Want to visualise coordinates from csv file by a heatmap, but only one axis is displayed in the graph and nothing else as the picture shows:
enter image description here
This is the code:
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
matplotlib.use('TkAgg')
data = np.genfromtxt("plik.csv", delimiter=";", dtype = float)
np.reshape(data, (-1, 2))
print(data.shape)
plt.imshow(data, cmap='hot')
plt.show()
And data in the file is displayed like this:
0.000000; 0.045761
0.000000; 0.016499
0.000013; 0.010060
0.013995; 0.065568
0.014008; 0.060024
0.007376; 0.066706
0.020661; 0.062069
0.019254; 0.060543
0.028329; 0.079392
0.021810; 0.058398
0.025076; 0.067873
0.068878; 0.120970
There are 9585 lines in the file.
Related
I downloaded a VLASS fits file and i'm trying to plot it without success.
The problem is, i think, the shape
print(image_data.shape)
which gives me (1, 1, 3722, 3722).
My code is:
import matplotlib.pyplot as plt
import numpy as np
from astropy.io import fits
from astropy.visualization import astropy_mpl_style
plt.style.use(astropy_mpl_style)
hdulist = fits.open("vla_test.fits")
hdu = hdulist[0]
plt.figure()
plt.imshow(hdu.data[0,0,:,:], cmap='Greys')
plt.colorbar()
I don't get any error but image doesn't show off and i get white (void) image.
I tried to download other files from the survey but i get same result.
When I run the code below I notice that the heatmap does not have a square shape knowing that I have used square=True but it did not work! Any idea how can I print the heatmap in a square format? Thank you!
The code:
from datetime import datetime
import numpy as np
import pandas as pd
import matplotlib as plt
import os
import seaborn as sns
temp_hourly_A5_A7_AX_ASHRAE=pd.read_csv('C:\\Users\\cvaa4\\Desktop\\projects\\s\\temp_hourly_A5_A7_AX_ASHRAE.csv',index_col=0, parse_dates=True, dayfirst=True, skiprows=2)
sns.heatmap(temp_hourly_A5_A7_AX_ASHRAE,cmap="YlGnBu", vmin=18, vmax=27, square=True, cbar=False, linewidth=0.0001);
The result:
square=True should work to have square cells, below is a working example:
import pandas as pd
import numpy as np
import seaborn as sns
df = pd.DataFrame(np.tile([0,1], 15*15).reshape(-1,15))
sns.heatmap(df, square=True)
If you want a square shape of the plot however, you can use set_aspect and the shape of the data:
ax = sns.heatmap(df)
ax.set_aspect(df.shape[1]/df.shape[0]) # here 0.5 Y/X ratio
You can use matplotlib and set a figsize before plotting heatmap.
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
rnd = np.random.default_rng(12345)
data = rnd.uniform(-100, 100, [100, 50])
plt.figure(figsize=(6, 5))
sns.heatmap(data, cmap='viridis');
Note that I used figsize=(6, 5) rather than a square figsize=(5, 5). This is because on a given figsize, seaborn also puts the colorbar, which might cause the heatmap to be squished a bit. You might want to change those figsizes too depending on what you need.
I want to replicate plots from this paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5000555/pdf/nihms774453.pdf I'm particularly interested in plot on page 16, right panel. I tried to do this in matplotlib but it seems to me that there is no way to access lines in linecollection.
I don't know how to change the color of the each line, according to the value at every index. I'd like to eventually get something like here: https://matplotlib.org/3.1.1/gallery/lines_bars_and_markers/multicolored_line.html but for every line, according to the data.
this is what I tried:
the data in numpy array: https://pastebin.com/B1wJu9Nd
import pandas as pd, numpy as np
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
from matplotlib import colors as mcolors
%matplotlib inline
base_range = np.arange(qq.index.max()+1)
fig, ax = plt.subplots(figsize=(12,8))
ax.set_xlim(qq.index.min(), qq.index.max())
# ax.set_ylim(qq.columns[0], qq.columns[-1])
ax.set_ylim(-5, len(qq.columns) +5)
line_segments = LineCollection([np.column_stack([base_range, [y]*len(qq.index)]) for y in range(len(qq.columns))],
cmap='viridis',
linewidths=(5),
linestyles='solid',
)
line_segments.set_array(base_range)
ax.add_collection(line_segments)
axcb = fig.colorbar(line_segments)
plt.show()
my result:
what I want to achieve:
I am trying to set a background image to a line plot that I have done in matplotlib. While importing the image and using zorder argument also, I am getting two seperate images, in place of a single combined image. Please suggest me a way out. My code is --
import quandl
import pandas as pd
import sys, os
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import itertools
def flip(items, ncol):
return itertools.chain(*[items[i::ncol] for i in range(ncol)])
df = pd.read_pickle('neer.pickle')
rows = list(df.index)
countries = ['USA','CHN','JPN','DEU','GBR','FRA','IND','ITA','BRA','CAN','RUS']
x = range(len(rows))
df = df.pct_change()
fig, ax = plt.subplots(1)
for country in countries:
ax.plot(x, df[country], label=country)
plt.xticks(x, rows, size='small', rotation=75)
#legend = ax.legend(loc='upper left', shadow=True)
plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
plt.show(1)
plt.figure(2)
im = plt.imread('world.png')
ax1 = plt.imshow(im, zorder=1)
ax1 = df.iloc[:,:].plot(zorder=2)
handles, labels = ax1.get_legend_handles_labels()
plt.legend(flip(handles, 2), flip(labels, 2), loc=9, ncol=12)
plt.show()
So in the figure(2) I am facing problem and getting two separate plots
In order to overlay background image over plot, we need imshow and extent parameter from matplotlib.
Here is an condensed version of your code. Didn't have time to clean up much.
First a sample data is created for 11 countries as listed in your code. It is then pickled and saved to a file (since there is no pickle file data).
import quandl
import pandas as pd
import sys, os
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import itertools
from scipy.misc import imread
countries = ['USA','CHN','JPN','DEU','GBR','FRA','IND','ITA','BRA','CAN','RUS']
df_sample = pd.DataFrame(np.random.randn(10, 11), columns=list(countries))
df_sample.to_pickle('c:\\temp\\neer.pickle')
Next the pickle file is read and we create bar plot directly from pandas
df = pd.read_pickle('c:\\temp\\neer.pickle')
my_plot = df.plot(kind='bar',stacked=True,title="Plot Over Image")
my_plot.set_xlabel("countries")
my_plot.set_ylabel("some_number")
Next we use imread to read image into plot.
img = imread("c:\\temp\\world.png")
plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
plt.imshow(img,zorder=0, extent=[0.1, 10.0, -10.0, 10.0])
plt.show()
Here is an output plot with image as background.
As stated this is crude and can be improved further.
You're creating two separate figures in your code. The first one with fig, ax = plt.subplots(1) and the second with plt.figure(2)
If you delete that second figure, you should be getting closer to your goal
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.mlab as mlab`
mu = np.loadtxt('my_data/corr.txt')
d = mu[:,2]
y=[]
tot=0
min=999
for i in d:
y.append(float(i))
tot=tot+float(i)
if (min>float(i)):
min=float(i)
av=tot/len(y)
z=[]
m=[]
for i in y:
z.append(i-av)
m.append(i-min)
plt.acorr(z,usevlines=True,maxlags=None,normed=True)
plt.show()
WIth this code I have the output showing a bar chart.
Now,
1) How do I change this plot style to give just the trend line? I cant modify the line properties by any means.
2) How do I write this output data to a dat or txt file?
this should be a working minimal example:
import matplotlib.pyplot as plt
import numpy as np
from numpy.random import normal
data = normal(0, 1, 1000)
# return values are lags, correlation vector and the drawn line
lags, corr, line, rest = plt.acorr(data, marker=None, linestyle='-', color='red', usevlines=False)
plt.show()
np.savetxt("correlations.txt", np.transpose((lags, corr)), header='Lags\tCorrelation')
But i would recommand not to connect the points.