first public appearance of the repository

Author: ibegleris

Conversion_efficiency_post_proc.ipynb

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+# SM-FOPO
+
+The repository holds the model of a unidirectional single mode FOPO based upon the system shown in. 
+There is now a build script that downloads and installs miniconda with all the equilavent packadges needed. Beware to have sudo now for MPICH if not already installed.
+
+<p align="center">
+<img src="https://github.com/ibegleris/strict-SM-FOPO/blob/master/build_data/FOPO.jpg">
+</p>

Conversion_efficiency_post_proc.py

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+channels:
+   - intel

README.md

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+channels:
+  - defaults

build_data/.conda_intel

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+channels:
+  -defaults

build_data/.condarc_default

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+wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh
+bash miniconda.sh -b -p $HOME/miniconda
+rm minconda.sh
+export PATH="$HOME/miniconda/bin:$PATH"
+hash -r
+conda config --set always_yes yes --set changeps1 no
+conda update conda -y
+conda config --add channels intel
+conda create -n intel intelpython3_core python=3
+source activate intel
+conda install cython numpy scipy matplotlib pandas h5py pytables jupyter joblib numba pytest nose -y
+source deactivate
+rm -rf ../.condarc
+mv build_data/.condarc_default ../.condarc
+mv build_data/.condarc_default ~/miniconda/envs/intel/.condarc
+conda update conda -y
+conda install numpy scipy matplotlib jupyter pandas h5py pytables jupyter numba pytest nose -y
+conda install python=3.6 -y
+if [ "$1" != 'cluster' ]; then
+	sudo apt-get update
+	sudo apt-get install mpich -y 
+fi
+echo 'export PATH="/home/$USER/miniconda/bin:$PATH"' >> ~/.bashrc
+source activate intel
+git clone https://github.com/mpi4py/mpi4py.git
+cd mpi4py
+python setup.py build
+python setup.py install
+cd ..
+rm -rf mpi4py
+pytest unittesting_scripts.py

build_data/.condarc_intel

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+import matplotlib as mpl
+mpl.use('Agg')
+import matplotlib.pyplot as plt
+import numpy as np
+import os
+from scipy.constants import c
+import h5py
+
+def w2dbm(W, floor=-100):
+	"""This function converts a power given in W to a power given in dBm.
+	   Inputs::
+		   W(float): power in units of W
+	   Returns::
+		   Power in units of dBm(float)
+	"""
+	if type(W) != np.ndarray:
+		if W > 0:
+			return 10. * np.log10(W) + 30
+		elif W == 0:
+			return floor
+		else:
+			print(W)
+			raise(ZeroDivisionError)
+	a = 10. * (np.ma.log10(W)).filled(floor/10-3) + 30
+	return a
+
+plt.gca().get_yaxis().get_major_formatter().set_useOffset(False)
+plt.gca().get_xaxis().get_major_formatter().set_useOffset(False)
+
+
+def plotter_dbm(index, nm, sim_wind, u, U, P0_p, P0_s, f_p, f_s, which,ro, pump_wave = '',filename=None, title=None, im=0, plots = True):
+	#u, U = np.reshape(u,(np.shape(u)[-1], np.shape(u)[0])), np.reshape(u,(np.shape(U)[-1], np.shape(U)[0]))
+	if plots == True:
+		fig = plt.figure(figsize=(20.0, 10.0))
+
+		plt.plot(1e-3*c/sim_wind.fv, 
+				w2dbm(np.abs(U[:,which])**2), '-*')
+		#plt.gca().get_yaxis().get_major_formatter().set_useOffset(False)
+		#plt.gca().get_xaxis().get_major_formatter().set_useOffset(False)
+		plt.xlabel(r'$\lambda (nm)$', fontsize=18)
+		plt.ylabel(r'$Spectrum (a.u.)$', fontsize=18)
+		plt.ylim([-80, 100])
+		plt.xlim([np.min(sim_wind.lv), np.max(sim_wind.lv)])
+		plt.xlim([900, 1250])
+		plt.title(title)
+		plt.grid()
+		if type(im) != int:
+			newax = fig.add_axes([0.8, 0.8, 0.2, 0.2], anchor='NE')
+			newax.imshow(im)
+			newax.axis('off')
+		if filename == None:
+			plt.show()
+		else:
+			plt.savefig('output'+pump_wave+'/output'+str(index)+'/figures/wavelength/'+filename, bbox_inched='tight')
+
+		plt.close(fig)
+
+		fig = plt.figure(figsize=(20.0, 10.0))
+		plt.plot(sim_wind.fv, w2dbm(np.abs(U[:,which])**2), '-*')
+		#plt.gca().get_yaxis().get_major_formatter().set_useOffset(False)
+		#plt.gca().get_xaxis().get_major_formatter().set_useOffset(False)
+		plt.xlabel(r'$f (THz)$', fontsize=18)
+		plt.ylabel(r'$Spectrum (a.u.)$', fontsize=18)
+		#plt.xlim([np.min(sim_wind.fv), np.max(sim_wind.fv)])
+		plt.ylim([-20, 120])
+		#plt.xlim(270,300)
+		plt.title(str(f_p)+' ' +str(f_s))
+		plt.grid()
+		if type(im) != int:
+			newax = fig.add_axes([0.8, 0.8, 0.2, 0.2], anchor='NE')
+			newax.imshow(im)
+			newax.axis('off')
+		if filename == None:
+			plt.show()
+		else:
+			plt.savefig('output'+pump_wave+'/output'+str(index)+'/figures/freequency/'+filename, bbox_inched='tight')
+		plt.close(fig)
+
+		fig = plt.figure(figsize=(20.0, 10.0))
+		
+		plt.plot(sim_wind.t,np.abs(u[:, which])**2, '*-')
+		#plt.gca().get_yaxis().get_major_formatter().set_useOffset(False)
+		plt.title('time space')
+		#plt.ylim([0, 160])
+		plt.grid()
+		plt.xlabel(r'$t(ps)$')
+		plt.ylabel(r'$Spectrum$')
+		if type(im) != int:
+			newax = fig.add_axes([0.8, 0.8, 0.2, 0.2], anchor='NE')
+			newax.imshow(im)
+			newax.axis('off')
+
+		if filename == None:
+			plt.show()
+		else:
+
+			plt.savefig('output'+pump_wave+'/output'+str(index)+'/figures/time/'+filename)
+		plt.close(fig)
+			
+
+	if filename is not(None):
+		if filename[:4] != 'port': 
+			layer = filename[-1]+'/'+filename[:-1]
+		else:
+			layer = filename
+		try:
+			
+			save_variables('data_large', layer, filepath='output'+pump_wave+'/output'+str(index)+'/data/', U = U[:,which], t=sim_wind.t, u=u[:,which],
+						   fv=sim_wind.fv, lv=sim_wind.lv,
+						   which=which, nm=nm, P0_p=P0_p, P0_s=P0_s, f_p=f_p, f_s=f_s, ro = ro)
+		except RuntimeError:
+			os.system('rm output'+pump_wave+'/output'+str(index)+'/data/data_large.hdf5')
+			save_variables('data_large', layer, filepath='output'+pump_wave+'/output'+str(index)+'/data/', U=U[:,which], t=sim_wind.t, u=u[:,which],
+						   fv=sim_wind.fv, lv=sim_wind.lv,
+						   which=which, nm=nm, P0_p=P0_p, P0_s=P0_s, f_p=f_p, f_s=f_s, ro = ro)
+			pass
+
+	return 0
+
+
+def plotter_dbm_load():
+	# class sim_window(object):
+	plotter_dbm(nm, sim_wind, Uabs, u, which)
+	return None
+
+
+
+def animator_pdf_maker(rounds, pump_index):
+	"""
+	Creates the animation and pdf of the FOPO at different parts of the FOPO 
+	using convert from imagemagic. Also removes the pngs so be carefull
+
+	"""
+	print("making pdf's and animations.")
+	space = ('wavelength', 'freequency', 'time')
+	for sp in space:
+		file_loc = 'output/output'+str(pump_index)+'/figures/'+sp+'/'
+		strings_large = ['convert '+file_loc+'00.png ']
+		for i in range(4):
+			strings_large.append('convert ')
+		for ro in range(rounds):
+			for i in range(4):
+				strings_large[i+1] += file_loc+str(ro)+str(i+1)+'.png '
+			for w in range(1, 4):
+				if i == 5:
+					break
+				strings_large[0] += file_loc+str(ro)+str(w)+'.png '
+		for i in range(4):
+			os.system(strings_large[i]+file_loc+str(i)+'.pdf')
+
+		file_loca = file_loc+'portA/'
+		file_locb = file_loc+'portB/'
+		string_porta = 'convert '
+		string_portb = 'convert '
+		for i in range(rounds):
+			string_porta += file_loca + str(i) + '.png '
+			string_portb += file_locb + str(i) + '.png '
+
+		string_porta += file_loca+'porta.pdf '
+		string_portb += file_locb+'portb.pdf '
+		os.system(string_porta)
+		os.system(string_portb)
+
+		for i in range(4):
+			os.system(
+				'convert -delay 30 '+file_loc+str(i)+'.pdf '+file_loc+str(i)+'.mp4')
+		os.system('convert -delay 30 ' + file_loca +
+				  'porta.pdf ' + file_loca+'porta.mp4 ')
+		os.system('convert -delay 30 ' + file_locb +
+				  'portb.pdf ' + file_locb+'portb.mp4 ')
+
+		for i in (file_loc, file_loca, file_locb):
+			print('rm ' + i + '*.png')
+			os.system('rm ' + i + '*.png')
+		os.system('sleep 5')
+	return None
+
+
+def read_variables(filename, layer, filepath=''):
+	with h5py.File(filepath+str(filename)+'.hdf5', 'r') as f:
+		D = {}
+		for i in f.get(layer).keys():
+			try: 
+				D[str(i)] = f.get(layer + '/' + str(i)).value
+			except AttributeError:
+				pass
+	return D
+
+
+def save_variables(filename, layers, filepath='', **variables):
+	with h5py.File(filepath + filename + '.hdf5', 'a') as f:
+		for i in (variables):
+			f.create_dataset(layers+'/'+str(i), data=variables[i])
+	return None

build_data/FOPO.jpg

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+import numpy as np
+import scipy.fftpack as scifft
+"""
+This file was made to test the speed of the fft's before they are used. After
+Intel released their own Scipy it became obsulete since intel scipy is always faster
+"""
+sfft, isfft = scifft.fft, scifft.ifft
+nfft,infft = np.fft.fft, np.fft.ifft
+from time import time
+try:
+	import accelerate.mkl.fftpack as mklfft
+	mfft, imfft = mklfft.fft, mklfft.ifft
+	import accelerate
+	complex128 = accelerate.numba.complex128
+	vectorize = accelerate.numba.vectorize
+	def timing(N, nm,times):
+		a = np.random.rand(2**N, nm)*100 + 1j*np.random.rand(2**N, nm)*100
+		dt = []
+		method_names = ('scipy','mklfft','numpy')
+		methods = (scifft.ifft,mklfft.ifft,np.fft.ifft)
+		dt_average = []
+		for method in methods:
+			dt = []
+			for i in range(times):
+				t = time()
+				test = method(a.T).T
+				t = time() - t
+
+				dt.append(t)
+			dt_average.append(np.average(dt))
+		
+
+		top = np.argsort(dt_average)
+		method_sorted = [method_names[i] for i in top]
+		dt_average_sorted = [dt_average[i] for i in top]
+		return method_sorted ,dt_average_sorted
+
+
+	def pick(N,nm,times,num_cores):
+		if num_cores != 1:
+			a = timing(N, nm, times)[0][0]
+		else:
+			a = 'scipy'
+
+		if a == 'scipy':
+			fft, ifft = sfft, isfft 
+		elif a == 'mklfft':
+			fft, ifft = mfft, imfft
+		else:
+			fft, ifft = nfft,infft
+		print(fft, ifft)
+		return fft,ifft,a
+
+
+except ImportError:
+	#print("You dont have accelerate on this system, defaulting to scipy")
+	def pick(N,nm,times,num_cores):
+		
+		fft, ifft = sfft, isfft 
+		
+		return fft, ifft,'scipy'
+
+
+
+
+if __name__ == '__main__':
+	import matplotlib.pyplot as plt
+	points = []
+	start = 100
+	time1 = []
+	time2 = []
+	time3 = []
+	for i in range(1,start,1):
+		points.append(i)
+		a ,b = timing(12,1,i)
+		time1.append(b[0])
+		time2.append(b[1])
+
+		time3.append(b[2])
+		names = a
+	plt.plot(points, time1, label= names[0])
+	plt.plot(points, time2, label= names[1])
+
+	plt.plot(points, time3, label= names[2])
+	plt.legend()
+	plt.show()