import matplotlib.pyplot as plt import numpy as np import math def calculate_pressure(K, H, S, V1, T2, V2, theta, d): if H >= S: P = (K * H) / (S * (d/V1 + T2) * V2 * math.tan(theta)) else: P = (K * (S - (S - H) / 2)) / (S * (d/V1 + T2) * V2 * math.tan(theta)) return P K = 1.5 H = 7.5 S = 10 V1 = 300 T2 = 5 V2 = 10 theta = np.radians(3) d_array = np.linspace(0, 1000, 10000) P_array = np.array([calculate_pressure(K, H, S, V1, T2, V2, theta, d) for d in d_array]) Z_array = (d_array / V1 + T2) * V2 + d_array mask = P_array >= 0.8 plt.plot(d_array[mask], Z_array[mask]) plt.xlabel('d') plt.ylabel('Z') plt.show()在图上标出线段两端点的坐标值
时间: 2024-03-24 07:41:20 浏览: 13
根据提供的代码,您可以使用以下代码标记出线段两端点的坐标值:
```python
# 找到线段两端点的坐标值
point1 = (d_array[mask][0], Z_array[mask][0])
point2 = (d_array[mask][-1], Z_array[mask][-1])
# 在图上标记出两个点
plt.plot(point1[0], point1[1], 'o', color='red')
plt.annotate('({}, {})'.format(point1[0], point1[1]), (point1[0], point1[1]), textcoords='offset points', xytext=(-20,-10), ha='center')
plt.plot(point2[0], point2[1], 'o', color='red')
plt.annotate('({}, {})'.format(point2[0], point2[1]), (point2[0], point2[1]), textcoords='offset points', xytext=(20,10), ha='center')
# 显示图像
plt.xlabel('d')
plt.ylabel('Z')
plt.show()
```
这将在图形上标记出线段两端点的坐标值。请注意,您可能需要根据实际情况调整标记点的位置和文本偏移量。
相关问题
K = 1.5 H = 7.5 S = 10 V1 = 300 T2 = 5 V2 = 10 theta = np.radians(3)重新回答
好的,根据您提供的数值,我们可以重新编写代码:
```python
import matplotlib.pyplot as plt
import numpy as np
import math
def calculate_pressure(K, H, S, V1, T2, V2, theta, d):
if H >= S:
P = (K * H) / (S * (d/V1 + T2) * V2 * math.tan(theta))
else:
P = (K * (S - (S - H) / 2)) / (S * (d/V1 + T2) * V2 * math.tan(theta))
return P
K = 1.5
H = 7.5
S = 10
V1 = 300
T2 = 5
V2 = 10
theta = np.radians(3)
d_array = np.linspace(0, 1000, 10000)
P_array = np.array([calculate_pressure(K, H, S, V1, T2, V2, theta, d) for d in d_array])
Z_array = (d_array / V1 + T2) * V2 + d_array
mask = P_array >= 0.8
plt.plot(d_array[mask], Z_array[mask])
plt.xlabel('d')
plt.ylabel('Z')
plt.show()
```
这段代码会生成一个图形窗口,显示出 P 大于等于 0.8 时,Z 和 d 的关系图。您可以根据需要调整常量和数组的值,来得到不同的图形结果。
请帮我看看这个代码,在python 3.7版本中显示operands could not be broadcast together with shapes (11,) (1000,) 请帮我改成可以运行的格式 import numpy as np import matplotlib.pyplot as plt from scipy.constants import c, pi # Input parameters wavelength = 380e-9 # m grating_constant = 1600e3 # m angle_range = np.linspace(-10, 10, 1000) # degrees # Convert angle to radians theta = np.deg2rad(angle_range) # Calculate grating period and wavenumber grating_period = 1 / grating_constant k = 2 * pi / wavelength # Calculate diffraction orders m = np.arange(-5, 6) # diffraction orders order_wavenumbers = m * k order_angles = np.rad2deg(np.arcsin(order_wavenumbers / grating_constant)) # Calculate diffraction efficiency diff_efficiency = np.sin(m * pi * grating_period * np.sin(theta))**2 / (m * pi * grating_period * np.sin(theta))**2 # Plot diffraction efficiency vs angle plt.plot(angle_range, diff_efficiency) plt.xlabel('Angle (degrees)') plt.ylabel('Diffraction efficiency') plt.title('Diffraction pattern for a grating with a constant of {} mm^-1'.format(grating_constant/1000)) plt.show()
这个错误通常是由于数组的形状不匹配导致的。在这个代码中,出现这个错误的原因可能是`diff_efficiency`和`angle_range`的形状不一致。
你可以尝试使用`np.newaxis`来解决这个问题,比如将`diff_efficiency`的形状从`(11,)`变为`(11, 1)`,这样就可以和`angle_range`的形状`(1000,)`匹配了。
以下是修改后的代码:
```python
import numpy as np
import matplotlib.pyplot as plt
from scipy.constants import c, pi
# Input parameters
wavelength = 380e-9 # m
grating_constant = 1600e3 # m
angle_range = np.linspace(-10, 10, 1000) # degrees
# Convert angle to radians
theta = np.deg2rad(angle_range)
# Calculate grating period and wavenumber
grating_period = 1 / grating_constant
k = 2 * pi / wavelength
# Calculate diffraction orders
m = np.arange(-5, 6)
order_wavenumbers = m * k
order_angles = np.rad2deg(np.arcsin(order_wavenumbers / grating_constant))
# Calculate diffraction efficiency
diff_efficiency = np.sin(m * pi * grating_period * np.sin(theta))**2 / (m * pi * grating_period * np.sin(theta))**2
diff_efficiency = diff_efficiency[:, np.newaxis] # Add a new axis to match the shape of angle_range
# Plot diffraction efficiency vs angle
plt.plot(angle_range, diff_efficiency)
plt.xlabel('Angle (degrees)')
plt.ylabel('Diffraction efficiency')
plt.title('Diffraction pattern for a grating with a constant of {} mm^-1'.format(grating_constant/1000))
plt.show()
```
希望这可以帮助你解决问题。