg '0.9.0')
	  * verbose (bool): if True, output file locations to stderr

	``Return``

	  * dirn (str): the directory where Solstice is installed in the Windows system
	"""

	if verbose: sys.stderr.write("Python is running from %s\n"%(sys.executable,))
	if not platform.system()=="Windows":
		raise RuntimeError("This function is only for Windows")
	# otherwise...
	if sys.version_info[0] < 3:
		if verbose: sys.stderr.write("Python 2, ")
		import _winreg as winreg
	else:
		if verbose: sys.stderr.write("Python 3, ")
		import winreg
	if sys.maxsize > 2**32:
		if verbose: sys.stderr.write("64-bit\n")
		# 64-bit Python
		key = winreg.OpenKey(winreg.HKEY_LOCAL_MACHINE,r"Software\Meso-Star\Solstice",0,winreg.KEY_READ)
	else:
		if verbose: sys.stderr.write("32-bit\n")
		key = winreg.OpenKey(winreg.HKEY_LOCAL_MACHINE,r"Software\Meso-Star\Solstice",0,winreg.KEY_WOW64_64KEY+winreg.KEY_READ)
	dirn, typd = winreg.QueryValueEx(key, 'root')
	ver, typv = winreg.QueryValueEx(key, 'version')
	if version_required:
		assert ver == version_required
	return dirn


[docs]def find_prog(name,version_required=None):
	"""Find the path to any required Solstice executable program

	``Arguments``

	  * name (str): stem-name (eg 'solpp') of the program (eg 'solpp.exe') required
	  * version_required (None or str): if not None, then enforce this specified version of Solstice (e.g. '0.9.0')

	``Return``

	  * path (str): path of the required Solstice executable program
	"""
	
	if platform.system()=="Windows":
		path = os.path.join(find_solstice_root(version_required),"bin","%s.exe"%(name,));
		if not os.path.exists(path):
			raise RuntimeError("Program '%s' was not found at path '%s'"%(name,path))
		return path
	else:
		# assume all solstice programs are on the PATH
		import subprocess
		with open(os.devnull, 'wb') as DEVNULL:
			proc = subprocess.run(['which',name],stdout=DEVNULL)
		if proc.returncode:
			raise RuntimeError("Program '%s' was not found in the PATH" %(name))
		return name


if __name__=="__main__":
	dirn = find_solstice_root('0.9.0',verbose=1)
	sys.stderr.write("Solstice is installed in %s\n\n" %(dirn,)) # works both python2+3 :o)

	import subprocess, os

	spath = os.path.join(dirn,"bin","solstice.exe")

	# check that installed version of solstice is 0.9.0:
	proc = subprocess.run([spath,"--version"],encoding='utf-8',stdout=subprocess.PIPE)
	assert proc.stdout.strip() == "Solstice 0.9.0"

	# output the help text from solstice:
	subprocess.run([spath,"-h"])
```

--------------------------------

### Calculate Heliostat Field Performance

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/cal_field.html

Example workflow for calculating field performance and exporting results to a VTK file for visualization in ParaView.

```python
>>> from solsticepy.cal_field import *
>>> pos_and_aiming=np.loadtxt('./pos_and_aiming.csv', delimiter=',', skiprows=2) #load the field layout file (refer to cal_layout.py)
>>> pos=pos_and_aiming[:,:3]
>>> aim=pos_and_aiming[:,4:]
>>> azimuth=np.r_[0.]
>>> zenith=np.r_[12.]
>>> field=FieldPF(np.r_[0,1,0])
>>> sun_vec=field.get_solar_vector(azimuth, zenith)
>>> norms=field.get_normals(towerheight=70., hstpos=pos, sun_vec=sun_vec)
>>> COORD, TRI, ele, nc=field.mesh_heliostat_field(width=10., height=8., normals=norms, hstpos=pos)
>>> cos=field.get_cosine(hst_norms=norms, sun_vec=sun_vec)
>>> savedir='./field.vtk'
>>> COS=np.repeat(cos, ele)
>>> DATA={'cos':COS}
>>> NORMS=np.repeat(norms, ele, axis=0)
>>> gen_vtk(savedir, COORD.T, TRI, NORMS, True, DATA)
```

--------------------------------

### find_solstice_root(version_required=None, verbose=0)

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/find_solstice.html

Locates the directory where Solstice is installed on a Windows system by querying the Windows Registry.

```APIDOC
## find_solstice_root(version_required=None, verbose=0)

### Description
Locates the installation directory of Solstice on Windows. This function requires the Windows platform.

### Parameters
- **version_required** (str, optional) - If provided, enforces a specific version of Solstice (e.g., '0.9.0').
- **verbose** (bool, optional) - If True, outputs file locations to stderr.

### Returns
- **dirn** (str) - The directory path where Solstice is installed.
```

--------------------------------

### Initialize Sun Parameters

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/gen_yaml.html

Demonstrates creating a Sun object and generating its YAML representation.

```python
>>> sun = Sun(dni=1000, sunshape='buie', csr=0.2)
>>> print(sun.yaml(spectrum = "*solar_spectrum"))
```

--------------------------------

### Generate a radial-stagger heliostat field

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/cal_layout.html

Example usage of the radial_stagger function to calculate heliostat positions and aiming points.

```python
>>> from solsticepy.cal_layout import *
>>> latitude=34.
>>> hst_width=13.
>>> hst_height=10.
>>> hst_z=5.
>>> target_area=75715.
>>> num_hst=target_area/hst_width/hst_height*2 # create a twice large field, so that the inefficient heliostat can be trimmed-off after optical simulations
>>> tower_height=110.
>>> R1=40. # the distance from the first row to the bottom of the tower
>>> fb=0.6
>>> casefolder='.' # replace it as the directory of your case folder
>>> plot=False # if you want to plot the field layout, set it as True
>>> pos_and_aim=radial_stagger(latitude, num_hst, hst_width, hst_height, hst_z, tower_height, R1, fb, savedir=casefolder,plot=plot)
```

--------------------------------

### Master.__init__

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/master.html

Initializes the Master simulation controller, establishing the case directory and configuring processor usage.

```APIDOC
## Master.__init__(casedir='.', nproc=None)

### Description
Sets up the Solstice simulation environment by establishing the case folder and configuring parallel processing settings.

### Parameters
- **casedir** (str) - Optional - The case directory path (default: '.')
- **nproc** (int) - Optional - Number of processors for parallel execution; None uses all available processors.
```

--------------------------------

### Master Class Initialization

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/master.html

Initializes the simulation environment by setting the case directory and processor count.

```python
def __init__(self, casedir='.', nproc=None):
		"""Set up the Solstice simulation, i.e. establishing the case folder, calling the Solstice program and post-processing the results

		``Argument``
		  * casedir (str): the case directory
	      * nproc   (int): number of processors, e.g. nproc=1 will run in serial mode, 
                                                      nproc=4 will run with 4 processors in parallel
													  nproc=None will run with any number of processors that are available
		"""
		self.casedir=os.path.abspath(casedir)
		self.nproc=nproc

		if not os.path.exists(self.casedir):
		    os.makedirs(self.casedir)
		    assert os.path.isdir(casedir)
		sys.stderr.write("Case directory is '%s'\n" % (yellow(self.casedir),))
```

--------------------------------

### Master.run

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/master.html

Executes an optical ray-tracing simulation for a specific sun position.

```APIDOC
## Master.run(azimuth, elevation, num_rays, rho_mirror, dni, folder, gen_vtk=False, printresult=False, verbose=False, system='crs')

### Description
Runs an optical simulation for a single sun position using Solstice. Optionally generates VTK files for rendering in Paraview.

### Parameters
- **azimuth** (float) - Required - Azimuth angle (East towards North).
- **elevation** (float) - Required - Elevation angle.
- **num_rays** (int) - Required - Number of rays to cast.
- **rho_mirror** (float) - Required - Mirror reflectivity.
- **dni** (float) - Required - Direct normal irradiance (W/m2).
- **folder** (str) - Required - Output folder for simulation results.
- **gen_vtk** (boolean) - Optional - If True, generates .vtk files.
- **system** (str) - Optional - System type: 'crs' or 'dish'.
```

--------------------------------

### Execute process_raw_results from Command Line

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/process_raw.html

Entry point for processing raw results using command-line arguments and printing the total efficiency to stderr.

```python
if __name__=='__main__':
    eta,pf_hst = proces_raw_results(sys.argv[1], sys.argv[2], sys.argv[3])
    sys.stderr.write('\nTotal efficiency: %s\n'%(repr(eta),))
```

--------------------------------

### Running Optical Simulations

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/master.html

Executes the Solstice ray-tracing simulation and performs optional post-processing tasks like VTK generation.

```python
def run(self, azimuth, elevation, num_rays, rho_mirror, dni, folder, gen_vtk=False, printresult=False, verbose=False, system='crs'):

		"""Run an optical simulation (one sun position) using Solstice 

		* `azimuth`   (float): the azimuth angle of the ray-tracing simulation in Solstice, counted from East towards to North
		* `elevation` (float): the elevation angle of the ray-tracing simulation in Solstice
		* `num_rays`    (int): number of rays to be cast in the ray-tracing simulation
		* `rho_mirror`(float): reflectivity of mirrors, required for results post-processing 
		* `dni`       (float): the direct normal irradiance (W/m2), required to obtain performance of individual heliostat
		* `gen_vtk` (boolean): if True, generate .vtk files for rendering in Paraview
		* `system`      (str): 'crs' for a central receiver system, or 'dish' for a parabolic dish system				

		Returns: no return value (results files are created and written)
		"""

		YAML_IN = self.in_case(self.casedir, 'input.yaml')
		RECV_IN = self.in_case(self.casedir, 'input-rcv.yaml')

		# main raytrace
		if self.nproc==None:
			run_prog("solstice",['-D%s,%s'%(azimuth,elevation),'-v','-n',num_rays,'-R',RECV_IN,'-fo',self.in_case(folder, 'simul'),YAML_IN])
		else:
			run_prog("solstice",['-D%s,%s'%(azimuth,elevation),'-v', '-t', self.nproc, '-n',num_rays,'-R',RECV_IN,'-fo',self.in_case(folder, 'simul'),YAML_IN])

		folder=os.path.abspath(folder)
		if gen_vtk and verbose:
			dirn = os.getcwd()
			try:
				os.chdir(folder)

				# Read "simul" results and produce a text file with the raw results
				run_prog('solppraw',[self.in_case(folder, 'simul')])

				# post processing
				run_prog("solstice",['-D%s,%s'%(azimuth,elevation),'-g','format=obj:split=geometry','-fo',self.in_case(folder, 'geom'),YAML_IN])

				# run a short raytrace to produce some ray paths
				run_prog("solstice",['-D%s,%s'%(azimuth,elevation),'-q','-n','100','-R',RECV_IN,'-p','default',YAML_IN], output_file=self.in_case(folder, 'solpaths'))

				# Read "simul" results and produce receiver files (.vtk) of incoming and/or absorbed solar flux per-primitive
				run_prog('solmaps',[self.in_case(folder, 'simul')])

				# Read "geom" and "simul" file results and produce primaries and receivers files (.vtk), and .obj geometry files
				run_prog('solpp',[self.in_case(folder, 'geom'),self.in_case(folder, 'simul')])

				# Read "solpaths" file and produce readable file (.vtk) by paraview to visualize the ray paths
				run_prog('solpaths',[self.in_case(folder, 'solpaths')])
			finally:
				os.chdir(dirn)
```

--------------------------------

### solsticepy.Master

Source: https://solsticepy.readthedocs.io/en/latest/index.html

Class for setting up and running Solstice simulations.

```APIDOC
## solsticepy.Master(casedir='.', nproc=None)

### Description
Set up the Solstice simulation, establishing the case folder, calling the Solstice program, and post-processing results.

### Parameters
- **casedir** (str) - Optional - The case directory.
- **nproc** (int) - Optional - Number of processors for parallel execution.
```

--------------------------------

### Master.run_annual

Source: https://solsticepy.readthedocs.io/en/latest/index.html

Runs a list of optical simulations to obtain annual performance.

```APIDOC
## Master.run_annual(nd, nh, latitude, num_rays, num_hst, rho_mirror, dni, gen_vtk=False, verbose=False)

### Description
Run a list of optical simulations to obtain annual performance (lookup table) using Solstice.

### Parameters
- **nd** (int) - Required - Number of rows in lookup table.
- **nh** (int) - Required - Number of columns in lookup table.
- **latitude** (float) - Required - Latitude angle (deg).
- **num_rays** (int) - Required - Number of rays to be cast.
- **num_hst** (int) - Required - Number of heliostats.
- **rho_mirror** (float) - Required - Reflectivity of mirrors.
- **dni** (float) - Required - Direct normal irradiance (W/m2).

### Returns
- **table** (numpy array) - Annual optical efficiency lookup table.
- **ANNUAL** (numpy array) - Annual output of each heliostat.
```

--------------------------------

### Run Annual Performance Simulation

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/master.html

Executes a series of optical simulations to generate an annual performance lookup table.

```python
	def run_annual(self, nd, nh, latitude, num_rays, num_hst,rho_mirror,dni, gen_vtk=False,verbose=False):

		"""Run a list of optical simulations to obtain annual performance (lookup table) using Solstice 

		``Arguments``

		  * nd (int): number of rows in the lookup table (discretisation of the declination angle)
		  * nh (int): number of columns in the lookup table (discretisation of the solar hour angle)
		  * latitude (float): the latitude angle of the plan location (deg)
		  * num_rays (int): number of rays to be cast in the ray-tracing simulation
		  * num_hst (int): number of heliostats 
	      * nproc (int): number of processors, e.g. nproc=1 will run in serial mode, 
                                                      nproc=4 will run with 4 processors in parallel
					  	  nproc=None will run with any number of processors that are available

		  * rho_mirror (float): reflectivity of mirrors, required for results post-processing 
		  * dni (float): the direct normal irradiance (W/m2), required to obtain performance of individual heliostat
		  * gen_vtk (bool): True - perform postprocessing for visualisation of  each individual ray-tracing scene (each sun position), False - no postprocessing for visualisation 


		``Return``

		  * table (numpy array), the annual optical efficiency lookup table
		  * ANNUAL (numpy array), the annual output of each heliostat
		"""

		YAML_IN = self.in_case(self.casedir, 'input.yaml')
		RECV_IN = self.in_case(self.casedir, 'input-rcv.yaml')

		sun=SunPosition()
		AZI, ZENITH,table,case_list=sun.annual_angles(latitude, casefolder=self.casedir, nd=nd, nh=nh)
		case_list=case_list[1:]
		SOLSTICE_AZI, SOLSTICE_ELE=sun.convert_convention('solstice', AZI, ZENITH)

		# performance of individual heliostat is recorded
		# TODO note, DNI is not varied in the simulation, 
		# i.e. performance is not dni-weighted
		ANNUAL=np.zeros((num_hst, 9))    
		run=np.r_[0]

		for i in range(len(case_list)):     
			c=int(case_list[i,0].astype(float))
			if c not in run:
				azimuth=SOLSTICE_AZI[c-1]
				elevation=SOLSTICE_ELE[c-1]
				#if np.sin(elevation*np.pi/180.)>=1.e-5:
				#	dni=1618.*np.exp(-0.606/(np.sin(elevation*np.pi/180.)**0.491))
				#else:
				#	dni=0.

			   
				sys.stderr.write("\n"+green('Sun position: %s \n'%c))
				print('azimuth: %.2f'% azimuth, ', elevation: %.2f'%elevation)

				onesunfolder=os.path.join(self.casedir,'sunpos_%s'%(c))

				# run solstice
				if elevation<1.: # 1 degree
				    efficiency_total=ufloat(0,0)
				    performance_hst=np.zeros((num_hst, 9))  
				else:
					efficiency_total, performance_hst=self.run(azimuth, elevation, num_rays, rho_mirror, dni, folder=onesunfolder, gen_vtk=gen_vtk, printresult=False, verbose=verbose)

					sys.stderr.write(yellow("Total efficiency: {:f}\n".format(efficiency_total)))

				ANNUAL+=performance_hst
			else:
				ANNUAL+=performance_hst


			for a in range(len(table[3:])):
				for b in range(len(table[0,3:])):
				    val=re.findall(r'\d+',    table[a+3,b+3])
				    if val==[]:
				        table[a+3,b+3]=0
				    else:
				        if c==float(val[0]):
				            table[a+3,b+3]=efficiency_total.nominal_value

			run=np.append(run,c)   

		annual_title=np.array(['Q_solar','Q_cosine', 'Q_shade', 'Q_hst_abs', 'Q_block', 'Q_atm', 'Q_spil', 'Q_refl', 'Q_rcv_abs']) 
		ANNUAL=np.vstack((annual_title, ANNUAL))
		if verbose:
			np.savetxt(self.casedir+'/lookup_table.csv', table, fmt='%s', delimiter=',')
			np.savetxt(self.casedir+'/result-heliostats-annual-performance.csv', ANNUAL, fmt='%s', delimiter=',')

		sys.stderr.write("\n"+green("Lookup table saved.\n"))
		sys.stderr.write(green("Completed successfully.\n"+"\n"))
		return table, ANNUAL
```

--------------------------------

### Organize Raw Flux Data

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/process_raw.html

Constructs a NumPy array containing raw simulation results for sun parameters, flux values, and virtual plane data.

```python
vir_area=get_rc(num_res+2+num_rec-1,2)
vir_income=get_rc(num_res+2+num_rec-1,3)
vir_income_err=get_rc(num_res+2+num_rec-1,4)

raw_res=np.array([
	['name','value', 'error']
	,['sun_azimuth', azimuth,'']
	,['sun_elevation', elevation, '']
	,['num hst', num_hst,'']
	,['num rays',num_rays, '']
	,['potential flux', potential, potential_err]
	,['absorbed flux', absorbed, absorbed_err]
	,['Cosine factor', Fcos, Fcos_err]
	,['shadow loss', shadow_loss, shadow_err]
	,['Mising loss', missing_loss, missing_err]
	,['materials loss', material_loss, material_loss_err]
	,['atomospheric loss', atmospheric_loss, atmospheric_err]
	,['','','']
	,['','','']
	,['Virtual plane','','']
	,['area', vir_area, '']
	,['income flux', vir_income,vir_income_err]])

for i in range(num_apertures):
	aperture_i = np.array([
	 ['','','']
	,['Aperture', i,'']
	,['area', rec_area[i], '']
	,['front income flux', rec_front_income[i], rec_front_income_err[i]]
	,['back income flux', rec_back_income[i], rec_back_income_err[i]]
	,['front absorbed flux', rec_front_absorbed[i], rec_front_absorbed_err[i]]
	,['back absorbed flux', rec_back_absorbed[i], rec_back_absorbed_err[i]]
	,['front efficiency', rec_front_eff[i], rec_front_eff_err[i]]
	,['back efficiency', rec_back_eff[i], rec_back_eff_err[i]]])

	raw_res=np.vstack((raw_res, aperture_i))
```

--------------------------------

### process_raw_results_dish(rawfile, savedir, rho_mirror, dni, verbose=False)

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/process_raw.html

Processes the raw Solstice 'simul' output file into readable CSV files for dish systems. It parses the simulation data, calculates performance metrics, and writes the organized results to the specified directory.

```APIDOC
## process_raw_results_dish

### Description
Processes the raw Solstice 'simul' output file into readable CSV files for dish systems. It parses the simulation data, calculates performance metrics, and writes the organized results to the specified directory.

### Parameters
- **rawfile** (str) - Required - The directory of the 'simul' file generated by Solstice.
- **savedir** (str) - Required - The directory for saving the organised results.
- **rho_mirror** (float) - Required - Mirror reflectivity (needed for reporting energy sums).
- **dni** (float) - Required - The direct normal irradiance (W/m2), required to obtain performance of individual heliostat.
- **verbose** (bool) - Optional - Enables verbose output if set to True.

### Returns
- **efficiency_total** (float) - The total optical efficiency.
```

--------------------------------

### File Path Management

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/master.html

Joins a filename with the case directory and ensures the target folder exists.

```python
def in_case(self, folder, fn):
		"""Joining a file name with the case directory

		``Argument``

		  * fn (str): file name

		``Return``

		  * a joining directory of the file in the case directory
		"""
		
		if not os.path.exists(folder):
		    os.makedirs(folder)
		    assert os.path.isdir(folder)

		return os.path.join(folder,fn)
```

--------------------------------

### Process Simulation Results

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/master.html

Handles result processing for different system configurations like dish or multi-aperture systems.

```python
		if system=='dish':
			eta=process_raw_results_dish(self.in_case(folder, 'simul'), folder, rho_mirror, dni, verbose=verbose)
			if printresult:
				sys.stderr.write('\n' + yellow("Total efficiency: {:f}\n".format(eta)))
				sys.stderr.write(green("Completed successfully.\n"))
			return eta

		else:
			if system=='multi-aperture':
				eta, performance_hst=process_raw_results_multi_aperture(self.in_case(folder, 'simul'), folder,rho_mirror, dni, verbose=verbose)
			else:
				eta, performance_hst=process_raw_results(self.in_case(folder, 'simul'), folder,rho_mirror, dni, verbose=verbose)

			if printresult:
				sys.stderr.write('\n' + yellow("Total efficiency: {:f}\n".format(eta)))
				sys.stderr.write(green("Completed successfully.\n"))
			return eta, performance_hst
```

--------------------------------

### Calculate and Visualize Heliostat Field

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/cal_field.html

Demonstrates loading heliostat positions, calculating solar vectors and normals, and exporting the field geometry to a VTK file.

```python
if __name__=='__main__':
    #pos_and_aiming=np.loadtxt('/media/yewang/Work/svn_ye/Solstice-tutorial/cases/2-Validation/layout.csv', delimiter=',', skiprows=2)
    pos_and_aiming=np.loadtxt('./pos_and_aiming.csv', delimiter=',', skiprows=2)
    pos=pos_and_aiming[:,:3]
    aim=pos_and_aiming[:,4:]
    azimuth=np.r_[0.]
    zenith=np.r_[12.]
    field=FieldPF(np.r_[0,1,0])
    sun_vec=field.get_solar_vector(azimuth, zenith)
    norms=field.get_normals(towerheight=70., hstpos=pos, sun_vec=sun_vec)
    #field.heliostat(10, 8)
    COORD, TRI, ele, nc=field.view_heliostats(width=10., height=8., normals=norms, hstpos=pos)
    cos=field.get_cosine(hst_norms=norms, sun_vec=sun_vec)
    savedir='./field.vtk'
    COS=np.repeat(cos, ele)
    DATA={'cos':COS}
    NORMS=np.repeat(norms, ele, axis=0)
    gen_vtk(savedir, COORD.T, TRI, NORMS, True, DATA)
```

--------------------------------

### Calculating Energy Balance

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/process_raw.html

Computes energy components and organizes them into a summary array using ufloat for uncertainty handling.

```python
Qtotal=ufloat(potential, 0)
Fcos=ufloat(Fcos,Fcos_err) 
Qcos=Qtotal*(1.-Fcos)
Qshade=ufloat(shadow_loss,shadow_err)
Qfield_abs=(Qtotal-Qcos-Qshade)*(1.-float(rho_mirror))
Qattn=ufloat(atmospheric_loss, atmospheric_err)
Qabs=ufloat(absorbed, absorbed_err)
Qspil=ufloat(vir_income,vir_income_err)-Qabs
Qrefl=ufloat(rec_front_income,rec_front_income_err)+ufloat(rec_back_income,rec_back_income_err)-Qabs
Qblock=Qtotal-Qcos-Qshade-Qfield_abs-Qspil-Qabs-Qrefl-Qattn

organised=np.array([
	['Name', 'Value', '+/-Error']
	,['Qall (kW)', Qtotal.n/1000., Qtotal.s/1000.]
	,['Qcos (kW)', Qcos.n/1000.,Qcos.s/1000.]
	,['Qshad (kW)', Qshade.n/1000., Qshade.s/1000.]
	,['Qfield_abs (kW)', Qfield_abs.n/1000., Qfield_abs.s/1000.]
	,['Qblcok (kW)', Qblock.n/1000.,  Qblock.s/1000.]
	,['Qattn (kW)',Qattn.n/1000., Qattn.s/1000.]
	,['Qspil (kW)', Qspil.n/1000., Qspil.s/1000.]
	,['Qrefl (kW)', Qrefl.n/1000.,Qrefl.s/1000.]
	,['Qabs (kW)', Qabs.n/1000., Qabs.s/1000.]
	,['rays', num_rays,'-']
])

efficiency_total=Qabs/Qtotal
```

--------------------------------

### Master.in_case

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/master.html

Utility method to join a filename with the established case directory.

```APIDOC
## Master.in_case(folder, fn)

### Description
Joins a file name with the specified folder path within the case directory.

### Parameters
- **folder** (str) - Required - The target folder path.
- **fn** (str) - Required - The file name to join.

### Returns
- (str) - The full path joining the folder and the file name.
```

--------------------------------

### Generate Spectral Data YAML

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/gen_yaml.html

Constructs YAML entries for solar spectrum and mirror reflectivity data based on spectral configuration.

```python
if spectral:
	I_sun=SolarSpectrum()
	# CREATE the spectrum for the sun
	iyaml+='- spectrum: &solar_spectrum  \n'
	for i in range(0,len(I_sun)-1):
	    iyaml+='  - {wavelength: %s, data: %s }\n' % (I_sun[i][0],I_sun[i][1])  
	i = len(I_sun)-1
	iyaml+='  - {wavelength: %s, data: %s }\n' % (I_sun[i][0],I_sun[i][1]) 
	iyaml+='\n'

	# CREATE the spectrum for the reflectivity (mirror)
	mirror_rho= MirrorRhoSpectrum()
	mirror_ref=mirror_rho
	for i in range(0,len(mirror_rho)):
	    mirror_ref[i][0] = mirror_rho[len(mirror_rho)-1-i][0]/1000.
	    mirror_ref[i][1] = mirror_rho[len(mirror_rho)-1-i][1]/100.
	mirror_ref.append([4,0.9])
	iyaml+='- spectrum: &%s  \n' % 'ref_mirror'
	for i in range(0,len(mirror_ref)-1):
	    iyaml+='  - {wavelength: %15.8e, data: %15.8e }\n' % (float(mirror_ref[i][0]),float(mirror_ref[i][1])) 
	i = len(mirror_ref)-1
	iyaml+='  - {wavelength: %15.8e, data: %15.8e }\n' % (float(mirror_ref[i][0]),float(mirror_ref[i][1])) 
	iyaml+='\n'
```

--------------------------------

### Exporting formatted results to CSV

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/process_raw.html

This snippet demonstrates how to structure simulation results into a NumPy array and save them as a CSV file.

```python
res=np.array([
	 ['Name', 'Value (kW)', 'eta Ratio']
    ,['Qall', Qtot,   1]
	,['Qcos', Qcos,   eta_cos]
	,['Qshad', Qshad, eta_shad]
	,['Qfield_abs', Qhst, eta_hst]
	,['Qblcok', Qblock, eta_block]
	,['Qattn',Qattn,  eta_attn]
	,['Qspil ', Qspil,eta_spil]
	,['Qrefl', Qrefl, eta_refl]
	,['Qabs ', Qabs,  eta_abs]
	,['After trimming', 'postprocessed results','-']
	])
	np.savetxt(casedir+'/des_point/result-formatted-designed.csv', res, fmt='%s', delimiter=',')
```

--------------------------------

### find_prog(name, version_required=None)

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/find_solstice.html

Finds the full path to a specific Solstice executable program.

```APIDOC
## find_prog(name, version_required=None)

### Description
Returns the path to a required Solstice executable. On Windows, it resolves the path based on the installation root; on other platforms, it checks the system PATH.

### Parameters
- **name** (str, required) - The stem-name of the program (e.g., 'solpp' for 'solpp.exe').
- **version_required** (str, optional) - If provided, enforces a specific version of Solstice.

### Returns
- **path** (str) - The absolute path to the executable.
```

--------------------------------

### Process raw simulation results

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/process_raw.html

Parses a raw Solstice simulation file and organizes the data into CSV files. Requires the raw file path, save directory, mirror reflectivity, and DNI value.

```python
import numpy as np
import re
import sys
import os
from uncertainties import ufloat
from uncertainties.umath import *
from .output_motab import output_motab 


[docs]def process_raw_results(rawfile, savedir,rho_mirror,dni,verbose=False):
	"""Process the raw Solstice `simul` output into readable CSV files for central receiver systems

	``Arguments``

	  * rawfile (str): the directory of the `simul` file that generated by Solstice
	  * savedir (str): the directory for saving the organised results
	  * rho_mirror (float): mirror reflectivity (needed for reporting energy sums)
	  * dni (float): the direct normal irradiance (W/m2), required to obtain performance of individual heliostat
	  * verbose (bool), write results to disk or not

	``Returns``

	  * efficiency_total (float): the total optical efficiency
	  * performance_hst (numpy array): the breakdown of losses of each individual heliostat
	  * The simulation results are created and written in the `savedir`
		
	"""

	# FIXME this approach seems fundamentally a bit messy... we are carefully
	# load the text output from 'solppraw' and then assuming that we can
	# correctly find the right bits of data in the right place. Wouldn't it
	# be easier and more robust to modify solppraw to create output that can
	# be directly loaded, along with data labels, eg a YAML file? Or to
	# create 'result-raw.csv' directly?

	rows = []
	index = 0
	with open(rawfile) as f:
		for r in f.readlines():
			if index<20:
				pass #sys.stderr.write("Line %d: %s"%(index,r))

			if r[0] == "#":
				#sys.stderr.write("^------Comment\n")
				#comment line
				rows.append([r])
			else:
				rows.append(r.split())			
			index+=1

	# sun direction

	#sys.stderr.write("SUN DIRECTION?\n")
	#sys.stderr.write(rows[0][0]+"\n")
	sun=re.findall("[-+]?\d*\.\d+|\d+", rows[0][0])
	#sys.stderr.write("SUN = %s\n"%(repr(sun),))

	azimuth=sun[0]
	elevation=sun[1]

	def get_rc(row,col):
		return float(rows[row][col])

	# Global results

	num_res=int(get_rc(1,0)) # number of global results
	num_rec=int(get_rc(1,1))
	num_hst=get_rc(1,2)
	num_rays=get_rc(1,3)

	potential=get_rc(2,0) #W
	potential_err=get_rc(2,1)

	absorbed=get_rc(3,0)
	absorbed_err=get_rc(3,1)    

	Fcos=get_rc(4,0)
	Fcos_err=get_rc(4,1)  

	shadow_loss=get_rc(5,0)
	shadow_err=get_rc(5,1)    

	missing_loss=get_rc(6,0)
	missing_err=get_rc(6,1) 

	material_loss=get_rc(7,0)
	material_err=get_rc(7,1)    

	atmospheric_loss=get_rc(8,0)
	atmospheric_err=get_rc(8,1)  

	# Target (receiver)
	# 0 receiver name
	# 1 - 2 id and area
	# 3 - 24 (total 22) front
	# 25- 46 (total 22) back 
	rec_area=0. # m2  

	rec_front_income=0.
	rec_front_income_err=0.
	#rec_no_material_loss=get_rc(num_res+2,5)
	#rec_no_material_loss_err=get_rc(num_res+2,6)
	#rec_no_atmo_loss=get_rc(num_res+2,7)
	#rec_no_atmo_loss_err=get_rc(num_res+2,8)
	#rec_material_loss=get_rc(num_res+2,9)
	#rec_material_loss_err=get_rc(num_res+2,10)
	rec_front_absorbed=0.
	rec_front_absorbed_err=0.
	rec_front_eff=0.
	rec_front_eff_err=0.

	rec_back_income=0.
	rec_back_income_err=0.
	rec_back_absorbed=0.
	rec_back_absorbed_err=0.
	rec_back_eff=0.
	rec_back_eff_err=0.

	rec_id={}
	for i in range(num_rec-1): # -1 the virtual target
		rec_id[i]=get_rc(num_res+2+i,1) # the id number of the receiver
		rec_area+=get_rc(num_res+2+i,2) # m2  
	
		rec_front_income+=get_rc(num_res+2+i,3)
		rec_front_income_err+=get_rc(num_res+2+i,4)
		#rec_no_material_loss=get_rc(num_res+2,5)
		#rec_no_material_loss_err=get_rc(num_res+2,6)
		#rec_no_atmo_loss=get_rc(num_res+2,7)
		#rec_no_atmo_loss_err=get_rc(num_res+2,8)
		#rec_material_loss=get_rc(num_res+2,9)
		#rec_material_loss_err=get_rc(num_res+2,10)
		rec_front_absorbed+=get_rc(num_res+2+i,13)
		rec_front_absorbed_err+=get_rc(num_res+2+i,14)
		rec_front_eff+=get_rc(num_res+2+i,23)
		rec_front_eff_err+=get_rc(num_res+2+i,24)

		rec_back_income+=get_rc(num_res+2+i,25)
		rec_back_income_err+=get_rc(num_res+2+i,26)
		rec_back_absorbed+=get_rc(num_res+2+i,35)
		rec_back_absorbed_err+=get_rc(num_res+2+i,36)
		rec_back_eff+=get_rc(num_res+2+i,-2)
		rec_back_eff_err+=get_rc(num_res+2+i,-1)
```

--------------------------------

### Generate Sun and Atmosphere YAML

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/gen_yaml.html

Defines the sun and atmospheric extinction parameters in the YAML output.

```python
if spectral:
	spectrum = "*solar_spectrum"
else:
	spectrum = None

iyaml += "- sun: %s\n" % (sun.yaml(spectrum),)

if medium>1e-99:
	iyaml+='- atmosphere: {extinction: %s}\n'%medium 
	iyaml+='\n'
```

--------------------------------

### Generate YAML Geometry and Entities

Source: https://solsticepy.readthedocs.io/en/latest/_modules/solsticepy/gen_yaml.html

This snippet demonstrates the iterative process of defining heliostat geometries, pylon structures, and templates, followed by assembling the final scene entities into a YAML file.

```python
	elif receiver=='multi-aperture':
		geom, rec_entt, rcv =multi_aperture_receiver(rec_param, hemisphere)
		iyaml+=geom
	#
	# Heliostats Geometry
	#
	if one_heliostat:
		hst_x=np.r_[hst_pos[0]]
		hst_y=np.r_[hst_pos[1]]
		hst_z=np.r_[hst_pos[2]]
		aim_x=np.r_[hst_aims[0]] 
		aim_y=np.r_[hst_aims[1]]
		aim_z=np.r_[hst_aims[2]]
		num_hst=1
		hst_foc=np.r_[hst_foc]
	else:
		hst_x=hst_pos[:,0]
		hst_y=hst_pos[:,1]
		hst_z=hst_pos[:,2]
		aim_x=hst_aims[:,0]
		aim_y=hst_aims[:,1]
		aim_z=hst_aims[:,2]
		num_hst=len(hst_x)
	slices = 4 # slices for the envelop circle
	pts_hst = [ [-hst_w*0.5, -hst_h*0.5], [-hst_w*0.5, hst_h*0.5], [hst_w*0.5, hst_h*0.5], [hst_w*0.5,-hst_h*0.5] ]
	# CREATE a reflective facet (mirror)
	for i in range(0,num_hst):
		name_hst_g = 'hst_g_'+str(i)
		iyaml+='- geometry: &%s\n' % name_hst_g 
		iyaml+='  - material: *%s\n' % 'material_mirror' 
		#iyaml+='    transform: { translation: %s, rotation: %s }\n' % ([hst_x[i], hst_y[i], hst_z[i]], [0, 0, 0]) )
		iyaml+='    parabol: \n'
		iyaml+='      focal: %s\n' % hst_foc[i]
		iyaml+='      clip: \n'  
		iyaml+='      - operation: AND \n'
		iyaml+='        vertices: %s\n' % pts_hst
		iyaml+='      slices: %d\n' % slices  

	# CREATE the pylon "pylon_g" geometry cylindrical shape
	h_pyl = 0.001 # pylon height
	r_pyl = 0.2 # pylon radius
	slices = 4 # slices for the envelop circle
	iyaml+='- geometry: &%s\n' % 'pylon_g' 
	iyaml+='  - material: *%s\n' % 'material_black' 
	iyaml+='    transform: { translation: %s, rotation: %s }\n' % ([0, 0, -h_pyl*3], [0, 90, 0]) 
	iyaml+='    cylinder: {height: %7.3f, radius: %7.3f, slices: %d }\n' % (h_pyl,r_pyl,slices) 
	#   

	# 
	### Section (5)
	# set the templates
	# (programming objects gathering geometries or pivot and geometries)
	#------------------------------
	# CREATE the heliostat templates
	for i in range(0,num_hst):    
		name_hst_t = 'hst_t_'+str(i)
		iyaml+='- template: &%s\n' % name_hst_t 
		name_hst_n = 'hst_'+ str(i)
		iyaml+='    name: %s\n' % name_hst_n 
		iyaml+='    primary: 0\n'   
		iyaml+='    geometry: *pylon_g\n'
		iyaml+='    children: \n' 
		iyaml+='    - name: pivot\n'
		iyaml+='      zx_pivot: {target: {position: %s}} \n' % ([aim_x[i],aim_y[i],aim_z[i]]) 
		iyaml+='      children: \n'
		iyaml+='      - name: reflect_surface\n'
		iyaml+='        primary: 1\n'
		iyaml+='        transform: {rotation: [-90,0,0]} \n'   
		name_hst_g = 'hst_g_'+str(i)
		iyaml+='        geometry: *%s\n' % name_hst_g 

	# 
	### Section (6)
	# set the entities
	# (gather templates to be created and active in the scene)
	#------------------------------
	#
	# receiver entities
	iyaml+=rec_entt
	#
	# tower entities
	iyaml+='\n- entity:\n'
	iyaml+='    name: tower_e\n'
	iyaml+='    primary: 0\n' 
	iyaml+='    transform: { translation: %s, rotation: %s }\n' % ([0, -tower_r, tower_h*0.5], [0, 0, 0]) 
	iyaml+='    geometry: *%s\n' % 'tower_g'    
	#
	# heliostat entities from the template
	for i in range(0,num_hst):
		name_e ='H_'+str(i)
		name_hst_t = 'hst_t_'+str(i)
		iyaml+='\n- entity:\n'
		iyaml+='    name: %s\n' % name_e
		iyaml+='    transform: { translation: %s, rotation: %s }\n' % ([hst_x[i], hst_y[i], hst_z[i]], [0, 0, 0]) 
		iyaml+='    children: [ *%s ]\n' % name_hst_t    

	with open(outfile_yaml,'w') as f:
		f.write(iyaml)

	with open(outfile_recv,'w') as f:
		f.write(rcv)
```
Tokens:
Raw