Fix: Fixes for hdf5 generation

config_generators/fersxml.py

@@ -14,7 +14,7 @@ def generate_chirp(ramp_period, sample_rate, bandwidth, init_freq=0, tau=0, phi=
  phi (int, optional): Phase offset (rad). Defaults to 0.
 
  Returns:
- nnp.array: chirp data array
+ np.array: chirp data array
  """
 
  import numpy as np
@@ -24,6 +24,76 @@ def generate_chirp(ramp_period, sample_rate, bandwidth, init_freq=0, tau=0, phi=
 
 
  return np.exp(1.j*(np.pi*bandwidth/(2*max(t_chirp))*pow((t_chirp - tau), 2) + 2*np.pi*init_freq*(t_chirp - tau) + phi))
+
+ def write_hdf5(IQ_data, file_name):
+ """Write IQ data to an HDF5 file.
+
+ Args:
+ IQ_data (_type_): _description_
+ filename (_type_): _description_
+ """
+
+ import os as os
+
+ _, file_extension = os.path.splitext(file_name)
+ if file_extension != ".hdf5":
+ file_name = file_name + ".hdf5"
+
+ import h5py
+ import numpy as np
+
+ h5 = h5py.File(file_name, 'w')
+ h5.create_dataset('/I/value', data=np.real(IQ_data))
+ h5.create_dataset('/Q/value', data=np.imag(IQ_data))
+ h5.close()
+
+
+ def read_hdf5(filename):
+ """ Read IQ data from an HDF5 file.
+
+ Args:
+ filename (_type_): _description_
+
+ Returns:
+ _type_: _description_
+ """
+
+ import os
+ import h5py
+ import numpy as np
+
+ if (os.path.exists(filename) == False):
+ print("HDF5 file not found. Please check the path.")
+ exit()
+
+ h5 = h5py.File(filename, 'r')
+
+ dataset_list = list(h5.keys())
+
+ # read attributes
+ # attribute_list = h5[dataset_list[0]].attrs.keys()
+ # for attr in attribute_list:
+ # print(attr, h5[dataset_list[0]].attrs[attr])
+
+ scale = np.float64(h5[dataset_list[0]].attrs['fullscale'])
+ # rate = np.float64(h5[dataset_list[0]].attrs['rate'])
+ # time = np.float64(h5[dataset_list[0]].attrs['time'])
+
+ n_pulses = int(np.floor(np.size(dataset_list)/2))
+ ns_pulse = int(np.size(h5[dataset_list[0]]))
+
+ i_matrix = np.zeros((n_pulses, ns_pulse), dtype='float64')
+ q_matrix = np.zeros((n_pulses, ns_pulse), dtype='float64')
+
+ for i in range(0, n_pulses):
+ i_matrix[i, :] = np.array(h5[dataset_list[2*i + 0]], dtype='float64')
+ q_matrix[i, :] = np.array(h5[dataset_list[2*i + 1]], dtype='float64')
+
+ dataset = np.array(i_matrix + 1j*q_matrix).astype('complex128')
+
+ dataset *= scale
+
+ return dataset
 
 class SimulationConfiguration:
  def __init__(self, name):

config_generators/tutorial_notebook.ipynb

@@ -38,7 +38,7 @@
  },
  {
  "cell_type": "code",
- "execution_count": 2,
+ "execution_count": 1,
  "metadata": {},
  "outputs": [],
  "source": [
@@ -64,7 +64,7 @@
  },
  {
  "cell_type": "code",
- "execution_count": 3,
+ "execution_count": 2,
  "metadata": {},
  "outputs": [
  {
@@ -80,6 +80,7 @@
  ],
  "source": [
  "import fersxml as fersxml\n",
+ "import numpy as np\n",
  "import matplotlib.pyplot as plt\n",
  "from scipy.signal import spectrogram\n",
  "\n",
@@ -114,11 +115,12 @@
  },
  {
  "cell_type": "code",
- "execution_count": null,
+ "execution_count": 4,
  "metadata": {},
  "outputs": [],
  "source": [
- "file_name = \"transmission\""
+ "file_name = \"lfm_transmision.hdf5\"\n",
+ "fersxml.SignalGenerator.write_hdf5(tx_chirp,file_name)"
  ]
  },
  {
@@ -147,9 +149,6 @@
  "SimulationConfiguration.set_simulaion_parameters(\"0\", \"5\",\"299792458\", \"1\", \"2048000\", \"16\")\n",
  "SimulationConfiguration.set_export_options(xml=\"false\",csv=\"false\",binary=\"false\",csvbinary=\"false\")\n",
  "\n",
- "# Define signals which may be used by platforms\n",
- "SimulationConfiguration.define_pulse(\"pulse1\",\"pulse1.hdf5\",\"1\", \"1\",\"1000000\")\n",
- "\n",
  "# Define timing sources which may be used by platforms\n",
  "SimulationConfiguration.define_timing_source(\"clock1\",\"true\",\"0\",\"0\",\"10000000\",\"0\",\"0\",\"0\",\"0\")\n",
  "\n",
@@ -159,6 +158,26 @@
  "\n"
  ]
  },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Define Signal Used In Simulation\n",
+ "\n",
+ "Use the named defined when writing hdf files"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "\n",
+ "# Define signals which may be used by platforms\n",
+ "SimulationConfiguration.define_pulse(\"pulse1\",file_name,\"1\", \"1\",\"1000000\")\n"
+ ]
+ },
  {
  "cell_type": "markdown",
  "metadata": {},