mirror of
https://github.com/nqrduck/LimeDriverBindings.git
synced 2024-06-27 16:09:08 +00:00
142 lines
5.2 KiB
Python
142 lines
5.2 KiB
Python
import h5py
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import numpy as np
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import matplotlib.pyplot as plt
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# class for accessing data of stored HDF5 file this is from the limr program by andrin doll
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class HDF():
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def __init__(self, filename = ''):
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# check first for the filename provided
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if filename != '':
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self.HDFsrc = filename
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else:
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self.HDFsrc = ''
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# get data
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self.__get_data()
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# just an alias for __init__ that does load a specific file
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def load(self, filename = ''):
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self.__init__(filename)
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# gets the data of the file
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def __get_data(self):
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if (self.HDFsrc == '') | (self.HDFsrc == []):
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# initialize all as empty
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self.tdy = []
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self.tdx = []
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self.attrs = []
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self.parsoutp = {}
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self.parvar = {}
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else:
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f = h5py.File(self.HDFsrc, 'r')
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HDFkeys = list(f.keys())
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for ii, HDFkey in enumerate(HDFkeys):
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if ii == 0:
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# initialize data array
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dsize = f[HDFkey].shape
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inddim = dsize[0]
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self.tdy = np.zeros((int(dsize[1]/2), int(dsize[0] * len(HDFkeys))),dtype=np.complex_)
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# initialize the output objects
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self.attrs = [dynclass() for jj in range(len(HDFkeys))]
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# get the attribute keys
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self.parsoutp = {}
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ii_oupargs = 0
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for item in f[HDFkey].attrs.items():
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itemname = item[0][5:]
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itemarg = item[0][1:4]
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if not ('///' in itemarg):
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self.parsoutp[itemarg] = [ item[1], itemname]
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else:
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self.parsoutp['//'+str(ii_oupargs)] = [ item[1], itemname]
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ii_oupargs+=1
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# look for eventual parvar lists
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self.parvar = {}
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for item in f.attrs.items():
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self.parvar[item[0]] = item[1]
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# Get the data
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data_raw = np.array(f[HDFkey])
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try:
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self.tdy[:,ii*inddim:(ii+1)*inddim] = np.transpose(np.float_(data_raw[:,::2])) + 1j*np.transpose(np.float_(data_raw[:,1::2]))
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except:
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pass
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# Get the arguments
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ii_oupargs = 0
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for item in f[HDFkey].attrs.items():
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itemname = item[0][5:]
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itemarg = item[0][1:4]
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if not ('///' in itemarg):
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setattr(self.attrs[ii], itemarg, item[1])
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else:
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setattr(self.attrs[ii], '//'+str(ii_oupargs), item[1])
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ii_oupargs+=1
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f.close()
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srate_MHz = getattr(self.attrs[0], 'sra')*1e-6
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self.tdx = 1/srate_MHz*np.arange(self.tdy.shape[0])
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# get an argument by matching the text description
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def attr_by_txt(self, pattern):
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for key in sorted(self.parsoutp):
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if pattern in self.parsoutp[key][1]: # pattern match
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attr = getattr(self.attrs[0], key)
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try:
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ouparr = np.zeros( ( len(attr), len(self.attrs)), attr.dtype)
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except:
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ouparr = np.zeros( ( 1, len(self.attrs)), attr.dtype)
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for ii in np.arange(len(self.attrs)):
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ouparr[:,ii] = getattr(self.attrs[ii], key)
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return np.transpose(ouparr)
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print('Problem obtaining the attribute from the description using the pattern ' + pattern + '!')
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print('Valid descriptions are: ')
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self.print_params()
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# get an argument by key
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def attr_by_key(self, key):
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if key in dir(self.attrs[0]):
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attr = getattr(self.attrs[0], key)
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try:
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ouparr = np.zeros( ( len(attr), len(self.attrs)), attr.dtype)
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except:
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ouparr = np.zeros( ( 1, len(self.attrs)), attr.dtype)
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for ii in np.arange(len(self.attrs)):
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ouparr[:,ii] = getattr(self.attrs[ii], key)
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return np.transpose(ouparr)
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print('Problem obtaining the attribute from key ' + key + '!')
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print('Valid keys are: ')
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self.print_params()
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# print the arguments
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def print_params(self, ouponly = False):
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for key in sorted(self.parsoutp):
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val = getattr(self.attrs[0], key)
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if not('//' in key): # input argument?
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if ouponly: continue;
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print('{:<5}: {:>50} {:<25}'.format(key, val, self.parsoutp[key][1]))
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def plot_dta(self):
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plt.plot(self.tdx, self.tdy.real)
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plt.xlabel('$t$ [$\mu$s]')
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plt.ylabel('$y$ [Counts]')
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plt.show()
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# empty class to store dynamic attributes, basically for the attributes in HDF keys
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class dynclass:
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pass |