I am a beginner to Python and experimenting with a plot. the script runs fine but plot does not show up.
the matplotlib and numpy libraries are installed.
import numpy as np
f= h5py.File('3DIMG_05JUN2021_0000_L3B_HEM_DLY.h5','r')
#Studying the structure of the file by printing what HDF5 groups are present
for key in f.keys():
print(key) #Names of the groups in HDF5 file.
# will print the variables in the file
#Get the HDF5 group
ls=list(f.keys())
print("ls")
print(ls)
tsurf = f['HEM_DLY'][:]
print("tsurf")
print(tsurf)
tsurf1=np.squeeze(tsurf)
print(tsurf1.shape)
import matplotlib.pyplot as plt
im= plt.plot(tsurf1)
#plt.colorbar()
plt.imshow(im)```
Python version is 3 running on Ubuntu
Difficult to give you the exact answer without the dataset (please update the question with the dataset), but for sure, plt.plot does not return an object that can be plotted with plt.imshow
Try instead:
ax = plt.plot(tsurf1)
plt.show()
Probably the error was on the final plot.Try this:
import numpy as np
import matplotlib.pyplot as plt
f= h5py.File('/path','r')
ls=list(f.keys())
tsurf = f['your_key_str'][:]
tsurf1=np.squeeze(tsurf)
im= plt.plot(tsurf1)
plt.show(im) # <-- plt.show() NOT plt.imshow()
Related
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import style
style.use("fivethirtyeight")
df = pd.DataFrame({'day':[1,2,3,4,5],'visitors':[200,302,480,590,680],'Bounce_rate':[20,30,40,50,60]})
df.set_index('day',inplace=True)
df.plot()
plt.show()
output is <Figure size 640x480 with 1 Axes>, the desired output is a graph (in VS Code).
I can see my code is correct when using cloud jupyter by achieving the desired output but it's not possible in VS Code jupyter view...
Am I doing something wrong? or is it something else?
I am new to programming, and I'm having difficulty plotting multiple graphs. What I am trying to get is a graph containing values of K along the Y-axis plotted against values of Dk. I need this graph to contain all the K=f(Dk) for each temperature Tcwin in range (10,40,1)
While the code seems to be working well and I have obtained the data I was trying to calculate, I can't seem to plot them. Any help would be appreciated.
import numpy as np
import pandas as pd
A=3000
d_in=20
CF=0.85
w=2.26
Tcwin=12
Dk=np.arange(27.418,301.598,27.418)
dk=(Dk*1000/(A*3.600))
cp=4.19
Gw=13000
e=2.718281828
f_velocity=w*1.1/(20**0.25)
for Tcwin in range(10,40,1):
while Tcwin<35:
print(Tcwin)
f_w=0.12*CF*(1+0.15*Tcwin)
Ф_в=f_velocity**f_w
K=CF*4070*((1.1*w/(d_in**0.25))**(0.12*CF*(1+0.15*Tcwin)))*(1-(((35-Tcwin)**2)*(0.52-0.0072*dk)*(CF**0.5))/1000)
n=(K*A)/(cp*Gw*1000)
Tcwout_theor=Tcwin+(Dk*2225/(cp*Gw))
Subcooling_theor=(Tcwout_theor-Tcwin)/(e**(K*A/(cp*(Gw*1000/3600)*1000)))
TR_theor=Tcwout_theor-Tcwin
Tsat_theor=Tcwout_theor+Subcooling_theor
print(K)
print(Tcwout_theor)
print(Subcooling_theor)
print(Tsat_theor)
Tcwin+=1
else:
print('Loop done')
Is this what you are looking for? plotting after each run:
import numpy as np
import pandas as pd
A=3000
d_in=20
CF=0.85
w=2.26
Tcwin=12
Dk=np.arange(27.418,301.598,27.418)
dk=(Dk*1000/(A*3.600))
cp=4.19
Gw=13000
e=2.718281828
f_velocity=w*1.1/(20**0.25)
for Tcwin in range(10,40,1):
while Tcwin<35:
print(Tcwin)
f_w=0.12*CF*(1+0.15*Tcwin)
Ф_в=f_velocity**f_w
K=CF*4070*((1.1*w/(d_in**0.25))**(0.12*CF*(1+0.15*Tcwin)))*(1-(((35-Tcwin)**2)*(0.52-0.0072*dk)*(CF**0.5))/1000)
n=(K*A)/(cp*Gw*1000)
Tcwout_theor=Tcwin+(Dk*2225/(cp*Gw))
Subcooling_theor=(Tcwout_theor-Tcwin)/(e**(K*A/(cp*(Gw*1000/3600)*1000)))
TR_theor=Tcwout_theor-Tcwin
Tsat_theor=Tcwout_theor+Subcooling_theor
print(K)
print(Tcwout_theor)
print(Subcooling_theor)
print(Tsat_theor)
Tcwin+=1
plt.plot(K,dk) #---------------> this is the code for plotting
else:
print('Loop done')
In the table below, I have values and frequencies. I'd like to draw a box-plot using Jupyter Notebook. I googled it but not able to find any answers.
My idea is to create a column, 2,2,2,2,4,4,4,4,4,4,4,...
But I think there must be a better way.
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
value=np.array([2,4,6,7,10])
freq=np.array([4,7,8,5,2])
# do something here
plt.boxplot(newdata)
plt.show()
use numpy's repeat:
newdata = np.repeat(value,freq)
I'm writing Python code on Databricks to process some data and output graphs. I want to be able to save these graphs as a picture file (.png or something, the format doesn't really matter) to DBFS.
Code:
import pandas as pd
import matplotlib.pyplot as plt
df = pd.DataFrame({'fruits':['apple','banana'], 'count': [1,2]})
plt.close()
df.set_index('fruits',inplace = True)
df.plot.bar()
# plt.show()
Things that I tried:
plt.savefig("/FileStore/my-file.png")
[Errno 2] No such file or directory: '/FileStore/my-file.png'
fig = plt.gcf()
dbutils.fs.put("/dbfs/FileStore/my-file.png", fig)
TypeError: has the wrong type - (,) is expected.
After some research, I think the fs.put only works if you want to save text files.
running the above code with plt.show() will get you a bar graph - I want to be able to save the bar graph as an image to DBFS. Any help is appreciated, thanks in advance!
Easier way, just with matplotlib.pyplot. Fix the dbfs path:
Example
import matplotlib.pyplot as plt
plt.scatter(x=[1,2,3], y=[2,4,3])
plt.savefig('/dbfs/FileStore/figure.png')
You can do this by saving the figure to memory and then using the Python local file APIs to write to the DataBricks filesystem (DBFS).
Example:
import matplotlib.pyplot as plt
from io import BytesIO
# Create a plt or fig, then:
buf = BytesIO()
plt.savefig(buf, format='png')
path = '/dbfs/databricks/path/to/file.png'
# Make sure to open the file in bytes mode
with open(path, 'wb') as f:
# You can also use Bytes.IO.seek(0) then BytesIO.read()
f.write(buf.getvalue())
I'm generating a heatmap from a pandas dataframe using a code that looks like this on my apple computer.
import matplotlib.pyplot as plt
import seaborn as sns
fig, ax = plt.subplots(figsize=(14,14))
sns.set(font_scale=1.4)
sns_plot = sns.heatmap(df, annot=True, linewidths=.5, fmt='g', ax=ax).set_yticklabels(ax.get_yticklabels(), rotation=0)
ax.set_ylabel('Product')
ax.set_xlabel('Manufacturer')
ax.xaxis.set_ticks_position('top')
ax.xaxis.set_label_position('top')
fig.savefig('output.png')
And I get a heatmap looking like this:
I then put my code in a docker container with an ubuntu image and I install the same version of seaborn. The only difference is that I need to add a matplotlib configuration so that TCL doesn't scream:
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import seaborn as sns
And I get a heatmap that looks like this (I use the same code and the same pandas dataframe):
I'm unable to find why the color gradient is inverted and would love to hear if you have any idea.
Thank you !
The default colormap has changed to 'rocket' for sequential data with 0.8 release of seaborn, see the release notes. The colormap looks this way now:
You can always use the cmap argument and specify which colormap you prefer to use. For example, to get the pre-0.8 colormap for non-divergent data use: cmap=sns.cubehelix_palette(light=.95, as_cmap=True).