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AndroidWeather |
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public class Event | |
{ | |
/** | |
* Event id | |
*/ | |
public String i; | |
/** | |
* Event parent |
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init_cell = (row_number, col_number, prop) -> | |
if row_number == undefined || col_number == undefined | |
return | |
day_number = col_number + 1 | |
row = table_data.get_row_by_index row_number | |
if row == undefined | |
return | |
day = row.get_day day_number | |
cellProperties = {} | |
# if col_number is last column( with total hours) |
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# | |
# Main file. | |
# Contains entry point | |
# | |
# @nodoc | |
previously_selected = undefined |
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Ext.namespace('Custom.config'); | |
/** | |
* The Configparser is responsible for: | |
* | |
* 1. loading the json-config-file into the application | |
* 2. parsing the json-file into a javascript object | |
* (while already transforming values for tileSize, extent and layer-attributes into | |
* their respective objects) | |
* 3. rendering the application: |
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import java.io.IOException; | |
import java.nio.file.Files; | |
import java.nio.file.Paths; | |
import java.time.LocalDate; | |
import java.util.regex.Matcher; | |
import java.util.regex.Pattern; | |
/** | |
* @author Pavel Gordon | |
*/ |
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if property_definition is not None: | |
print("property_definition.Name", property_definition.Name) | |
props = {} | |
if property_definition.is_a("isExternal") or property_definition.is_a("LoadBearing") or property_definition.is_a("FireRating"): | |
print("has isExternal or LoadBearing or FireRating") | |
for q in property_definition.Quantities: | |
print("property_definition.Quantities: ", q) |
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import ifcopenshell | |
f = ifcopenshell.open("Stratumsedijk_AC17_08-04-2015.ifc") | |
windows = f.by_type("ifcWindow") | |
print(windows) | |
print(len(windows)) # when i have the zero in brakets after f.by_type _ i get the number of elements in brackets for the first element | |
# print(windows.is_a())# in this case this commands in working and shows that its ifcWindows. | |
# when i have no 0 in brakets, the command len gives the number of windows in the file . and command windows.is_a does not work |
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import pandas as pd | |
import numpy | |
df= pd.read_excel('dwfef.xlsx') | |
arr = df.to_numpy().flatten() #convert 2dimentional dataframe to 1dimentional list | |
arr = arr[~pd.isnull(arr)] # remove 'nan' - empty strings | |
striper = lambda t: str(t.strip()) | |
arr = np.array([striper(xi) for xi in arr]).astype(str) # remove whitespaces before and after each word | |
unique_elements, counts_elements = np.unique(arr, return_counts=True) |
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shadowJar { | |
baseName = 'object-randomizer' | |
classifier = null | |
version = null | |
} |
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