.cdf 文件的频谱图

Question

我有一个 .cdf 文件，其中包含变量

Epoch, FEDU and L

。我想绘制一个在 x 轴上具有

Epoch

（代表时间）并变化

L

和

FEDU

的频谱图。我使用的数据位于text。我还尝试了连续三天的绘图。

我尝试过这个，但不知道如何插入

L

def plot_spectrogram(cdf_file, variable_name, datetime_values):
    # Open the CDF file
    cdf = cdflib.CDF(cdf_file)
    
    # Read the variable data
    data = cdf[variable_name][...]
    
    # Define values to remove
    values_to_remove = [-1.e+31, -1.00000e+31, -9.9999998e+30]
    
    # Filter out the values
    filtered_data = np.where(np.isin(data, values_to_remove), np.nan, data)
    
    # Average or sum the filtered data across the alpha dimension
    averaged_data = np.nanmean(filtered_data, axis=2)  # Using np.nanmean to ignore NaN values
    
    # Convert datetime objects to numerical timestamps for plotting
    numerical_times = date2num(datetime_values)
    
    # Plot the aggregated spectrogram
    plt.figure(figsize=(10, 6))
    plt.imshow(averaged_data.T, aspect='auto', origin='lower', cmap='rainbow', extent=[numerical_times[0], numerical_times[-1], 0, averaged_data.shape[1]])
    plt.colorbar(label='Intensity ($cm^2$ s sr keV)')
    plt.xlabel('Time')
    plt.ylabel('Energy (keV)')
    plt.title('Aggregated Spectrogram of {}'.format(variable_name))
    plt.gca().xaxis.set_major_formatter(DateFormatter('%Y-%m-%d %H:%M:%S'))  # Format x-axis ticks as datetime
    plt.xticks(rotation=15)
    plt.tight_layout()
    plt.show()

# Usage example
cdf_files = ['C:/Users/User/Desktop/AB/cdf/H1/rbspa_ect-elec-L3_20140923_v1.0.0.cdf',
             'C:/Users/User/Desktop/AB/cdf/H1/rbspa_ect-elec-L3_20140924_v1.0.0.cdf',
             'C:/Users/User/Desktop/AB/cdf/H1/rbspa_ect-elec-L3_20140925_v1.0.0.cdf']

# Concatenate spectrogram data from all files
datetime_values = []
for cdf_file in cdf_files:
    cdf = cdflib.CDF(cdf_file)
    epoch_values = cdf['Epoch'][...]
    datetime_values.extend(cdflib.cdfepoch.encode(epoch_values))
    cdf.close()

# Plot the concatenated spectrogram
plot_spectrogram(cdf_files[0], 'FEDU', datetime_values)  # Assuming same variable name for all files

最终结果应如下所示，其中 log(flux) 应替换为 FEDU

Answer 1

一种方法是针对选定的间隔或 L 值绘制多个频谱图，可以在单独的图中或作为一个图中的子图。

import cdflib
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.dates import date2num, DateFormatter

def plot_spectrogram_for_l_range(cdf_file, variable_name, datetime_values, l_values, l_range):
    cdf = cdflib.CDF(cdf_file)
    
    data = cdf[variable_name][...]
    l_data = cdf[l_values][...]
    
    values_to_remove = [-1.e+31, -1.00000e+31, -9.9999998e+30]
    
    filtered_data = np.where(np.isin(data, values_to_remove), np.nan, data)
    
    l_mask = (l_data >= l_range[0]) & (l_data <= l_range[1])
    data_within_l = filtered_data[l_mask, :]
    
    aggregated_data = np.nanmean(data_within_l, axis=0)  
    
    numerical_times = date2num(datetime_values)
    
    numerical_times_within_l = numerical_times[l_mask]
    
    plt.figure(figsize=(10, 6))
    plt.imshow(aggregated_data.T, aspect='auto', origin='lower', cmap='rainbow', extent=[numerical_times_within_l[0], numerical_times_within_l[-1], 0, aggregated_data.shape[1]])
    plt.colorbar(label='Intensity ($cm^2$ s sr keV)')
    plt.xlabel('Time')
    plt.ylabel('Energy (keV)')
    plt.title(f'Aggregated Spectrogram of {variable_name} for L range {l_range}')
    plt.gca().xaxis.set_major_formatter(DateFormatter('%Y-%m-%d %H:%M:%S'))
    plt.xticks(rotation=45)
    plt.tight_layout()
    plt.show()


l_range = [4, 6]  

cdf_files = [r"******\Downloads\rbspa_rel03_ect-rept-sci-L3_20140101_v5.0.0.cdf"]

datetime_values = []
for cdf_file in cdf_files:
    cdf = cdflib.CDF(cdf_file)
    epoch_values = cdf['Epoch'][...]
    datetime_values.extend(cdflib.cdfepoch.encode(epoch_values))
    
plot_spectrogram_for_l_range(cdf_files[0], 'FEDU', datetime_values, 'L', l_range)

这给出了