Adding documentation for defs.OFR, renaming same folder to create a better module structure, updating the environment.yml file and setting up a batch job to create documentation. To execture batch job and create documentation, navigate to project directory in PowerShell and type 'Start-Process get_docu.bat' and press ENTER.
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@@ -1,3 +1,6 @@
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"""The docstring for this submodule
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"""
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### ----------------------------------------------------------------------------------------------------------------------------------- ###
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### IMPORTS AND CONFIGURATIONS
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@@ -11,6 +14,20 @@ import warnings
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class Distribution():
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r"""Object representing a distribution.
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Description
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-----------
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Bla Bla Bla
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Attributes
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----------
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var: np.ndarray
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A 1D array containing the (independent) variable, for instance the diameter $D$.
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fct: np.ndarray
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rA 1D array containing the dependent functional value, for instance count density $\frac{d\log_{10}N}{d\log_{10}D}$
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"""
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def __init__(self, variable_array, function_array, form = 'log10'):
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self.var = variable_array
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@@ -20,6 +37,18 @@ class Distribution():
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def transform(self, to = 'linear'):
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"""A method to transform distributions between different representations
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Description
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-----------
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Bla bla bla
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Parameters
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----------
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to: str
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Indicating into which representation the distribution should be transformed. Possible values are: `linear`, `ln` or `log10`
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"""
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if self.__form == to:
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warnings.warn("Already in desired format. Transformation has no effect.")
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return
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@@ -57,6 +86,20 @@ class Distribution():
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self.__form = 'log10'
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def update_units(self, new_var_units, new_fct_units):
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"""A method to update the units of the distribution
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Description
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-----------
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Bla Bla Bla
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Parameters
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----------
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new_var_units: float
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The SI factor used to transform the independent variable `self.var`
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new_fct_units: float
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The SI factor used to transform the dependent variable `self.fct`
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"""
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old_from = self.__form
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self.transform(to='linear')
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@@ -67,6 +110,14 @@ class Distribution():
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self.transform(to=old_from)
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def integrate(self) -> np.float64:
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"""A method to integrate over the spectrum $dN/d f(D)$
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Description
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-----------
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Bla Bla Bla
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"""
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return np.trapezoid(y = self.fct, x = self.var)
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def median():
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@@ -219,6 +270,26 @@ class OFRSample:
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class OFRAnalyser:
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"""An object representing an OFR experiment
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Description
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-----------
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Bla Bla Bla
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Attributes
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----------
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data_source_file: str
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A string pointing to the data source file
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flows_source_file: str
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A string pointing to the flow data source file
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sample_number_list: [int]
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A list of integers indicating which samples to consider
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max_samples: int
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The highest sample available in the data
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data: pandas.DataFrame
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A dataframe containing all the data
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"""
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def __init__(self, data_source_file, flows_source_file, sample_number_list, data_separator = ',') -> None:
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self.data_source_file = data_source_file
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@@ -248,6 +319,13 @@ class OFRAnalyser:
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def GetData(self) -> None:
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"""Method to get the data
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Description
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-----------
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Bla Bla Bla
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"""
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# TODO make this work also for a specific sample!
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# TODO convert everything is SI units, making live a lot easier...
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@@ -328,24 +406,24 @@ class OFRAnalyser:
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mass_produced = [(mpr * duration) for mpr, duration in zip(mass_production_rate, sampling_times)]
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cumulative_mass_produced = np.cumsum(np.array(mass_produced)).tolist()
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self.data = pd.DataFrame({'Sample (-)': numbers_of_sample,
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'Number (#/m^3)': number_concentrations,
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'Length (m/m^3)': length_concentrations,
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'Surface (m^2/m^3)': surface_concentrations,
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'Volume (m^3/m^3)': volume_concentrations,
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'Density (kg/m^3)': aerosol_densities,
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'Mass (kg/m^3)': mass_concentrations,
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'Start (s)': starting_times,
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'Stop (s)': stopping_times,
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'Duration (s)': sampling_times,
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'Dry Air Flow (m^3/s)': dry_air_flows,
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'Species Flow (m^3/s)': species_flows,
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'Ozone Flow (m^3/s)': ozone_flows,
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'Total Flow (m^3/s)': total_flows,
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'CPC Flow (m^3/s)': cpc_flows,
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'Mass Production Rate (kg/s)': mass_production_rate,
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'Mass Produced (kg)': mass_produced,
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'Cumulative Mass Produced (kg)': cumulative_mass_produced})
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self.data = pd.DataFrame({'Sample (-)': numbers_of_sample,
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'Number (#/m^3)': number_concentrations,
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'Length (m/m^3)': length_concentrations,
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'Surface (m^2/m^3)': surface_concentrations,
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'Volume (m^3/m^3)': volume_concentrations,
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'Density (kg/m^3)': aerosol_densities,
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'Mass (kg/m^3)': mass_concentrations,
|
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'Start (s)': starting_times,
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'Stop (s)': stopping_times,
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'Duration (s)': sampling_times,
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'Dry Air Flow (m^3/s)': dry_air_flows,
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'Species Flow (m^3/s)': species_flows,
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'Ozone Flow (m^3/s)': ozone_flows,
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'Total Flow (m^3/s)': total_flows,
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'CPC Flow (m^3/s)': cpc_flows,
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'Mass Production Rate (kg/s)': mass_production_rate,
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'Mass Produced (kg)': mass_produced,
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'Cumulative Mass Produced (kg)': cumulative_mass_produced})
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### ----------------------------------------------------------------------------------------------------------------------------------- ###
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@@ -0,0 +1,653 @@
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<!doctype html>
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<html lang="en">
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<head>
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<meta charset="utf-8">
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<meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1">
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<meta name="generator" content="pdoc3 0.11.1">
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<title>defs.OFR API documentation</title>
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<meta name="description" content="The docstring for this submodule">
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<script defer src="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.9.0/highlight.min.js" integrity="sha512-D9gUyxqja7hBtkWpPWGt9wfbfaMGVt9gnyCvYa+jojwwPHLCzUm5i8rpk7vD7wNee9bA35eYIjobYPaQuKS1MQ==" crossorigin></script>
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hljs.highlightAll();
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})</script>
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</head>
|
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<body>
|
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<main>
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<article id="content">
|
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<header>
|
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<h1 class="title">Module <code>defs.OFR</code></h1>
|
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</header>
|
||||
<section id="section-intro">
|
||||
<p>The docstring for this submodule</p>
|
||||
</section>
|
||||
<section>
|
||||
</section>
|
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<section>
|
||||
</section>
|
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<section>
|
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</section>
|
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<section>
|
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<h2 class="section-title" id="header-classes">Classes</h2>
|
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<dl>
|
||||
<dt id="defs.OFR.Distribution"><code class="flex name class">
|
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<span>class <span class="ident">Distribution</span></span>
|
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<span>(</span><span>variable_array, function_array, form='log10')</span>
|
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</code></dt>
|
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<dd>
|
||||
<div class="desc"><p>Object representing a distribution.</p>
|
||||
<h2 id="description">Description</h2>
|
||||
<p>Bla Bla Bla</p>
|
||||
<h2 id="attributes">Attributes</h2>
|
||||
<dl>
|
||||
<dt><strong><code>var</code></strong> : <code>np.ndarray</code></dt>
|
||||
<dd>A 1D array containing the (independent) variable, for instance the diameter $D$.</dd>
|
||||
<dt><strong><code>fct</code></strong> : <code>np.ndarray</code></dt>
|
||||
<dd>rA 1D array containing the dependent functional value, for instance count density $\frac{d\log_{10}N}{d\log_{10}D}$</dd>
|
||||
</dl></div>
|
||||
<details class="source">
|
||||
<summary>
|
||||
<span>Expand source code</span>
|
||||
</summary>
|
||||
<pre><code class="python">class Distribution():
|
||||
|
||||
r"""Object representing a distribution.
|
||||
|
||||
Description
|
||||
-----------
|
||||
Bla Bla Bla
|
||||
|
||||
Attributes
|
||||
----------
|
||||
var: np.ndarray
|
||||
A 1D array containing the (independent) variable, for instance the diameter $D$.
|
||||
fct: np.ndarray
|
||||
rA 1D array containing the dependent functional value, for instance count density $\frac{d\log_{10}N}{d\log_{10}D}$
|
||||
"""
|
||||
|
||||
def __init__(self, variable_array, function_array, form = 'log10'):
|
||||
|
||||
self.var = variable_array
|
||||
self.fct = function_array
|
||||
|
||||
self.__form = form
|
||||
|
||||
def transform(self, to = 'linear'):
|
||||
|
||||
"""A method to transform distributions between different representations
|
||||
|
||||
Description
|
||||
-----------
|
||||
Bla bla bla
|
||||
|
||||
Parameters
|
||||
----------
|
||||
to: str
|
||||
Indicating into which representation the distribution should be transformed. Possible values are: `linear`, `ln` or `log10`
|
||||
"""
|
||||
|
||||
if self.__form == to:
|
||||
warnings.warn("Already in desired format. Transformation has no effect.")
|
||||
return
|
||||
|
||||
# TODO: check the transformations!
|
||||
# TODO: check the order of the transformation (first variable, then function, or vice versa) to avoid having a mess!
|
||||
|
||||
match to:
|
||||
case 'linear':
|
||||
if self.__form == 'ln':
|
||||
self.var = np.exp(self.var)
|
||||
self.fct = np.divide(self.fct, self.var)
|
||||
self.__form = 'linear'
|
||||
elif self.__form == 'log10':
|
||||
self.var = np.power(10, self.var)
|
||||
self.fct = np.divide(self.fct, self.var * np.log(10))
|
||||
self.__form = 'linear'
|
||||
case 'ln':
|
||||
if self.__form == 'linear':
|
||||
self.var = np.log(self.var)
|
||||
self.fct = np.multiply(self.var, self.fct)
|
||||
self.__form = 'ln'
|
||||
elif self.__form == 'log10':
|
||||
self.var = np.log(np.power(10, self.var))
|
||||
self.fct = np.divide(self.fct, np.log(10))
|
||||
self.__form = 'ln'
|
||||
case 'log10':
|
||||
if self.__form == 'linear':
|
||||
self.fct = np.multiply(self.var, self.fct * np.log(10))
|
||||
self.var = np.log10(self.var)
|
||||
self.__form = 'log10'
|
||||
elif self.__form == 'ln':
|
||||
self.var = np.log10(np.exp(self.var))
|
||||
self.fct = np.multiply(self.fct, np.log(10))
|
||||
self.__form = 'log10'
|
||||
|
||||
def update_units(self, new_var_units, new_fct_units):
|
||||
|
||||
"""A method to update the units of the distribution
|
||||
|
||||
Description
|
||||
-----------
|
||||
Bla Bla Bla
|
||||
|
||||
Parameters
|
||||
----------
|
||||
new_var_units: float
|
||||
The SI factor used to transform the independent variable `self.var`
|
||||
new_fct_units: float
|
||||
The SI factor used to transform the dependent variable `self.fct`
|
||||
"""
|
||||
|
||||
old_from = self.__form
|
||||
self.transform(to='linear')
|
||||
|
||||
self.var = self.var * new_var_units
|
||||
self.fct = self.fct * new_fct_units
|
||||
|
||||
self.transform(to=old_from)
|
||||
|
||||
def integrate(self) -> np.float64:
|
||||
|
||||
"""A method to integrate over the spectrum $dN/d f(D)$
|
||||
|
||||
Description
|
||||
-----------
|
||||
Bla Bla Bla
|
||||
"""
|
||||
|
||||
return np.trapezoid(y = self.fct, x = self.var)
|
||||
|
||||
def median():
|
||||
# TODO: implement that method
|
||||
pass
|
||||
|
||||
def mode():
|
||||
# TODO: implement that method
|
||||
pass
|
||||
|
||||
def mean():
|
||||
# TODO: implement that method
|
||||
pass
|
||||
|
||||
def variance():
|
||||
# TODO: implement that method
|
||||
pass</code></pre>
|
||||
</details>
|
||||
<h3>Methods</h3>
|
||||
<dl>
|
||||
<dt id="defs.OFR.Distribution.integrate"><code class="name flex">
|
||||
<span>def <span class="ident">integrate</span></span>(<span>self) ‑> numpy.float64</span>
|
||||
</code></dt>
|
||||
<dd>
|
||||
<div class="desc"><p>A method to integrate over the spectrum $dN/d f(D)$</p>
|
||||
<h2 id="description">Description</h2>
|
||||
<p>Bla Bla Bla</p></div>
|
||||
</dd>
|
||||
<dt id="defs.OFR.Distribution.mean"><code class="name flex">
|
||||
<span>def <span class="ident">mean</span></span>(<span>)</span>
|
||||
</code></dt>
|
||||
<dd>
|
||||
<div class="desc"></div>
|
||||
</dd>
|
||||
<dt id="defs.OFR.Distribution.median"><code class="name flex">
|
||||
<span>def <span class="ident">median</span></span>(<span>)</span>
|
||||
</code></dt>
|
||||
<dd>
|
||||
<div class="desc"></div>
|
||||
</dd>
|
||||
<dt id="defs.OFR.Distribution.mode"><code class="name flex">
|
||||
<span>def <span class="ident">mode</span></span>(<span>)</span>
|
||||
</code></dt>
|
||||
<dd>
|
||||
<div class="desc"></div>
|
||||
</dd>
|
||||
<dt id="defs.OFR.Distribution.transform"><code class="name flex">
|
||||
<span>def <span class="ident">transform</span></span>(<span>self, to='linear')</span>
|
||||
</code></dt>
|
||||
<dd>
|
||||
<div class="desc"><p>A method to transform distributions between different representations</p>
|
||||
<h2 id="description">Description</h2>
|
||||
<p>Bla bla bla</p>
|
||||
<h2 id="parameters">Parameters</h2>
|
||||
<dl>
|
||||
<dt><strong><code>to</code></strong> : <code>str</code></dt>
|
||||
<dd>Indicating into which representation the distribution should be transformed. Possible values are: <code>linear</code>, <code>ln</code> or <code>log10</code></dd>
|
||||
</dl></div>
|
||||
</dd>
|
||||
<dt id="defs.OFR.Distribution.update_units"><code class="name flex">
|
||||
<span>def <span class="ident">update_units</span></span>(<span>self, new_var_units, new_fct_units)</span>
|
||||
</code></dt>
|
||||
<dd>
|
||||
<div class="desc"><p>A method to update the units of the distribution</p>
|
||||
<h2 id="description">Description</h2>
|
||||
<p>Bla Bla Bla</p>
|
||||
<h2 id="parameters">Parameters</h2>
|
||||
<dl>
|
||||
<dt><strong><code>new_var_units</code></strong> : <code>float</code></dt>
|
||||
<dd>The SI factor used to transform the independent variable <code>self.var</code></dd>
|
||||
<dt><strong><code>new_fct_units</code></strong> : <code>float</code></dt>
|
||||
<dd>The SI factor used to transform the dependent variable <code>self.fct</code></dd>
|
||||
</dl></div>
|
||||
</dd>
|
||||
<dt id="defs.OFR.Distribution.variance"><code class="name flex">
|
||||
<span>def <span class="ident">variance</span></span>(<span>)</span>
|
||||
</code></dt>
|
||||
<dd>
|
||||
<div class="desc"></div>
|
||||
</dd>
|
||||
</dl>
|
||||
</dd>
|
||||
<dt id="defs.OFR.OFRAnalyser"><code class="flex name class">
|
||||
<span>class <span class="ident">OFRAnalyser</span></span>
|
||||
<span>(</span><span>data_source_file, flows_source_file, sample_number_list, data_separator=',')</span>
|
||||
</code></dt>
|
||||
<dd>
|
||||
<div class="desc"><p>An object representing an OFR experiment</p>
|
||||
<h2 id="description">Description</h2>
|
||||
<p>Bla Bla Bla</p>
|
||||
<h2 id="attributes">Attributes</h2>
|
||||
<dl>
|
||||
<dt><strong><code>data_source_file</code></strong> : <code>str</code></dt>
|
||||
<dd>A string pointing to the data source file</dd>
|
||||
<dt><strong><code>flows_source_file</code></strong> : <code>str</code></dt>
|
||||
<dd>A string pointing to the flow data source file</dd>
|
||||
<dt><strong><code>sample_number_list</code></strong> : <code>[int]</code></dt>
|
||||
<dd>A list of integers indicating which samples to consider</dd>
|
||||
<dt><strong><code>max_samples</code></strong> : <code>int</code></dt>
|
||||
<dd>The highest sample available in the data</dd>
|
||||
<dt><strong><code>data</code></strong> : <code>pandas.DataFrame</code></dt>
|
||||
<dd>A dataframe containing all the data</dd>
|
||||
</dl></div>
|
||||
<details class="source">
|
||||
<summary>
|
||||
<span>Expand source code</span>
|
||||
</summary>
|
||||
<pre><code class="python">class OFRAnalyser:
|
||||
|
||||
"""An object representing an OFR experiment
|
||||
|
||||
Description
|
||||
-----------
|
||||
Bla Bla Bla
|
||||
|
||||
Attributes
|
||||
----------
|
||||
data_source_file: str
|
||||
A string pointing to the data source file
|
||||
flows_source_file: str
|
||||
A string pointing to the flow data source file
|
||||
sample_number_list: [int]
|
||||
A list of integers indicating which samples to consider
|
||||
max_samples: int
|
||||
The highest sample available in the data
|
||||
data: pandas.DataFrame
|
||||
A dataframe containing all the data
|
||||
"""
|
||||
|
||||
def __init__(self, data_source_file, flows_source_file, sample_number_list, data_separator = ',') -> None:
|
||||
|
||||
self.data_source_file = data_source_file
|
||||
self.flows_source_file = flows_source_file
|
||||
self.sample_number_list = sample_number_list
|
||||
self.__data_separator = data_separator
|
||||
|
||||
with open(self.data_source_file, 'r', errors = 'ignore') as file:
|
||||
for i, line in enumerate(file.readlines()):
|
||||
if i == 17:
|
||||
items = line.split(',')
|
||||
max_sample_number = int(len(items) / 2)
|
||||
else:
|
||||
continue
|
||||
|
||||
self.max_samples = max_sample_number
|
||||
self.data = None
|
||||
|
||||
def __sample_number_list_check(self, sample_number_list) -> None:
|
||||
|
||||
# TODO: implement a similar check for the flow data file!
|
||||
|
||||
last_sample = sample_number_list[-1]
|
||||
|
||||
if last_sample > self.max_samples:
|
||||
raise IndexError("The last sample(s) are out of range of the number of recorded samples")
|
||||
|
||||
def GetData(self) -> None:
|
||||
|
||||
"""Method to get the data
|
||||
|
||||
Description
|
||||
-----------
|
||||
Bla Bla Bla
|
||||
"""
|
||||
|
||||
# TODO make this work also for a specific sample!
|
||||
# TODO convert everything is SI units, making live a lot easier...
|
||||
|
||||
self.__sample_number_list_check(self.sample_number_list)
|
||||
|
||||
numbers_of_sample = [] # (-)
|
||||
number_concentrations = [] # (#/m^3)
|
||||
length_concentrations = [] # (m/m^3)
|
||||
surface_concentrations = [] # (m^2/m^3)
|
||||
volume_concentrations = [] # (m^3/m^3)
|
||||
aerosol_densities = [] # (kg/m^3)
|
||||
mass_concentrations = [] # (kg/m^3)
|
||||
starting_times = [] # (s)
|
||||
stopping_times = [] # (s)
|
||||
sampling_times = [] # (s)
|
||||
dry_air_flows = [] # (m^3/s)
|
||||
species_flows = [] # (m^3/s)
|
||||
ozone_flows = [] # (m^3/s)
|
||||
total_flows = None # (m^3/s)
|
||||
cpc_flows = [] # (m^3/s)
|
||||
mass_production_rate = None # (kg/s)
|
||||
mass_produced = None # (kg)
|
||||
cumulative_mass_produced = None # (kg)
|
||||
|
||||
|
||||
for sample_number in self.sample_number_list:
|
||||
sample = OFRSample(source_file=self.data_source_file, sample_number = sample_number, data_separator = self.__data_separator)
|
||||
|
||||
numbers_of_sample.append(sample_number)
|
||||
number_concentrations.append(sample.Count.integrate())
|
||||
length_concentrations.append(sample.Length.integrate())
|
||||
surface_concentrations.append(sample.Surface.integrate())
|
||||
volume_concentrations.append(sample.Volume.integrate())
|
||||
aerosol_densities.append(sample.SOA_density)
|
||||
mass_concentrations.append(sample.Mass.integrate())
|
||||
|
||||
starting_times.append((sample_number - 1) * sample.sampling_time)
|
||||
stopping_times.append(sample_number * sample.sampling_time)
|
||||
|
||||
sampling_times.append(sample.sampling_time)
|
||||
|
||||
out_flag = False
|
||||
|
||||
with open(self.flows_source_file, 'r', errors='ignore') as file:
|
||||
|
||||
j = 1
|
||||
|
||||
for line_counter, line in enumerate(file.readlines()):
|
||||
|
||||
if out_flag == True:
|
||||
continue
|
||||
|
||||
if line_counter >= 6:
|
||||
|
||||
if line.startswith('-'):
|
||||
out_flag = True
|
||||
continue
|
||||
|
||||
i = 0
|
||||
items = line.split()
|
||||
|
||||
while i < int(items[-1]):
|
||||
|
||||
if j in self.sample_number_list:
|
||||
dry_air_flows.append(float(items[0]) * 6E-4)
|
||||
species_flows.append(float(items[1]) * 6E-4)
|
||||
ozone_flows.append(float(items[2]) * 6E-4)
|
||||
cpc_flows.append(float(items[3]) * 6E-4)
|
||||
|
||||
i += 1
|
||||
j += 1
|
||||
|
||||
else:
|
||||
continue
|
||||
|
||||
total_flows = [(flow_1 + flow_2 + flow_3) for flow_1, flow_2, flow_3 in zip(dry_air_flows, species_flows, ozone_flows)]
|
||||
mass_production_rate = [(mass * flow) for mass, flow in zip(mass_concentrations, total_flows)]
|
||||
mass_produced = [(mpr * duration) for mpr, duration in zip(mass_production_rate, sampling_times)]
|
||||
cumulative_mass_produced = np.cumsum(np.array(mass_produced)).tolist()
|
||||
|
||||
self.data = pd.DataFrame({'Sample (-)': numbers_of_sample,
|
||||
'Number (#/m^3)': number_concentrations,
|
||||
'Length (m/m^3)': length_concentrations,
|
||||
'Surface (m^2/m^3)': surface_concentrations,
|
||||
'Volume (m^3/m^3)': volume_concentrations,
|
||||
'Density (kg/m^3)': aerosol_densities,
|
||||
'Mass (kg/m^3)': mass_concentrations,
|
||||
'Start (s)': starting_times,
|
||||
'Stop (s)': stopping_times,
|
||||
'Duration (s)': sampling_times,
|
||||
'Dry Air Flow (m^3/s)': dry_air_flows,
|
||||
'Species Flow (m^3/s)': species_flows,
|
||||
'Ozone Flow (m^3/s)': ozone_flows,
|
||||
'Total Flow (m^3/s)': total_flows,
|
||||
'CPC Flow (m^3/s)': cpc_flows,
|
||||
'Mass Production Rate (kg/s)': mass_production_rate,
|
||||
'Mass Produced (kg)': mass_produced,
|
||||
'Cumulative Mass Produced (kg)': cumulative_mass_produced})</code></pre>
|
||||
</details>
|
||||
<h3>Methods</h3>
|
||||
<dl>
|
||||
<dt id="defs.OFR.OFRAnalyser.GetData"><code class="name flex">
|
||||
<span>def <span class="ident">GetData</span></span>(<span>self) ‑> None</span>
|
||||
</code></dt>
|
||||
<dd>
|
||||
<div class="desc"><p>Method to get the data</p>
|
||||
<h2 id="description">Description</h2>
|
||||
<p>Bla Bla Bla</p></div>
|
||||
</dd>
|
||||
</dl>
|
||||
</dd>
|
||||
<dt id="defs.OFR.OFRSample"><code class="flex name class">
|
||||
<span>class <span class="ident">OFRSample</span></span>
|
||||
<span>(</span><span>source_file, sample_number, data_separator=',')</span>
|
||||
</code></dt>
|
||||
<dd>
|
||||
<div class="desc"><p>Object to represent a single sample from the OFR</p>
|
||||
<h2 id="description">Description</h2>
|
||||
<p>Bla bla bla</p>
|
||||
<h2 id="attributes">Attributes</h2>
|
||||
<dl>
|
||||
<dt><strong><code>number</code></strong> : <code>int</code></dt>
|
||||
<dd>The sample number</dd>
|
||||
<dt><strong><code>sourcefile</code></strong> : <code>str</code></dt>
|
||||
<dd>The path to the data file</dd>
|
||||
<dt><strong><code>headlines</code></strong> : <code>int</code></dt>
|
||||
<dd>The number of lines in the data file until raw data is reached</dd>
|
||||
<dt><strong><code>lower_bound</code></strong> : <code>float</code></dt>
|
||||
<dd>The lower bound diameter (nm) of the SMPS</dd>
|
||||
<dt><strong><code>upper_bound</code></strong> : <code>float</code></dt>
|
||||
<dd>The upper bound diameter (nm) of the SMPS</dd>
|
||||
<dt><strong><code>scan_up</code></strong> : <code>float</code></dt>
|
||||
<dd>The time (s) to ramp up voltage in SMPS</dd>
|
||||
<dt><strong><code>scan_down</code></strong> : <code>float</code></dt>
|
||||
<dd>The time (s) to ramp voltage back down in SMPS</dd>
|
||||
<dt><strong><code>delta_time</code></strong> : <code>float</code></dt>
|
||||
<dd>The time interval (s) between two measured data points of the raw count density</dd>
|
||||
<dt><strong><code>SOA_density</code></strong> : <code>float</code></dt>
|
||||
<dd>The density (kg/m3) of the SOA produced in the OFR</dd>
|
||||
</dl></div>
|
||||
<details class="source">
|
||||
<summary>
|
||||
<span>Expand source code</span>
|
||||
</summary>
|
||||
<pre><code class="python">class OFRSample:
|
||||
|
||||
"""Object to represent a single sample from the OFR
|
||||
|
||||
Description
|
||||
-----------
|
||||
Bla bla bla
|
||||
|
||||
Attributes
|
||||
----------
|
||||
|
||||
number: int
|
||||
The sample number
|
||||
sourcefile: str
|
||||
The path to the data file
|
||||
headlines: int
|
||||
The number of lines in the data file until raw data is reached
|
||||
lower_bound: float
|
||||
The lower bound diameter (nm) of the SMPS
|
||||
upper_bound: float
|
||||
The upper bound diameter (nm) of the SMPS
|
||||
scan_up: float
|
||||
The time (s) to ramp up voltage in SMPS
|
||||
scan_down: float
|
||||
The time (s) to ramp voltage back down in SMPS
|
||||
delta_time: float
|
||||
The time interval (s) between two measured data points of the raw count density
|
||||
SOA_density: float
|
||||
The density (kg/m3) of the SOA produced in the OFR
|
||||
"""
|
||||
|
||||
def __get_data(self) -> np.float64:
|
||||
|
||||
footer_flag = False
|
||||
footer_start_index = 0
|
||||
data_flag = False
|
||||
data_lines = []
|
||||
|
||||
midpoints = []
|
||||
counts = []
|
||||
|
||||
with open(self.source_file, 'r', errors = 'ignore') as file:
|
||||
for i, line in enumerate(file.readlines()):
|
||||
if i == 20:
|
||||
data_flag = True
|
||||
continue
|
||||
if data_flag == True:
|
||||
data_lines.append(line)
|
||||
if line.split(self.__data_separator)[0] == 'Scan Up Time(s)':
|
||||
data_flag = False
|
||||
footer_flag = True
|
||||
footer_start_index = i
|
||||
self.scan_up_time = float(line.split(self.__data_separator)[1])
|
||||
continue
|
||||
if footer_flag == False:
|
||||
continue
|
||||
else:
|
||||
if i == footer_start_index + 1:
|
||||
self.scan_down_time = float(line.split(self.__data_separator)[1])
|
||||
continue
|
||||
elif i == footer_start_index + 6:
|
||||
self.aerosol_flow = float(line.split(self.__data_separator)[1])
|
||||
continue
|
||||
elif i == footer_start_index + 11:
|
||||
self.lower_diameter_bound = float(line.split(self.__data_separator)[1])
|
||||
continue
|
||||
elif i == footer_start_index + 12:
|
||||
self.upper_diameter_bound = float(line.split(self.__data_separator)[1])
|
||||
continue
|
||||
elif i == footer_start_index + 13:
|
||||
self.SOA_density = float(line.split(self.__data_separator)[1])
|
||||
continue
|
||||
|
||||
self.sampling_time = self.scan_up_time + self.scan_down_time
|
||||
data_lines.pop(-1)
|
||||
|
||||
for line in data_lines:
|
||||
items = line.split(self.__data_separator)
|
||||
local_diameter_midpoint = float(items[0])
|
||||
if self.lower_diameter_bound <= local_diameter_midpoint and local_diameter_midpoint <= self.upper_diameter_bound:
|
||||
midpoints.append(local_diameter_midpoint)
|
||||
items.pop(0)
|
||||
counts.append(float(items[(self.sample_number - 1) * 2]))
|
||||
else:
|
||||
continue
|
||||
|
||||
self.aerosol_flow = self.aerosol_flow * 6E-4
|
||||
self.SOA_density = self.SOA_density * 1E3
|
||||
self.lower_diameter_bound = self.lower_diameter_bound * 1E-9
|
||||
self.upper_diameter_bound = self.upper_diameter_bound * 1E-9
|
||||
|
||||
|
||||
# Input data from file is in (nm)
|
||||
return [np.array(midpoints), np.array(counts)]
|
||||
|
||||
def __init__(self, source_file, sample_number, data_separator = ','):
|
||||
|
||||
## VALUES READ IN FROM DISK
|
||||
#--------------------------
|
||||
|
||||
# Sample information
|
||||
self.source_file = source_file # where the data is stored, i.e. "C:/Users/tschan_d/..."
|
||||
self.sample_number = sample_number # sample number, i.e. 33
|
||||
self.__data_separator = data_separator
|
||||
|
||||
self.scan_up_time = None # Time to scan up the voltage range in DMA, in (s)
|
||||
self.scan_down_time = None # Time to scan down the voltage range in DMA, in(s)
|
||||
self.sampling_time = None # Total time to scan voltage up and back down in DMA, in (s)
|
||||
|
||||
self.lower_diameter_bound = None # Lower Diameter bound of CPC, in (nm)
|
||||
self.upper_diameter_bound = None # Upper Diameter bound of CPC, in (nm)
|
||||
self.aerosol_flow = None # Aerosol flow, in (L/min)
|
||||
self.SOA_density = None # Expected density of SOA, in (g/cm3)
|
||||
|
||||
# Distributions of the relevant quantities (all relative to nanometer)
|
||||
data = self.__get_data()
|
||||
|
||||
# Getting Distribution objects
|
||||
self.Count = Distribution(variable_array = np.log10(data[0]), function_array = data[1], form='log10')
|
||||
self.Count.update_units(new_fct_units=1E15, new_var_units=1E-9)
|
||||
|
||||
self.Length = Distribution(variable_array = np.log10(data[0]), function_array = data[0]*data[1], form = 'log10')
|
||||
self.Length.update_units(new_fct_units=1E6, new_var_units=1E-9)
|
||||
|
||||
self.Surface = Distribution(variable_array = np.log(data[0]), function_array = ((math.pi)* data[0] ** 2) * data[1], form = 'log10')
|
||||
self.Surface.update_units(new_fct_units=1E-3, new_var_units=1E-9)
|
||||
|
||||
self.Volume = Distribution(variable_array = np.log10(data[0]),function_array = ((math.pi / 6) * data[0] ** 3) * data[1], form = 'log10')
|
||||
self.Volume.update_units(new_fct_units=1E-12, new_var_units=1E-9)
|
||||
|
||||
self.Mass = Distribution(variable_array = self.Volume.var, function_array = self.Volume.fct * self.SOA_density, form='log10')</code></pre>
|
||||
</details>
|
||||
</dd>
|
||||
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|
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|
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|
||||
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|
||||
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|
||||
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|
||||
<h4><code><a title="defs.OFR.Distribution" href="#defs.OFR.Distribution">Distribution</a></code></h4>
|
||||
<ul class="two-column">
|
||||
<li><code><a title="defs.OFR.Distribution.integrate" href="#defs.OFR.Distribution.integrate">integrate</a></code></li>
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
<li><code><a title="defs.OFR.Distribution.update_units" href="#defs.OFR.Distribution.update_units">update_units</a></code></li>
|
||||
<li><code><a title="defs.OFR.Distribution.variance" href="#defs.OFR.Distribution.variance">variance</a></code></li>
|
||||
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|
||||
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|
||||
<li>
|
||||
<h4><code><a title="defs.OFR.OFRAnalyser" href="#defs.OFR.OFRAnalyser">OFRAnalyser</a></code></h4>
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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hljs.configure({languages: ['bash', 'css', 'diff', 'graphql', 'ini', 'javascript', 'json', 'plaintext', 'python', 'python-repl', 'rust', 'shell', 'sql', 'typescript', 'xml', 'yaml']});
|
||||
hljs.highlightAll();
|
||||
})</script>
|
||||
</head>
|
||||
<body>
|
||||
<main>
|
||||
<article id="content">
|
||||
<header>
|
||||
<h1 class="title">Module <code>defs.computing</code></h1>
|
||||
</header>
|
||||
<section id="section-intro">
|
||||
</section>
|
||||
<section>
|
||||
</section>
|
||||
<section>
|
||||
</section>
|
||||
<section>
|
||||
</section>
|
||||
<section>
|
||||
<h2 class="section-title" id="header-classes">Classes</h2>
|
||||
<dl>
|
||||
<dt id="defs.computing.OFRAnalyser"><code class="flex name class">
|
||||
<span>class <span class="ident">OFRAnalyser</span></span>
|
||||
<span>(</span><span>sourcefile, headlines=238, density=1.2, lower_bound=0, upper_bound=1896, scan_up=160, scan_down=20, flow_rate=5)</span>
|
||||
</code></dt>
|
||||
<dd>
|
||||
<div class="desc"></div>
|
||||
<details class="source">
|
||||
<summary>
|
||||
<span>Expand source code</span>
|
||||
</summary>
|
||||
<pre><code class="python">class OFRAnalyser:
|
||||
|
||||
def __init__(self, sourcefile, headlines = 238, density=1.2, lower_bound = 0, upper_bound = 1896, scan_up=160, scan_down=20,
|
||||
flow_rate=5) -> None:
|
||||
|
||||
# where to take data from:
|
||||
self.sourcefile = sourcefile
|
||||
# how many lines to skip until the raw counts data section is reached:
|
||||
self.headlines = headlines
|
||||
# assumed SOA density
|
||||
self.density = density
|
||||
self.lower_bound = lower_bound
|
||||
self.upper_bound = upper_bound
|
||||
self.scan_up = scan_up
|
||||
self.scan_down = scan_down
|
||||
self.flow_rate = flow_rate
|
||||
|
||||
with open(self.sourcefile) as file:
|
||||
file_reader = csv.reader(file)
|
||||
for index, row in enumerate(file_reader):
|
||||
if index != self.headlines:
|
||||
continue
|
||||
else:
|
||||
head_row = row
|
||||
|
||||
self.max_samples = int((len(head_row) - 1) / 2)
|
||||
|
||||
# total mass in mg
|
||||
self.total_counts = None
|
||||
self.total_surface = None
|
||||
self.total_volume = None
|
||||
self.total_mass = None
|
||||
|
||||
def __sample_number_list_check(self, sample_number_list) -> None:
|
||||
|
||||
last_sample = sample_number_list[-1]
|
||||
|
||||
if last_sample > self.max_samples:
|
||||
raise IndexError("The last sample(s) are out of range of the number of recorded samples")
|
||||
|
||||
def AggregateSamples(self, samples = [1]) -> None:
|
||||
|
||||
self.__sample_number_list_check(samples)
|
||||
|
||||
counts = []
|
||||
surfaces = []
|
||||
volumes = []
|
||||
masses = []
|
||||
|
||||
for samplenumber in samples:
|
||||
sample = OFRSample(number=samplenumber, sourcefile=self.sourcefile, headlines=self.headlines, density=self.density,
|
||||
lower_bound = self.lower_bound, upper_bound = self.upper_bound, scan_up = self.scan_up,
|
||||
scan_down = self.scan_down)
|
||||
|
||||
counts.append(sample.total_count)
|
||||
surfaces.append(sample.total_surface)
|
||||
volumes.append(sample.total_volume)
|
||||
masses.append(sample.total_mass)
|
||||
|
||||
self.total_count = sum(counts)
|
||||
self.total_surface = sum(surfaces)
|
||||
self.total_volume = sum(volumes)
|
||||
self.total_mass = sum(masses)</code></pre>
|
||||
</details>
|
||||
<h3>Methods</h3>
|
||||
<dl>
|
||||
<dt id="defs.computing.OFRAnalyser.AggregateSamples"><code class="name flex">
|
||||
<span>def <span class="ident">AggregateSamples</span></span>(<span>self, samples=[1]) ‑> None</span>
|
||||
</code></dt>
|
||||
<dd>
|
||||
<div class="desc"></div>
|
||||
</dd>
|
||||
</dl>
|
||||
</dd>
|
||||
<dt id="defs.computing.OFRSample"><code class="flex name class">
|
||||
<span>class <span class="ident">OFRSample</span></span>
|
||||
<span>(</span><span>number, sourcefile, headlines, density, lower_bound, upper_bound, scan_up, scan_down, delta_time=0.1)</span>
|
||||
</code></dt>
|
||||
<dd>
|
||||
<div class="desc"><p>Object to represent a single sample from the OFR</p>
|
||||
<p>Description: Bla</p>
|
||||
<h2 id="attributes">Attributes</h2>
|
||||
<dl>
|
||||
<dt><strong><code>number</code></strong> : <code>int</code></dt>
|
||||
<dd>The sample number</dd>
|
||||
<dt><strong><code>sourcefile</code></strong> : <code>str</code></dt>
|
||||
<dd>The path to the data file</dd>
|
||||
<dt><strong><code>headlines</code></strong> : <code>int</code></dt>
|
||||
<dd>The number of lines in the data file until raw data is reached</dd>
|
||||
<dt><strong><code>lower_bound</code></strong> : <code>float</code></dt>
|
||||
<dd>The lower bound diameter (nm) of the SMPS</dd>
|
||||
<dt><strong><code>upper_bound</code></strong> : <code>float</code></dt>
|
||||
<dd>The upper bound diameter (nm) of the SMPS</dd>
|
||||
<dt><strong><code>scan_up</code></strong> : <code>float</code></dt>
|
||||
<dd>The time (s) to ramp up voltage in SMPS</dd>
|
||||
<dt><strong><code>scan_down</code></strong> : <code>float</code></dt>
|
||||
<dd>The time (s) to ramp voltage back down in SMPS</dd>
|
||||
<dt><strong><code>delta_time</code></strong> : <code>float</code></dt>
|
||||
<dd>The time interval (s) between two measured data points of the raw count density</dd>
|
||||
<dt><strong><code>SOA_density</code></strong> : <code>float</code></dt>
|
||||
<dd>The density (kg/m3) of the SOA produced in the OFR</dd>
|
||||
</dl>
|
||||
<h2 id="methods">Methods</h2>
|
||||
<p><strong>init</strong>(number, sourcefile, headlines, density, lower_bound, upper_bound, scan_up, scan_down, delta_time) -> OFRSample:
|
||||
The constructor of the Object</p>
|
||||
<p>Constructor of a OFRSample object</p>
|
||||
<p>Description:</p>
|
||||
<h2 id="parameters">Parameters</h2>
|
||||
<dl>
|
||||
<dt><strong><code>number</code></strong> : <code>int</code></dt>
|
||||
<dd>The sample number</dd>
|
||||
</dl>
|
||||
<h2 id="returns">Returns</h2>
|
||||
<dl>
|
||||
<dt><strong><code>None</code></strong> : <code>None</code></dt>
|
||||
<dd>Does not have a return value</dd>
|
||||
</dl></div>
|
||||
<details class="source">
|
||||
<summary>
|
||||
<span>Expand source code</span>
|
||||
</summary>
|
||||
<pre><code class="python">class OFRSample:
|
||||
|
||||
"""Object to represent a single sample from the OFR
|
||||
|
||||
Description: Bla
|
||||
|
||||
Attributes
|
||||
----------
|
||||
number: int
|
||||
The sample number
|
||||
sourcefile: str
|
||||
The path to the data file
|
||||
headlines: int
|
||||
The number of lines in the data file until raw data is reached
|
||||
lower_bound: float
|
||||
The lower bound diameter (nm) of the SMPS
|
||||
upper_bound: float
|
||||
The upper bound diameter (nm) of the SMPS
|
||||
scan_up: float
|
||||
The time (s) to ramp up voltage in SMPS
|
||||
scan_down: float
|
||||
The time (s) to ramp voltage back down in SMPS
|
||||
delta_time: float
|
||||
The time interval (s) between two measured data points of the raw count density
|
||||
SOA_density: float
|
||||
The density (kg/m3) of the SOA produced in the OFR
|
||||
|
||||
Methods
|
||||
-------
|
||||
__init__(number, sourcefile, headlines, density, lower_bound, upper_bound, scan_up, scan_down, delta_time) -> OFRSample:
|
||||
The constructor of the Object
|
||||
"""
|
||||
|
||||
def __init__(self, number, sourcefile, headlines, density, lower_bound, upper_bound, scan_up, scan_down, delta_time = 0.1):
|
||||
|
||||
"""Constructor of a OFRSample object
|
||||
|
||||
Description:
|
||||
|
||||
Parameters
|
||||
----------
|
||||
number: int
|
||||
The sample number
|
||||
|
||||
Returns
|
||||
-------
|
||||
None: None
|
||||
Does not have a return value
|
||||
"""
|
||||
|
||||
# Sample information
|
||||
self.number = number # sample number, i.e. 33
|
||||
self.sourcefile = sourcefile # where the data is stored, "C:/Users/tschan_d/..."
|
||||
self.headlines = headlines # Number of lines before raw data is reached, usually 238
|
||||
self.lower_bound = lower_bound # Lower Diameter (nm) where CPC works
|
||||
self.upper_bound = upper_bound # Upper Diameter (nm) where CPC works
|
||||
self.scan_up = scan_up # Time to scan up the voltage range in DMA
|
||||
self.scan_down = scan_down # Time to ramp the voltage back down in DMA
|
||||
self.delta_time = delta_time # Measuring interval to get raw count density; (s)
|
||||
self.SOA_density = density # Expected density of SOA (kg/m3)
|
||||
|
||||
# Sample distributions
|
||||
self.diameters = None # Diameters (nm)
|
||||
self.count_density = None # Count Density (#/(m3*m*s))
|
||||
self.surface_density = None # Surface Density (m2/(m3*m*s))
|
||||
self.volume_density = None # Volume Density (m3/(m3*m*s))
|
||||
self.mass_density = None # Mass Density (kg/(m3*m*s))
|
||||
|
||||
self.total_count = None # Total Count (#/(m3*s))
|
||||
self.total_surface = None # Total Surface (m2/(m3*s))
|
||||
self.total_volume = None # Total Volume (m3/(m3*s))
|
||||
self.total_mass = None # Total Mass (kg/(m3*s))
|
||||
|
||||
self.get_data()
|
||||
|
||||
def get_data(self):
|
||||
|
||||
columns = ['Diameter #' + str(self.number), 'Counts #' + str(self.number)]
|
||||
sample_data = pd.read_csv(filepath_or_buffer=self.sourcefile, header=self.headlines, usecols=columns, index_col=False,
|
||||
skipfooter=1, engine='python').to_numpy()
|
||||
|
||||
filter_array = np.where((sample_data[:, 0] >= self.lower_bound) & (sample_data[:, 0] <= self.upper_bound), True, False)
|
||||
|
||||
# Particle Diameter: Raw data in (nm) -> Output data in (m): 1 nm = 1E-9 m
|
||||
self.diameters = sample_data[filter_array, 0] * 1E-9
|
||||
|
||||
# Particle Count Density: Raw data in (#/(cm3*nm*0.1s)) -> Output data in (#/(m3*m*s)): 1/(cm3*nm*s) = 1E16/(m3*m*s)
|
||||
self.count_density = sample_data[filter_array, 1] * 1E16
|
||||
|
||||
self.surface_density = np.multiply(math.pi * self.diameters ** 2, self.count_density)
|
||||
self.volume_density = np.multiply((math.pi / 6) * self.diameters ** 3, self.count_density)
|
||||
self.mass_density = np.multiply(self.SOA_density, self.volume_density)
|
||||
|
||||
self.total_count = self.__integrator(integrand = self.count_density)
|
||||
self.total_surface = self.__integrator(integrand = self.surface_density)
|
||||
self.total_volume = self.__integrator(integrand = self.volume_density)
|
||||
self.total_mass = self.total_volume * self.SOA_density
|
||||
|
||||
def __integrator(self, integrand: np.float64) -> np.float64:
|
||||
|
||||
return np.trapezoid(y = integrand, x = self.diameters)</code></pre>
|
||||
</details>
|
||||
<h3>Methods</h3>
|
||||
<dl>
|
||||
<dt id="defs.computing.OFRSample.get_data"><code class="name flex">
|
||||
<span>def <span class="ident">get_data</span></span>(<span>self)</span>
|
||||
</code></dt>
|
||||
<dd>
|
||||
<div class="desc"></div>
|
||||
</dd>
|
||||
</dl>
|
||||
</dd>
|
||||
</dl>
|
||||
</section>
|
||||
</article>
|
||||
<nav id="sidebar">
|
||||
<div class="toc">
|
||||
<ul></ul>
|
||||
</div>
|
||||
<ul id="index">
|
||||
<li><h3>Super-module</h3>
|
||||
<ul>
|
||||
<li><code><a title="defs" href="index.html">defs</a></code></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li><h3><a href="#header-classes">Classes</a></h3>
|
||||
<ul>
|
||||
<li>
|
||||
<h4><code><a title="defs.computing.OFRAnalyser" href="#defs.computing.OFRAnalyser">OFRAnalyser</a></code></h4>
|
||||
<ul class="">
|
||||
<li><code><a title="defs.computing.OFRAnalyser.AggregateSamples" href="#defs.computing.OFRAnalyser.AggregateSamples">AggregateSamples</a></code></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li>
|
||||
<h4><code><a title="defs.computing.OFRSample" href="#defs.computing.OFRSample">OFRSample</a></code></h4>
|
||||
<ul class="">
|
||||
<li><code><a title="defs.computing.OFRSample.get_data" href="#defs.computing.OFRSample.get_data">get_data</a></code></li>
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
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</nav>
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<footer id="footer">
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<p>Generated by <a href="https://pdoc3.github.io/pdoc" title="pdoc: Python API documentation generator"><cite>pdoc</cite> 0.11.1</a>.</p>
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|
||||
</body>
|
||||
</html>
|
||||
+357
-15
@@ -2,18 +2,360 @@ name: MA
|
||||
channels:
|
||||
- conda-forge
|
||||
dependencies:
|
||||
- python=3.12
|
||||
- ipython
|
||||
- ipykernel
|
||||
- ipywidgets
|
||||
- matplotlib
|
||||
- jupyterlab
|
||||
- notebook
|
||||
- numpy
|
||||
- pandas
|
||||
- seaborn
|
||||
- scipy
|
||||
- sympy
|
||||
- cython
|
||||
- spyder
|
||||
- pip
|
||||
- _openmp_mutex=4.5=20_gnu
|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
- fonttools=4.63.0=py312h05f76fc_0
|
||||
- fqdn=1.5.1=pyhd8ed1ab_1
|
||||
- freetype=2.14.3=h57928b3_1
|
||||
- fribidi=1.0.16=hfd05255_0
|
||||
- frozenlist=1.8.0=py312hfdf67e6_0
|
||||
- fzf=0.73.1=hd02998f_0
|
||||
- glib=2.88.1=h355229b_2
|
||||
- glib-tools=2.88.1=h81d4522_2
|
||||
- graphite2=1.3.15=hac47afa_0
|
||||
- gst-plugins-base=1.26.11=h88486b4_0
|
||||
- gstreamer=1.26.11=hae9036a_0
|
||||
- h11=0.16.0=pyhcf101f3_1
|
||||
- h2=4.3.0=pyhcf101f3_0
|
||||
- harfbuzz=14.2.1=h5a1b470_0
|
||||
- hpack=4.1.0=pyhd8ed1ab_0
|
||||
- httpcore=1.0.9=pyh29332c3_0
|
||||
- httpx=0.28.1=pyhd8ed1ab_0
|
||||
- hyperframe=6.1.0=pyhd8ed1ab_0
|
||||
- icu=78.3=h637d24d_0
|
||||
- idna=3.17=pyhcf101f3_0
|
||||
- imagesize=2.0.0=pyhd8ed1ab_0
|
||||
- importlib-metadata=9.0.0=pyhcf101f3_0
|
||||
- importlib_resources=7.1.0=pyhd8ed1ab_0
|
||||
- inflection=0.5.1=pyhd8ed1ab_1
|
||||
- intervaltree=3.1.0=pyhd8ed1ab_1
|
||||
- ipykernel=6.31.0=pyh6dadd2b_0
|
||||
- ipython=9.14.1=pyhe2676ad_0
|
||||
- ipython_pygments_lexers=1.1.1=pyhd8ed1ab_0
|
||||
- ipywidgets=8.1.8=pyhd8ed1ab_0
|
||||
- isoduration=20.11.0=pyhd8ed1ab_1
|
||||
- isort=8.0.1=pyhd8ed1ab_0
|
||||
- jaraco.classes=3.4.0=pyhcf101f3_3
|
||||
- jaraco.context=6.1.2=pyhcf101f3_0
|
||||
- jaraco.functools=4.5.0=pyhcf101f3_0
|
||||
- jedi=0.19.2=pyhd8ed1ab_1
|
||||
- jellyfish=1.2.1=py312hb0142fd_1
|
||||
- jinja2=3.1.6=pyhcf101f3_1
|
||||
- json5=0.14.0=pyhd8ed1ab_0
|
||||
- jsonpointer=3.1.1=pyhcf101f3_0
|
||||
- jsonschema=4.26.0=pyhcf101f3_0
|
||||
- jsonschema-specifications=2025.9.1=pyhcf101f3_0
|
||||
- jsonschema-with-format-nongpl=4.26.0=hcf101f3_0
|
||||
- jupyter-lsp=2.3.1=pyhcf101f3_0
|
||||
- jupyter_client=8.9.1=pyhcf101f3_0
|
||||
- jupyter_core=5.9.1=pyh6dadd2b_0
|
||||
- jupyter_events=0.12.1=pyhcf101f3_0
|
||||
- jupyter_server=2.19.0=pyhcf101f3_0
|
||||
- jupyter_server_terminals=0.5.4=pyhcf101f3_0
|
||||
- jupyterlab=4.5.8=pyhd8ed1ab_0
|
||||
- jupyterlab_pygments=0.3.0=pyhd8ed1ab_2
|
||||
- jupyterlab_server=2.28.0=pyhcf101f3_0
|
||||
- jupyterlab_widgets=3.0.16=pyhcf101f3_1
|
||||
- keyring=25.7.0=pyh7428d3b_0
|
||||
- kiwisolver=1.5.0=py312h78d62e6_0
|
||||
- krb5=1.22.2=h0ea6238_0
|
||||
- lark=1.3.1=pyhd8ed1ab_0
|
||||
- lcms2=2.19.1=hf2c6c5f_1
|
||||
- lerc=4.1.0=hd936e49_0
|
||||
- libblas=3.11.0=8_h8455456_mkl
|
||||
- libbrotlicommon=1.2.0=hfd05255_1
|
||||
- libbrotlidec=1.2.0=hfd05255_1
|
||||
- libbrotlienc=1.2.0=hfd05255_1
|
||||
- libcblas=3.11.0=8_h2a3cdd5_mkl
|
||||
- libclang13=22.1.7=default_ha2db4b5_1
|
||||
- libdeflate=1.25=h51727cc_0
|
||||
- libexpat=2.8.1=hac47afa_1
|
||||
- libffi=3.5.2=h3d046cb_0
|
||||
- libfreetype=2.14.3=h57928b3_1
|
||||
- libfreetype6=2.14.3=hdbac1cb_1
|
||||
- libgcc=15.2.0=h8ee18e1_19
|
||||
- libglib=2.88.1=h7ce1215_2
|
||||
- libgomp=15.2.0=h8ee18e1_19
|
||||
- libhwloc=2.13.0=default_h049141e_1000
|
||||
- libiconv=1.18=hc1393d2_2
|
||||
- libintl=0.22.5=h5728263_3
|
||||
- libintl-devel=0.22.5=h5728263_3
|
||||
- libjpeg-turbo=3.1.4.1=hfd05255_0
|
||||
- liblapack=3.11.0=8_hf9ab0e9_mkl
|
||||
- liblzma=5.8.3=hfd05255_0
|
||||
- libogg=1.3.5=h2466b09_1
|
||||
- libpng=1.6.58=h7351971_0
|
||||
- libsodium=1.0.22=h6a83c73_1
|
||||
- libspatialindex=2.1.0=h2854ae6_1
|
||||
- libsqlite=3.53.2=hf5d6505_0
|
||||
- libtiff=4.7.1=h8f73337_1
|
||||
- libvorbis=1.3.7=h5112557_2
|
||||
- libvulkan-loader=1.4.341.0=h477610d_0
|
||||
- libwebp=1.6.0=h4d5522a_0
|
||||
- libwebp-base=1.6.0=h4d5522a_0
|
||||
- libwinpthread=12.0.0.r4.gg4f2fc60ca=h57928b3_10
|
||||
- libxcb=1.17.0=h0e4246c_0
|
||||
- libxml2=2.15.3=h8ef44ab_0
|
||||
- libxml2-16=2.15.3=h3cfd58e_0
|
||||
- libxslt=1.1.43=h0fbe4c1_1
|
||||
- libzlib=1.3.2=hfd05255_2
|
||||
- llvm-openmp=22.1.7=h4fa8253_0
|
||||
- lsprotocol=2025.0.0=pyhe01879c_0
|
||||
- mako=1.3.12=pyhcf101f3_0
|
||||
- markdown=3.10.2=pyhcf101f3_0
|
||||
- markdown-it-py=4.2.0=pyhd8ed1ab_0
|
||||
- markupsafe=3.0.3=py312h05f76fc_1
|
||||
- matplotlib=3.10.9=py312h2e8e312_0
|
||||
- matplotlib-base=3.10.9=py312h0ebf65c_0
|
||||
- matplotlib-inline=0.2.2=pyhd8ed1ab_0
|
||||
- mccabe=0.7.0=pyhd8ed1ab_1
|
||||
- mdurl=0.1.2=pyhd8ed1ab_1
|
||||
- mistune=3.2.1=pyhcf101f3_0
|
||||
- mkl=2026.0.0=hac47afa_908
|
||||
- more-itertools=11.1.0=pyhcf101f3_0
|
||||
- mpmath=1.4.1=pyhd8ed1ab_0
|
||||
- multidict=6.7.1=py312h05f76fc_0
|
||||
- munkres=1.1.4=pyhd8ed1ab_1
|
||||
- mypy_extensions=1.1.0=pyha770c72_0
|
||||
- narwhals=2.23.0=pyhcf101f3_0
|
||||
- nbclient=0.11.0=pyhd8ed1ab_0
|
||||
- nbconvert=7.17.1=hb502eef_0
|
||||
- nbconvert-core=7.17.1=pyhcf101f3_0
|
||||
- nbconvert-pandoc=7.17.1=h08b4883_0
|
||||
- nbformat=5.10.4=pyhd8ed1ab_1
|
||||
- nest-asyncio=1.6.0=pyhd8ed1ab_1
|
||||
- notebook=7.5.7=pyhcf101f3_1
|
||||
- notebook-shim=0.2.4=pyhd8ed1ab_1
|
||||
- numpy=2.4.6=py312ha3f287d_0
|
||||
- numpydoc=1.10.0=pyhcf101f3_0
|
||||
- onemkl-license=2026.0.0=h57928b3_908
|
||||
- openjpeg=2.5.4=h0e57b4f_0
|
||||
- openssl=3.6.3=hf411b9b_0
|
||||
- overrides=7.7.0=pyhd8ed1ab_1
|
||||
- packaging=26.2=pyhc364b38_0
|
||||
- pandas=3.0.3=py312h95189c4_0
|
||||
- pandoc=3.10=h57928b3_0
|
||||
- pandocfilters=1.5.0=pyhd8ed1ab_0
|
||||
- pango=1.56.4=h13911b6_1
|
||||
- parso=0.8.7=pyhcf101f3_0
|
||||
- pathspec=1.1.1=pyhd8ed1ab_0
|
||||
- patsy=1.0.2=pyhcf101f3_0
|
||||
- pcre2=10.47=hd2b5f0e_0
|
||||
- pdoc3=0.11.1=pyhd8ed1ab_0
|
||||
- pexpect=4.9.0=pyhd8ed1ab_1
|
||||
- pickleshare=0.7.5=pyhd8ed1ab_1004
|
||||
- pillow=12.2.0=py312h31f0997_0
|
||||
- pip=26.1.2=pyh8b19718_0
|
||||
- pixman=0.46.4=h5112557_1
|
||||
- platformdirs=4.10.0=pyhcf101f3_0
|
||||
- pluggy=1.6.0=pyhf9edf01_1
|
||||
- ply=3.11=pyhd8ed1ab_3
|
||||
- prometheus_client=0.25.0=pyhd8ed1ab_0
|
||||
- prompt-toolkit=3.0.52=pyha770c72_0
|
||||
- propcache=0.5.2=py312h05f76fc_0
|
||||
- psutil=7.2.2=py312he5662c2_0
|
||||
- pthread-stubs=0.4=h0e40799_1002
|
||||
- ptyprocess=0.7.0=pyhd8ed1ab_1
|
||||
- pure_eval=0.2.3=pyhd8ed1ab_1
|
||||
- pycodestyle=2.12.1=pyhd8ed1ab_1
|
||||
- pyconify=0.2.1=pyhd8ed1ab_0
|
||||
- pycparser=3.0=pyhcf101f3_0
|
||||
- pydocstyle=6.3.0=pyhd8ed1ab_1
|
||||
- pyflakes=3.2.0=pyhd8ed1ab_1
|
||||
- pygithub=2.9.1=pyhd8ed1ab_0
|
||||
- pygments=2.20.0=pyhd8ed1ab_0
|
||||
- pyjwt=2.13.0=pyhcf101f3_0
|
||||
- pylint=4.0.6=pyhcf101f3_0
|
||||
- pylint-venv=3.0.4=pyhd8ed1ab_1
|
||||
- pyls-spyder=0.4.0=pyhd8ed1ab_1
|
||||
- pynacl=1.6.2=py312h297b7f0_2
|
||||
- pyopenssl=26.3.0=pyhcf101f3_0
|
||||
- pyparsing=3.3.2=pyhcf101f3_0
|
||||
- pyqt=5.15.11=py312h7eb3e20_2
|
||||
- pyqt5-sip=12.17.0=py312hbb81ca0_2
|
||||
- pyqtwebengine=5.15.11=py312hffa3973_2
|
||||
- pyside6=6.11.1=py312ha7d0d2e_1
|
||||
- pysocks=1.7.1=pyh09c184e_7
|
||||
- python=3.12.13=h0159041_0_cpython
|
||||
- python-dateutil=2.9.0.post0=pyhe01879c_2
|
||||
- python-fastjsonschema=2.21.2=pyhe01879c_0
|
||||
- python-gil=3.12.13=hd8ed1ab_0
|
||||
- python-gssapi=1.11.1=py312hcf70c7a_1
|
||||
- python-json-logger=4.1.0=pyhd8ed1ab_0
|
||||
- python-lsp-black=2.0.0=pyhff2d567_1
|
||||
- python-lsp-jsonrpc=1.1.2=pyhff2d567_1
|
||||
- python-lsp-ruff=2.3.1=pyhcf101f3_0
|
||||
- python-lsp-server=1.14.0=pyh332efcf_0
|
||||
- python-lsp-server-base=1.14.0=pyhd8ed1ab_0
|
||||
- python-slugify=8.0.4=pyhd8ed1ab_1
|
||||
- python-tzdata=2026.2=pyhd8ed1ab_0
|
||||
- python_abi=3.12=8_cp312
|
||||
- pytokens=0.4.1=py312he5662c2_2
|
||||
- pytoolconfig=1.2.5=pyhd8ed1ab_1
|
||||
- pyuca=1.2=pyhd8ed1ab_2
|
||||
- pywin32=312=py312h829343e_0
|
||||
- pywin32-ctypes=0.2.3=py312h2e8e312_3
|
||||
- pywinpty=2.0.15=py312h275cf98_1
|
||||
- pyyaml=6.0.3=py312h05f76fc_1
|
||||
- pyzmq=27.1.0=py312h343a6d4_3
|
||||
- qdarkstyle=3.2.3=pyhd8ed1ab_1
|
||||
- qhull=2020.2=hc790b64_5
|
||||
- qstylizer=0.2.4=pyhff2d567_0
|
||||
- qt-main=5.15.15=hc95f6a6_8
|
||||
- qt-webengine=5.15.15=h087ee03_1
|
||||
- qt6-main=6.11.1=pl5321hfcac499_1
|
||||
- qtawesome=1.4.2=pyh9208f05_0
|
||||
- qtconsole=5.7.2=pyhd8ed1ab_0
|
||||
- qtconsole-base=5.7.2=pyha770c72_0
|
||||
- qtpy=2.4.3=pyhd8ed1ab_1
|
||||
- referencing=0.37.0=pyhcf101f3_0
|
||||
- requests=2.34.2=pyhcf101f3_0
|
||||
- rfc3339-validator=0.1.4=pyhd8ed1ab_1
|
||||
- rfc3986-validator=0.1.1=pyh9f0ad1d_0
|
||||
- rfc3987-syntax=1.1.0=pyhe01879c_1
|
||||
- rich=15.0.0=pyhcf101f3_0
|
||||
- roman-numerals=4.1.0=pyhd8ed1ab_0
|
||||
- rope=1.14.0=pyhd8ed1ab_0
|
||||
- rpds-py=2026.5.1=py312hd944d65_0
|
||||
- rtree=1.4.1=pyh11ca60a_0
|
||||
- ruff=0.15.17=h45713df_0
|
||||
- scipy=1.18.0=py312h9b3c559_0
|
||||
- seaborn=0.13.2=hd8ed1ab_3
|
||||
- seaborn-base=0.13.2=pyhd8ed1ab_3
|
||||
- send2trash=2.1.0=pyh6dadd2b_1
|
||||
- setuptools=82.0.1=pyh332efcf_0
|
||||
- sip=6.10.0=py312hbb81ca0_1
|
||||
- six=1.17.0=pyhe01879c_1
|
||||
- sniffio=1.3.1=pyhd8ed1ab_2
|
||||
- snowballstemmer=3.1.1=pyhd8ed1ab_0
|
||||
- sortedcontainers=2.4.0=pyhd8ed1ab_1
|
||||
- soupsieve=2.8.4=pyhd8ed1ab_0
|
||||
- sphinx=9.1.0=pyhd8ed1ab_0
|
||||
- sphinxcontrib-applehelp=2.0.0=pyhd8ed1ab_1
|
||||
- sphinxcontrib-devhelp=2.0.0=pyhd8ed1ab_1
|
||||
- sphinxcontrib-htmlhelp=2.1.0=pyhd8ed1ab_1
|
||||
- sphinxcontrib-jsmath=1.0.1=pyhd8ed1ab_1
|
||||
- sphinxcontrib-qthelp=2.0.0=pyhd8ed1ab_1
|
||||
- sphinxcontrib-serializinghtml=2.0.0=pyhd8ed1ab_0
|
||||
- spyder=6.1.4=hd8ed1ab_0
|
||||
- spyder-base=6.1.4=py312h2e8e312_0
|
||||
- spyder-kernels=3.1.4=win_pyh7428d3b_0
|
||||
- stack_data=0.6.3=pyhd8ed1ab_1
|
||||
- statsmodels=0.14.6=py312h196c9fc_0
|
||||
- superqt=0.8.0=pyh9208f05_0
|
||||
- sympy=1.14.0=pyh04b8f61_6
|
||||
- tbb=2023.0.0=hd3d4ead_2
|
||||
- terminado=0.18.1=pyh6dadd2b_1
|
||||
- text-unidecode=1.3=pyhd8ed1ab_2
|
||||
- textdistance=4.6.3=pyhd8ed1ab_1
|
||||
- three-merge=0.1.1=pyhd8ed1ab_1
|
||||
- tinycss2=1.5.1=pyhcf101f3_0
|
||||
- tk=8.6.13=h6ed50ae_3
|
||||
- toml=0.10.2=pyhcf101f3_3
|
||||
- tomli=2.4.1=pyhcf101f3_0
|
||||
- tomlkit=0.15.0=pyha770c72_0
|
||||
- tornado=6.5.7=py312he06e257_0
|
||||
- traitlets=5.15.1=pyhcf101f3_0
|
||||
- typing-extensions=4.15.0=h396c80c_0
|
||||
- typing_extensions=4.15.0=pyhcf101f3_0
|
||||
- typing_utils=0.1.0=pyhd8ed1ab_1
|
||||
- tzdata=2025c=hc9c84f9_1
|
||||
- ucrt=10.0.26100.0=h57928b3_0
|
||||
- ujson=5.13.0=py312ha1a9051_0
|
||||
- unicodedata2=17.0.1=py312he06e257_0
|
||||
- uri-template=1.3.0=pyhd8ed1ab_1
|
||||
- urllib3=2.7.0=pyhd8ed1ab_0
|
||||
- vc=14.5=h1b7c187_39
|
||||
- vc14_runtime=14.51.36231=h1b9f54f_39
|
||||
- vcomp14=14.51.36231=h1b9f54f_39
|
||||
- watchdog=6.0.0=py312h209ec74_3
|
||||
- wcwidth=0.8.1=pyhd8ed1ab_0
|
||||
- webcolors=25.10.0=pyhd8ed1ab_0
|
||||
- webencodings=0.5.1=pyhd8ed1ab_3
|
||||
- websocket-client=1.9.0=pyhd8ed1ab_0
|
||||
- whatthepatch=1.0.7=pyhd8ed1ab_1
|
||||
- wheel=0.47.0=pyhd8ed1ab_0
|
||||
- widgetsnbextension=4.0.15=pyhd8ed1ab_0
|
||||
- win_inet_pton=1.1.0=pyh7428d3b_8
|
||||
- winpty=0.4.3=4
|
||||
- wrapt=2.2.1=py312he06e257_0
|
||||
- xarray=2026.4.0=pyhc364b38_0
|
||||
- xorg-libxau=1.0.12=hba3369d_1
|
||||
- xorg-libxdmcp=1.1.5=hba3369d_1
|
||||
- xyzservices=2026.3.0=pyhd8ed1ab_0
|
||||
- yaml=0.2.5=h6a83c73_3
|
||||
- yapf=0.43.0=pyhd8ed1ab_1
|
||||
- yarl=1.24.2=py312h05f76fc_0
|
||||
- zeromq=4.3.5=h3a581c9_11
|
||||
- zipp=4.1.0=pyhcf101f3_0
|
||||
- zlib=1.3.2=hfd05255_2
|
||||
- zlib-ng=2.3.3=h0261ad2_1
|
||||
- zstd=1.5.7=h534d264_6
|
||||
prefix: C:\Users\tschan_d\AppData\Local\miniforge3\envs\MA
|
||||
@@ -0,0 +1,4 @@
|
||||
@echo off
|
||||
echo Compiling documentation...
|
||||
pdoc defs/ -o doc/ --html --force --config latex_math=True
|
||||
pause
|
||||
@@ -1,5 +1,5 @@
|
||||
# Imports
|
||||
from defs.computing import OFRSample, OFRAnalyser
|
||||
from defs.OFR import OFRSample, OFRAnalyser
|
||||
import numpy as np
|
||||
from pathlib import Path
|
||||
|
||||
|
||||
@@ -10,14 +10,14 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"execution_count": null,
|
||||
"id": "8769766b",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# Imports\n",
|
||||
"\n",
|
||||
"from defs.computing import OFRSample, OFRAnalyser\n",
|
||||
"from defs.OFR import OFRSample, OFRAnalyser\n",
|
||||
"import numpy as np\n",
|
||||
"from pathlib import Path\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
|
||||
Reference in new issue
Block a user