def save_cube_process(self, output_filename, cube_peaks, peak_count):
"""
Saves the cube_fit as an hdf5 file
"""
output_file = h5py.File(output_filename,'w')
output_file.attrs['peak_count'] = peak_count
peaks = output_file.create_group("peaks")
for peak in np.arange(peak_count):
peak_holder = peaks.create_group("Peak%d"%peak)
peak_function = fit_analysis.get_peak_function(cube_peaks, peak)
peak_name = fit_analysis.get_peak_name(cube_peaks, peak)
peak_penalty_function = fit_analysis.get_peak_penalty_function(cube_peaks,peak)
peak_ranges = fit_analysis.get_peak_ranges(cube_peaks, peak)
peak_variables = fit_analysis.get_peak_variables(cube_peaks, peak)
peak_holder.attrs['function'] = peak_function
peak_holder.attrs['name'] = peak_name
peak_holder.attrs['penalty_function'] = peak_penalty_function
peak_holder.attrs['ranges'] = peak_ranges
peak_holder.attrs['variables'] = peak_variables
for variable in peak_variables:
image_cube = self.get_image_cube(variable)
image = fit_analysis.get_image_from_cube(image_cube, peak)
peak_holder.create_dataset(variable, data=image)
output_file.create_dataset("integrated_residuals",
data=self.cube_residuals)
output_file.close()
def plot_peaks(self, image_cube, peak_count):
for peak_number in np.arange(peak_count):
axes = plt.subplot(1, peak_count, peak_number)
axes.set_title("Peak Number %s"%str(peak_number+1))
image = fit_analysis.get_image_from_cube(image_cube, peak_number)
plt.imshow(image, interpolation='nearest')
plt.colorbar()
def save_cube_process(self, output_filename, cube_peaks, peak_count):
"""
Saves the cube_fit as an hdf5 file
"""
output_file = h5py.File(output_filename, 'w')
output_file.attrs['peak_count'] = peak_count
peaks = output_file.create_group("peaks")
for peak in np.arange(peak_count):
peak_holder = peaks.create_group("Peak%d" % peak)
peak_function = fit_analysis.get_peak_function(cube_peaks, peak)
peak_name = fit_analysis.get_peak_name(cube_peaks, peak)
peak_penalty_function = fit_analysis.get_peak_penalty_function(
cube_peaks, peak)
peak_ranges = fit_analysis.get_peak_ranges(cube_peaks, peak)
peak_variables = fit_analysis.get_peak_variables(cube_peaks, peak)
peak_holder.attrs['function'] = peak_function
peak_holder.attrs['name'] = peak_name
peak_holder.attrs['penalty_function'] = peak_penalty_function
peak_holder.attrs['ranges'] = peak_ranges
peak_holder.attrs['variables'] = peak_variables
for variable in peak_variables:
image_cube = self.get_image_cube(variable)
image = fit_analysis.get_image_from_cube(image_cube, peak)
peak_holder.create_dataset(variable, data=image)
output_file.create_dataset("integrated_residuals",
data=self.cube_residuals)
output_file.close()
def plot_peaks(self, image_cube, peak_count):
for peak_number in np.arange(peak_count):
axes = plt.subplot(1, peak_count, peak_number)
axes.set_title("Peak Number %s" % str(peak_number + 1))
image = fit_analysis.get_image_from_cube(image_cube, peak_number)
plt.imshow(image, interpolation='nearest')
plt.colorbar()