I have the following code:
from scipy import signal
import numpy as np
import matplotlib.pyplot as plt
from scipy.io import wavfile
fs, data = wavfile.read("New Recording 2.wav")
f, t , zxx = signal.stft(data, fs)
fa = np.array(f)
ta = np.array(t)
plt.plot(ta, fa, np.abs(zxx))
plt.show()
I want to plot a graph like this: Graph, with time (secs) on x axis and Khz on Y axis.
When I run the above code I run into the value error
"ValueError: x and y must have same first dimension, but have shapes (3,) and (2,)"
I thought this was a quirk in numpy hence me converting f and t to np.arrays instead of the arrays outputted by scipy.
Any help would be appreciated.
Related
I'm studying about Fourier Series with python.
I drew it with cosine and sine function.
My code is like this.
import numpy as np
import matplotlib.pyplot as plt
from sympy import *
x = Symbol('x')
fx=0
j=10
for i in range(1,j):
fx=fx+(2)/(np.pi*i)*(1-cos(i*np.pi))*(sin(i*x))
y_func=lambdify(x, fx, "numpy")
x_val=np.linspace(-np.pi,np.pi,315)
y_val=y_func(x_val)
plt.plot(x_val,y_val)
plt.show()
I could get the correct graph.
And I tried to make the graph into animaion effect like this gif file.
enter image description here
I wrote the code like below using by ArtistAnimation , but I couldn't get the animation.
How can i get the animation?
import numpy as np
import matplotlib.pyplot as plt
from sympy import *
from matplotlib.animation import ArtistAnimation
x = Symbol('x')
fx=0
j=10
img=[]
fig, ax=plt.subplots(constrained_layout=True)
for i in range(1,j):
fx=fx+(2)/(np.pi*i)*(1-cos(i*np.pi))*(sin(i*x))
y_func=lambdify(x, fx, "numpy")
x_val=np.linspace(-np.pi,np.pi,315)
y_val=y_func(x_val)
fs=plt.plot(x_val,y_val)
img.append([fs])
anim=ArtistAnimation(fig,img,interval=5)
anim.save("Fourier_Series01.gif",fps=24)
I tried to make the code with ArtistAnimation
Thank you for your answer
How to find Shift phase between two sinusoids in Python.
For example, I created two sinusoid with phase shift 180 radian (Visually). Can we calculate the phase shift in python script if we know only graph_1 and graph_2?
import matplotlib.pyplot as plt
import numpy as np
data=[]
def sin (f):
x=np.array(range(1,200))
y = 10*np.sin((0.1*x)+f)
return (y)
import matplotlib.pyplot as plt
graph_1 = sin(3.12)
graph_2 = sin(0)
plt.plot(graph_1 ,graph_2)
plt.show()
Please see the image here
I have created a list of values of Shannon entropy for a pair of multiple sequence aligned sequences. While plotting the values I get a simple plot. I want to plot a smooth curve over the lines. Can anyone suggest to me what will be the right way to process it? BAsically I want to plot a smooth curve that touches the tip of every bar and goes to zero where the "y axis value" is zero.
link for image: [1]: https://i.stack.imgur.com/SY3jH.png
#importing the relevant packages
import math
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from scipy.interpolate import make_interp_spline
from Bio import AlignIO
import warnings
warnings.filterwarnings("ignore")
#function to calculate the Shannon Entropy of a MSA
# H = -sum[p(x).log2(px)]
def shannon_entropy(list_input):
unique_aa = set(list_input)
M = len(list_input)
entropy_list = []
# Number of residues in column
for aa in unique_aa:
n_i = list_input.count(aa)
P_i = n_i/float(M)
entropy_i = P_i*(math.log(P_i,2))
entropy_list.append(entropy_i)
sh_entropy = -(sum(entropy_list))
#print(sh_entropy)
return sh_entropy
#importing the MSA file
#importing the clustal file
align_clustal1 =AlignIO.read("/home/clustal.aln", "clustal")
def shannon_entropy_list_msa(alignment_file):
shannon_entropy_list = []
for col_no in range(len(list(alignment_file[0]))):
list_input = list(alignment_file[:, col_no])
shannon_entropy_list.append(shannon_entropy(list_input))
return shannon_entropy_list
clustal_omega1 = shannon_entropy_list_msa(align_clustal1)
# Plotting the data
plt.figure(figsize=(18,10))
plt.plot(clustal_omega1, 'r')
plt.xlabel('Residue', fontsize=16)
plt.ylabel("Shannon's entropy", fontsize=16)
plt.show()
Edit 1:
Here is what my graph looks like after implementing the "pchip" method. link for the pchip output: https://i.stack.imgur.com/hA3KW.png
pchip monotonic spline output
One approach would be to use PCHIP interpolation, which will give you the monotonic curve with the required behaviour for zero values on the y-axis.
We can't run your exact code example on our machines because you point to a local Clustal file in your 'home' directory.
Here's a simple working example, with link to output image:
import numpy as np
import matplotlib.pyplot as plt
from scipy.interpolate import pchip
mylist = [10,0,0,0,0,9,9,0,0,0,11,11,11,0,0]
mylist_np = np.array(mylist)
samples = np.array(range(len(mylist)))
xnew = np.linspace(samples.min(), samples.max(), 100)
plt.plot(xnew,pchip(samples, mylist_np )(xnew))
plt.show()
I'm creating a sine wave of 100Hz and trying to plot it's stft :
import scipy.io
import numpy as np
import librosa
import librosa.display
#%matplotlib notebook
import matplotlib.pyplot as plt
A = 1 # Amplitude
f0 = 100 # frequency
Fs = f0 * 800 # Sampling frequency
t = np.arange(Fs) / float(Fs)
X = np.sin(2*np.pi*t*f0)
plt.plot(t, X)
plt.xlabel("Time")
plt.ylabel("Amplitude")
plt.show()
D = np.abs(librosa.stft(X))
librosa.display.specshow(librosa.amplitude_to_db(D,ref=np.max),y_axis='log', x_axis='time')
I was expecting a single line at 100Hz instead.
Also, how can I plot Frequency(X-axis) vs Amplitude(Y-axis) graph to see a peak at 100Hz?
You need to pass the sample rate to specshow, using the sr keyword argument. Otherwise it will default to 22kHz, which will give wrong results.
D = np.abs(librosa.stft(X))
db = librosa.amplitude_to_db(D,ref=np.max)
librosa.display.specshow(db, sr=Fs, y_axis='log', x_axis='time')
I am trying to make a contour plot from a csv file. I would like the first column to be the x axis, the first row (with has values) to be the y, and then the rest of the matrix is what should be contoured, see the basic example in the figure below.
Simple table example
What I am really struggling is to get that first row to be the y axis, and then how to define that set of values so that they can be called into the contourf function. Any help would be very much appreciated as I am very new to python and am really don't know where to start with this problem.
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import csv
import pandas as pd
import numpy as np
from csv import reader
from matplotlib import cm
f = pd.read_csv('/trialforplot.csv',dayfirst=True,index_col=0)
x = f.head()
y = f.columns
X,Y = np.meshgrid(x,y)
z=(x,y)
z=np.array(z)
Z=z.reshape((len(x),len(y)))
plt.contour(Y,X,Z)
plt.colorbar=()
plt.xlabel('Time')
plt.ylable('Particle Size')
plt.show()
I'm stuck at defining the z values and getting my contour plot plotting.