Hi there I am getting this error:
ValueError: setting an array element with a sequence.
When I run this code:
import metpy.calc as mpcalc
from metpy.units import units
import cartopy.crs as ccrs
import cartopy.feature as cfeat
import os
from netCDF4 import Dataset as netcdf_dataset
fname = os.path.join(config["repo_data_dir"],
'netcdf', "nam_218_20170625_1200_031.nc"
)
dataset = netcdf_dataset(fname)
lat = dataset.variables['gridlat_0'][:]
lon = dataset.variables['gridlon_0'][:]
sfct=units.degC*(np.mean(dataset.variables['TMP_P0_L103_GLC0'][:,:,:],0)-273.15)
dp=units.degC*(dataset.variables['DPT_P0_L103_GLC0'][:]-273.15)
sfcp=units.hPa*(dataset.variables['PRES_P0_L103_GLC0'][:]/100.0)
lcl_pressure=np.empty(((428),(614)))
lcl_temperature=np.empty(((428),(614)))
lclht=np.empty(((428),(614)))
for i in range(428):
for j in range(614):
lcl_pressure[i,j], lcl_temperature[i,j] = mpcalc.lcl(sfcp[i,j],sfct[i,j],dp[i,j])
lclht[i,j]=mpcalc.pressure_to_height_std(lcl_pressure[i,j]).to('feet')
The line in question is this:
lcl_pressure[i,j], lcl_temperature[i,j] = mpcalc.lcl(sfcp[i,j],sfct[i,j],dp[i,j])
since I am unsure as to how that's causing it as the line in question works for a different code where it says
lcl_pressure[i,j], lcl_temperature[i,j] = mpcalc.lcl(p[0],t[0],dp[0])
as the p,t, and dp in that 2nd version are also arrays
Related
I have working code that is utilizing dbscan to find tight groups of sparse spatial data imported with pd.read_csv.
I am maintaining the original spatial data locations and would like to annotate the labels returned by dbscan for each data point to the original dataframe and then write a csv with the same information.
So the code below is doing exactly what I would expect it to at this point, I would just like to extend it to import the label for each row in the original dataframe.
import argparse
import string
import os, subprocess
import pathlib
import glob
import gzip
import re
import time
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as patches
from sklearn.cluster import DBSCAN
X = pd.read_csv(tmp_csv_name)
X = X.drop('Name', axis = 1)
X = X.drop('Type', axis = 1)
X = X.drop('SomeValue', axis = 1)
# only columns 'x' and 'y' now remain
db=DBSCAN(eps=EPS, min_samples=minSamples, metric='euclidean', algorithm='auto', leaf_size=30).fit(X)
labels = def_inst_dbsc.labels_
unique_labels = set(labels)
# maxX , maxY are manual inputs temporarily
while sizeX > 16 or sizeY > 16 :
sizeX=sizeX*0.8 ; sizeY=sizeY*0.8
fig, ax = plt.subplots(figsize=(sizeX,sizeY))
plt.xlim(0,maxX)
plt.ylim(0,maxY)
plt.scatter(X['x'], X['y'], c=colors, marker="o", picker=True)
# hackX , hackY are manual inputs temporarily
# which represent the boundaries defined in the original dataset
poly = patches.Polygon(xy=list(zip(hackX,hackY)), fill=False)
ax.add_patch(poly)
plt.show()
Sample image
I need to extract CR No.from the sample image given above. Using Easyocr, I got the output in complex nested list form. How to update the code to filter out all the detected text/numbers and get only CR No. I am running out of ideas, and help will be appreciated. What I have tried so far-
#Import libraries
import os
import easyocr
import cv2
from matplotlib import pyplot as plt
import numpy as np
IMAGE_PATH = 'H://CDAC//Spyder_projects//CR_No//input_image//input7.jpg'
reader = easyocr.Reader(['en'])
result3 = reader.readtext(IMAGE_PATH)
result3
my_list2 = []
length = len(result3)
for i in range(length):
if (result3[i][1]) == 'CR No':
print(result3[i])
print(result3[i+1])
my_list2.append(result3[i+1]+result3[i])
print(my_list2)
print('The CR No is:', my_list2[0][1])
The expected output should be- 211022203481161
I've been trying to convert string date into a format that can be plotted on a graph.
The code
import matplotlib.pyplot as plt
import numpy as np
import urllib
import matplotlib.dates as mdates
import datetime
def graph_data():
fig=plt.figure()
ax1=plt.subplot2grid((1,1),(0,0))
stock_price_url = 'https://pythonprogramming.net/yahoo_finance_replacement'
source_code = urllib.request.urlopen(stock_price_url).read().decode()
stock_data = []
split_source=source_code.split('\n')
print(len(split_source))
for line in split_source[1:]:
stock_data.append(line)
date,openn,closep,highp,lowp,openp,volume=np.loadtxt(stock_data,delimiter=',',unpack=True)
x = [datetime.strptime(d, '%Y-%m-%d') for d in date]
ax1.plot_date(x,closep,'-',linewidth=0.1)
plt.xlabel('x')
plt.ylabel('y')
plt.title('Graph')
plt.show()
graph_data()
Any method of conversion just gives the same error
ValueError: could not convert string to float: '2017-07-26'
What method can I use to convert the string into date that can be plotted
Ther's nothing wrong with your code. The problem is with the data.
If you look at the data, you will find that from date to volume features your data is a string like this :
data = '2017-07-26,153.3500,153.9300,153.0600,153.5000,153.5000,12778195.00'.
That is the representation of a string.
So you need to do some preprocessing first. There may be various methods to do so.
I found this method helpful to me:
First, you have to remove the commas in data and replace them with spaces and then use the split function to convert data into a split format.
So, you need to make these changes in your code:
date = []
closep = []
for i in range(len(stock_data)):
temp = stock_data[i].replace(',', ' ').split()
date.append(temp[0])
closep.append(temp[2])
0 and two are the positions of date and closep in your dataset.
Now instead of 'x' and 'closep' as you have used in your plot method, use these 'date ' and 'closep' I just shared you via code.
One more thing is that the graph is having trouble with this big dataset I think.
So use date[0:100], closep[0:100] to try the plot for smaller dataset.
The complete code would look like this:
import matplotlib.pyplot as plt
import numpy as np
import urllib
import matplotlib.dates as mdates
import datetime
def graph_data():
fig = plt.figure()
ax1 = plt.subplot2grid((1, 1), (0, 0))
stock_price_url =
'https://pythonprogramming.net/yahoo_finance_replacement'
source_code = urllib.request.urlopen(stock_price_url).read().decode()
stock_data = []
split_source = source_code.split('\n')
for line in split_source[1:]:
stock_data.append(line)
date = []
closep = []
for i in range(len(stock_data)):
temp = stock_data[i].replace(',', ' ').split()
date.append(temp[0])
closep.append(temp[2])
ax1.plot_date(date[0:100], closep[0:100], '-', linewidth=0.1)
plt.xlabel('x')
plt.ylabel('y')
plt.title('Graph')
plt.show()
graph_data()
Hope this helps.
I'm basically sorting my CNN images into a list with even and odd indexing. Even index will have positive images and odd index will have negative images. Here's my code so far:
from PIL import Image
import matplotlib.pyplot as plt
import os
import glob
import torch
from torch.utils.data import Dataset
def show_data(data_sample, shape = (28, 28)):
plt.imshow(data_sample[0].numpy().reshape(shape), cmap='gray')
plt.title('y = ' + data_sample[1])
directory="/resources/data"
negative='Negative'
negative_file_path=os.path.join(directory,negative)
negative_files=[os.path.join(negative_file_path,file) for file in os.listdir(negative_file_path) if file.endswith(".jpg")]
negative_files.sort()
negative_files[0:3]
positive="Positive"
positive_file_path=os.path.join(directory,positive)
positive_files=[os.path.join(positive_file_path,file) for file in os.listdir(positive_file_path) if file.endswith(".jpg")]
positive_files.sort()
positive_files[0:3]
n = len(negative_files)
p = len(positive_files)
number_of_samples = n + p
print(number_of_samples)
Y=torch.zeros([number_of_samples])
Y=Y.type(torch.LongTensor)
Y.type()
Y[::2]=1
Y[1::2]=0
Replace the code with:
directory="resources/data/"
I am trying to create a Time-Series model for forecasting few values. But whenever I am trying to read the file, I am getting an error.
The line which is in bold and italic is generating error.
This is my code :
import warnings
import itertools
import numpy as np
import matplotlib.pyplot as plt
warnings.filterwarnings("ignore")
plt.style.use('fivethirtyeight')
import pandas as pd
import statsmodels.api as sm
import matplotlib
matplotlib.rcParams['axes.labelsize'] = 14
matplotlib.rcParams['xtick.labelsize'] = 12
matplotlib.rcParams['ytick.labelsize'] = 12
matplotlib.rcParams['text.color'] = 'k'
***df = pd.read_csv["forecasting.csv", ","]***
t1 = df.loc[df['Technology'] == 't_1']
Use round brackets - ( and ), not square brackets [ and ], i.e.
df = pd.read_csv("forecasting.csv", ",")