from ruamel import yaml import os, sys import numpy as np import matplotlib.pyplot as plt import seaborn as sns sns.set(style="ticks") import cmocean from SEGPlot import * from matplotlib.ticker import FormatStrFormatter import matplotlib.ticker as plticker def slicedict(d, s): return {k:v for k,v in d.items() if k.startswith(s)} # Converts Lemma/Merlin/Akvo serialized Eigen arrays into numpy ones for use by Python class VectorXr(yaml.YAMLObject): """ Converts Lemma/Merlin/Akvo serialized Eigen arrays into numpy ones for use by Python """ yaml_tag = u'VectorXr' def __init__(self, array): self.size = np.shape(array)[0] self.data = array.tolist() def __repr__(self): # Converts to numpy array on import return "np.array(%r)" % (self.data) class AkvoData(yaml.YAMLObject): """ Reads an Akvo serialized dataset into a standard python dictionary """ yaml_tag = u'AkvoData' def __init__(self, array): pass #self.size = np.shape(array)[0] #self.Imp = array.tolist() def __repr__(self): # Converts to a dictionary with Eigen vectors represented as Numpy arrays return self def loadAkvoData(fnamein): """ Loads data from an Akvo YAML file. The 0.02 is hard coded as the pulse length. This needs to be corrected in future kernel calculations. The current was reported but not the pulse length. """ fname = (os.path.splitext(fnamein)[0]) with open(fnamein, 'r') as stream: try: AKVO = (yaml.load(stream, Loader=yaml.Loader)) except yaml.YAMLError as exc: print(exc) return AKVO def plotQt( akvo ): plt.style.use('ggplot') #plt.style.use('seaborn-white') for pulse in akvo.Gated: if pulse[0:5] == "Pulse": #print(akvo.GATED[pulse].keys()) nq = akvo.Pulses[pulse]["current"].size for chan in slicedict(akvo.Gated[pulse], "Chan."): # accumulate pulse moments CA = np.zeros( (nq, len( akvo.Gated[pulse]["abscissa"].data )) ) RE = np.zeros( (nq, len( akvo.Gated[pulse]["abscissa"].data )) ) IM = np.zeros( (nq, len( akvo.Gated[pulse]["abscissa"].data )) ) for q in range(nq): #plt.plot( akvo.Gated[pulse]["abscissa"].data, akvo.Gated[pulse][chan]["Q-" + str(q)+" CA"].data ) CA[q] = akvo.Gated[pulse][chan]["Q-" + str(q)+" CA"].data RE[q] = akvo.Gated[pulse][chan]["Q-" + str(q)+" RE"].data IM[q] = akvo.Gated[pulse][chan]["Q-" + str(q)+" IM"].data #X[q] = akvo.Gated[pulse][chan]["Q-" + str(q)+" RE"].data Windows = akvo.Gated[pulse]["windows"].data Centres = akvo.Gated[pulse]["abscissa"].data Q = np.array(akvo.Pulses[pulse]["current"].data) print("pulse length ", akvo.pulseLength[0]) Q *= akvo.pulseLength[0] fig = plt.figure( figsize=( pc2in(20), pc2in(26) ) ) ax1 = fig.add_axes([.25,.05,.6,.9]) #im = ax1.pcolormesh(Windows, Q, CA, cmap=cmocean.cm.curl_r, vmin=-np.max(np.abs(CA)), vmax=(np.max(np.abs(CA)))) im = ax1.pcolormesh(Centres, Q, CA, cmap=cmocean.cm.curl_r, vmin=-np.max(np.abs(CA)), vmax=(np.max(np.abs(CA)))) cb = plt.colorbar( im, orientation='horizontal', pad=.175, ) cb.set_label("FID (nV)", fontsize=10) cb.ax.tick_params(labelsize=10) ax1.set_yscale('log') ax1.set_ylabel("Q (A$\cdot$s)", fontsize=10) ax1.set_xscale('log') ax1.set_xlabel("time (s)", fontsize=10) #loc = plticker.MultipleLocator(25) #base=50.0) # this locator puts ticks at regular intervals #loc = plticker.MaxNLocator(5, steps=[1,2]) #base=50.0) # this locator puts ticks at regular intervals #ax1.xaxis.set_major_locator(loc) #ax1.xaxis.set_minor_locator(plticker.NullLocator()) ax1.xaxis.set_major_formatter(FormatStrFormatter('%2.0f')) ax1.yaxis.set_major_formatter(FormatStrFormatter('%2.1f')) #plt.figure() #sns.kdeplot(Windows, Q, CA) #, kind="hex", color="#4CB391") #sns.heatmap(CA, annot=False, center=0) #plt.matshow(RE) #plt.matshow(IM) plt.savefig("data.pgf") plt.savefig("data.png", dpi=300) plt.show() if __name__ == "__main__": akvo = loadAkvoData( sys.argv[1] ) #, "Chan. 1") plotQt(akvo)