Here are the highlights of this release: - Aggregated test and JaCoCo reports - Marking additional test source directories as tests in IntelliJ - Support for Adoptium JDKs in Java toolchains For more details see https://docs.gradle.org/7.4/release-notes.html Starting a Gradle Daemon (subsequent builds will be faster) FAILURE: Build failed with an exception. * Where: Build file '/data/jenkins/workspace/STM-Android/build.gradle' line: 17 * What went wrong: A problem occurred evaluating root project 'PanGu'. > For input string: ""这个报错是jenkins的打包报错，具体是什么问题

根据您提供的信息，这个错误是由于在构建文件“/data/jenkins/workspace/STM-Android/build.gradle”的第17行中出现了输入字符串的问题。具体原因可能需要查看构建文件的内容，以及构建时使用的Gradle版本和配置。您可以检查一下构建文件中第17行的代码，看看是否存在语法错误或其他问题。另外，您也可以查看Gradle的日志，以获取更详细的错误信息，从而更好地排除问题。

相关问题

Automatize this process for all the x-ray diffraction files and display x-ray diagrams on asame figure with the subplot function. In addition, you should display on each diagram : 1. the file name 2. the position angle of the first peak computed with the fitting function3. vertical lines that highlights the peak positions

To automate this process for all the x-ray diffraction files, you can use a loop to iterate through each file in a directory. Here's an example code snippet in Python:

import os
import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import find_peaks
from scipy.optimize import curve_fit

# define the fitting function
def gaussian(x, a, x0, sigma):
    return a * np.exp(-(x - x0) ** 2 / (2 * sigma ** 2))

# set up the subplot figure
fig, axs = plt.subplots(nrows=3, ncols=3, figsize=(12, 8))

# iterate through each file in the directory
for i, filename in enumerate(os.listdir('/path/to/directory')):
    # load the data from the file
    data = np.loadtxt(filename, skiprows=2)
    x = data[:, 0]
    y = data[:, 1]

    # find the peaks in the data
    peaks, _ = find_peaks(y, height=0.05)

    # fit a Gaussian to the first peak
    p0 = [1, x[peaks[0]], 0.1]
    popt, _ = curve_fit(gaussian, x, y, p0=p0)

    # plot the data and the fitted Gaussian
    ax = axs[i // 3, i % 3]
    ax.plot(x, y)
    ax.plot(x, gaussian(x, *popt), 'r-')
    ax.set_title(filename)
    ax.axvline(popt[1], color='gray', linestyle='--')
    for peak in peaks:
        ax.axvline(x[peak], color='gray', linestyle='--')

# add some spacing between the subplots
plt.tight_layout()

# display the figure
plt.show()

This code assumes that all the x-ray diffraction files are in the same directory. You can modify the `os.listdir` function to point to the correct directory.

The `find_peaks` function is used to find the peaks in the data. The `height` parameter determines the minimum height of the peaks. You can adjust this parameter to suit your needs.

The `curve_fit` function is used to fit a Gaussian to the first peak. The initial parameters for the Gaussian are set using the `p0` parameter. You can adjust these parameters to improve the fit.

The `ax.axvline` function is used to draw vertical lines at the position of the fitted peak and the detected peaks. The `ax.set_title` function is used to display the filename as the title of the subplot.

Hope this helps!

y be called inside of the body of a function component. This could happen for one of the following reasons: 1. You might have mismatching v

This error message usually appears when there is a mismatch between the number of opening and closing parentheses or curly braces in a function component, causing the code to be invalid.

To fix this error, you should check the code and ensure that all parentheses and curly braces are properly matched. You may also want to use an editor that highlights matching parentheses or braces to help identify any mismatches.

Additionally, it's important to note that the error message may also indicate that a variable or function is not defined or is out of scope. In this case, you should ensure that all variables and functions are properly declared and accessible within the component.